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theory is kept general to cover a wide range of settings. We note the estimation theory developed by Kelejian and Prucha …
Persistent link: https://www.econbiz.de/10003790570
In this paper we specify a linear Cliff and Ord-type spatial model. The model allows for spatial lags in the dependent variable, the exogenous variables, and disturbances. The innovations in the disturbance process are assumed to be heteroskedastic with an unknown form. We formulate a multi-step...
Persistent link: https://www.econbiz.de/10003792846
This paper considers the estimation problem of structural models for which empirical restrictions are characterized by a fixed point constraint, such as structural dynamic discrete choice models or models of dynamic games. We analyze the conditions under which the nested pseudo-likelihood (NPL)...
Persistent link: https://www.econbiz.de/10003805996
This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM)...
Persistent link: https://www.econbiz.de/10003808637
The paper explores the effect of measurement errors on the estimation of a linear panel data model. The conventional fixed effects estimator, which ignores measurement errors, is biased. By correcting for the bias one can construct consistent and asymptotically normal estimators. In addition, we...
Persistent link: https://www.econbiz.de/10003824983
; extreme value theory ; bootstrapping …
Persistent link: https://www.econbiz.de/10003891679
This article examines the role of the interaction between product market and labor market imperfections in determining total factor productivity growth (TFPG). Embedding Dobbelaere and Mairesse's (2009) generalization of Hall's (1990) approach, allowing for the possibility that wages are...
Persistent link: https://www.econbiz.de/10003974678
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Persistent link: https://www.econbiz.de/10003711864
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