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Econometrics papers.

For further information about this series and for press inquiries please contact Lubala Chibwe, by email: [email protected].

Econometrics Paper

Multivariate kernel regression in vector and product metric spaces.

Marcia M Schafgans and Victoria Zinde-Walsh

Nonparametric kernel regression is widely used in econometrics and has been applied to models with cross-sectional, time series and panel data. As functional data analysis is gaining attention, our analysis extends to th... Read more...

Keywords: nadaraya-watson estimator ; singular distribution ; multivariate functional regression ; small cube probability

Empirical likelihood for manifolds

Daisuke Kurisu and Taisuke Otsu

There has been growing interest in statistical analysis on random objects taking values in a non-Euclidean metric space. One important class of such objects consists of data on manifolds. This article is concerned with i... Read more...

6 February 2024

Keywords: riemannian manifold ; empirical likelihood

Nonparametric causal inference with functional covariates

Daisuke Kurisu, Taisuke Otsu and Mengshan Xu

Functional data and their analysis have become increasingly popular in various fields of data sciences. This paper considers estimation and inference of the average treatment effect under unconfoundedness when the covari... Read more...

25 October 2023

Keywords: causal inference ; functional data

Inference in the presence of unknown rates

Hao Dong, Taisuke Otsu and Luke Taylor

The convergence rate of an estimator can vary when applied to datasets from differ- ent populations. As the population is unknown in practice, so is the corresponding convergence rate. In this paper, we introduce a metho... Read more...

26 September 2023

Keywords: subsampling ; convergence rate ; measurement error

Empirical likelihood for network data

Yukitoshi Matsushita and Taisuke Otsu

This article develops a concept of nonparametric likelihood for network data based on network moments, and proposes general inference methods by adapting the theory of jackknife empirical likelihood. Our methodology can ... Read more...

7 August 2023

Keywords: network data ; empirical likelihood ; jackknife

Model averaging for global Fréchet regression

Petersen and Müller (2019) generalized the notion of regression analysis to non-Euclidean response objects. Meanwhile, in the conventional regression analysis, model averaging has long history and is widely applied in st... Read more...

21 July 2023

Keywords: non-euclidean data ; fréchet regression ; model averaging ; cross validation

Regression adjustment in randomized controlled trials with many covariates

Harold D Chiang, Yukitoshi Matsushita and Taisuke Otsu

This paper is concerned with estimation and inference on average treatment effects in randomized controlled trials when researchers observe potentially many covariates. By em- ploying Neyman’s (1923) finite population pe... Read more...

9 February 2023

Keywords: randomized controlled trials ; regression adjustment ; many covariates

Regression discontinuity design with potentially many covariates

Yoichi Arai, Taisuke Otsu and Myung Hwan Seo

This paper studies the case of possibly high-dimensional covariates in the regression discontinuity design (RDD) analysis. In particular, we propose estimation and inference methods for the RDD models with covariate sele... Read more...

31 October 2022

Keywords: regression discontinuity design ; covariate selection ; lasso

GLS under monotone heteroskedasticity

Yoichi Arai, Taisuke Otsu and Mengshan Xu

The generalized least square (GLS) is one of the most basic tools in regression analyses. A major issue in implementing the GLS is estimation of the conditional variance function of the error term, which typically requir... Read more...

27 October 2022

Keywords: generalized least squares ; monotonicity ; isotonic regression

Conditional likelihood ratio test with many weak instruments

Sreevidya Ayyar, Yukitoshi Matsushita and Taisuke Otsu

This paper extends validity of the conditional likelihood ratio (CLR) test developed by Moreira (2003) to instrumental variable regression models with unknown error variance and many weak instruments. In this setting, we... Read more...

11 October 2022

Keywords: many weak instruments ; conditional likelihood ratio test

Isotonic propensity score matching

Taisuke Otsu and Mengshan Xu

We propose a one-to-many matching estimator of the average treatment effect based on propensity scores estimated by isotonic regression. The method relies on the monotonicity assumption on the propensity score function, ... Read more...

19 July 2022

Keywords: matching ; propensity score ; isotonic regression

Minimax Risk in Estimating Kink Threshold and Testing

Javier Hidalgo, Heejun Lee, Jungyoon Lee and Myung Hwan Seo

We derive a risk lower bound in estimating the threshold parameter without knowing whether the threshold regression model is continuous or not. The bound goes to zero as the sample size n grows only at the cube root ra... Read more...

3 March 2022

Keywords: continuity test ; kink ; risk lower bound ; unknown threshold

Nonparametric prediction with spatial data

Abhimanyu Gupta and Javier Hidalgo

We describe a (nonparametric) prediction algorithm for spatial data, based on a canonical factorization of the spectral density function. We provide theoretical results showing that the predictor has desirable asymptot... Read more...

Keywords: lattice data ; unilateral models ; canonical factorization ; spectral density ; nonparametric prediction

Bandwidth selection for nonparametric regression with errors-in-variables

We propose two novel bandwidth selection procedures for the nonparametric regression model with classical measurement error in the regressors. Each method is based on evaluating the prediction errors of the regression us... Read more...

25 January 2022

Keywords: bandwidth selection ; measurement error ; bootstrap

Estimating density ratio of marginals to joint: Applications to causal inference

Yukitoshi Matsushita, Taisuke Otsu and Keisuke Takahata

In various fields of data science, researchers often face problems of estimating the ratios of two probability densities. Particularly in the context of causal inference, the product of marginals for a treatment variable... Read more...

7 January 2022

Keywords: density ratio ; causal inference ; nonparametric estimation

Equilibrium multiplicity in dynamic games: testing and estimation

Taisuke Otsu and Martin Pesendorfer

This paper surveys the recent literature on dynamic games estimation when there is a concern of equilibrium multiplicity. We focus on the questions of testing for equilibrium multiplicity and estimation in the presence o... Read more...

26 October 2021

Keywords: dynamic markov game ; multiplicity of equilibria

Multiway empirical likelihood

his paper develops a general methodology to conduct statistical inference for observations indexed by multiple sets of entities. We propose a novel multiway empirical likeli- hood statistic that converges to a chi-square... Read more...

19 October 2021

Keywords: multiway data ; empirical likelihood ; bipartite network

Nonparametric inference for extremal conditional quantiles

This paper studies asymptotic properties of the local linear quantile estimator under the extremal order quantile asymptotics, and develops a practical inference method for conditional quantiles in extreme tail areas. By... Read more...

14 September 2021

Keywords: quantile regression ; extreme value theory ; point process ; subsampling

On linearization of nonparametric deconvolution estimators for repeated measurements model

By utilizing intermediate Gaussian approximations, this paper establishes asymptotic linear representations of nonparametric deconvolution estimators for the classical measurement error model with repeated measurements. ... Read more...

19 July 2021

Keywords: measurement error ; deconvolution ; confidence band

Reweighted nonparametric likelihood inference for linear functionals

Karun Adusumilli, Taisuke Otsu and Chen Qiu

This paper is concerned with inference on finite dimensional parameters in semiparametric moment condition models, where the moment functionals are linear with respect to unknown nuisance functions. By exploiting this li... Read more...

1 December 2020

Keywords: nonparametric likelihood ; linear functional ; balancing weights

Jackknife Lagrange multiplier test with many weak instruments

This paper proposes a jackknife Lagrange multiplier (JLM) test for instrumental variable regression models, which is robust to (i) many instruments, where the number of instruments may increase proportionally with the sa... Read more...

5 August 2020

Keywords: many instruments ; weak instruments ; lagrange multiplier test ; jackknife

Second-order refinements for t-ratios with many instruments

This paper studies second-order properties of the many instruments robust t-ratios based on the limited information maximum likelihood and Fuller estimators for instrumental variable regression models under the many inst... Read more...

12 May 2020

Keywords: simultaneous equation ; many instrumental variables ; higher order expansion

Estimation of (static or dynamic) games under equilibrium multiplicity

Taisuke Otsu, Martin Pesendorfer, Yuya Sasaki and Yuya Takahashi

We propose a multiplicity-robust estimation method for (static or dynamic) games. The method allows for distinct behaviors and strategies across markets by treating market specific behaviors as correlated latent variable... Read more...

20 January 2020

Switching Regressions with Imperfect Regime Classification Information: Theory and Applications

V A Hajivassiliou

Read more...

8 January 2020

Keywords: switching regressions models ; measurement errors ; trigger-price mechanisms ; price-&#133 ; xing

Estimation and Specification Testing of Panel Data Models with Non-Ignorable Persistent Heterogeneity, Contemporaneous and Intertemporal Simultaneity, and Observable and Unobservable Dynamics

This paper proposes efficient estimation methods for panel data limited dependent variables (LDV) models possessing a variety of complications: non-ignorable persistent heterogeneity; contemporaneous and intertemporal en... Read more...

3 December 2019

Nonparametric intermediate order regression quantiles

Hidehiko Ichimura, Taisuke Otsu and Joseph Altonji

This paper studies nonparametric estimation of d-dimensional conditional quantile functions and their derivatives in the tails. We investigate asymptotic properties of the local and global nonparametric quantile regressi... Read more...

26 November 2019

Keywords: quantile regression ; local polynomial regression: extremes

Estimation of Varying Coefficient Models with Measurement Error

We propose a semiparametric estimator for varying coe&#64259;cient models when the regressors in the nonparametric component are measured with error. Varying coe&#64259;cient models are an extension of other popular semi... Read more...

Novel Approaches to Coherency Conditions in Dynamic LDV Models: Quantifying Financing Constraints and a Firm's Decision and Ability to Innovate

V A Hajivassiliou, Frédérique Savignac and Frédérique Savignac

We develop novel methods for establishing coherency conditions in Static and Dynamic Limited Dependent Variables (LDV) Models. We propose estimation strategies based on Conditional Maximum Likelihood Estimation for simul... Read more...

5 November 2019

Keywords: financing constraints ; innovation ; dynamic limited dependent variable models ; joint bivariate probit model ; econometric coherency conditions ; state dependence

Jackknife, small bandwidth and high-dimensional asymptotics

This paper sheds light on problems of statistical inference under alternative or nonstandard asymptotic frameworks from the perspective of jackknife empirical likelihood (JEL). Examples include small bandwidth asymptotic... Read more...

22 July 2019

Keywords: jackknife ; empirical likelihood ; nonstandard asymptotics

On the uniform convergence of deconvolution estimators from repeated measurements

This paper studies the uniform convergence rates of Li and Vuong's (1998) nonparametric deconvolution estimator and its regularized version by Comte and Kappus (2015) for the classical measurement error model, where repe... Read more...

Keywords: measurement error ; deconvolution ; uniform convergence

Score estimation of monotone partially linear index model

Mengshan Xu and Taisuke Otsu

17 May 2019

Average derivative estimation under measurement error

Causal inference on regression discontinuity designs by high-dimensional methods.

7 January 2019

Nonparametric Estimation of Additive Model with Errors-in-Variables

Hao Dong and Taisuke Otsu

In estimation of nonparametric additive models, conventional methods, such as backfitting and series approximation, cannot be applied when measurement errors are present in covariates. We propose an estimator for such ... Read more...

27 November 2018

Keywords: additive model ; measurement error ; deconvolution

Likelihood ratio inference for missing data models

Karun Adusumilli and Taisuke Otsu

Missing or incomplete outcome data is a ubiquitous problem in biomedical and social sciences. Under the missing at random setup, inverse probability weighting is widely applied to estimate and make inference on the popul... Read more...

30 October 2018

Keywords: missing data ; empirical balancing ; treatment effect ; nonparametric likelihood

Likelihood corrections for two-way models

Koen Jochmans and Taisuke Otsu

The use of two-way fixed-effect models is widespread. The presence of incidental parameter bias, however, invalidates statistical inference based on the likelihood. In this paper we consider modifications to the (profile... Read more...

19 February 2018

Keywords: asymptotic bias ; bias correction ; fixed effects ; information bias ; modified profile likelihood ; panel data ; mcmc ; penalization ; rectangular-array asymptotics

Inference Without Smoothing for Large Panels with Cross- Sectional and Temporal Dependence

Javier Hidalgo and Marcia M Schafgans

This paper addresses inference in large panel data models in the presence of both cross-sectional and temporal dependence of unknown form. We are interested in making inferences without relying on the choice of any smoo... Read more...

20 February 2018

Keywords: large panel data models ; cross-sectional strong-dependence ; central limit theorems ; clustering ; discrete fourier transformation ; nonparametric bootstrap algorithms

Adaptive Inference on Pure Spatial Models

Jungyoon Lee and Peter M Robinson

We consider adaptive tests and estimates which are asymptotically efficient in the presence of unknown, nonparametric, distributional form in pure spatial models. A novel adaptive Lagrange Multiplier testing procedure f... Read more...

26 January 2018

Keywords: efficient test ; adaptive estimation ; spatial models

Information theoretic approach to high dimensional multiplicative models: Stochastic discount factor and treatment effect

Taisuke Otsu and Chen Qiu

This paper is concerned with estimation of functionals of a latent weight function that satisfies possibly high dimensional multiplicative moment conditions. Main examples are missing data problems, treatment effects, an... Read more...

4 January 2018

Keywords: stochastic discount factor ; treatment effect ; information theory ; high dimension

Inference on distribution functions under measurement error

Karun Adusumilli, Taisuke Otsu and Yoon-Jae Whang

13 November 2017

Keywords: measurement error ; confidence band ; stochastic dominance

Relative error accurate statistic based on nonparametric likelihood

Lorenzo Camponovo, Yukitoshi Matsushita and Taisuke Otsu

This paper develops a new test statistic for parameters defined by moment conditions that exhibits desirable relative error properties for the approximation of tail area probabilities. Our statistic, called the tilted ex... Read more...

Keywords: nonparametric likelihood ; saddlepoint ; moment condition model

Likelihood inference on semiparametric models: Average derivative and treatment effect

In the past few decades, much progress has been made in semiparametric modeling and estimation methods for econometric analysis. This paper is concerned with inference (i.e., confidence intervals and hypothesis testing) ... Read more...

27 June 2017

Keywords: semiparametric ; jackknife ; empirical likelihood

Empirical likelihood for high frequency data

With increasing availability of high frequency financial data as a background, various volatility measures and related statistical theory are developed in the recent literature. This paper introduces the method of empiri... Read more...

21 February 2017

Keywords: high frequency data ; volatility ; empirical likelihood

Robust Inference and Testing of Continuity in Threshold Regression Models

Javier Hidalgo, Jungyoon Lee and Myung Hwan Seo

This paper is concerned with inference in regression models with either a kink or a jump at an unknown threshold, particularly when we do not know whether the kink or jump is the true specification. One of our main resu... Read more...

13 February 2017

Local M-estimation with discontinuous criterion for dependent and limited observations

Myung Hwan Seo and Taisuke Otsu

This paper examines asymptotic properties of local M-estimators under three sets of high-level conditions. These conditions are sufficiently general to cover the minimum volume predictive region, conditional maximum scor... Read more...

17 October 2016

Keywords: cube root asymptotics ; maximal inequality ; mixing process ; partial identification ; parameter-dependent localization

Likelihood inference on semiparametric models with generated regressors

Hahn and Ridder (2013) formulated influence functions of semiparametric three step estimators where generated regressors are computed in the first step. This class of estimators covers several important examples for empi... Read more...

5 September 2016

Keywords: generated regressor ; empirical likelihood

Specification testing for errors-in-variables models

Taisuke Otsu and Luke Taylor

This paper considers specification testing for regression models with errors-in-variables and proposes a test statistic comparing the distance between the parametric and nonparametric fits based on deconvolution techniqu... Read more...

15 August 2016

Keywords: specification test ; measurement errors ; deconvolution

Nonparametric instrumental regression with errors in variables

This paper considers nonparametric instrumental variable regression when the endogenous variable is contaminated with classical measurement error. Existing methods are inconsistent in the presence of measurement error. W... Read more...

21 July 2015

Keywords: nonparametric instrumental variable regression ; measurement error ; inverse problem ; deconvolution ; measurement error

Testing for Breaks in Regression Models with Dependent Data

Violetta Dalla and Javier Hidalgo

4 June 2015

Keywords: nonparametric regression ; breaks ; smoothness ; strong dependence ; extreme-values distribution ; frequency domain bootstrap algorithms.

Inference and Testing Breaks in Large Dynamic Panels with Strong Cross Sectional Dependence

This paper is concerned with various issues related to inference in large dynamic panel data models (where both n and T increase without bound) in the presence of, possibly, strong cross-sectional dependence. Our first a... Read more...

1 April 2015

Keywords: large panel data ; dynamic models ; cross-sectional strong-dependence ; central limit theorems ; homogeneity ; bootstrap algorithms

Pooling data across markets in dynamic Markov games

Taisuke Otsu, Martin Pesendorfer and Yuya Takahashi

This paper proposes several statistical tests for finite state Markov games to examine the null hypothesis that data from distinct markets can be pooled. We formulate tests of (i) the conditional choice and state transit... Read more...

16 March 2015

Keywords: dynamic markov game ; poolability ; multiplicity of equilibria ; hypothesis testing

Nonparametric likelihood for volatility under high frequency data

We propose a nonparametric likelihood inference method for the integrated volatility under high frequency financial data. The nonparametric likelihood statistic, which contains the conventional statistics such as empiric... Read more...

