Estimation in the presence of incidental parameters

1982 ◽  
Vol 10 (2) ◽  
pp. 121-132 ◽  
Author(s):  
Tak K. Mak
Keyword(s):  
Incidental Parameters

PANEL DATA MODELS WITH FINITE NUMBER OF MULTIPLE EQUILIBRIA

2009 ◽  
Vol 26 (3) ◽  
pp. 863-881 ◽  
Author(s):  
Jinyong Hahn ◽  
Hyungsik Roger Moon
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Multiple Equilibria ◽  
Finite Sample ◽  
Finite Support ◽  
Time Dimension ◽  
Cross Sectional ◽  
Incidental Parameters ◽  
Cross Sectional Dimension ◽  
Fixed Effects Estimator

We study a nonlinear panel data model in which the fixed effects are assumed to have finite support. The fixed effects estimator is known to have the incidental parameters problem. We contribute to the literature by making a qualitative observation that the incidental parameters problem in this model may not be not as severe as in the conventional case. Because fixed effects have finite support, the probability of correctly identifying the fixed effect converges to one even when the cross sectional dimension grows as fast as some exponential function of the time dimension. As a consequence, the finite sample bias of the fixed effects estimator is expected to be small.

scholarly journals Model selection in the presence of incidental parameters

2015 ◽  
Vol 188 (2) ◽  
pp. 474-489 ◽  
Author(s):  
Yoonseok Lee ◽  
Peter C.B. Phillips
Keyword(s):  
Model Selection ◽  
Incidental Parameters

Small Chamber Ideal Point Estimation

2009 ◽  
Vol 17 (3) ◽  
pp. 276-290 ◽  
Author(s):  
Michael Peress
Keyword(s):  
Supreme Court ◽  
Latin American ◽  
Ideal Point ◽  
Point Estimation ◽  
Multidimensional Space ◽  
Incidental Parameters ◽  
Ideal Points ◽  
Point Estimators ◽  
The Ideal ◽  
Ideal Point Estimation

Ideal point estimation is a topic of central importance in political science. Published work relying on the ideal point estimates of Poole and Rosenthal for the U.S. Congress is too numerous to list. Recent work has applied ideal point estimation to the state legislatures, Latin American chambers, the Supreme Court, and many other chambers. Although most existing ideal point estimators perform well when the number of voters and the number of bills is large, some important applications involve small chambers. We develop an estimator that does not suffer from the incidental parameters problem and, hence, can be used to estimate ideal points in small chambers. Our Monte Carlo experiments show that our estimator offers an improvement over conventional estimators for small chambers. We apply our estimator to estimate the ideal points of Supreme Court justices in a multidimensional space.

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