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Full-Text Articles in Social and Behavioral Sciences
Robust Dynamic Space-Time Panel Data Models Using Ε- Contamination: An Application To Crop Yields And Climate Change, Badi H. Baltagi, Georges Bresson, Anoop Chaturvedi, Guy Lacroix
Robust Dynamic Space-Time Panel Data Models Using Ε- Contamination: An Application To Crop Yields And Climate Change, Badi H. Baltagi, Georges Bresson, Anoop Chaturvedi, Guy Lacroix
Center for Policy Research
This paper extends the Baltagi et al. (2018, 2021) static and dynamic ε-contamination papers to dynamic space-time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach de-parts from the standard Bayesian framework in two ways. First, we consider the ε-contamination class of prior distributions for the model parameters as well as for the individual effects. Second, both the base elicited priors and the ε-contamination priors use Zellner (1986)’s g-priors for the variance-covariance matrices. We propose a general “toolbox” for a wide range of specifications which includes the …
Lasso For Stochastic Frontier Models With Many Efficient Firms, William C. Horrace, Hyunseok Jung, Yoonseok Lee
Lasso For Stochastic Frontier Models With Many Efficient Firms, William C. Horrace, Hyunseok Jung, Yoonseok Lee
Center for Policy Research
We apply the adaptive LASSO (Zou, 2006) to select a set of maximally efficient firms in the panel fixed-effect stochastic frontier model. The adaptively weighted L1 penalty with sign restrictions for firm-level inefficiencies allows simultaneous estimation of the maximal efficiency and firm-level inefficiency parameters, which results in a faster rate of convergence of the corresponding estimators than the least-squares dummy variable approach. We show that the estimator possesses the oracle property and selection consistency still holds with our proposed tuning parameter selection criterion. We also propose an efficient optimization algorithm based on coordinate descent. We apply the method to estimate …