15 January 2015

Keywords: nonparametric likelihood ; volatility ; high frequency data

Bootstrap inference of matching estimators for average treatment effects

Taisuke Otsu and Yoshiyasu Rai

Abadie and Imbens (2008) showed that the standard naive bootstrap is inconsistent to estimate the distribution of the matching estimator for treatment effects with a fixed number of matches. This article proposes an asym... Read more...

13 January 2015

Keywords: treatment effect ; matching ; bootstrap

Robust estimation of moment condition models with weakly dependent data

Kirill Evdokimov, Yuichi Kitamura and Taisuke Otsu

This paper considers robust estimation of moment condition models with time series data. Researchers frequently use moment condition models in dynamic econometric analysis. These models are particularly useful when one w... Read more...

5 December 2014

Keywords: blocking ; generalized empirical likelihood ; hellinger distance ; robustness ; efficient estimation ; mixing

Regularization for Spatial Panel Time Series Using the Adaptive LASSO

Clifford Lam and Pedro Souza

This paper proposes a model for estimating the underlying cross-sectional dependence structure of a large panel of time series. Technical difficulties meant such a structure is usually assumed before further analysis. We... Read more...

25 November 2014

Keywords: spatial econometrics ; adaptive lasso ; sign consistency ; asymptotic normality ; non-asymptotic oracle inequalities ; spatial weight matrices

Dynamic Panels with Threshold Effect and Endogeneity

Myung Hwan Seo and Yongcheol Shin

This paper addresses an important and challenging issue as how best to model nonlinear asymmetric dynamics and cross-sectional heterogeneity, simultaneously, in the dynamic threshold panel data framework, in which both t... Read more...

1 September 2014

Keywords: dynamic panel threshold models ; endogenous threshold effects and regressors ; fd-gmm and fd-2sls estimation ; linearity test ; exogeneity test ; investment and dividend smoothing.

A Cusum Test of Common Trends in Large Heterogeneous Panels

Javier Hidalgo and Jungyoon Lee

This paper examines a nonparametric CUSUM-type test for common trends in large panel data sets with individual fixed effects. We consider, as in Zhang, Su and Phillips (2012), a partial linear regression model with unkno... Read more...

Keywords: common trends ; large data set ; partial linear models ; bootstrap algorithms

Estimation of Nonseparable Models with Censored Dependent Variables and Endogenous Regressors.

In this paper we develop a nonparametric estimator for the local average response of a censored dependent variable to endogenous regressors in a nonseparable model where the unobservable error term is not restricted to b... Read more...

6 August 2014

Empirical Likelihood for Random Sets

We extend the method of empirical likelihood to cover hypotheses involving the Aumann expectation of random sets. By exploiting the properties of random sets, we convert the testing problem into one involving a continuum... Read more...

25 June 2014

Empirical Likelihood for Regression Discontinuity Design

Taisuke Otsu, Ke-Li Xu and Yukitoshi Matsushita

7 February 2014

Robustness of bootstrap in instrumental variable regression

Lorenzo Camponovo and Taisuke Otsu

This paper studies robustness of bootstrap inference methods for instrumental variable (IV)regression models. We consider test statistics for parameter hypotheses based on the IV estimatorand generalized method of trimme... Read more...

21 January 2014

Keywords: bootstrap ; breakdown point ; instrumental variables

Asymptotics for maximum score method under general conditions

Abstract. Since Manski's (1975) seminal work, the maximum score method for discrete choice models has been applied to various econometric problems. Kim and Pollard (1990) established the cube root asymptotics for the max... Read more...

Revised August 2014

Keywords: maximum score ; cube root asymptotics ; set inference

Series Estimation under Cross-sectional Dependence

An asymptotic theory is developed for nonparametric and semiparametric series estimation under general cross-sectional dependence and heterogeneity. A uniform rate of consistency, asymptotic normality, and sufficient con... Read more...

25 November 2013

Keywords: series estimation ; nonparametric regression ; spatial data ; cross-sectional dependence ; uniform rate of consistency ; functional central limit the- orem ; data-driven studentization

Panel Nonparametric Regression with Fixed Effects

Nonparametric regression is developed for data with both a temporal and a cross-sectional dimension. The model includes additive, unknown, individual-specifi…c components and allows also for cross-sectional and temporal ... Read more...

Keywords: panel data ; nonparametric regression ; cross-sectional dependence ; generalized least squares ; optimal bandwidth

Non-Nested Testing of Spatial Correlation

Miguel A. Delgado and Peter M Robinson

We develop non-nested tests in a general spatial, spatio-temporal or panel data context. The spatial aspect can be interpreted quite generally, in either a geographical sense, or employing notions of economic distance, o... Read more...

Keywords: on-nested test ; spatial correlation ; pseudo maximum likelihood estimation

Efficient Inference on Fractionally Integrated Panel Data Models with Fixed Effects

Peter M Robinson and Carlos Velasco

A dynamic panel data model is considered that contains possibly stochastic individual components and a common fractional stochastic time trend. We propose four different ways of coping with the individual effects so as t... Read more...

20 November 2013

Keywords: panel data ; fractional time series ; estimation ; testing ; bias correction

Improved Lagrange Multiplier Tests in Spatial Autoregressions

Peter M Robinson and Francesca Rossi

For testing lack of correlation against spatial autoregressive alternatives, Lagrange multiplier tests enjoy their usual computational advantages, but the (x squared) first-order asymptotic approximation to critical valu... Read more...

Keywords: spatial autocorrelation ; lagrange multiplier test ; edgeworth expansion ; bootstrap ; finite-sample corrections.

Improved Tests for Spatial Correlation

We consider testing the null hypothesis of no spatial autocorrelation against the alternative of first order spatial autoregression. A Wald test statistic has good first order asymptotic properties, but these may not be ... Read more...

Keywords: spatial autocorrelation ; ordinary least squares ; hypothesis testing ; edgeworth expansion ; bootstrap.

Extremum Sieve Estimation in k-out-of-n Systems

Tatiana Komarova

The paper considers nonparametric estimation of absolutely continuous distribution functions of lifetimes of non-identical components in k-out-of-n systems from the observed “autopsy” data. In economics,ascending “button... Read more...

27 August 2013

Keywords: k-out-of-n systems ; competing risks ; sieve estimation ; bernstein polynomials

Testing for equality of an increasing number of spectral density functions

Javier Hidalgo, Pedro Souza and Pedro Souza

Nowadays it is very frequent that a practitioner faces the problem of modelling large data sets. Relevant examples include spatio-temporal or panel data models with large N and T. In these cases deciding a particular dyn... Read more...

1 July 2013

SPECIFICATION FOR LATTICE PROCESSES

Javier Hidalgo and Myung Hwan Seo

We consider an omnibus test for the correct speci…cation of the dynamics of a sequence fx (t)gt2Zd in a lattice. As it happens with causal models and d = 1, its asymptotic distribution is not pivotal and depends on the e... Read more...

15 May 2013

Keywords: specification test ; spatial processes ; lattice ; spectral domain ; cusum ; bootstrap.

Testing for Structural Stability in the Whole Sample

The paper examines a Lagrange Multiplier type test for the constancy of the parameter in general models with dependent data without imposing any arti…cial choice of the possible location of the break. In order to prove t... Read more...

1 September 2012

Keywords: structural stability ; gmm estimation ; strong approximation ; extreme value distribution.

ON TESTABILITY OF COMPLEMENTARITY IN MODELS WITH MULTIPLE EQUILIBRIA

This paper revisits testability of complementarity in economic models with multiple equilibria studied by Echenique and Komunjer (2009). We find that Echenique and Komunjer’s (2009) testable implications on extreme quant... Read more...

1 February 2013

Keywords: complementarity ; testability ; quantile.

Binary Choice Models with Discrete Regressors: Identification and Misspecification

In semiparametric binary response models, support conditions on the regressors are required to guarantee point identification of the parameter of interest. For example,one regressor is usually assumed to have continuous ... Read more...

Keywords: binary response models ; discrete regressors ; partial identification ; misspecification ; support vector machines

TESTING FOR STRUCTURAL STABILITY IN THE WHOLE SAMPLE

Javier Hidalgo and Myunghwan Seo

The paper examines a Lagrange Multiplier type test for the constancy of the parameter in general models with dependent data without imposing any artificial choice of the possible location of the break. In order to prove ... Read more...

1 October 2011

Keywords: structural stability. gmm estimation. strong approximation. extreme value distribution.

Adapting Kernel Estimation to Uncertain Smoothness

Yulia Kotlyarova, Marcia M Schafgans and Victoria Zinde-Walsh

For local and average kernel based estimators, smoothness conditions ensure that the kernel order determines the rate at which the bias of the estimator goes to zero and thus allows the econometrician to control the rate... Read more...

Keywords: nonparametric estimation ; kernel based estimator ; combined stimator ; variance bootstrap.

Inference on Power Law Spatial Trends (Running Title: Power Law Trends)

Peter M Robinson

Power law or generalized polynomial regressions with unknown real-valued exponents and coefficients, and weakly dependent errors, are considered for observations over time, space or space-time. Consistency and asymptotic... Read more...

Keywords: asymptotic normality ; consistency ; correlation ; generalized polynomial ; lattice ; power law.0út

Asymptotic Theory for Nonparametric Regression with Spatial Data

Nonparametric regression with spatial, or spatio-temporal, data is considered. The conditional mean of a dependent variable, given explanatory ones, is a nonparametric function, while the conditional covariance reflects ... Read more...

September 2010

Keywords: nonparametric regression ; spatial data ; weak dependence ; long range dependence ; heterogeneity ; consistency ; central limit theorem. ;

Statistical Inference on Regression with Spatial Dependence

Peter M Robinson and Supachoke Thawornkaiwong

Central limit theorems are developed for instrumental variables estimates of linear and semi-parametric partly linear regression models for spatial data. General forms of spatial dependence and heterogeneity in explanato... Read more...

Keywords: linear regression ; partly linear regression ; nonparametric regression ; spatial data ; instrumental variables ; asymptotic normality ; variance estimation

Nonparametric Trending Regression with Cross-Sectional Dependence

Panel data, whose series length T is large but whose cross-section size N need not be, are assumed to have a common time trend. The time trend is of unknown form, the model includes additive, unknown, individual-specific... Read more...

January 2010

Keywords: panel data ; nonparametric time trend ; cross-sectional dependence ; generalized least squares ; optimal bandwidthw

Quantile Uncorrelation and Instrumental Regression

Tatiana Komarova, Thomas Severini and Elie Tamer

We introduce a notion of median uncorrelation that is a natural extension of mean (linear) uncorrelation. A scalar random variable Y is median uncorrelated with a kdimensional random vector X if and only if the slope fro... Read more...

Semiparametric Estimation of Locally Stationary Diffusion Models

Bonsoo Koo and Oliver Linton

This paper proposes a class of locally stationary diffusion processes. The model has a time varying but locally linear drift and a volatility coefficient that is allowed to vary over time and space. We propose estimators... Read more...

August 2010

Keywords: diffusion processes ; local stationarity ; term structure dynamics ; density matching ; option pricing.

Semiparametric Estimation of Markov Decision Processeswith Continuous State Space

Sorawoot Srisuma and Oliver Linton

We propose a general two-step estimation method for the structural parameters of popular semiparametric Markovian discrete choice models that include a class of Markovian Games and allow for continuous observable state s... Read more...

Keywords: discrete markov decision models ; kernel smoothing ; markovian games ; semi-parametric estimation ; well-posed inverse problem.d

Loch Linear Fitting under Near Epoch Dependence: Uniform Consistency with Convergence Rate

Degui Li, Zudi Lu and Oliver Linton

Local linear fitting is a popular nonparametric method in nonlinear statistical and econometric modelling. Lu and Linton (2007) established the point wise asymptotic distribution (central limit theorem) for the local lin... Read more...

Keywords: local linear fitting ; near epoch dependence ; convergence rates ; uniform consistency.

Estimation of Structural Optimization Models: A Note on Identification

Sorawoot Srisuma

Bajari, Benkard and Levin (2007) propose an estimation methodology for a broad class of dynamic optimization problems. To carry out their procedure, one needs to select a set of alternative policy functions and compare t... Read more...

Keywords: consistency ; identification ; optimization models

Nonparametric Identification in Asymmetric Second-Price Auctions: A New Approach

This paper proposes an approach to proving nonparametric identification for distributions of bidders' values in asymmetric second-price auctions. I consider the case when bidders have independent private values and the o... Read more...

October 2009

Efficient Estimation of a Multivariate Multiplicative Volatility Model

Christian M. Hafner and Oliver Linton

We propose a multivariate generalization of the multiplicative volatility model of Engle and Rangel (2008), which has a nonparametric long run component and a unit multivariate GARCH short run dynamic component. We sugge... Read more...

Keywords: garch ; kernel estimation ; local stationarity ; semiparametric

ESTIMATION OF A SEMIPARAMETRIC IGARCH(1,1) MODEL

Woocheol Kim and Oliver Linton

We propose a semiparametric IGARCH model that allows for persistence in variance but also allows for more flexible functional form. We assume that the difference of the squared process is weakly stationary. We propose an... Read more...

Keywords: inverse problem ; instrumental variable ; igarch ; kernel estimation ; nonparametric regression

Nonparametric Regression with a Latent Time Series

Oliver Linton, Søren Feodor Nielsen and Jens Perch Nielsen

In this paper we investigate a class of semiparametric models for panel datasets where the cross-section and time dimensions are large. Our model contains a latent time series that is to be estimated and perhaps forecast... Read more...

Keywords: kernel estimation ; forecasting ; panel data ; unit roots

Optimal Smoothing for a Computationally and Statistically Efficient Single Index Estimator

Wolfgang Härdle, Oliver Linton and Yingcun Xia

In semiparametric models it is a common approach to under-smooth the nonparametric functions in order that estimators of the finite dimensional parameters can achieve root-n consistency. The requirement of under-smoothin... Read more...

Keywords: ade ; asymptotics ; bandwidth ; mave method ; semiparametric efficiency.

An Alternative Way of Computing Efficient Instrumental Variable Estimators

Xiaohong Chen, David T. Jacho-Chávez and Oliver Linton

A new way of constructing efficient semiparametric instrumental variable estimators is proposed. The method involves the combination of a large number of possibly inefficient estimators rather than combining the instrume... Read more...

Keywords: instrumental variables ; minimum distance ; semiparametric efficiency ; two-stage least squares

Uniform Bahadur Representation for Local Polynomial Estimates of M-Regression and Its Application to The Additive Model

Efang Kong, Oliver Linton and Yingcun Xia

We use local polynomial fitting to estimate the nonparametric M-regression function for strongly mixing stationary processes {(Y_i,?X_i ) } . We establish a strong uniform consistency rate for the Bahadur representation ... Read more...

January 2009

Nonparametric Estimation of a Polarization Measure

Gordon Anderson, Oliver Linton and Yoon-Jae Whang

This paper develops methodology for nonparametric estimation of a polarization measure due to Anderson (2004) and Anderson, Ge, and Leo (2006) based on kernel estimation techniques. We give the asymptotic distribution th... Read more...

Keywords: kernel estimation ; inequality ; overlap coefficient ; poissonization

Large-Sample Inference on Spatial Dependence

We consider cross-sectional data that exhibit no spatial correla- tion, but are feared to be spatially dependent. We demonstrate that a spatial version of the stochastic volatility model of financial econometrics, entail... Read more...

Keywords: spatial dependence ; parameter estimation ; asymptotic theory ; independence testing.

Inference On Nonparametrically Trending Time Series With Fractional Errors

The central limit theorem for nonparametric kernel estimates of a smooth trend, with linearly-generated errors, indicates asymptotic independence and homoscedasticity across fixed points, irrespective of whether disturba... Read more...

Developments in the Analysis of Spatial Data

Disregarding spatial dependence can invalidate methods for analyzing cross-sectional and panel data. We discuss ongoing work on developing methods that allow for, test for, or estimate, spatial dependence. Much of the st... Read more...

Correlation Testing in Time Series, Spatial and Cross-Sectional Data

We provide a general class of tests for correlation in time series, spatial, spatiotemporal and cross-sectional data. We motivate our focus by reviewing how computational and theoretical difficulties of point estimation ... Read more...

Keywords: heteroscedasticity ; lagrange multiplier tests.

Smoothness Adaptive Average Derivative Estimation

Many important models, such as index models widely used in limited dependent variables, partial linear models and nonparametric demand studies utilize estimation of average derivatives (sometimes weighted) of the conditi... Read more...

August 2008

Keywords: nonparametric estimation ; density weighted average derivative estimator ; combined estimator.

Bootstrap Tests of Stochastic Dominance with Asymptotic Similarity on the Boundary

Oliver Linton, Kyungchul Song and Yoon-Jae Whang

We propose a new method of testing stochastic dominance which improves on existing tests based on bootstrap or subsampling. Our test requires estimation of the contact sets between the marginal distributions. Our tests h... Read more...

