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This paper examines the asymptotics of the QMLE for unit root dynamic panel data models with spatial effect and fixed effects. We consider a unit root dynamic panel data model with spatially correlated disturbances and a unit root spatial dynamic panel data model. For both models the estimate of...
Persistent link: https://www.econbiz.de/10008506428
This paper establishes asymptotic properties of quasi-maximum likelihood estimators for spatial dynamic panel data with both time and individual fixed effects when the number of individuals <italic>n</italic> and the number of time periods <italic>T</italic> can be large. We propose a data transformation approach to eliminate...
Persistent link: https://www.econbiz.de/10008516788
This paper investigates the asymptotic distribution of the maximum likelihood estimator in a stochastic frontier function when the firms are all technically efficient. For such a situation the true parameter vector is on the boundary of the parameter space, and the scores are linearly dependent....
Persistent link: https://www.econbiz.de/10005411684
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In this article, we investigate a bias in an asymptotic expansion of the simulated maximum likelihood estimator introduced by Lerman and Manski (pp. 305–319 in C. Manski and D. McFadden (eds.), <italic>Structural Analysis of Discrete Data with Econometric Applications</italic>, Cambridge: MIT Press, 1981) for...
Persistent link: https://www.econbiz.de/10005104561
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In this paper, we extend the GMM framework for the estimation of the mixed-regressive spatial autoregressive model by Lee(2007a) to estimate a high order mixed-regressive spatial autoregressive model with spatial autoregressive disturbances. Identification of such a general model is considered....
Persistent link: https://www.econbiz.de/10008496677