Estimation and Welfare Calculations in a Generalized Corner Solution Model with an Application to Recreation Demand

The Kuhn-Tucker model of Wales and Woodland (1983) provides a utility theoretic framework for estimating preferences over commodities for which individuals choose not to consume one or more of the goods. Due to the complexity of the model, however, there have been few applications in the literature and little attention has been paid to the problems of welfare analysis within the Kuhn-Tucker framework. This paper provides an application of the model to the problem of recreation demand. In addition, we develop and apply a methodology for estimating compensating variation, relying on Monte Carlo integration to derive expected welfare changes.

[1]  P. Kokkonen,et al.  [Resources in the future]. , 2001, Duodecim; laaketieteellinen aikakauskirja.

[2]  Catherine L. Kling,et al.  Nonlinear Income Effects in Random Utility Models , 1999, Review of Economics and Statistics.

[3]  Daniel McFadden,et al.  Computing Willingness-to-Pay in Random Utility Models , 1996 .

[4]  Timothy J. Feist,et al.  Contaminant Trends in Lake Trout and Walleye From the Laurentian Great Lakes , 1996 .

[5]  G. Parsons,et al.  A Demand Theory for Number of Trips in a Random Utility Model of Recreation , 1995 .

[6]  D. Hellerstein,et al.  A Discrete-Count Model of Recreational Demand , 1995 .

[7]  V. Kerry Smith,et al.  Using Random Utility Models to Estimate the Recreational Value of Estuarine Resources , 1995 .

[8]  Jeffrey Englin,et al.  Estimating Social Welfare Using Count Data Models: An Application to Long-Run Recreation Demand under Conditions of Endogenous Stratification and Truncation , 1995 .

[9]  D. Waldman,et al.  Searching for a Model of Multiple-Site Recreation Demand that Admits Interior and Boundary Solutions , 1995 .

[10]  John Geweke,et al.  Monte carlo simulation and numerical integration , 1995 .

[11]  Gregory K. Leonard,et al.  A utility-consistent, combined discrete choice and count data model Assessing recreational use losses due to natural resource damage , 1995 .

[12]  N. Kalaitzandonakes Price Protection and Productivity Growth , 1994 .

[13]  Peter Feather,et al.  Sampling and Aggregation Issues in Random Utility Model Estimation , 1994 .

[14]  Teofilo Ozuna,et al.  ESTIMATING A SYSTEM OF RECREATION DEMAND FUNCTIONS USING A SEEMINGLY UNRELATED POISSON REGRESSION APPROACH , 1994 .

[15]  W. Adamowicz,et al.  Participation, Trip Frequency and Site Choice: A Multinomial-Poisson Hurdle Model of Recreation Demand , 1994 .

[16]  Russell S. Winer,et al.  Using Neoclassical Consumer-Choice Theory to Produce a Market Map From Purchase Data , 1994 .

[17]  A. Lyke Discrete choice models to value changes in environmental quality : a great lakes case study , 1993 .

[18]  George R. Parsons,et al.  Site Aggregation in a Random Utility Model of Recreation , 1992 .

[19]  B. Fortin,et al.  Labour supply, tax evasion and the marginal cost of public funds an empirical investigation , 1994 .

[20]  B. Fortin,et al.  Utility-Based Estimation of Labor Supply Functions in the Regular and Irregular Sectors , 1992 .

[21]  R. Perrin,et al.  Theory and Measurement of Producer Response under Quotas, The , 1992 .

[22]  C Levenstein,et al.  Environmental Economics , 2019 .

[23]  W. Douglass Shaw,et al.  A Discrete-Choice Model of Recreational Participation, Site Choice, and Activity Valuation When Complete Trip Data Are Not Available' , 1991 .

[24]  D. Heien,et al.  Demand Systems Estimation With Microdata: A Censored Regression Approach , 1990 .

[25]  Ivar E. Strand,et al.  Sample Selection Bias in the Estimation of Recreation Demand Functions: An Application to Sportfishing , 1990 .

[26]  Michael Creel,et al.  Theoretical and Empirical Advantages of Truncated Count Data Estimators for Analysis of Deer Hunting in California , 1990 .

[27]  W. Dunn,et al.  Polychlorinated dibenzofurans and polychlorinated dibenzo‐p‐dioxins in great lakes fish: A baseline and interlake comparison , 1989 .

[28]  S. Yen,et al.  Estimation of a Two-Level Demand System with Limited Dependent Variables , 1989 .

[29]  D. Waldman,et al.  Specification and estimation of a generalized corner solution model: An Amemiya-Tobin approach , 1989 .

[30]  V. Smith,et al.  Selection and Recreation Demand , 1988 .

[31]  D. Shaw,et al.  On-site samples' regression : Problems of non-negative integers, truncation, and endogenous stratification , 1988 .

[32]  Lung-fei Lee,et al.  Microeconometric Models of Rationing, Imperfect Markets, and Non-Negativity Constraints , 1987 .

[33]  Michael R. Ransom,et al.  An Empirical Model of Discrete and Continuous Choice in Family Labor Supply , 1987 .

[34]  W. Michael Hanemann,et al.  Estimating the Value of Water Quality Improvements in a Recreational Demand Framework , 1987 .

[35]  M. Ransom,et al.  The Labor Supply of Married Men: A Switching Regressions Model , 1985, Journal of Labor Economics.

[36]  C. Kling Measuring the recreational benefits of environmental amenities using multiple site models: an evaluation of techniques. , 1987 .

[37]  Lung-fei Lee,et al.  Specification and Estimation of Consumer Demand Systems with Many Binding Non-Negativity Constraints , 1986 .

[38]  Lung-fei Lee,et al.  Microeconometric Demand Systems with Binding Nonnegativity Constraints: The Dual Approach , 1986 .

[39]  E. Morey The Choice of Ski Areas: Estimation of a Generalized CES Preference Ordering with Characteristics , 1984 .

[40]  W. Hanemann Discrete-Continuous Models of Consumer Demand , 1984 .

[41]  T. Wales,et al.  Estimation of consumer demand systems with binding non-negativity constraints☆ , 1983 .

[42]  Ivar E. Strand,et al.  Measuring the Cost of Time in Recreation Demand Analysis: An Application to Sportfishing , 1981 .

[43]  D. McFadden Econometric Models of Probabilistic Choice , 1981 .

[44]  Takeshi Amemiya,et al.  Multivariate Regression and Simultaneous Equation Models when the Dependent Variables Are Truncated Normal , 1974 .

[45]  B. Achiriloaie,et al.  VI REFERENCES , 1961 .

[46]  J. Tobin Estimation of Relationships for Limited Dependent Variables , 1958 .