February 2008

Keywords: set estimation ; size of test ; unbiasedness ; similarity ; bootstrap ; subsampling.

Multiple Local Whittle Estimation in Stationary Systems

Moving from univariate to bivariate jointly dependent long memory time series introduces a phase parameter (?), at the frequency of principal interest, zero; for short memory series ? = 0 automatically. The latter case h... Read more...

October 2007

Keywords: long memory ; phase ; cointegration ; semiparametric estimation ; consistency ; asymptotic normality.

Efficient Estimation of a Semiparametric Characteristic-Based Factor Model of Security Returns

Gregory Connor, Matthias Hagmann and Oliver Linton

This paper develops a new estimation procedure for characteristic-based factor models of security returns. We treat the factor model as a weighted additive nonparametric regression model, with the factor returns serving ... Read more...

Keywords: additive models ; arbitrage pricing theory ; factor model ; fama-french ; kernel estimation ; nonparametric regression ; panel data.

Inference about Realized Volatility using Infill Subsampling

Ilze Kalnina and Oliver Linton

We investigate the use of subsampling for conducting inference about the quadratic variation of a discretely observed diffusion process under an infill asymptotic scheme. We show that the usual subsampling method of Poli... Read more...

September 2007

Keywords: realised volatility ; semimartingale ; subsampling ; infill asymptotic scheme

DIAGNOSTIC TESTING FOR COINTEGRATION

Peter Robinson

We develop a sequence of tests for specifying the cointegrating rank of, possibly fractional, multiple time series. Memory parameters of observables are treated as unknown, as are those of possible cointegrating errors. ... Read more...

Keywords: fractional cointegration ; diagnostic testing ; specification testing ; cointegrating rank ; semiparametric estimation.

ON DISCRETE SAMPLING OF TIME-VARYING CONTINUOUS-TIME SYSTEMS

We consider a multivariate continuous time process, generated by a system of linear stochastic differential equations, driven by white noise and involving coefficients that possibly vary over time. The process is observa... Read more...

Keywords: stochastic differential equations ; time-varying coefficients ; discrete sampling ; irregular sampling.

Fractional Cointegration In Stochastic Volatility Models

Afonso Gonçalves da Silva and Peter M Robinson

Asset returns are frequently assumed to be determined by one or more common factors. We consider a bivariate factor model, where the unobservable common factor and idiosyncratic errors are stationary and serially uncorre... Read more...

Keywords: fractional cointegration ; stochastic volatility ; narrow band least squares ; semiparametric analysis.

SPECIFICATION TESTING FOR REGRESSION MODELS WITH DEPENDENT DATA

Javier Hidalgo

We describe and examine a consistent test for the correct specification of a regression function with dependent data. The test is based on the supremum of the difference between the parametric and nonparametric estimates... Read more...

Keywords: functional specification. variable selection. nonparametric kernel regression. frequency domain bootstrap.

Estimation of Nonlinear Error Correction Models

Myung Hwan Seo

Asymptotic inference in nonlinear vector error correction models (VECM) that exhibit regime-specific short-run dynamics is nonstandard and complicated. This paper contributes the literature in several important ways. Fir... Read more...

Keywords: threshold cointegration ; smooth transition error correction ; least squares ; smoothed least squares ; consistency ; convergence rate.

SEMIPARAMETRIC ESTIMATION OF A BINARY RESPONSE MODEL WITH A CHANGE-POINT DUE TO A COVARIATE THRESHOLD

Sokbae Lee and Myunghwan Seo

This paper is concerned with semiparametric estimation of a threshold binary response model. The estimation method considered in the paper is semiparametric since the parameters for a regression function are finite-dimen... Read more...

February 2007

Keywords: binary response model ; maximum score estimation ; semiparametric estimation ; threshold regression ; nonlinear random utility models.

Efficient Estimation of the Semiparametric Spatial Autoregressive Model

Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, containing nonstochastic explanatory variables and innovations suspected to be non-normal. The main stress is on the cas... Read more...

Keywords: spatial autoregression ; efficient estimation ; adaptive estimation ; simultaneity bias. © the author. all rights reserved. short sections of text ; not to exceed two paragraphs ; may be quoted without explicit permission provided that full credit ; including © notice ; is given to the source.

Selectivity and the gender wage gap decomposition in the presence of a joint decision process

Marcia M Schafgans and Morton Stelcnery

In this paper we revisit the gender decomposition of wages in the presence of selection bias. We show that when labor market participation decisions of couples are not independent, the sample selection corrections used i... Read more...

December 2006

Keywords: sample selection model ; gender wage differences ; oaxaca wage decomposition ; ‘discrimination’.

Estimating Quadratic Variation Consistently in the Presence of Correlated Measurement Error

We propose an econometric model that captures the e¤ects of market microstructure on a latent price process. In particular, we allow for correlation between the measurement error and the return process and we allow the m... Read more...

October 2006

Keywords: endogenous noise ; market microstructure ; realised volatility ; semimartingale

Identification and Nonparametric Estimation of a Transformed Additively Separable Model

David T. Jacho-Chávez, Arthur Lewbel and Oliver Linton

Let r (x, z) be a function that, along with its derivatives, can be consistently estimated nonparametrically. This paper discusses identification and consistent estimation of the unknown functions H, M, G and F, where r ... Read more...

September 2006

Keywords: partly separable models ; nonparametric regression ; dimension reduction ; generalized homothetic function ; production function.

ESTIMATING FEATURES OF A DISTRIBUTION FROM BINOMIAL DATA

Arthur Lewbel, Oliver Linton and DL McFadden

A statistical problem that arises in several fields is that of estimating the features of an unknown distribution, which may be conditioned on covariates, using a sample of binomial observations on whether draws from thi... Read more...

Keywords: willingness to pay ; contingent valuation ; discrete choice ; bi-nomial response ; bioassay ; destructive duration testing ; semiparametric ; nonparametric ; latent variable models.

Semiparametric Estimation of a Characteristic-based Factor Model of Common Stock Returns

Gregory Connor and Oliver Linton

We introduce an alternative version of the Fama-French three-factor model of stock returns together with a new estimation methodology. We assume that the factor betas in the model are smooth nonlinear functions of observ... Read more...

Keywords: characteristic-based factor model ; arbitrage pricing theory ; kernel estimation ; nonparametric estimation.

Conditional-Sum-of-Squares Estimation of Models for Stationary Time Series with Long Memory

Employing recent results of Robinson (2005) we consider the asymptotic properties of conditional-sum-of-squares (CSS) estimates of parametric models for stationary time series with long memory. CSS estimation has been co... Read more...

Keywords: long memory ; conditional-sum-of-squares estimation ; central limit theorem ; almost sure convergence.

TESTING FOR STOCHASTIC MONOTONICITY

Sokbae Lee, Oliver Linton and Yoon-Jae Whang

We propose a test of the hypothesis of stochastic monotonicity. This hypothesis is of interest in many applications. Our test is based on the supremum of a rescaled U-statistic. We show that its asymptotic distribution i... Read more...

August 2006

Keywords: distribution function ; extreme value theory ; gaussian process ; monotonicity.

Nonparametric Transformation to White Noise

Oliver Linton and Enno Mammen

We consider a semiparametric distributed lag model in which the “news impact curve” m is nonparametric but the response is dynamic through some linear filters. A special case of this is a nonparametric regression with se... Read more...

Keywords: efficiency ; inverse problem ; kernel estimation ; nonparametric regression ; time series ; unit roots.

Semiparametric Estimation of Fractional Cointegration

Javier Hualde and Peter M Robinson

A semiparametric bivariate fractionally cointegrated system is considered, integration orders possibly being unknown and I (0) unobservable inputs having nonparametric spectral density. Two kinds of estimate of the coint... Read more...

Keywords: fractional cointegration ; semiparametric model ; unknown integration orders.

Finite Sample Performance in Cointegration Analysis of Nonlinear Time Series with Long Memory

Nonlinear functions of multivariate financial time series can exhibit long memory and fractional cointegration. However, tools for analysing these phenomena have principally been justified under assumptions that are inva... Read more...

Keywords: fractional cointegration ; memory estimation ; stochastic volatility.

Instrumental Variables Estimation of Stationary and Nonstationary Cointegrating Regressions

Peter M Robinson and M. Gerolimetto

Instrumental variables estimation is classically employed to avoid simultaneous equations bias in a stable environment. Here we use it to improve upon ordinary least squares estimation of cointegrating regressions betwee... Read more...

Keywords: cointegration ; instrumental variables estimation ; i(d) processes.

ROOT-N-CONSISTENT ESTIMATION OF WEAK FRACTIONAL COINTEGRATION

Empirical evidence has emerged of the possibility of fractional cointegration such that the gap, ß, between the integration order d of observable time series, and the integration order ? of cointegrating errors, is less ... Read more...

Keywords: fractional cointegration ; parametric estimation ; asymptotic normality.

Nonparametric Spectrum Estimation for Spatial Data

Smoothed nonparametric kernel spectral density estimates are considered for stationary data observed on a d-dimensional lattice. The implications for edge effect bias of the choice of kernel and bandwidth are considered.... Read more...

February 2006

Keywords: nonparametric spectrum estimation ; edge effect ; tapering.

Consistent estimation of the memory parameter for nonlinear time series

Violetta Dalla, Liudas Giraitis and Javier Hidalgo

For linear processes, semiparametric estimation of the memory parameter, based on the log-periodogram and local Whittle estimators, has been exhaustively examined and their properties are well established. However, excep... Read more...

January 2006

Keywords: long memory ; semiparametric estimation ; local whittle estimator.

A Smoothed Least Squares Estimator For Threshold Regression Models

Myunghwan Seo and Oliver Linton

We propose a smoothed least squares estimator of the parameters of a threshold regression model. Our model generalizes that considered in Hansen (2000) to allow the thresholding to depend on a linear index of observed re... Read more...

October 2005

Keywords: index model ; sample splitting ; segmented regression ; smoothing ; threshold estimation.

Pseudo-Maximum Likelihood Estimation of ARCH(8) Models

Peter M Robinson and Paolo Zaffaroni

Strong consistency and asymptotic normality of the Gaussian pseudo-maximum likelihood estimate of the parameters in a wide class of ARCH(8) processes are established. We require the ARCH weights to decay at least hyperbo... Read more...

Keywords: arch (8) ; pseudo-maximum likelihood estimation ; asymptotic inference

A method of moments estimator for semiparametric index models

Bas Donkers and Marcia M Schafgans

We propose an easy to use derivative based two-step estimation procedure for semi-parametric index models. In the first step various functionals involving the derivatives of the unknown function are estimated using nonpa... Read more...

Keywords: semiparametric estimation ; multiple index models ; average derivative functionals ; generalized methods of moments estimator ; rank testing

Modified Whittle Estimation of Multilateral Models on a Lattice

Peter M Robinson and J Vidal Sanz

In the estimation of parametric models for stationary spatial or spatio-temporal data on a d-dimensional lattice, for d >= 2, the achievement of asymptotic efficiency under Gaussianity, and asymptotic normality more gene... Read more...

Keywords: spatial data ; multilateral modelling ; whittle estimation ; edge effect ; consistent variance estimation

Modelling Memory of Economic and Financial Time Series

Much time series data are recorded on economic and financial variables. Statistical modelling of such data is now very well developed, and has applications in forecasting. We review a variety of statistical models from t... Read more...

Keywords: long memory ; short memory ; stochastic volatility

A Parametric Bootstrap Test for Cycles

The paper proposes a simple test for the hypothesis of strong cycles and as a by-product a test for weak dependence for linear processes. We show that the limit distribution of the test is the maximum of a (semi)Gaussian... Read more...

February 2005

Keywords: cyclical data ; strong and weak dependence ; spectral density functions ; whittle estimator ; bootstrap algorithms

Testable Implications of Forecast Optimality

Andrew J. Patton and Allan Timmermann

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted on the assumption of mean squared error loss under which forecasts should be unbiased and forecast errors serially uncorrel... Read more...

January 2005

Keywords: forecast evaluation ; loss function ; rationality tests

Unit Root Test in a Threshold Autoregression: Asymptotic Theory and Residual-based Block Bootstrap

Myunghwan Seo

There is a growing literature on unit root testing in threshold autoregressive models. This paper makes two contributions to the literature. First, an asymptotic theory is developed for unit root testing in a threshold a... Read more...

Keywords: threshold autoregression ; unit root test ; threshold cointegration ; residual-based block bootstrap

The Bootstrap and the Edgeworth Correction for Semiparametric Averaged Derivatives

Yoshihiko Nishiyama and Peter M Robinson

In a number of semiparametric models, smoothing seems necessary in order to obtain estimates of the parametric component which are asymptotically normal and converge at parametric rate. However, smoothing can inflate the... Read more...

Keywords: bootstrap ; edgeworth correction ; semiparametric averaged derivatives

Distribution Free Goodness-of-Fit Tests for Linear Processes

Miguel A. Delgado, Javier Hidalgo and Carlos Velasco

This article proposes a class of goodness-of-fit tests for the autocorrelation function of a time series process, including those exhibiting long-range dependence. Test statistics for composite hypotheses are functionals... Read more...

Keywords: nonparametric model checking ; spectral distribution ; linear processes ; martingale decomposition ; local alternatives ; omnibus ; smooth and directional tests ; long-range alternatives

Semiparametric Estimation for Stationary Processes whose Spectra have an Unknown Pole

We consider the estimation of the location of the pole and memory parameter, ?⁰ and a respectively, of covariance stationary linear processes whose spectral density function f(?) satisfies f(?) ~ C|? - ?<sup>0... Read more...

Keywords: spectral density estimation ; long memory processes ; gaussian processes

Efficiency Improvements in Inference on Stationary and Nonstationary Fractional Time Series

We consider a time series model involving a fractional stochastic component, whose integration order can lie in the stationary/invertible or nonstationary regions and be unknown, and additive deterministic component cons... Read more...

November 2004

Keywords: fractional processes ; efficient semiparametric estimation ; adaptive estimation ; nonstationary processes ; series estimation ; m-estimation

Forecasting the density of asset returns

Trino-Manuel Niguez and Javier Perote

In this paper we introduce a transformation of the Edgeworth-Sargan series expansion of the Gaussian distribution, that we call Positive Edgeworth-Sargan (PES). The main advantage of this new density is that it is well d... Read more...

October 2004

Keywords: density forecasting ; edgeworth-sargan distribution ; probability integral transformations ; p-value plots ; var

Cointegration in Fractional Systems with Deterministic Trends

Fabrizio Iacone and Peter M Robinson

We consider a cointegrated system generated by processes that may be fractionally integrated, and by additive polynomial and generalized polynomial trends. In view of the consequent competition between stochastic and det... Read more...

Keywords: fractional cointegration ; deterministic trends ; ordinary least squares estimation ; generalized least squares estimation ; wald tests.

Nonparametric Inference for Unbalanced Time Series Data

Oliver Linton

This paper is concerned with the practical problem of conducting inference in a vector time series setting when the data is unbalanced or incomplete. In this case, one can work only with the common sample, to which a sta... Read more...

Keywords: bootstrap ; efficient ; hac estimation ; missing data ; subsampling.

ROBUST COVARIANCE MATRIX ESTIMATION: 'HAC' Estimates with Long Memory/Antipersistence Correction

Smoothed nonparametric estimates of the spectral density matrix at zero frequency have been widely used in econometric inference, because they can consistently estimate the covariance matrix of a partial sum of a possibl... Read more...

Keywords: covariance matrix estimation ; long memory ; antipersistence correction ; hac estimates ; vector process ; spectral density.

The Distance between Rival Nonstationary Fractional Processes

Asymptotic inference on nonstationary fractional time series models, including cointegrated ones, is proceeding along two routes, determined by alternative definitions of nonstationary processes. We derive bounds for the... Read more...

Keywords: nonstationary fractional processes ; memory parameter estimation ; fractional cointegration ; rates of convergence.

Consistent Testing for Stochastic Dominance under General Sampling Schemes

Oliver Linton, Esfandiar Maasoumi and Yoon-Jae Whang

We propose a procedure for estimating the critical values of the extended Kolmogorov-Smirnov tests of Stochastic Dominance of arbitrary order in the general K-prospect case. We allow for the observations to be serially d... Read more...

December 2003

Keywords: bootstrap ; dominance ; kolmogorov-smirnov ; subsampling.

A Quantilogram Approach to Evaluating Directional Predictability

Oliver Linton and Yoon-Jae Whang

In this note we propose a simple method of measuring directional predictability and testing for the hypothesis that a given time series has no directional predictability. The test is based on the correlogram of quantile ... Read more...

November 2003

Keywords: correlogram ; dependence ; efficient markets ; quantiles.

A Bootstrap Causality Test for Covariance Stationary Processes

This paper examines a nonparametric test for Granger-causality for a vector covariance stationary linear process under, possibly, the presence of long-range dependence. We show that the test converges to a non-distributi... Read more...

Keywords: causality tests ; long range ; bootstrap tests.

Nonparametric Estimation of Homothetic and Homothetically Separable Functions

Arthur Lewbel and Oliver Linton

For vectors x and w, let r(x,w) be a function that can be nonparametrically estimated consistently and asymptotically normally. We provide consistent, asymptotically normal estimators for the functions g and h, where r(x... Read more...

