1) and income when individuals do not consume all goods in strictly positive quantities. Results from a Monte Carlo experiment suggest that these biases can be substantial for large-scale policy shocks when prices are highly correlated."> 1) and income when individuals do not consume all goods in strictly positive quantities. Results from a Monte Carlo experiment suggest that these biases can be substantial for large-scale policy shocks when prices are highly correlated.">
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Incomplete Demand Systems, Corner Solutions, and Welfare Measurement

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  • von Haefen, Roger H.
Abstract
This paper demonstrates how corner solutions raise difficulties for the specification, estimation, and use of incomplete demand systems for welfare measurement with disaggregate consumption data, as is common in the outdoor recreation literature. A simple analytical model of consumer behavior is used to elucidate the potential biases for welfare measurement arising from modeling the demand for M goods as a function of M + N prices (N > 1) and income when individuals do not consume all goods in strictly positive quantities. Results from a Monte Carlo experiment suggest that these biases can be substantial for large-scale policy shocks when prices are highly correlated.

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  • von Haefen, Roger H., 2010. "Incomplete Demand Systems, Corner Solutions, and Welfare Measurement," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 39(1), pages 1-15, February.
    • Handle: RePEc:ags:arerjl:59327
    DOI: 10.22004/ag.econ.59327
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    1. Daniel J. Phaneuf & Catherine L. Kling & Joseph A. Herriges, 2000. "Estimation and Welfare Calculations in a Generalized Corner Solution Model with an Application to Recreation Demand," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 83-92, February.
    2. Phaneuf, Daniel J. & Carbone, Jared C. & Herriges, Joseph A., 2009. "Non-price equilibria for non-marketed goods," Journal of Environmental Economics and Management, Elsevier, vol. 57(1), pages 45-64, January.
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    4. Phaneuf, Daniel J., 1999. "A Dual Approach to Modeling Corner Solutions in Recreation Demand," Journal of Environmental Economics and Management, Elsevier, vol. 37(1), pages 85-105, January.
    5. V. Kerry Smith, 1993. "Welfare Effects, Omitted Variables, and the Extent of the Market," Land Economics, University of Wisconsin Press, vol. 69(2), pages 121-131.
    6. von Haefen R.H. & Phaneuf D.J. & Parsons G.R., 2004. "Estimation and Welfare Analysis With Large Demand Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 194-205, April.
    7. Catherine L. Kling, 1989. "A Note on the Welfare Effects of Omitting Substitute Prices and Qualities from Travel Cost Models," Land Economics, University of Wisconsin Press, vol. 65(3), pages 290-296.
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    4. Pinjari, Abdul Rawoof & Augustin, Bertho & Sivaraman, Vijayaraghavan & Faghih Imani, Ahmadreza & Eluru, Naveen & Pendyala, Ram M., 2016. "Stochastic frontier estimation of budgets for Kuhn–Tucker demand systems: Application to activity time-use analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 117-133.
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    7. Castro, Marisol & Bhat, Chandra R. & Pendyala, Ram M. & Jara-Díaz, Sergio R., 2012. "Accommodating multiple constraints in the multiple discrete–continuous extreme value (MDCEV) choice model," Transportation Research Part B: Methodological, Elsevier, vol. 46(6), pages 729-743.

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