Demand Estimation with Selection Bias: A Dynamic Game Approach with an Application to the US Railroad Industry

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The working papers published in the Series constitute work in progress circulated to stimulate discussion and critical comments. Views expressed represent exclusively the authors' own opinions and do not necessarily reflect those of the editor. Terms of use: Documents in ABSTRACTThis paper is motivated by the US freight railroad industry, which is characterized by a major restructuring over the last 30 years. In particular, the number of active firms decreased from 26 in 1978 to seven in 2006 due to several takeover waves. The empirical focus concerns the estimation of a structural demand model for the US railroad industry. Then, the demand estimates are used to compute the evolution of the mark-ups, the quality of the freight services provided, and the consumer surplus. The restructuring of this industry involves significant exit and takeovers. This implies that the data is characterized by an attrition issue, which generates a selection problem. A focus is to provide an estimation algorithm which takes explicitly into account this attrition issue. I find that the algorithm produces more plausible estimates of demand coefficients compared to standard estimation procedures. Moreover, using the model, I recover the evolution of the marginal costs, mark-ups, and the consumer surplus over time. I find that the takeover waves have led to efficiency gains by decreasing the marginal costs, and this was translated into lower prices and an increase in the consumer surplus. Finally, the takeovers have led to a reallocation of assets from the less efficient firms to the most efficient firms, which improved the quality of the freight services provided.

The Static-Dynamic Efficiency Trade-off in the US Rail Freight Industry: Assessment of an Open Access Policy

“…The correction term is significant at the 5% level. This confirms that the methodology of Coublucq (2013) helps to deal with endogenous attrition due to concentration. 13 The Sargan test does not reject the over-identifying restriction, which therefore validates the choice of the instruments.…”

“…The econometric model includes two elements. The first element is the estimation of a demand model, where the issue of attrition due to the concentration in the US railroad industry over time is fully addressed using the methodology developed by Coublucq (2013). This estimated demand model is later used to simulate the expected future profits with an open-access market structure.…”

“…A discussion of the validity of the instruments and the estimation algorithm is in Appendix 2. (For further details, seeCoublucq, 2013. )…”

“…Coublucq (2013) provides an estimation algorithm to deal with endogenous attrition due to concentration in the US railroad industry. The economic intuition behind the selection issue is that the better management takes the control through mergers.…”

The flexible coefficient multinomial logit (FC‐MNL) model of demand for differentiated products

“…26 Specifically, a product was assumed missing in period t if the realization of a uniform random variable on [0,1] was less than 0.2, subject to the constraint that every market was assumed to have at least one inside good. 27 See Coublucq (2010) for a first attempt to address this issue. be 1.…”