October 2003

Keywords: cost function ; economic scale ; homogeneous function ; homothetic function ; index models ; nonparametric ; production function ; separability.

LARCH, Leverage and Long Memory

Liudas Giraitis, Remigijus Leipus, Peter M Robinson and Donatas Surgailis

We consider the long memory and leverage properties of a model for the conditional variance of an observable stationary sequence, where the conditional variance is the square of an inhomogeneous linear combination of pas... Read more...

Keywords: leverage ; long memory ; linear arch ; larch ; finiteness of moments.

A Local Instrumental Variable Estimation Method for Generalized Additive Volatility Models

We investigate a new separable nonparametric model for time series, which includes many ARCH models and AR models already discussed in the literature. We also propose a new estimation procedure based on a localization of... Read more...

Keywords: arch ; kernel estimation ; nonparametric ; volatility.

Nonparametric Neural Network Estimation of Lyapunov Exponents and a Direct Test for Chaos

Oliver Linton and Mototsugu Shintani

This paper derives the asymptotic distribution of the nonparametric neural network estimator of the Lyapunov exponent in a noisy system. Positivity of the Lyapunov exponent is an operational definition of chaos. We intro... Read more...

Keywords: artificial neural networks ; nonlinear dynamics ; nonlinear time series ; nonparametric regression ; sieve estimation

Semiparametric Regression Analysis under Imputation for Missing Response Data

Wolfgang Haerdle, Oliver Linton and Qihua Wang

We develop inference tools in a semiparametric regression model with missing response data. A semiparametric regression imputation estimator, a marginal average estimator and a (marginal) propensity score weighted estima... Read more...

Keywords: asymptotic normality ; empirical likelihood ; semiparametric imputation.

Estimating Semiparametric ARCH (8) Models by Kernel Smoothing Methods

We investigate a class of semiparametric ARCH(8) models that includes as a special case the partially nonparametric (PNP) model introduced by Engle and Ng (1993) and which allows for both flexible dynamics and flexible f... Read more...

Keywords: arch ; inverse problem ; kernel estimation ; news impact curve ; nonparametric regression ; profile likelihood ; semiparametric estimation ; volatility

An Alternative Bootstrap to Moving Blocks for Time Series Regression Models

The purpose of this paper is to introduce and examine two alternative, although similar, approaches to the Moving Blocks and subsampling Bootstraps to bootstrapping the estimator of the parameters for time series regress... Read more...

Keywords: least squares estimation ; long-range estimation ; bootstrap methods.

Asymptotic Expansions for Some Semiparametric Program Evaluation Estimators

Hidehiko Ichimura and Oliver Linton

We investigate the performance of a class of semiparametric estimators of the treatment effect via asymptotic expansions. We derive approximations to the first two moments of the estimator that are valid to 'second order... Read more...

Keywords: bandwidth selection ; kernel estimation ; program evaluation ; semiparametric estimation ; treatment effect.

Estimation of Semiparametric Models when the Criterion Function is not Smooth

Xiaohong Chen, Oliver Linton and Ingrid Van Keilegom

We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard smoothness conditions ... Read more...

Keywords: empirical processes ; non-smooth criterion ; semiparametric estimation ; stochastic equicontinuity.

Cointegration in Fractional Systems with Unkown Integration Orders

The semiparametric local Whittle or Gaussian estimate of the long memory parameter is known to have especially nice limiting distributional properties, being asymptotically normal with a limiting variance that is complet... Read more...

February 2003

Keywords: fractional cointegration ; unknown integration orders ; system estimates ; mixed normal asymptotics.

Edgeworth Expansions for Semiparametric Whittle Estimation of Long Memory

Liudas Giraitis and Peter M Robinson

September 2002

Keywords: edgeworth expansion ; long memory ; semiparametric estimation.

Denis Sargan: Some Perspectives

We attempt to present Denis Sargan's work in some kind of historical perspective, in two ways. First, we discuss some previous members of the Tooke Chair of Economic Science and Statistics, which was founded in 1859 and ... Read more...

Keywords: denis sargan ; tooke chair of economic science and statistics ; asymptotic theory and large models ; semiparametric econometrics.

Higher-Order Kernel Semiparametric M-Estimation of Long Memory

Marc Henry and Peter M Robinson

Econometric interest in the possibility of long memory has developed as a flexible alternative to, or compromise between, the usual short memory or unit root prescriptions, for example in the context of modelling cointeg... Read more...

Keywords: long memory ; semiparametric methods ; higher-order kernel ; m-estimation ; bias ; mean-squared error.

More Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors

Raymond J Carroll, Oliver Linton, Enno Mammen and Zhijie Xiao

We propose a modification of kernel time series regression estimators that improves efficiency when the innovation process is autocorrelated. The procedure is based on a pre-whitening transformation of the dependent vari... Read more...

Keywords: backfitting ; efficiency ; kernel estimation ; time series.

Nonparametric Neutral Network Estimation of Lyapunov Exponents and a Direct Test for Chaos

This paper derives the asymptotic distribution of nonparametric neural network estimator of the Lyapunov exponent in a noisy system proposed by Nychka et al (1992) and others. Positivity of the Lyapunov exponent is an op... Read more...

Keywords: artificial neural networks ; nonlinear dynamics ; nonlinear time series ; nonparametric regression ; sieve estimation.

Consistent Testing for Stochastic Dominance: A Subsampling Approach

We study a very general setting, and propose a procedure for estimating the critical values of the extended Kolmogorov-Smirnov tests of First and Second Order Stochastic Dominance due to McFadden (1989) in the general k-... Read more...

Keywords: prospect theory ; stochastic dominance ; stochastic equicontinuity ; subsampling.

Consistent Order Selection with Strongly Dependent Data and its Application to Efficient Estimation

Order selection based on criteria by Akaike (1974), AIC, Schwarz (1978), BIC or Hannan and Quinn (1979) HIC is often applied in empirical examples. They have been used in the context of order selection of weakly dependen... Read more...

February 2002

Keywords: order selection ; distributed lag models ; strong dependence.

Adapting to Unknown Disturbance Autocorrelation in Regression with Long Memory

Javier Hidalgo and Peter M Robinson

We show that it is possible to adapt to nonparametric disturbance auto-correlation in time series regression in the presence of long memory in both regressors and disturbances by using a smoothed nonparametric spectrum e... Read more...

September 2001

Keywords: time series regression ; long memory ; adaptive estimation.

Gaussian Estimation of Parametric Spectral Density with Unknown Pole

Liudas Giraitis, Javier Hidalgo and Peter M Robinson

We consider a parametric spectral density with power-law behaviour about a fractional pole at the unknown frequency w. The case of unknown w, especially w = 0, is standard in the long memory literature. When w is unknown... Read more...

August 2001

Keywords: long-range dependence ; unknown pole.

Determination of Cointegrating Rank in Fractional Systems

Peter M Robinson and Yoshihiro Yajima

This paper develops methods of investigating the existence and extent of cointegration in fractionally integrated systems. We focus on stationary series, with some discussion of extension to nonstationarity. The setting ... Read more...

Keywords: fractional cointegration ; long memory.

Finite Sample Improvement in Statistical Inference with I(1) Processes

D Marinucci and Peter M Robinson

Robinson and Marinucci (1998) investigated the asymptotic behaviour of a narrow-band semiparametric procedure termed Frequency Domain Least Squares (FDLS) in the broad context of fractional cointegration analysis. Here w... Read more...

Keywords: fully-modified ordinary least squares ; finite sample improvements ; statistical inference with i(1) processes ; monte carlo study ; parametric estimates.

Narrow-Band Analysis of Nonstationary Processes

The behaviour of averaged periodograms and cross-periodograms of a broad class of nonstationary processes is studied. The processes include nonstationary ones that are fractional of any order, as well as asymptotically s... Read more...

Keywords: nonstationary processes ; long-range dependence ; least squares estimation ; narrow-band estimation ; cointegration analysis.

Semiparametric Fractional Cointegration Analysis

Fractional cointegration is viewed from a semiparametric viewpoint as a narrow-band phenomenon at frequency zero. We study a narrow-band frequency domain least squares estimate of the cointegrating vector, and related se... Read more...

Keywords: semiparametric analysis ; fractional cointegration.

A Nonparametric Regression Estimator that Adapts to Error Distribution of Unknown Form

Oliver Linton and Zhijie Xiao

We propose a new estimator for nonparametric regression based on local likelihood estimation using an estimated error score function obtained from the residuals of a preliminary nonparametric regression. We show that our... Read more...

Keywords: adaptive estimation ; asymptotic expansions ; efficiency ; kernel ; local likelihood estimation ; nonparametric regression.

Prediction and Signal Extraction of Strong Dependent Processess in the Frequency Domain

Javier Hidalgo and Yoshihiro Yajima

We frequently observe that one of the aims of time series analysts is to predict future values of the data. For weakly dependent data, when the model is known up to a finite set of parameters, its statistical properties ... Read more...

Keywords: prediction ; strong dependence ; spectral density function ; canonical factorization ; signal extraction.

Parametric Estimation under Long-Range Dependence

Parametric estimation is discussed in a variety of models exhibiting long-range dependence.... Read more...

Keywords: parametric estimation ; long-range dependence.

The Estimation of Conditional Densities

Xiaohong Chen, Oliver Linton and Peter M Robinson

We discuss a number of issues in the smoothed nonparametric estimation of kernel conditional probability density functions for stationary processes. The kernel conditional density estimate is a ratio of joint and margina... Read more...

Keywords: conditional density estimation ; serial dependence ; bandwidth choice.

Estimating Multiplicative and Additive Hazard Functions by Kernel Methods

Oliver Linton, Jens Perch Nielsen and Sara van de Geer

We propose new procedures for estimating the univariate quantities of interest in both additive and multiplicative nonparametric marker dependent hazard models. We work with a full counting process framework that allows ... Read more...

February 2001

Keywords: additive model ; censoring ; kernel ; proportional hazards ; survival analysis

The Memory of Stochastic Volatility Models

A valid asymptotic expansion for the covariance of functions of multivariate normal vectors is applied to approximate autovariances of time series generated by nonlinear transformation of Gaussian latent variates, and no... Read more...

Keywords: stochastic volatility ; long memory ; nonlinear functions of gaussian processes

The Averaged Periodogram for Nonstationary Vector Time Series

Averaged periodogram; nonstationary processes; fractional Brownian motion.... Read more...

December 2000

Keywords: averaged periodogram ; nonstationary processes ; fractional brownian motion.

Whittle Estimation of ARCH Models

For a class of parametric ARCH models, Whittle estimation based on squared observations is shown to be inconsistent and asymptotically normal. Our conditions require the squares to have short memory autocorrelation, by c... Read more...

November 2000

Keywords: arch models ; whittle estimation.

Testing of Seasonal Fractional Integration in UK and Japanese Consumption and Income

L A Gil-Alaña and Peter M Robinson

The seasonal structure of quarterly UK and Japanese consumption and income is examined by means of fractionally-based tests proposed by Robinson (1994). These series were analysed from an autoregressive unit root viewpoi... Read more...

Keywords: fractional integration ; nonstationarity ; seasonality

Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems

Steve Berry, Oliver Linton and Ariel Pakes

We provide an asymptotic distribution theory for a class of Generalized Method of Moments estimators that arise in the study of differentiated product markets when the number of observations is associated with the number... Read more...

Keywords: choice models ; method of moments ; multinominal ; random coefficients ; vertical model

Edgeworth Approximations for Semiparametric Instrumental Variable Estimators and Test Statistics

We stablish the validity of higher order asymptotic expansions to the distribution of a version of the nonlinear semiparametric instrumental variable considered in Newey (1990) as well as to the distribution of a Wald st... Read more...

Keywords: bandwidth selection ; edgeworth approximation ; instrumental viariables ; kernel estimation ; local polynomials.

Testing the Capital Asset Pricing Model Efficiently under Elliptical Symmetry: A Semiparametric Approach

Douglas J Hodgson, Oliver Linton and Keith Vorkink

Adaptive estimation; capital asset pricing model; efficiency... Read more...

Keywords: adaptive estimation ; capital asset pricing model ; efficiency

Nonparametric Estimation with Aggregated Data

We introduce a kernel-based estimator of the density function and regression function for data that have been grouped into family totals. We allow for a common intra-family component but require that observations from di... Read more...

Keywords: aggregated data ; deconvolution ; grouped data ; kernel ; nonparametric regression

Simulated Asymptotic Least Squares Theory

Ramdan Dridi

We develop in this paper a general econometric methodology referred to as the Simulated Asymptotic Least Squares (SALS). It is shown that this approach provides a unifying theory for 'approximation-based' or simulation-b... Read more...

Keywords: simulated asymptotic least squares ; approximation-based and simulation-based estimation ; efficiency bounds in direction ; gmm ; snls ; spml ; smm ; ii ; gii ; emm.

Noise and Competition in Strategic Oligopoly

Ramdan Dridi and Laurent Germain

Focusing on homogeneous beliefs, we can distinguish two commonly shared ideas that, i) the competition between informed traders destroys their trading profits, ii) trading with a noisy signal brings about a loss in the e... Read more...

Keywords: competition ; optimal noise ; price manipulation

Semi-Parametric Indirect Inference

Ramdan Dridi and Eric Renault

We develop in this paper a generalization of the Indirect Inference (II) to semi-parametric settings and termed Semi-parametric Indirect Inference (SII). We introduce a new notion of Partial Encompassing which lays the e... Read more...

Keywords: indirect inference ; partial encompassing ; pseudo-true value of interest ; structural models ; instrumental models ; wald encompassing tests.

Whittle Pseudo-Maximum Likelihood Estimation for Nonstationary Time Series - (Now published in 'Journal of the American Statistical Association', 95, (2000), pp.1229-1243.)

Whittle pseudo-maximum likelihood estimates of parameters for stationary time series have been found to be consistent and asumptotically normal in the presence of long-range dependence. Generalizing the definition of the... Read more...

Keywords: long-range dependence ; nonstationary long memory time series ; nonstationary fractional models ; frequency domain estimation ; tapering.

Edgeworth Expansions for Spectral Density Estimates and Studentized Sample Mean - (Now published in 'Economic Theory', 17 (2001), pp.497-539.

We establish valid Edgeworth expansions for the distribution of smoothed nonparametric spectral estimates, and of studentized versions of linear statistics such as the same mean, where the studentization employs such a n... Read more...

Keywords: edgeworth expansions ; nonparametric spectral estimates ; stationary gaussian series ; studentized sample mean ; bandwidth choice.

Nonparametric Censored and Truncated Regression

The nonparametric censored regression model, with a fixed, known censoring point (normalized to zero), is y = max[0,m(x) + e], where both the regression function m(x) and the distribution of the error e are unknown. This... Read more...

Keywords: semiparametric ; nonparametric ; censored regression ; truncated regression ; tobit ; latent variable

Adaptive Varying-Coefficient Linear Models

Zongwu Cai, Jianqin Fan and Qiwei Yao

Varying-coefficient linear models arise from multivariate nonparametric regression, nonlinear time series modelling and forecasting, functional data analysis, longitudinal data analysis, and others. It has been a common ... Read more...

Keywords: akaike information criterion ; backfitting algorithm ; generalised cross-validation ; local linear regression ; local significant variable selection ; one-step estimation ; smoothing index ; varying-coefficient linear models.

Nonparametric Test for Causality with Long-Range Dependence - (Now published in 'Econometrica', 68, (2000) pp.1465-1490.

This paper introduces a nonparametric Granger-causality test for covariance stationary linear processes under, possibly, the presence of long-range dependence. We show that the test is consistent and has power against co... Read more...

Keywords: causality ; long-range dependence ; spectral analysis ; distributed lag model ; consistent test

The Existence and Asymptotic Properties of a Backfitting Projection Algorithm under Weak Conditions

Oliver Linton, Enno Mammen and N Nielsen

We derive the asymptotic distribution of a new backfitting procedure for estimating the closest additive approximation to a nonparametric regression function. The procedure employs a recent projection interpretation of p... Read more...

Keywords: additive models ; alternating projections ; backfitting ; kernel smoothing ; local polynomials ; nonparametric regression.

Yield Curve Estimation by Kernel Smoothing Methods

Oliver Linton, Enno Mammen, Jens Perch Nielsen and C Tanggaard

We introduce a new method for the estimation of discount functions, yield curves and forward curves from government issued coupon bonds. Our approach is nonparametric and does not assume a particular functional form for ... Read more...

Keywords: coupon bonds ; kernel estimation ; hilbert space ; nonparametric regression ; term structure estimation ; yield curve ; zero coupon.

Stationarity and Memory of ARCH Models

Paolo Zaffaroni

Sufficient conditions for strict stationarity of ARCH(8) are established, without imposing covariance stationarity and for any specification of the conditional second moment coefficients. GARCH(p,q) as well as the case o... Read more...

Keywords: arch (8) ; garch(p ; q) ; nonlinear moving average representation ; strict and weak stationarity ; memory.

A Model for Long Memory Conditional Heteroscedasticity - (Now published in 'Annals of Applied Probability', 10 (2000), pp.1002-1024.)

