Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/204583
Authors: 
Pua, Andrew Adrian Yu
Fritsch, Markus
Schnurbus, Joachim
Year of Publication: 
2019
Series/Report no.: 
Passauer Diskussionspapiere - Betriebswirtschaftliche Reihe No. B-38-19
Abstract: 
We study the estimation of the lag parameter of linear dynamic panel data models with first order dynamics based on the quadratic Ahn and Schmidt (1995) moment conditions. Our contribution is twofold: First, we show that extending the standard assumptions by mean stationarity and time series homoscedasticity and employing these assumptions in estimation restores standard asymptotics and mitigates the non-standard distributions found in the literature. Second, we consider an IV estimator based on the quadratic moment conditions that consistently identifies the true population parameter under standard assumptions. Standard asymptotics hold for the estimator when the cross section dimension is large and the time series dimension is finite. We also suggest a data-driven approach to obtain standard errors and confidence intervals that preserves the time series dependence structure in the data.
Subjects: 
panel data
linear dynamic model
quadratic moment conditions
root selection
standard asymptotics
inference
JEL: 
C18
C23
C26
Document Type: 
Working Paper

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