Structural estimation of real options models
Gamba, Andrea and Tesser, Matteo. (2009) Structural estimation of real options models. Journal of Economic Dynamics and Control, Vol.33 (No.4). pp. 798-816. ISSN 0165-1889Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/j.jedc.2008.10.001
We propose a numerical approach for structural estimation of a class of discrete (Markov) decision processes emerging in real options applications. The approach is specifically designed to account for two typical features of aggregate data sets in real options: the endogeneity of firms’ decisions; the unobserved heterogeneity of firms. The approach extends the nested fixed point algorithm by Rust [1987. Optimal replacement of GMC bus engines: an empirical model of Harold Zurcher. Econometrica 55(5), 999–1033; 1988. Maximum likelihood estimation of discrete control processes. SIAM Journal of Control and Optimization 26(5), 1006–1024] because both the nested optimization algorithm and the integration over the distribution of the unobserved heterogeneity are accommodated using a simulation method based on a polynomial approximation of the value function and on recursive least squares estimation of the coefficients. The Monte Carlo study shows that omitting unobserved heterogeneity produces a significant estimation bias because the model can be highly non-linear with respect to the parameters.
|Item Type:||Journal Article|
|Subjects:||H Social Sciences > HG Finance|
|Divisions:||Faculty of Social Sciences > Warwick Business School > Finance Group
Faculty of Social Sciences > Warwick Business School
|Journal or Publication Title:||Journal of Economic Dynamics and Control|
|Number of Pages:||19|
|Page Range:||pp. 798-816|
|Access rights to Published version:||Restricted or Subscription Access|
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