Liudas Giraitis, Peter M Robinson and Donatas Surgailis

Keywords: long-range dependence ; semiparametric model ; rates of convergence ; adaptive bandwidth selection.

On Intercept Estimation in the Sample Selection Model

Marcia M Schafgans

We provide a proof of the consistency and asymptotic normality of the estimator suggested by Heckman (1990) for the intercept of a semiparametrically estimated sample selection model. The estimator is based on 'identific... Read more...

January 2000

Keywords: asymptotic normality ; sample selection model ; semiparametric estimation

Adaptive Semiparametric Estimation of the Memory Parameter - (Now published with revised title, Adaptive Rate-Optimal Estimation of the Memory Parameter, in 'Journal of Multivariate Analysis, 72 (2000), pp.183-207.)

Liudas Giraitis, Peter M Robinson and Alexander Samarov

Keywords: long-range dpendence ; semiparametric model ; rates of convergence ; adaptive bandwidth selection.

Contemporaneous Aggregation of GARCH Processes

We study the impact of large cross-sections of contemporaneous aggregation of GARCH processes and of dynamic GARCH factor models. The results crucially depend on the shape of the cross-sectional distribution of the GARCH... Read more...

Keywords: contemporaneous aggregation ; garch ; conditionally heteroskedastic factor models ; common and idiosyncratic risk ; nonlinearity ; memory

Studentization in Edgworth Expansions for Estimates of Semiparametric Index Models - (Now published in C Hsiao, K Morimune and J Powell (eds): 'Nonlinear Statistical Modeling' (Festschrift for Takeshi Amemiya), (Cambridge University Press, 2001), pp.197-240.)

We establish valid theoretical and empirical Edgeworth expansions for density-weighted averaged derivative estimates of semiparametric index models.... Read more...

October 1999

Keywords: edgeworth expansions ; semiparametric estimates ; averaged derivatives

Edgeworth Expansions for Semiparametric Averaged Derivatives - (Now published in 'Econometrica', 68 (2000), pp.931-979.)

A valid Edgeworth expansion is established for the limit distribution of density-weighted semiparametric averaged derivative estimates of single index models. The leading term that corrects the normal limit varies in mag... Read more...

Keywords: edgeworth expansion ; semiparametric estimates ; averaged derivatives

Testing for the Presence of a Random Walk in Series with Structural Breaks - (Now published in 'Journal of Time Series Analysis', 22 (2001), pp.127-150.)

Fabio Busetti and Andrew C Harvey

The paper considers tests for the presence of a random walk component in a stationary or trend stationary time series and extends them to series which contain structural breaks. The locally best invariant (LBI) test is d... Read more...

December 1998

Keywords: brownian bridge ; cram?r-von mises distribution ; intervention analysis ; locally best invariant test ; structural time series model ; unobserved components.

Variance-Type Estimation of Long Memory - (Now published in 'Stochastic Processes and their Applications', 29 (1999), pp.1-24.)

The aggregation procedure when a sample of length N is divided into blocks of length m = o(N), m ? ? and observations in each block are replaced by their sample mean, is widely used in statistical inference. Taqqu, Tever... Read more...

October 1998

Keywords: long memory ; aggregation ; semiparametric model

Seasonal and Cyclical Long Memory - (Now published in S Ghosh (ed): 'Asymptotics, Nonparametrics and Time Series: A Tribute to Madam Lal Puri (Marcel Decker, 1999), pp.115-145.)

Josu Artech and Peter M Robinson

There has recently been great interest in time series with long memory, namely series whose dependence decays slowly in the sense that autocovariances are not summable and the spectral density is unbounded. This concept ... Read more...

September 1998

Keywords: long memory ; seasonal time series ; cyclic time series

Semiparametric Inference in Seasonal and Cyclical Long Memory Processes - (Now published in 'Journal of Time Series Analysis', 21 (2000), pp.1-25.)

Several semiparametric estimates of the memory parameter in standard long memory time series are now available. They consider only local behaviour of the spectrum near zero frequency, about which the spectrum is symmetri... Read more...

Keywords: semiparametric inference ; long memory ; seasonality

Long and Short Memory Conditional Heteroscedasticity in Estimating the Memory Parameter of Levels - (Now published in 'Econometric Theory', 15 (1999), pp.299-336.)

Semiparametric estimates of long memory seem useful in the analysis of long financial time series because they are consistent under much broader conditions than parametric estimates. However, recent large sample theory f... Read more...

August 1998

Keywords: long memory ; dynamic conditional heteroscedasticity ; semiparametric estimation

Alternative Forms of Fractional Brownian Motion - (Now published in 'Journal of Statistical Planning and Inference', 80 (1999), pp.111-122.)

It is pointed out that two contradictory definitions of fractional Brownian motion are well established, one prevailing in the probabilistic literature, the other in the econometric literature. Each is associated with a ... Read more...

Keywords: frational brownian motion ; nonstationary time series ; long-range dependence

Band Spectrum Regression for Cointegrated Time Series with Long Memory Innovations

D Marinucci

Band spectrum regression is considered for cointegrated time series with long memory innovations. The estimates we advocate are shown to be consistent when cointegrating relationships among stationary variables are inves... Read more...

Keywords: long-range dependence ; band spectrum regression ; cointegration

Weak Convergence of Multivariate Fractional Processes - (Now published in 'Stochastic Processes and their Applications', 80 (1999), pp.103-120.)

Weak convergence to a form of fractional Brownian motion is established for a wide class of nonstationary fractionally integrated multivariate processes. Instrumental for the main argument is a result of some independent... Read more...

Keywords: nonstationary fractional integration ; functional central limit theorem

Aggregation of Simple Linear Dynamics: Exact Asymptotic Results

Marco Lippi and Paolo Zaffaroni

his paper deal with aggregation of AR(1) micro variables driven by a common and idiosyncratic shock with random coefficients. We provide a rigorous analysis, based on results on sums of r.v.'s with a possibly finite firs... Read more...

Keywords: aggregation ; idiosymcratic-driven fluctuations ; long memory ; nonstationarity.

Semiparametric Frequency Domain Analysis of Fractional Cointegration - (Revised version forthcoming in P M Robinson: 'Time Series with Long Memory' (Oxford University Press).

The concept of cointegration has principally been developed under the assumption that the raw data vector zt is I(1) and the cointegrating residual et is I(0), but is also of interest in more general, including fractiona... Read more...

Keywords: fractional cointegration ; narrow-band frequency analysis

Interpolating Exogenous Variables in Open Continuous Time Dynamic Models

J R McCrorie

As the exact discrete model induced by an open continuous time system depends on the continous time paths of the exogenous variables, these need to be interpolated for the purpose of estimation. We examine some recently ... Read more...

December 1997

Keywords: continous time ; exact discrete model ; aliasing ; exogenous variables ; interpolation

Deriving the Exact Discrete Analog of a Continuous Time System

We present a method of deriving the exact discrete model satisfied by equispaced data generated by a system of linear stochastic differential equations without implying the usual restrictions on observed discrete data th... Read more...

Keywords: continuous time ; exact discrete model ; random measure ; matrix exponential

A Nonparametric Test for I(0) - (Now published in 'Review of Economic Studies', 65 (1998), pp.475-495.)

Ignacio Lobato and Peter M Robinson

There is frequently interest in testing that a scalar or vector time series is I(0), possibly after first- differencing or other detrending, while the I(0) assumption is also taken for granted in autocorrelation-consiste... Read more...

November 1997

Keywords: nonparametric testing ; weak dependence ; long memory

Some Practical Issues in Maximum Simulated Likelihood

In this paper, I explore ways of recapturing the efficiency property for estimators that rely on simulation. In particular, I show that this can be achieved by exploiting two-step maximum stimulated likelihood (SL) estim... Read more...

Keywords: simulation estimation ; maximum simulated likelihood ; limited dependent variable models ; antithetic acceleration.

Inference-without-Smoothing in the Presence of Nonparametric Autocorrelation - (Now published in 'Econometrica', 66 (1998), pp.1163-1182.)

In a number of econometric models, rules of large-sample inference require a consistent estimate of f(0), where f (?) is the spectral density matrix of yt = ut?xt, for covariance stationary vectors ut, xt. Typically yt i... Read more...

October 1997

Keywords: autocorrelation-consistent variance estimation ; long-range dependence ; simultaneous equations systems.

Large-Sample Inference for Nonparametric Regression with Dependent Errors - (Now published in 'Annals of Statistics', 28 (1997), pp.2054-2083.)

A central limit theorem is given for certain weighted sums of a covariance stationary process, assuming it is linear in martingale differences, but without any restriction on its spectrum. We apply the result to kernel n... Read more...

September 1997

Keywords: central limit theorem ; nonparametric regression ; autocorrelation ; long-range dependence

Beta Convergence

C Michelacci and Paolo Zaffaroni

Unit root in output, an exceptional 2% rate of convergence, and no change in the underlying dynamics of output seems to be three stylized facts that can not go together. This paper extends the Solow-Swan growth model all... Read more...

Keywords: growth model ; convergence ; long memory ; aggregation

Gaussian Estimation of Long-Range Dependent Volatility in Asset Prices

Asset returns have a very complicated dynamic pattern. Yet they display regularity across different assets and periods. We consider a new family of volatility models which account for such patterns, focussing in particul... Read more...

Keywords: stochastic volatility ; long memory ; asymptotics.

The Method of Simulated Scores for the Estimation of LDV Models

V A Hajivassiliou and DL McFadden

The method of simulated scores (MSS) is presented for estimating limited dependent variables models (LDV) with flexible correlation structure in the unobservables. We propose simulators that are continuous in the unknown... Read more...

Keywords: limited dependent variable models ; simulation estimation ; gibbs resampling

Messy Time Series: A Unified Approach - (Now published in 'Advances in Econometrics', 13 (1998)pp.103-143.)

Andrew C Harvey, Siem Jan Koopman and J Penzer

Many series are subject to data irregularities such as missing values, outliers, structural breaks and irregular spacing. Data can also be messy, and hence difficult to handle by standard procedures, when they are intrin... Read more...

Keywords: arima models ; data aggregation ; importance sampling ; irregularly spaced data ; kalman filter ; missing observations ; outliers ; smoother ; splines ; state space form ; structural breaks ; structural time series models ; weekly observations.

Semiparametric Estimation of a Sample Selection Model: A Simulation Study

Standard approaches to the estimation of sample selection models are known to be inconsistent under non-normality. In particular, this paper considers the two-step Heckman (1976, 1979) estimator of the interecept of the ... Read more...

Keywords: sample selection models ; semiparametric estimation ; error distributions ; bandwidth parameter ; two-step parametric estimator.

Gender Wage Differences in Malaysia: Parametric and Semiparametric Estimation

This paper is an empirical study on the labor force in (Peninsular) Malaysia. It applies both parametric and semiparametric sample selection methods to the estimation of wage equations. These equations are then used to a... Read more...

Keywords: malaysia ; gender wage differences ; gender discrimination ; wage determining characteristics ; parametric and semiparametric estimation.

Testing Game-Theoretic Models of Price Fixing Behaviour

This paper analyses price fixing by the Joint Executive Committee railroad cartel from 1880 to 1886 and develops tests of two game-theoretic models of tacit collusion. The first model, due to Abreu, Pearce and Stacchetti... Read more...

Keywords: price-fixing ; trigger-price mechanism ; switching regression models ; measurement errors ; simulation estimation.

Rate Optimal Semiparametric Estimation of the Memory Parameter of the Gaussian Time Serieswith Long-Range Dependence - (Now published in 'Journal of Time Series Analysis', 18 (1997), pp.49-60.)

There exist several estimators of the memory parameter in long-memory time series models with mean µ and the spectrum specified only locally near zero frequency. In this paper we give a lower bound for the rate of conver... Read more...

February 1997

Keywords: long-range dependence ; semiparametric models ; optimal rates of convergence ; lower bounds

Nonlinear Time Series with Long Memory: A Model for Stochastic Volatility - (Now published in 'Journal of Statistical Planning and Inference', 68 (1998), pp.359-371.)

We introduce a nonlinear model of stochastic volatility within the class of ?product type? models. It allows different degrees of dependence for the ?raw? series and for the ?squared? series, for instance implying weak d... Read more...

January 1997

Keywords: long memory ; two-shock model ; stochastic volatility

Modelling Nonlinearity and Long Memory in Time Series - (Now published in 'Nonlinear Dynamics and Time Series', C D Cutler and D T Kaplan (eds), Fields Institute Communications, 11 (1997), pp.61-170.)

We discuss models that impart a form of long memory in raw time series xt or instantaneous functions thereof, in particular . on the basis of a linear or nonlinear model. The capacity of linear models for xt to imply lon... Read more...

Keywords: long memory ; arch ; nonlinear moving average. jel no.: c22

Time Series Regression with Long Range Dependence - (Now published in 'Annals of Statistics', 25, (1997)pp.2054-2083.)

A general limit theorem is established for time series regression estimates which include generalized least squares, in the presence of long range dependence in both errors and stochastic regressors. The setting and resu... Read more...

Keywords: long-range dependence ; linear regression ; generalized least squares ; nonlinear regression

Testing of Unit Root and Other Nonstationary Hypotheses in Macroeconomic Time Series - (Now published in 'Journal of Econometrics', 80, 1997, pp.241-268.)

Recently proposed tests for unit root and other nonstationarity of Robinson (1994a) are applied to an extended version of the data set used by Nelson and Plosser (1982). Unusually, the tests are efficient (against approp... Read more...

December 1996

Keywords: nonstationarity ; macroeconomic time series ; fractional integration

Autocorrelation-Robust Inference - (Now published in 'Handbook of Statistics', vol.15, G S Maddala and C R Rao (eds), Elsevier Science Publishers BV (1997), pp.267-298.)

We consider statistical inference in the presence of serial dependence. The main focus is on use of statistics that are constructed as if no dependence were believed present, and are asymptotically normal in the presence... Read more...

Keywords: time series ; variance estimation ; spectral methods

Multivariate Structural Time Series Models - (Now published in 'System Dynamics in Economic and Financial Models', CHeij, H Schumacher, B Hanzon and C Praagman (eds.) John Wiley & Sons, Chichester (1997), pp.269-298.)

Andrew C Harvey and Siem Jan Koopman

Much of economic analysis presupposes that certain economic time series can be decomposed into trends and cycles. Structural time series models are explicitly set up in terms of such unobserved components. This paper set... Read more...

Keywords: co-integration ; commontrends ; cycles ; kalman filter ; structural time series model ; triangular representation

Testing for a Slowly Changing Level with Special Reference to Stochastic Volatility - (Now published in 'Journal of Econometrics', 87 (1998), pp.167-189.)

Andrew C Harvey and Mariane Streibel

A test for the presence of a stationary first-order autoregressive process embedded in white noise is constructed so as to be relatively powerful when the autoregressive parameter is close to one. This is done by setting... Read more...

Keywords: exchange rates ; garch model ; locally best invariant test ; serial correlation ; stochastic volatility ; unobserved components ; von mises distribution.

Nonparametric Estimation with Strongly Dependent Multivariate Time-Series - (Now published in 'Journal of Time Series Analysis',18 (1997)pp.95-122.)

Smooth nonparametric kernel density and regression estimators are studied when the data is strongly dependent. In particular, we derive Central (and Noncentral) Limit Theorems for the kernel density estimator of a multiv... Read more...

February 1996

Keywords: nonparametric ; strong dependence ; hermite and appell polynomials ; rosenblatt and hermite pocesses.

Spectral Analysis for Bivariate Time Series with Long Memory - (Now published in 'Econometric Theory',12 (1997)pp.773-792.)

This paper provides limit theorems for special density matrix estimators and functionals of it for a bivariate co variance stationary process whose spectral density matrix has singularities not only at the origin but pos... Read more...

Keywords: long memory ; spectral density matrix ; spectral estimation ; weighted autocovariance

Aggregate and Regional Disagggregate Fluctuations (Now published in Empirical Economics (1996), vol.21, no.1, pp.137-159.)

This paper models fluctuations in regional disaggregates as a nonstationary, dynamically evolving distribution. Doing so enables study of the dynamics of aggregate fluctuations jointly with those of the rich cross-sectio... Read more...

August 1995

Keywords: aggregate disturbance ; business cycle ; distribution dynamics ; regional fluctuation ; stochastic kernel.

The Modelling and Seasonal Adjustment of Weekly Observations - (Now published in 'Journal of Business and Economic Statistics', 15 (1997), pp.354-368.)

Andrew C Harvey, Siem Jan Koopman and Marco Riani

A number of important economic time series are recorded on a particular day every week. Seasonal adjustment of such series is difficult because the number of weeks varies between 52 and 53 and the position of the recordi... Read more...

Keywords: structural time series model ; seasonal adjustment ; trend extraction ; filtering and smoothin algorithms ; money supply.

Measuring Core Inflation (Now published in Economic Journal, vol. 105, No. 432 (September 1995), pp.1130-1144.)

Danny Quah and Shaun P. Vahey

In this paper, we argue that measured (RPI) inflation is conceptually mismatched with core inflation: the difference is more than just 'measurement error'. We propose a technique for measuring core inflation, based on an... Read more...

