Estimation of a Panel Data Model with Parametric Temporal Variation in Individual Effects

By Chirok Han, Luis Orea, P. Schmidt. 2004

52 citations recorded by the source corpus.

This paper considers models with time-varying individual effects (also known as factor models). The paper extends Ahn, Lee and Schmidt, Journal of Econometrics, 2001 and Bai, Econometrica, 2003 to allow a parametric function of time for the time factor. It provides a fixed-effects treatment of random effects models suggested by Kumbhakar and by Battese and Coelli for the frontier production function problem. The paper presents a number of GMM estimators based on assumptions of different strengths. Least squares has unusual properties: consistency depends on white noise errors, and given white noise errors it is less efficient than a GMM estimator. The model is applied to the measurement of the cost efficiency of Spanish banks

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/81f319f039585db9f2c56f463884d165dd369cd9

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In Economics and Econometrics

Citations in the corpus

A NEW PANEL DATA TREATMENT FOR HETEROGENEITY IN TIME TRENDS (2012, methodology): “Ta4For a more detailed discussion of data, see the Appendix in Jayasiriya (2000). 5When we assume L = 1 and test the null hypothesis that the individual effect is constant, the test statistic Z is 165.”
GMM with Many Moment Conditions (2004, methodology): “Since yi1 = β0 + αi + εit , the (T − 1) moment functions are g◦it(β θ)= [yit − λt(θ)yi1] − [1 − λt(θ)]β (t = 2 T ) GMM WITH MANY MOMENT CONDITIONS 175 (See Han, Orea, and Schmidt (2005), for the derivation of the moment conditions.)”
Stochastic Frontier Analysis using Stata (2013, background): “Han, Orea, and Schmidt (2005) and Ahn, Hoon Lee, and Schmidt (2001) propose estimating the models of Cornwell, Schmidt, and Sickles (1990) and Lee and Schmidt (1993), respectively, through a generalized method of moments (GMM) approach.”
A test of cross section dependence for a linear dynamic panel model with regressors (2009, methodology): “Sargans (1958), or Hansens (1982) test statistic of overidentifying restrictions for the full set of moment conditions in (21) is based on DIF2 and is given by”
Reconsidering heterogeneity in panel data estimators of the stochastic frontier model (2005, background): “Some extensions that have been suggested include models with time varying effects suggested by Cornwell et al. (1990), Lee and Schmidt (1993) and Han et al. (2002).”
Controlling for Individual Heterogeneity in Longitudinal Models, with Applications to Student Achievement (2007, background): “For example, Ahn, Lee and Schmidt (2) and Han, Orea and Schmidt (18) develop and compare consistent generalized method of moments and concentrated least squares estimators under structural models similar to our Example 1, where the coefficients on the individual-specific factors vary across measurem”
Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics (2006, methodology): “These data were previously analyzed by Cuesta and Orea (2002) and Han, Orea and Schmidt (2005) , to which the reader is referred for detail.”
Fixed and Random Effects in Stochastic Frontier Models (2005, background): “2 See Heckman and MaCurdy (1981), Polachek and Yoon (1994, 1996), Berry et al.”