Abstract
Often empirical researchers face many data constraints when estimating models of demand. These constraints can sometimes prevent adequate evaluation of policies. In this article, we discuss two such missing data problems that arise frequently: missing data on prices and missing information on the size of the potential market. We present some ways to overcome these limitations in the context of two recent research projects. Jacobi and Sovinsky (2018), which addresses how to incorporate unobserved price heterogeneity, and Hidalgo and Sovinsky (2018), which focuses on how to use modelling techniques to estimate missing market size. Our aim is to provide a starting point for thinking about ways to overcome common data issues.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Adams, B. and B. Martin (1996) “Cannabis: Pharmacology and Toxicology in Animals and Humans”, Addiction, Vol. 91, pp. 1585–1614.
Berry, S. (1994) “Estimating Discrete Choice Models of Product Differentiation”, Rand Journal of Economics, Vol. 25, No. 2, pp. 242–262.
——, J. Levinsohn and A. Pakes (1995) “Automobile Prices in Market Equilibrium”, Econometrica, Vol. 63, No 4, pp. 841–890.
Chiang, J., S. Chib and C. Narasimhan (1999) “Markov Chain Monte Carlo and Models of Consideration Set and Parameter Heterogeneity”, Journal of Econometrics, Vol. 89, pp. 223–248.
Geroski, P. (2000) “Models of Technology Diffusion”, Research Policy, Vol. 29, Nos 4–5, pp. 603–625.
Griliches, Z. (1957) “Hybrid Corn: An Exploration in the Economics of Technical Change”, Econometrica, Vol. 25, pp. 501–522.
Gruber, H. and F. Verboven (2001) “The Diffusion of Mobile Telecommunications Services in the European Union”, European Economic Review, Vol. 45, pp. 577–588.
Hidalgo, J. and M. Sovinsky (2018) “Internet (Power) to the People: The Impact of Demand-Side Subsidies in Colombia”, Working Paper, University of Mannheim.
Jacobi, L. and M. Sovinsky (2016) “Marijuana on Main Street: Estimating Demand in Markets with Limited Access”, American Economic Review, Vol. 106, No. 8, pp. 2009–45.
—— and —— (2018) “Incorporating (Unobserved) Price Heterogeneity”, Mimeo, University of Mannheim.
Mehta, N., S. Rajiv and K. Srinivasan (2003) “Price Uncertainty and Consumer Search: A Structural Model of Consideration Set Formation”, Marketing Science, Vol. 22, No. 1, pp. 58–84.
Nevo, A. (2000) “A Practitioner’s Guide to Estimation of Random Coefficients Logit Models of Demand”, Journal of Economics and Management Strategy, Vol. 9, No. 4, pp. 513–548.
Nierop, E., R. Paap, B. Bronnenberg, P. Franses and M. Wedel (2010) “Retreiving Unobserved Consideration Sets from Household Panel Data”, Journal of Marketing Research, Vol. 47, No. 1, pp. 63–74.
Parey, M. and I. Rasul (2017) “Measuring the Market Size for Cannabis: a New Approach Using Forensic Economics”, Economica, ISSN 0013-0427 (in press).
Poulsen, H. and G. Sutherland (2000) “The Potency of Cannabis in New Zealand from 1976 to 1996”, Science and Justice, Vol. 40, pp. 171–176.
Sovinsky Goeree, M. (2008) “Limited Information and Advertising in the US Personal Computer Industry”, Econometrica, Vol. 76, No. 5, pp. 1017–1074.
Sutton, P. (1997). “Modeling Population Density with Night-time Satellite Imagery and GIS”, Computers, Environment and Urban Systems, Vol. 21, Nos 3–4, pp. 227–244.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Hidalgo, J., Sovinsky, M. Forensic Econometrics: Demand Estimation When Data are Missing. JER 70, 403–410 (2019). https://doi.org/10.1111/jere.12242
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1111/jere.12242