Keywords: core inflation ; vector autoregression ; dynamic restrictions

Empirics for Economic Growth and Convergence (Now published in European Economic Review, vol.40, no.6 (1996), pp.1353-1375.)

The convergence hypothesis has generated a huge empirical literature: this paper critically reviews some of the earlier key findings, clarifies their implications, and relates them to more recent results. Particular atte... Read more...

Keywords: evolving distributions ; galton's fallacy ; polarization ; regional dynamics ; stochastic kernel ; unit root.

Convergence Empirics Across Economies with (Some)Capital Mobility (Now published in Journal of Economic Growth, vol.1, No.1 ( March 1996),pp.95-124.)

This paper reinterprets a simple model of growth and fluctuations across many economies to allow explicitly characterizing the dynamically evolving corss-economy distribution of income. Such a framework provides a more n... Read more...

Keywords: growth and fluctuations ; cross-country distribution of income ; convergence hypothesis ; intra-distribution mobility ; capital investment

Exploiting Cross Section Variation for Unit Root Inference in Dynamic Data (Now published in Economics Letters 44 (1), 1994, pp.9-19.)

This paper considers unit root regressions in data having simultaneously extensive cross-section and time-series variation. The standard least-squares estimators in such data structures turn out to have an asymptotic dis... Read more...

Keywords: random field ; time series ; panel data ; unit root

Estimation and Testing of Stochastic Variance Models

Andrew C Harvey and N.G. Shephard

A stochastic variance model may be estimated by quasi-maximum likelihood procedure by transforming to a linear state space form. The properties of observations corrected for heteroscedasticity can be derived. A model wit... Read more...

Keywords: generalised least squares ; heteroscedasticity ; quasi-maximum likelihood ; smoothing ; volatiliy.

Seasonality in Dynamic Regression Models (Now published in Economic Journal 104 (1994), pp.1324-1345.)

Andrew C Harvey and Andrew Scott

This paper examines the implications of treating seasonality as an unobserved component which changes slowly over time. This approach simplifies the specification of dynamic relationships by separating non-seasonal from ... Read more...

Keywords: seasonality ; dynamic relationships ; stable error correction model ; autoregressive models

Galton's Fallacy and Tests of the Convergence Hypothesis (Now published in Scandinavian Journal of Economics 95 (4), 1993, pp.427-443.)

Recent tests for the convergence hypothesis derive from regressing average growth rates on initial levels: a negative initial coefficient is interpreted as convergence. These tests turn out to be plagued by Galton's clas... Read more...

Keywords: convergence hypothesis ; regressing average growth rates ; galton's fallacy ; coefficients of arbitrary signs ; divergence of cross-country incomes.

The Multivariate Invariance Principle for Globally Nonstationary Processes, with an Application to I(2) Models

James Davidson

A multivariate invariance principle is given for dependent processes exhibiting trending variances and other types of global nonstationarity. The limit processes obtained in these results are not Brownian motion, but mem... Read more...

Keywords: multivariate invariance principle ; dependent processes ; trending variances ; global nonstationarity ; gaussian diffusion process ; stochastic integrals ; integrated variables.

Conditions for Strong and Uniform Mixing in Linear Processes

A sufficiency condition for strong mixing in infinite order moving average processes due to Gorodetski (1977) is extended, showing how smoothness conditions on the marginal distributions can be traded off against summabi... Read more...

Keywords: strong mixing ; uniform mixing ; moving avrage process

Deletion Diagnostics and Transformations for Time Series

A.C. Atkinson and N.G. Shephard

Deletion diagnostics are developed for structural time series models. These show the effect of the deletion of individual observations on residuals and on the estimates of regression parameters. The methods are extended ... Read more...

Keywords: deletion diagnostics ; structural time series models ; regression parameters ; index plots.

Quasi-Maximum Likelihood Estimation of Stochastic Variance Models

Esther Ruiz

Changes in variance or volatility over time can be modelled using stochastic volatility (SV) models. This approach is based on treating the variance as an unobservable variable, the logarithm of which is modelled as a li... Read more...

Keywords: stochastic variance models ; volatility ; asymptotic and finite sample properties ; qml estimator ; generalized method of moments ; autoregression.

The Central Limit Theorem for Globally Nonstationary Near-Epoch Dependent Functions of Mixing Processes: The Asymptotically Degenerate Case (Now published in Economic Theory 9 (1993), pp.402-412.)

The central limit theorem in Davidson (1992a) is extended to allow cases where the variances of sequence coordinates can be tending to zero. A trade off is demonstrated between the degree of dependence (mixing size) and ... Read more...

Keywords: central limit theorem ; sequence coordinates ; rate of degeneration ; mixing processes ; martingale difference.

An L1-Convergence Theorem for Heterogeneous Mixingale Arrays with Trending Moments (Now published in Statistics & Probability Letters 16 (1993), pp.301-304.)

This paper gives a generalization of an L1-convergence theorem for dependent processes due to Andrews (1988). Among the cases covered by this result are weak laws of large numbers of random sequences {X1} having moments ... Read more...

Keywords: l1-convergence theorem ; heterogeneous mixingale arrays ; weak laws of large numbers ; random sequences ; trending moments.

Exact Score for Time Series Models in State Space Form (Now published in Biometrika (1992), 79, 4, pp.283-6.)

Siem Jan Koopman and N.G. Shephard

The score vector for a time series model which fits into the Gaussian state space form can be approximated by numerically differentiating the log-likelihood. If the parameter vector is of length p, this involves the runn... Read more...

Keywords: smoothing ; kahman filter ; em algorithm ; unobserved components model ; profile likelihood.

Detrending, Stylized Facts and The Business Cycle (Now published in Journal of Applied Econometrics, vol.8 (1993), pp.231-247.)

Andrew C Harvey and Albert Jaeger

The stylized facts of macroeconomic time series can be presented by fitting structural time series models. Within this framework, we analyze the consequences of the widely used detrending technique popularized by Hodrick... Read more...

Keywords: detrending ; filters ; persistence ; structural time series models.

A Local Scale Model: An Unobserved Component Alternative to Integrated GARCH Processes (Now published in Journal of Econometrics, vol.60, (1994), pp.181-202.)

N.G. Shephard

Central Limit Theorems for Nonstationary Mixing Processes and Near-Epoch Dependent Functions (Now published in Economic Theory, vol.8, no.3 (1992).)

Cointegration in recursive systems: the structure of wage and price determination in the united kingdom (now published in economic journal res/aute 1990 conference supplement, vol.101, march 1991, pp.239-251.).

James Davidson and Stephen Hall

Least-Squares Autoregression with Near-Unit Root

Jan R. Magnus and Thomas J. Rothenberg

The Exact Multiperiod Mean-Square Forecast Error for the First-Order Autoregressive Model with an Intercept (Now published in Journal of Econometrics, 42, (1989), pp.157-179.)

Jan R. Magnus and Bahram Pesaran

The Bias of Forecasts from a First-Order Autoregression (Now published in Econometric Theory, 7, (1991), pp.222-235.)

Cointegration in linear dynamic systems (now published in journal of time series analysis, 12,1 (1991), pp.41-62.), the exact multiperiod mean-square forecast error for the first-order autoregressive model (now published in journal of econometrics, 39, (1988), pp.327-346.).

Asraul Hoque, Jan R. Magnus and Bahram Pesaran

The Exact Moments of a Ratio of Quadratic Forms in Normal Variables (Now published in Annales d'Economie et de Statistique, Vol.1 (1986).)

Jan R. Magnus

A Note on Instrumental Variables and Maximum Likelihood Estimation Procedures (Now published in Annales d'Economie et de Statistique, 10, (1988), pp.121-138.)

Alberto Holly and Jan R. Magnus

Some Properties of the Bordered Hessian Matrix (Now published in Advanced Lectures in Quantitative Economics (ed. F. van der Ploeg), (Academic Press, London, 1990), pp.583-604.)

Some evidence on the robustness of nonlinear fiqml, symmetry, 0-1 matrices, and jacobians: a review (now published in econometric theory, vol.2 (1986).).

Jan R. Magnus and H. Neudecker

Interfuel substitution and separability in Dutch Manufacturing: A Multivariate Error Components Approach (Now published in Applied Economics, 19, (1987), pp.1639-1664.)

Jan R. Magnus and Alan D. Woodland

Money Disequilibrium: An Approach to Modelling Monetary Phenomena in the U.K. (Now published in The Operation and Regulation of Financial Markets, edited by Charles Goodhart, David Llewellyn and David Currie, (Macmillan, 1987).)

A generalization of the univariate logit model and its bivariate extension.

Takamitsu Sawa

On Differentiating Eigenvalues and Eigenvectors (Now published in Econometric Theory, Vol.1 (1985).)

Asymptotic normality of the maximum likelihood estimation in the nonlinear regression model with normal errors (now published in econometric theory, vol.2 (1986) pp.374-412.).

Risto D.H. Heijmans and Jan R. Magnus

Error Correction Systems

Consistent maximum likelihood estimation of the nonlinear regression model with normal errors (now published in journal of econometrics, vol.32 (1986).), on the asymptotic normality of the maximum likelihood estimator with dependent observations (now published in statistica neerlandia, vol.40 (1986).), econometric modelling of the sterling effective exchange rate (now published in review of economic studies, lii (1985), pp.231 240.), on the consistency of the maximum likelihood estimator with dependent observations (now published in the journal of econometrics, vol.32 (1986).), money demand stability in the u.k. and error correction mechanism.

Manfred Keil

Computer Price Functions (Now published in Oxford Bulletin of Economics and Statistics, Vol.45, No.4, (1983), pp.339-356.)

Anthony Horsley and G.M.P. Swann

Alternative Estimates for Systems with Log-Linear Stochastic Equations and Linear Identities

An econometric model of the money supply and balance of payments in the united kingdom.

James Davidson and Manfred Keil

Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of Inflationary Expectations (Now published in Econometrica, Vol.50, July 1982, pp.987-1007.)

Robert F. Engle

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Journal of Econometric Methods

• Online ISSN: 2156-6674
• Type: Journal
• Language: English
• Publisher: De Gruyter
• First published: January 1, 2011
• Publication Frequency: 2 Issues per Year
• Audience: researchers, practitioners and instructors in the field of econometrics

Department of Economics

Econometrics/research methods.

• Undergraduate
• Areas of Study

Econometrics is a set of statistical tools that allows economists to test hypotheses using real world data.

Relevant Courses

• ECON1620 Introduction to Econometrics
• ECON1629 Applied Research Methods
• ECON1630 Mathematical Econometrics I
• ECON1640 Mathematical Econometrics II
• ECON1650 Financial Econometrics
• ECON1660 Big Data
• ECON1670 Advanced Topics in Econometrics
• ECON1740 Mathematical Finance

Toru Kitagawa

Soonwoo kwon, andriy norets, jonathan roth, susanne schennach.

Research Paper in Introductory Econometrics

Through this independent research project, students experience the process of doing real economics research using appropriate econometric methods.

Expand for more detail

Activity Classification and Connections to Related Resources Collapse

Grade level, learning goals.

Students will:

• Develop an understanding of how economists conduct applied research. This means more than simply learning the statistical methods. In order to use the methods appropriately, students must know the underlying theory as well as the existing literature on the issue.
• Develop important (marketable) computer skills. To handle the large data sets and complex econometric techniques several specialized software packages have emerged in the market. The program used in this class SAS. It is one of the most widely-used statistical programming languages in the world. While some work can be done with minimal knowledge of SAS coding, it is important for students to learn the basics of SAS syntax and logic to be an efficient econometrician.
• Develop the ability to critically evaluate others' research.
• Develop written and oral communication skills.

Context for Use

Teaching materials, teaching notes and tips.

The key is scaffolding the 6-week process so that students end with an econometrically rigorous and (relatively) complete paper. Of course, there is no way these kinds of papers can meet the level of thoroughness that you would expect out of a semester- or year-long independent research project. The instructor has to make deliberate decisions on where students should and should not devote their scarce time.

One area I sacrifice in is the literature. This is not a thesis and does not require a full-blown literature review. Having said that, students do need to have read at least a handful (6-8 is a reasonable expectation) of papers on the topic. I should note that many of these papers are related to other term papers students have written or are writing in their upper-level electives. For example, a student writing a paper about the literature on the gender-wage gap for a labor class will already have an extensive knowledge of the literature. The implication here is that there are spillovers from other classes that make use of to make this project successful. What they will not have done in that class, however, is to have done a full-blown, rigorous econometric study. Many of the papers I see in econometrics are like this.

The most challenging part is to get them to develop enough of a theory so that they can make the appropriate econometric decisions. For example, if they are looking at the price of beach-front housing on the coast, they need to understand and explain the appropriateness of the Hedonic model and its assumptions in the context of this market to have addressed the question of simultaneity. Otherwise, students are doing little more than an "applied regression" paper (a statistics project vs. an econometrics project).

Furthermore, since the papers are individualized, each topic and dataset will present its own unique set of econometric challenges. These include (1) multicollinearity, (2) incorrect functional form, (3) heteroscedasticity, (4) autocorrelation, (5) omitted variables, (6) measurement error and (7) simultaneity. Students are expected to address the relevant problems in a satisfactory way. The challenge is to get them to think about their data and theoretical problems early on so that it is not merely an exercise in data-mining.

To help with that, I have developed a series of short homework assignments to (1) keep them on task and (2) lead them to address the requisite issues that are addressed in the course:

• After their proposals are approved, I require a 2-page written summary where they discuss each independent variable theoretically. They explain from theory the effects it should have on the dependent variable and why. In addition, I ask them to pay close attention to two things: (1) whether the variable is endogenous and why (or, if it is exogenous they must justify that); (2) whether the theoretical relationship is linear or non-linear. I also ask them to sketch the XY scatter plot from a theoretical point of view (remember: they have not collected the data yet).
• Following that, their data are due. They are required to come to class with the data imported into SAS. I check their data one-by-one and we discuss issues of dummy variables, transformations, etc. The data are generally due 10-14 days after the proposal. This leaves 4 weeks in the semester for them to complete the econometric work and write the paper.

The final challenge has to do with the timing of content. As they are doing their papers over the last 4 weeks, we are covering topics such as limited dependent variables and panel data. I end the delivery of new content the before Thanksgiving, leaving 2 weeks of class time for them to work on their projects in class and have an in-class final exam (I use the final exam period for presentations). This timing means that students doing topics using, say, logistic regression, do not have that knowledge until 2 weeks left in class. Thus, I have all students begin with benchmark OLS regression model. A lot of diagnostics can be done at this stage, even if OLS is inefficient due to the non-linearities. For example, multicollinearity can be dealt with in OLS.

Since this is an econometrics class, assessment of the papers are biased towards the course objectives. As with all papers, of course, I do expect them to be well-written and complete. But those criteria are treated more as "minus" if they are not up-to-par rather than something that will make the difference between, say and A and a B. Thus, grades are determined by:

• whether the economic theory and the specification of the benchmark econometric model are consistent;
• the extent to which the student has correctly diagnosed the relevant econometric problems;
• the extent to which the student has dealt with the econometric problems in an appropriate and convincing way;
• the extent to which the paper is well-written and complete (e.g., is there a reasonable introduction with a clearly defined thesis? has the student done a reasonable amount of literature review for a semester project? has the student written a reflective discussion of the results?)
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• Resources for Students

Undergrad research opportunities

Several economics associations invite undergraduates to present essays at their annual meetings and some award prizes for the best essay. Other organizations invite participation by undergraduates and provide summer and other opportunities for college students to pursue their interest in economics.

Annual Meetings that Invite Submission of Undergraduate Essays

Eastern Economic Association Undergraduate Sessions The Eastern Economic Association invites undergraduates to submit essays for presentation at its annual meeting in late Feburary or early March. The deadline for submission is early November.

International Atlantic Economic Society: Best Undergraduate Paper Competition To encourage undergraduate interest in economic issues, the International Atlantic Economic Society invites undergraduate students to compete in the IAES annual undergraduate paper competition. The winner of the student competition will receive: a $500 check, a handsome commemorative plaque, and complimentary publication of the paper in the Atlantic Economic Journal . The winner will be selected at the International Atlantic Economic Conference annual conference in October. The submission deadline is June 15.

Midwest Economics Association Undergraduate Sessions The Midwest Economics Association invites undergraduates to present their essays at special undergraduate sessions of the annual meeting each March. An award of $200 goes to the best undergraduate essay. The deadline for submission of the essay is November 15.

Missouri Valley Economic Association invites undergraduates to submit proposals to present essays at the MVEA annual meeting and provide cash awards for top essays.

Council on Undergraduate Research provides a variety of venues for undergraduates to present their research.

Carroll Round at Georgetown University is an annual conference on international economics "provides a unique forum for research and discussion among the nation’s top undergraduates."

Journals for Undergraduate Student Research in Economics

The Berkeley Economic Review is the University of California at Berkeley's undergraduate, peer-reviewed, academic economics journal, and publishes undergraduate research papers and honors theses in the field of economics, political science, public policy, business, statistics, and related fields. They also accept academic term papers, class essays, policy briefs, and op-eds. All undergraduate students currently enrolled in an accredited four-year college or university are welcome to submit content for review.

