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 0165-1889

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Abstract

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
Publisher:	Elsevier BV
ISSN:	0165-1889
Date:	2009
Volume:	Vol.33
Number:	No.4
Number of Pages:	19
Page Range:	pp. 798-816
Identification Number:	10.1016/j.jedc.2008.10.001
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
URI:	http://wrap.warwick.ac.uk/id/eprint/44779

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