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Persistent link: https://www.econbiz.de/10011339341
We propose a new methodology for estimating demand and cost functions of differentiated products models when demand and cost data are available. The method deals with the endogeneity of prices to demand shocks and the endogeneity of outputs to cost shocks by using cost data. We establish...
Persistent link: https://www.econbiz.de/10012904513
Persistent link: https://www.econbiz.de/10013441750
We propose a new methodology for estimating the demand and cost functions of differentiated products models when demand and cost data are available. The method deals with the endogeneity of prices to demand shocks and the endogeneity of outputs to cost shocks, but does not require instruments...
Persistent link: https://www.econbiz.de/10010463385
We propose a new methodology for estimating the demand and cost functions of differentiated products models when demand and cost data are available. The method deals with the endogeneity of prices to demand shocks and the endogeneity of outputs to cost shocks, but does not require instruments...
Persistent link: https://www.econbiz.de/10011380824
We propose a new methodology for estimating the demand and cost functions of differentiated products models when demand and cost data are available. The method deals with the endogeneity of prices to demand shocks and the endogeneity of outputs to cost shocks, but does not require instruments...
Persistent link: https://www.econbiz.de/10011122620
This paper provides a step-by-step guide to estimating infinite horizon discrete choice dynamic programming (DDP) models using a new Bayesian estimation algorithm (Imai, Jain and Ching, Econometrica 77:1865-1899, 2009) (IJC). In the conventional nested fixed point algorithm, most of the...
Persistent link: https://www.econbiz.de/10014046570
We propose a new methodology for structural estimation of infinite horizon dynamic discrete choice models. We combine the Dynamic Programming (DP) solution algorithm with the Bayesian Markov Chain Monte Carlo algorithm into a single algorithm that solves the DP problem and estimates the...
Persistent link: https://www.econbiz.de/10014047635
Persistent link: https://www.econbiz.de/10009554676
This paper provides a step-by-step guide to estimating discrete choice dynamic programming (DDP) models using the Bayesian Dynamic Programming algorithm developed in Imai, Jain and Ching (2008) (IJC). The IJC method combines the DDP solution algorithm with the Bayesian Markov Chain Monte Carlo...
Persistent link: https://www.econbiz.de/10003823595