The Developing Economist is edited at the University of Texas at Austin and welcome submissions from undergraduate economists.

Equilibria: Duke Economics Review accepts outstanding papers in economics and related fields such as business, accounting, finance, marketing, public policy, and game theory. Students from all academic disciplines may submit their work.

Issues in Political Economy is edited and refereed by undergraduates and publishes essays by undergraduates. This journal is published by Elon University and the University of Mary Washington.

Undergraduate Economic Review is edited by undergraduates and publishes essays authored by undergraduates. It is based at Illinois Wesleyan University.

The Columbia Economic Review publishes essays by undergraduate with an issue each semester. It is published by students at Columbia University. 

The Stanford Economic Review is Stanford's only undergraduate economics publication, accepting research papers and commentaries from all fields related to economics, including public policy, finance, international relations, business, and more.

The Student Monthly Labor Review is a pilot project by the Bureau of Labor Statistics dedicated to publishing social science research by undergraduate students. Subjects that the Student Monthly Labor Review publishes include, but are not exclusive to, demographics, labor economics, prices, environment, community research, and social statistics.

Summer Opportunities for Undergraduates

American Economic Association Summer Program and Minority Scholarship Program The American Economic Association's Summer Program and Minority Scholarship Program is now based at Howard University. A program begun in 1974, the AEA Summer Program seeks to prepare talented undergraduates for doctoral programs in Economics and related disciplines, by offering a unique opportunity for students to gain technical skills in Economics, and conduct research with prominent faculty.

Contests for Students

St. Norbert College cosponsors the iOMe Challenge , inviting teams of undergraduatres to submit an essay and a short video to illustrate some of the economic issues associated with financial security. A blue ribbon panel chooses winning teams. The top prize is $10,000 to the winning student team and $2,000 to that team's faculty advisor. The winning team may also be invited to Washington, D.C. to present their entry to Members of Congress, policymakers and other notables interested in this policy issue. There will also be honorable mention prizes of $2,500 for teams and their faculty advisors. More details and specific rules are available at the contest's website . The deadline for teams to submit the essay and video is in the fall. 

Other Organizations

American Economic Association Membership in the American Economic Association includes subscription to nine journals and a reduced rate for registration at the annual meeting. The journals are the American Economic Review , American Economic Review: Insights , the Journal of Economic Literature , the Journal of Economic Perspectives , the American Economic Journal: Macroeconomics , the  American Economic Journal: Microeconomics , the American Economic Journal: Economic Policy , the American Economic Journal: Applied Economics , and AEA Papers and Proceedings . The American Economic Review is published monthly and the other journals are published quarterly, with the exception of AEA Papers and Proceedings , which is published once a year in May. The AEA annual meeting happens every year in January. Economists from all over the world attend the meetings. There is also a job market for economists.

Committee on the Status of Women in the Economics Profession CSWEP, a committee of the American Economic Association, publishes a newsletter containing information that helps women keep up-to-date about what is happening in the profession.

Omicron Delta Epsilon ODE is an honorary society of economics students, organized as chapters at participating campuses.  ODE honors "achievement in economics worldwide" and published The American Economist .

Council for Economic Education The Council for Economic Education is a nationwide network that leads in promoting economic literacy with students and their teachers. The mission is to help students develop the real-life skills they need to succeed: to be able to think and choose responsibly as consumers, savers, investors, citizens, members of the workforce, and effective participants in a global economy.

Graduate degrees in economics

Careers in economics.

Student Research

As an undergraduate or graduate student at one of the foremost institutions in the nation, there are many reasons to delve into research. Research sparks critical thinking and creativity and hones the ability to post the right question, solve for the right answer, and dispel the messy, complex, and abstract thoughts of a lab notebook into an elegant argument. Research is the innate pursuit of progress and service and the catalyst of innovation. We work to enhance it.

Georgia Tech undergraduate students have many opportunities to participate in research with faculty across campus. The best way for you to begin your career in research is to review faculty web pages and working papers see who is doing research that you find exciting. Read more about getting started in undergraduate research .

Undergraduate students should also look for information on the Undergraduate Research Opportunities Program website.  Graduate students should speak to their faculty advisor for information on the thesis, dissertation, or independent research and view the Graduate Studies Theses and Dissertations website.

Georgia Tech Library

The Georgia Tech Library offers many resources for both undergraduate and graduate students. The School of Economics has a subject librarian who is available to offer advice on ways to research topics and give assistance with verification of bibliographic citations. He can also provide library orientations and give assistance in developing research assignments. Please visit the Georgia Tech Library website for further information.

Georgia Tech Library Digital Repository

All Georgia Tech theses and dissertations are available electronically through the Georgia Tech institutional repository. Theses and dissertations published 2004 to the present are openly accessible.  You can search for School of Economics papers in the repository or submit a paper or dissertation to the repository .

ECON 3161:  Econometric Analysis

Students enrolled in ECON 3161: Econometric Analysis are required to write a research paper using the knowledge learned in the course. If you would like to review past papers produced by our students, please see the Econometric Analysis Series page in the Georgia Tech Library Digital Repository dedicated to the course.

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102 Best Econometrics Research Topics

College and university professors require students to write about econometrics research topics to gauge their comprehension of the relationship between mathematical economics, statistics, and economics.

The purpose of this integration is to provide numerical values to economic relationships and parameters. Usually, econometrics involves economic theories and their presentation in mathematical forms and the empirical study of business. Perhaps, this integration explains why some students struggle to choose topics for research in econometrics.

What Is Econometrics?

As hinted, econometrics is an economics branch that focuses on the relationships between economics, statistics, and mathematical economics. Ideally, econometrics entails the quantitative application of mathematical and statistical models using data to test hypotheses and develop economic theories while forecasting future trends based on historical data. Econometricians subject real-world data to various statistical trials while comparing and contrasting the results against the idea under examination.

Writing an econometric research paper is a process that starts with the selection of an interesting topic. Once you’ve chosen a title and the supervisor approves it, embark on extensive research using the prompt from your teacher. Proceed by gathering and analyzing all relevant information from different sources. Engaging in in-depth study and comprehensive analysis will enable you to write an informative paper that will compel the educator to award you the best grade in your class. Below are the steps to follow to write a high-quality econometric thesis or essay.

Write the introduction: Introduce your econometrics topic and tell the audience why it’s crucial. Also, include a thesis statement summarizing the entire paper. Describe the theoretical model: Tell the readers about the theoretical models to structure the empirical work. Present the data: Describe the data, whether time series or cross-sectional. Use descriptive statistics data and graphics if possible. Present the empirical model: Explain the model you intend to estimate and the functional form you intend to use. Present your empirical results: This section presents empirical results using a table to summarize them. Conclude the paper: Describe lessons from the research and state whether it supports the theory. Also, suggest approaches for future research on the topic.

Your paper should also include a reference section comprising the information sources you used to gather data.

Interesting Econometrics Paper Topics

Maybe you know the process of writing a paper on an econometrics topic but don’t have an idea to explore. If so, consider these exciting econometrics paper ideas.

• How privatizing public enterprises could affect economic development and policy
• Cashless economy: How demonetization affects medium and small businesses
• How Gini index dynamics reflect the income inequality problem
• Consumption evolution over the last decade: Consumer behavior and trends
• Investigating salary inequalities and the forces behind them
• How income changes affect consumer choices
• How does allowing the labor force to participate in public budgeting affect the economy
• How the marital status affect the labor force composition
• How consumption attitudes have changed over the last decade
• How economic convergence relates to salary levels
• How income affects life insurance
• The consequences of leaving the rat race
• Testing Okun’s Law in the U.S
• Analysis of spending on disposable income and imports
• Comparing the unemployment rate in the United States to the rest of the world
• Regional labor mobility and unemployment
• Stock market evolution: Analyzing the causes and effects
• How internet productivity relate to connectivity in the workplace
• How currency devaluation affects medium and small companies
• How government spending and inflation relate in an economy
• The relationship between stock prices and inflation in a country
• How income tax revenue affects a developing economy
• How government expenditure affects economic growth
• Factors contributing to the global recession
• How a country’s unemployment rate relates to economic growth

Any of these topics can be an excellent basis for an econometrics paper. However, you require extensive research about any of these topics to develop a winning thesis.

Undergraduate Econometrics Project Ideas

Maybe your school or faculty requires you to write an econometrics paper to graduate from university. In that case, consider these econometrics research topics for undergraduates.

• Analyzing the impact of income inequality on the poverty level
• Analyzing gender differences in education between developing and developed countries
• How immigration affects unemployment in the European Union
• How economic growth relates to trade
• Are immigrants more in countries with a high income?
• How high taxations affect GSP
• Analyzing the relationship between local income level and house prices
• How income, education, and life expectancy affect the human development index
• How inflation affects national savings
• How life expectancy relates to national income
• How financial development affects the economic growth of a country
• Crime index versus the average education years
• Investigating the correlation between youth unemployment and minimum wage
• How economic prosperity relate to government systems
• Economic factors that affect housing prices in the United States
• Economic factors contributing to homelessness in the U.S
• Socioeconomic and economic determinants of infant mortality
• Econometric analysis: Impact of trade barriers
• Why matching methods are essential in econometrics
• How a randomized experiment can aid econometrics
• Why instrumental variables matter in econometrics
• Can experts predict the future using econometrics?
• Econometrics as a numerical estimates source for economic relationship variables
• Ways of testing economic theories that econometricians present
• Regression discontinuity: Describe its application

These are great ideas to consider for an econometrics project. Nevertheless, you require sufficient time to research any of these topics and write a winning essay or dissertation.

Easy Econometric Research Topics

Perhaps, you need an easy topic for an econometrics paper. Maybe you have a short time to complete your assignment. In that case, these econometrics topics are ideal for you.

• Theory suggestion- The initial econometrics methodology step
• Why estimating variables is important
• The importance of Proof-reading once you have evaluated the variables
• Why testing a hypothesis matters
• The impact of poverty on education
• How poverty relates to childhood obesity
• Human development and income inequality
• The link between religion and ideologies on a country’s economy
• Income and importation- How do they connect?
• Personal income and life expectancy- What is the connection?
• The effects of minimum wage on unemployment
• Investigating monetary policies and bank regulations
• A study of the economies of scale
• The impact and relevance of comparative institutional economics
• Analyzing the effect of making a company international
• Studying the macroeconomics of rare events
• Investigating customer behavior towards green products
• Trade patterns: Investigating different trade patterns and their applications
• Different stochastic processes concepts
• Accurate stochastic processes prediction

Any of these topics can be a sound basis of a simple paper. Nevertheless, you still require time to research the idea and analyze data to develop a quality paper.

Financial Econometrics Research Paper Topics

Perhaps, you want to write an academic paper about a financial econometrics topic. If so, consider these ideas.

• How does bank regulation affect the economy?
• A critical look into the loan markets
• How a cashless policy affects the economy
• Structure and implementation of the monetary policy
• Lessons to learn from financial crises
• Investigating regression models
• Statistical tools in the financial econometrics

These are good topics to explore in financial econometrics. However, follow the prompt from your teacher to write an impressive paper.

Econometrics Empirical Project Ideas FExor Ph.D. Level

Maybe you’re pursuing your Ph.D. and want to write a dissertation about an econometrics topic. In that case, this category comprises excellent ideas for you.

• Analytical statistics versus theoretical statistics
• The effects of the low and high demand of labor on an economy
• The arbitrage pricing theory
• How goods production and productivity affect econometrics at a national level
• Applied econometrics- Its essence in turning qualitative economic ideas into quantitative ones
• Definition, relevance, and application of the general line model
• Theoretical econometrics’ study and application
• The macro behavioral theory
• Panel data methods applications- A microeconomics subsection
• The impacts of the spillover effect on econometrics
• The impact of labor supply on a local economy
• Why labor markets are essential to econometrics
• What is micro-econometrics modeling?
• Micro-econometrics methods and applications
• Statistical tools and their use in financial econometrics

This list also has fantastic economics paper topic ideas. But like the topics in the other sections, each of these notions requires extensive research to write a quality paper.

Exciting Econometrics Questions

Maybe you need a question to serve as the basis of your econometrics research. In that case, here are exciting queries to inspire you.

• What is the current state of your country’s economy?
• What’s the difference between the current state of the local and international trades?
• What are the latest forecasts for the global economy?
• How do the foreign exchange market and the local businesses relate?
• What’s the impact of exportation and importation on the local economy?
• How do businesses monopolies affect a country’s economy?
• What are the effects of international banks on the local banking sector?
• How does population growth affect economic development?
• How can a natural disaster affect an emerging economy?
• What techniques do companies use to “nudge” consumers into spending more?

This comprehensive list has some of the best econometrics ideas for essays and research papers. Nevertheless, having a topic is not a guarantee that you’ll write a good essay. You might still need help with your assignment after choosing a topic.

Get Help With Thesis About Econometrics Topic

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Which Investors Matter for Equity Valuations and Expected Returns?

Econometrics Research Paper Topics

This page provides an extensive list of econometrics research paper topics divided into 10 categories, expert advice on topic selection, and valuable insights on how to write a successful econometrics research paper. Additionally, the page introduces the writing services provided by iResearchNet, offering students the opportunity to order custom econometrics research papers on any topic. With expert writers, in-depth research, and top-quality custom papers, iResearchNet ensures a seamless and efficient experience for students seeking assistance in their econometrics research endeavors.

100 Econometrics Research Paper Topics

Welcome to the comprehensive list of econometrics research paper topics. As a student of economics, you may be tasked with writing a research paper that delves into the world of econometrics—the application of statistical methods to economic data. This list is designed to provide you with a wide range of research paper topics in econometrics, divided into 10 categories. Each category offers a collection of 10 unique and engaging topics that cover various aspects of econometric analysis. Whether you are interested in time series analysis, cross-sectional analysis, applied microeconometrics, or any other subfield of econometrics, you will find a plethora of intriguing research ideas to explore. So, let’s dive into this rich collection of econometrics research paper topics and discover the fascinating intersection between economics and statistical analysis.

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Time Series Analysis Research Paper Topics:

• Modeling and forecasting stock market returns using time series econometric models
• The impact of macroeconomic variables on exchange rates: A time series analysis
• Analyzing volatility in financial markets using ARCH/GARCH models
• Econometric modeling of economic growth: A time series approach
• Cointegration analysis and its implications for long-run equilibrium relationships
• Autoregressive integrated moving average (ARIMA) models in economic forecasting
• Analysis of panel data and fixed effects models in time series econometrics
• Dynamic factor models and their applications in time series analysis
• Nonlinear time series analysis and its relevance in understanding economic dynamics
• Estimation and testing in time series econometrics: Challenges and advancements

Cross-Sectional Analysis Research Paper Topics:

• Determinants of firm performance using panel data and econometric techniques
• Analysis of income inequality and its drivers: A cross-sectional econometric study
• Impact evaluation of public policies using experimental and quasi-experimental designs
• Quantile regression and its applications in cross-sectional analysis
• The relationship between education and earnings: An econometric examination
• Analyzing labor market outcomes and human capital using cross-sectional data
• Modeling consumer behavior and demand estimation: A cross-sectional perspective
• Spatial econometrics and its relevance in studying regional disparities
• Health economics and econometric analysis of healthcare outcomes
• Estimating production functions and efficiency analysis using cross-sectional data

Panel Data Analysis Research Paper Topics:

• Fixed effects versus random effects models: A comparative analysis
• Dynamics of financial contagion: A panel data approach
• Analysis of firm-level productivity using panel data econometric techniques
• The impact of foreign direct investment on economic growth: A panel data analysis
• Panel cointegration analysis and its implications for long-run relationships
• Endogeneity and instrumental variable approaches in panel data analysis
• Analysis of trade flows and gravity models using panel data econometrics
• Panel data analysis of environmental sustainability and economic development
• The role of institutions in economic performance: A panel data study
• Dynamic panel data models and their applications in economic research

Applied Microeconometrics Research Paper Topics:

• The impact of minimum wage policies on employment: An empirical analysis
• Estimating demand elasticity for specific goods: A microeconometric approach
• Analysis of consumer behavior and choice modeling using microeconometric techniques
• The effects of government interventions on market outcomes: A microeconometric study
• Estimating the returns to education using microeconometric methods
• Labor market outcomes and the impact of training programs: An empirical investigation
• Health economics and the evaluation of healthcare interventions: A microeconometric perspective
• The role of social networks in economic outcomes: An applied microeconometric analysis
• Econometric analysis of industrial organization and market structure
• Discrete choice modeling and its applications in empirical microeconomics

Applied Macroeconometrics Research Paper Topics:

• The role of monetary policy in stabilizing the economy: An applied macroeconometric analysis
• Estimating fiscal multipliers and the impact of government spending on economic growth
• Time-varying parameter models in macroeconometrics: Theory and applications
• The effects of exchange rate fluctuations on trade: An empirical investigation
• Macroeconomic forecasting using state-space models and Bayesian econometrics
• Empirical analysis of business cycles and their synchronization across countries
• The impact of financial shocks on macroeconomic stability: An econometric perspective
• Dynamic stochastic general equilibrium (DSGE) models and their applications in macroeconomics
• The role of expectations in shaping macroeconomic outcomes: An econometric study
• The interaction between monetary and fiscal policy: Empirical evidence and policy implications

