It is a well-known property that standard GMM estimators for dynamic panel data might perform poorly in small samples. Several papers have noted this to be especially true for the estimated standard errors, which are normally biased downwards. The aim of the present paper is to compare how two recently suggested bootstrap procedures can assist inference in dynamic panel data models, when the mentioned small-sample bias is a potential problem. We do this by means of Monte Carlo experiments, forming tests using both standard errors estimated by asymptotic approximations, as well as by bootstrap procedures.
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Paper provided by Uppsala - Working Paper Series in its series Papers with number
1997-23.
Length: 17 pages Date of creation: 1997 Date of revision: Handle: RePEc:fth:uppaal:1997-23
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Find related papers by JEL classification: C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
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Bergström, Pål & Dahlberg, Matz & Johansson, Eva, 1998.
"Municipal labour demand,"
Working Paper Series
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