Engel Functions, Panel Data, and Latent Variables

Identifying Latent Structures in Panel Data

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized regression techniques. We focus on linear models where the slope parameters are heterogeneous across groups but homogenous within a group and the group membership is unknown. Two approaches are considered — penalized least squares (PLS) for models without endogenous regress...

Instrumental Variables Quantile Regression for Panel Data with Measurement Errors∗

This paper develops an instrumental variables estimator for quantile regression in panel data with fixed effects. Asymptotic properties of the instrumental variables estimator are studied for large N and T when Na/T → 0, for some a > 0. Wald and Kolmogorov-Smirnov type tests for general linear restrictions are developed. The estimator is applied to the problem of measurement errors in variables...

Nonlinear Errors in Variables: Estimation of Some Engel Curves

Latent variables in econometrics

Unobservable variables in econometrics are represented in one of three ways: by variables contaminated by measurement errors, by proxy variables, or by various manifest indicators and/or causes. This paper contains a discussion of models involving each of these representations, and highlights certain interesting implications that have been ‘insufficiently emphasized or completely unrecognized i...

Financial Development and Economic Growth: Panel Data and Trilateral Analysis

A large body of literatures links financial development to economic growth, yet the channels through which inflation and economic development affect this relationship have been less thoroughly explored. This research takes econometric and trilateral graphic approaches to examine these channels using 99 developing and developed countries during the years 1960-2009. Findings prove that respecti...