Financial Econometrics Research Paper Topics:

• Estimating risk and return in financial markets using econometric models
• Analyzing the efficiency of financial markets using event study methodologies
• GARCH models and volatility forecasting in financial econometrics
• The impact of macroeconomic factors on stock market performance: An empirical analysis
• Value-at-Risk (VaR) modeling and its applications in risk management
• Asset pricing models and their empirical validation using financial econometric techniques
• Credit risk modeling and default prediction: An econometric perspective
• High-frequency financial data analysis and its implications for trading strategies
• The relationship between interest rates and stock market returns: A financial econometric study
• Econometric analysis of financial contagion and systemic risk in banking

Applied Econometrics in Development Economics Research Paper Topics:

• Impact evaluation of development programs using randomized controlled trials (RCTs)
• Estimating the effects of foreign aid on economic growth: An applied econometric analysis
• The role of institutions in development: An empirical investigation
• Analyzing the determinants of poverty and inequality using applied econometric techniques
• Econometric analysis of migration and its impact on development outcomes
• The effects of trade liberalization on economic development: An empirical examination
• Financial inclusion and its relationship with economic development: An applied econometric study
• Empirical analysis of social protection programs and their impact on poverty reduction
• Evaluating the effectiveness of education policies in promoting human capital development
• Econometric analysis of infrastructure investment and its contribution to economic development

 Environmental and Resource Economics Research Paper Topics:

• Econometric modeling of environmental pollution and its impact on health outcomes
• Valuation of ecosystem services and their contribution to economic welfare: An applied econometric approach
• The effects of climate change on agricultural productivity: A resource economics perspective
• Empirical analysis of renewable energy policies and their impact on economic sustainability
• Dynamic optimization models in environmental economics and resource management
• Econometric analysis of water resource allocation and its implications for economic efficiency
• The role of market-based instruments in environmental regulation: An empirical examination
• The impact of deforestation on economic development and sustainability: An econometric study
• Non-market valuation of environmental goods and ecosystem conservation: An applied econometric analysis
• Econometric analysis of environmental policy effectiveness and its implications for sustainable development

International Economics Research Paper Topics:

• Empirical analysis of trade patterns and globalization using international econometric techniques
• Exchange rate regimes and their impact on trade and economic stability: An econometric analysis
• The role of foreign direct investment in economic growth: An empirical investigation
• Gravity models and their applications in international trade analysis
• Trade liberalization and its effects on labor markets: An applied international econometric study
• The impact of trade policies on income distribution: A cross-country analysis
• Empirical analysis of exchange rate pass-through and its implications for import and export prices
• The relationship between financial integration and economic growth: An international econometric perspective
• Economic convergence and divergence across countries: An econometric examination
• The effects of trade agreements on trade flows and economic integration: An empirical analysis

Applied Econometrics in Public Finance Research Paper Topics:

• The impact of tax policies on economic behavior: An applied econometric study
• Analyzing the effectiveness of government expenditure on public goods: An empirical investigation
• Fiscal sustainability and the implications for long-run economic growth: An econometric analysis
• Estimating the incidence and distributional effects of taxation using applied econometric techniques
• Empirical analysis of government debt and its implications for macroeconomic stability
• The role of public investment in fostering economic development: An applied econometric study
• Econometric analysis of the determinants of tax compliance and tax evasion
• The effects of social welfare programs on labor market outcomes: An empirical examination
• Evaluating the impact of education spending on human capital development: An econometric analysis
• The relationship between government size and economic performance: An applied econometric study

Econometrics Research Paper Writing Guide

Welcome to the world of econometrics research! As an economics student, you have embarked on a journey to explore the fascinating realm of econometric analysis and its application in the field of economics. Writing a research paper in econometrics provides you with an opportunity to delve deeper into this quantitative discipline and contribute to the existing body of knowledge.

This page serves as a comprehensive guide specifically tailored for economics students who are tasked with writing an econometrics research paper. Whether you are new to econometrics or seeking to enhance your understanding and skills in this field, this guide will provide you with valuable insights and resources to navigate the process effectively.

Within this page, you will find an abstract that encapsulates the essence of exploring econometrics research paper topics, followed by a comprehensive list of research topics divided into 10 categories. Additionally, expert advice on selecting suitable topics and valuable guidance on how to write an econometrics research paper will be provided to support you throughout your research journey.

To further assist you in your academic endeavors, iResearchNet offers custom writing services where you can order a custom econometrics research paper tailored to your specific requirements. With a team of expert degree-holding writers, in-depth research capabilities, and a commitment to top-quality customized solutions, iResearchNet is dedicated to providing you with a seamless and successful research paper writing experience.

Let’s dive into the world of econometrics research, explore intriguing research topics, and equip ourselves with the knowledge and skills to excel in this exciting field.

How to Choose an Econometrics Topic

Choosing the right econometrics research paper topic is crucial to the success of your study. With the vast array of possibilities within the field of econometrics, it can be challenging to narrow down your options and select a topic that is both interesting and feasible. To help you navigate through this process, we have compiled some expert advice on choosing econometrics research paper topics:

• Identify your research interests : Begin by reflecting on your personal interests within the field of economics. Are you fascinated by macroeconomic issues, labor markets, financial econometrics, or perhaps environmental economics? Understanding your areas of passion will guide you towards selecting a research topic that aligns with your interests and motivates you throughout the research process.
• Review current literature : Familiarize yourself with the existing literature in econometrics, especially recent publications and studies. This will not only deepen your understanding of the subject but also give you insights into the latest research trends and gaps in knowledge. Look for areas where you can contribute new perspectives or address unanswered questions.
• Consider data availability : Before finalizing your research topic, assess the availability of relevant data. Econometrics heavily relies on empirical analysis, and having access to high-quality and appropriate datasets is crucial. Ensure that you can obtain the necessary data for your research topic and assess its suitability for your analysis.
• Narrow down your scope : Econometrics research can range from broad macroeconomic studies to more focused microeconometric analyses. Consider the scope of your research and determine whether you want to explore a specific aspect within a broader context or delve deep into a specific area. Narrowing down your scope will allow you to conduct a more focused and impactful study.
• Consult with your advisor : Seek guidance from your advisor or faculty members who have expertise in econometrics. They can provide valuable insights, suggest potential research areas, and help you refine your research question. Their expertise and experience will be invaluable in ensuring that your research topic is viable and aligns with current research trends.
• Balance complexity and feasibility : While it’s important to choose a topic that challenges you academically, it’s equally crucial to consider the feasibility of your research within the available timeframe and resources. Strive for a balance between a topic that pushes the boundaries of knowledge and one that is realistic to accomplish within the given constraints.
• Brainstorm and refine : Engage in brainstorming sessions where you jot down ideas, concepts, and potential research questions. Refine these ideas by evaluating their significance, relevance, and feasibility. Consider the potential impact of your research and its contribution to the field of econometrics.

Remember, the key to choosing a successful econometrics research paper topic is finding a balance between your interests, the availability of data, the scope of your research, and the guidance of experts. By carefully considering these factors and leveraging the expertise of your advisors, you can select a compelling research topic that will drive your study forward.

How to Write an Econometrics Research Paper

Writing an econometrics research paper requires a systematic approach to effectively communicate your findings and contribute to the field of economics. Whether you are a seasoned researcher or new to the world of econometrics, the following guidelines will help you navigate the process of writing an impactful econometrics research paper:

• Understand the research question : Start by clearly defining your research question or objective. What specific problem or issue are you addressing? Ensure that your research question is focused, well-defined, and aligns with the broader scope of econometrics.
• Review relevant literature : Conduct a comprehensive review of existing literature related to your research topic. Familiarize yourself with the theories, methodologies, and empirical findings that are relevant to your research question. This will provide a strong foundation for your study and help you position your research within the existing body of knowledge.
• Develop a theoretical framework : Construct a theoretical framework that outlines the concepts, relationships, and hypotheses underlying your research. Identify the key variables and their expected effects. The theoretical framework will guide your empirical analysis and provide a coherent structure for your paper.
• Choose appropriate econometric techniques : Select the appropriate econometric techniques and models to analyze your data and test your hypotheses. Consider whether your research requires time series analysis, panel data analysis, cross-sectional analysis, or a combination of these approaches. Justify your choice of econometric techniques and explain how they align with your research objectives.
• Collect and preprocess data : Gather the necessary data for your analysis. Ensure that the data is reliable, relevant, and suitable for econometric analysis. Preprocess the data by cleaning, organizing, and transforming it as needed. Document the steps taken in data collection and preprocessing to ensure transparency and reproducibility.
• Conduct empirical analysis : Apply the selected econometric techniques to analyze your data. Present the empirical results in a clear and concise manner, using appropriate tables, graphs, and statistical measures. Interpret the results in the context of your research question and theoretical framework. Discuss any limitations or challenges encountered during the empirical analysis.
• Discuss implications and policy recommendations : Evaluate the implications of your findings and their relevance to the broader field of economics. Discuss the significance of your results in addressing the research question and advancing economic knowledge. If applicable, provide policy recommendations based on your empirical analysis.
• Structure your paper : Organize your research paper into sections that flow logically and coherently. Typically, an econometrics research paper includes an introduction, literature review, theoretical framework, data and methodology, empirical analysis, results, discussion, conclusion, and references. Follow a clear and concise writing style, using appropriate terminology and providing sufficient details for readers to understand and replicate your study.
• Revise and edit : After completing the initial draft, carefully review and revise your research paper. Pay attention to the clarity of your arguments, the coherence of your ideas, and the accuracy of your findings. Proofread for grammar, spelling, and formatting errors. Seek feedback from peers or mentors to gain additional perspectives and suggestions for improvement.
• Cite sources properly : Accurately cite all the sources you have referenced in your research paper using an appropriate citation style, such as APA, MLA, or Chicago. Adhere to ethical guidelines and avoid plagiarism by properly attributing the ideas, theories, and empirical results of others.

By following these guidelines, you can effectively structure and communicate your econometrics research findings. Remember to stay focused, provide clear explanations, and contribute to the advancement of econometric knowledge in your field.

Order a Custom Research Paper

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• Expert degree-holding writers : Our team consists of writers with advanced degrees in economics and expertise in econometrics. They possess the knowledge and skills to conduct rigorous research, analyze data, and write high-quality econometrics research papers.
• Custom written works : We understand the importance of originality and customization. Your research paper will be crafted from scratch, based on your specific instructions, research question, and data. We ensure that each paper is unique and tailored to meet your academic needs.
• In-depth research : Our writers are adept at conducting thorough and comprehensive research. They have access to a wide range of reputable sources, databases, and econometric software tools to gather relevant information and empirical data for your research paper.
• Custom formatting : We adhere to the formatting style of your choice, whether it’s APA, MLA, Chicago/Turabian, or Harvard. Our writers are well-versed in the specific requirements of each formatting style and will ensure that your research paper follows the prescribed guidelines.
• Top quality and customized solutions : We prioritize quality and strive to deliver research papers that meet the highest academic standards. Our writers pay meticulous attention to detail, ensuring that your paper is well-structured, coherent, and effectively communicates your research findings.
• Flexible pricing : We offer competitive and flexible pricing options to accommodate the budgetary constraints of students. Our pricing structure takes into account factors such as the complexity of the research paper, the urgency of the deadline, and the desired level of customization.
• Short deadlines : We understand that students often face tight deadlines. Our writing services offer short turnaround times, allowing you to receive a custom econometrics research paper even with urgent deadlines.
• Timely delivery : We prioritize timely delivery to ensure that you have sufficient time to review the research paper, request revisions if needed, and submit it within your academic timeline.
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70 Econometrics Research Topics for You

Econometrics is an interesting area of research. However, picking econometric research topics may be a bit difficult. This is because it is a broad aspect of economics with increasing relevance by the day.

Economic relationships can be accurately measured and defined. This involves a certain statistical and mathematical approach known as econometrics. It is the foundation for economic forecasting.

In this article, you will find 70 interesting econometrics topics crafted for you! We have done the hard work, saving you the stress of picking the right topics for your presentation, research work, or seminar. Are you ready? Let’s get started!

Easy Econometrics Paper Topics

Need to write an econometrics research paper? Here are some econometrics research paper topics for you!

• The suggestion of theory- the initial step in econometrics methodology
• How Inflation affects National Savings
• Estimating variables- why it must be done
• The essence of Proof-reading after estimating variables
• Why the need for testing a hypothesis
• How Trade Relates to Economic growth: An in-depth look.
• Analyzing how Income Affects Life Insurance

Econometrics Research Topics for Undergraduates

Need to write an undergraduate econometrics research paper? Here are some econometrics topics suitable for undergraduate research purposes.

• How poverty affects education
• Relationship between childhood obesity and poverty
• Income inequality and human development
• The link between ideologies and religion on the economy of a country
• Importation and income- what is the relationship?
• Life expectancy and personal income- the link
• How minimum wage affects unemployment

Econometrics Topics for a Project

If you are studying something around econometrics at college, you’ll need to do a project! Here are some econometrics research paper topics for your project!

• Can econometrics be used to predict the future?
• Econometrics is a source of numerical estimates for the variables of economic relationships
• How to test economic theories presented by econometricians using econometrics
• What is regression discontinuity, and how can it be applied?
• The role of instrumental variables in econometrics
• How randomized experiments aid econometrics
• The essence of matching methods in econometrics

Interesting Econometrics Research Topics

If econometric research is one of the things that gives you goosebumps, we have added to your excitement. We just saved you the stress of having to look for interesting econometrics research topics. Here are 7 interesting econometrics topics for you!

• A study of customer behavior for green products
• Trade patterns- a research on the various kinds and their applications today
• A study on rare events and their macroeconomics
• A study of the effect of making a business international
• Comparative institutional economics- relevance and impact
• Research on the economies of scale
• A close look at bank regulations and monetary policies

Sports Econometrics Topics

The economics of sport is analyzed using sports econometrics. This makes it easier to make forecasts and accurate predictions. We have selected interesting econometrics topics in the sports niche for you. See them here:

• How a sports team affects the local economy
• The impact of discrimination in sports
• Sports attendance and its economic relevance
• Factors that affect competitive balance in sports and its effect on the economy
• The relationship between threshold efficiency and market competition in sports
• The economics of professional football contracts
• Professional hockey- skill, performance, and earnings

Financial Econometrics Research Topics

There are numerous topics for econometrics research papers. We have made it hassle-free for you to pick one for your next research work. Here are some econometrics topics research papers below.

• Latest statistical tools for financial econometrics
• A study on multiple regression model and its applications
• What to learn from recent financial crises
• Monetary policy- structuring and implementation
• Cashless policy and its impact on the economy
• The loan markets-A critical look and survey
• Bank regulation and policy-the impact on the economy

Micro Econometrics Topics Suggestions

Micro econometrics is an interesting area to make a presentation. To this end, we have picked out seven relevant topics in econometrics that pertain to micro econometrics. See them below!

• The methods and applications of micro econometrics
• Micro econometric modeling
• The role of the labor market in econometrics
• How labor supply impacts the local economy
• What is the spillover effect, and how does it affect econometrics?
• The application of panel data methods- a subsection of microeconomics
• Micro behavioral theory

Advanced Topics in Econometrics

Need some advanced econometrics topics? Here are some advanced econometrics research topics just for you.

• The study and application of theoretical econometrics
• General line model- definition, application, and relevance
• Applied econometrics- the key to converting qualitative economic statements into quantitative ones
• How productivity and goods production affects econometrics at the national level
• The theory of arbitrage pricing
• The impact of high or low demand of labor on the economy
• Theoretical statistics vs. Analytical statistics

Good Simple Econometric Research Topics

Need some good econometrics topics that are easy to work on? Below are some simple topics in econometrics for your research!

• The various concepts of stochastic processes
• Accurate prediction of stochastic processes
• Line time series model- its definition, estimation, and application
• The purpose of dynamic econometric models
• Multiple time series model- a critical approach to determine its application
• The relevance of vector autoregressive processes
• Causality and impulse-response analysis

Receive Your Econometrics Research Paper

Want someone to hand over simple research paper topics to you? The following are econometric paper topics selected for you!

• The state of the national economy
• InterInternal trades and local economic status
• The impact of importation and exportation on the local economy
• Supply and demand forecast
• A critique on international banks
• The foreign exchange market-how it relates to local businesses
• Business monopolies in the nation- a critical study

If you’re pursuing a thesis in the field of econometrics and find yourself in need of expert support, you might want to consider seeking professional assistance for writing your thesis. Our reputable academic writing services provide specialized help that can alleviate the challenges you may encounter during the thesis writing process. By requesting us to ‘ write my thesis for me ,’ you can tap into the expertise of experienced writers who possess in-depth knowledge of econometrics. Our experts will guide you through the intricacies of data analysis, statistical modeling, and hypothesis testing, ensuring that your thesis adheres to the highest academic standards

We believe you now have more than enough topics in econometrics in your arsenal. With these interesting econometric topics, you can make the best seminar presentations or research around econometrics! Have fun!

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