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The value of leisure time of weekends and long holidays: The multiple discrete–continuous extreme value (MDCEV) choice model with triple constraints

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  • Kuriyama, Koichi
  • Shoji, Yasushi
  • Tsuge, Takahiro

Abstract

In this study, we apply the multiple discrete–continuous extreme value (MDCEV) model with triple constraints to identify the value of leisure time during weekends and long holidays. Our approach models the economic behavior of leisure trips with the triple constraints of budget, duration of weekend, and duration of holiday. The econometric model is developed to construct an estimation using the observed allocation of goods and time between a weekend and a long holiday. Our proposed approach models endogenous time allocation and analyzes the substitution effect between weekends and long holidays. Furthermore, we solve a system of nonlinear equations using the Karush-Kuhn-Tucker condition and the Markov Chain Monte Carlo (MCMC) method, which constructs the value of leisure times, demand prediction, and welfare analysis. Finally, we apply the proposed model to the recreation demand for national parks in Japan. The results suggest a significantly large difference in the value of leisure time between weekends and long holidays with low substitution effects between them.

Suggested Citation

  • Kuriyama, Koichi & Shoji, Yasushi & Tsuge, Takahiro, 2020. "The value of leisure time of weekends and long holidays: The multiple discrete–continuous extreme value (MDCEV) choice model with triple constraints," Journal of choice modelling, Elsevier, vol. 37(C).
    • Handle: RePEc:eee:eejocm:v:37:y:2020:i:c:s1755534520300361
    DOI: 10.1016/j.jocm.2020.100238
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    1. 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.
    2. Lew, Daniel K. & Larson, Douglas M., 2005. "Accounting for stochastic shadow values of time in discrete-choice recreation demand models," Journal of Environmental Economics and Management, Elsevier, vol. 50(2), pages 341-361, September.
    3. Feather, Peter & Shaw, W. Douglass, 1999. "Estimating the Cost of Leisure Time for Recreation Demand Models," Journal of Environmental Economics and Management, Elsevier, vol. 38(1), pages 49-65, July.
    4. Lloyd-Smith, Patrick, 2018. "A new approach to calculating welfare measures in Kuhn-Tucker demand models," Journal of choice modelling, Elsevier, vol. 26(C), pages 19-27.
    5. Evans, Alan W, 1972. "On the Theory of the Valuation and Allocation of Time," Scottish Journal of Political Economy, Scottish Economic Society, vol. 19(1), pages 1-17, February.
    6. Sikder, Sujan & Pinjari, Abdul Rawoof, 2013. "The benefits of allowing heteroscedastic stochastic distributions in multiple discrete-continuous choice models," Journal of choice modelling, Elsevier, vol. 9(C), pages 39-56.
    7. Fezzi, Carlo & Bateman, Ian J. & Ferrini, Silvia, 2014. "Using revealed preferences to estimate the Value of Travel Time to recreation sites," Journal of Environmental Economics and Management, Elsevier, vol. 67(1), pages 58-70.
    8. Chandra Bhat & Rajul Misra, 1999. "Discretionary activity time allocation of individuals between in-home and out-of-home and between weekdays and weekends," Transportation, Springer, vol. 26(2), pages 193-229, May.
    9. Hensher, D A & Hotchkiss, W E, 1974. "Choice of Mode and the Value of Travel Time Savings for the Journey to Work," The Economic Record, The Economic Society of Australia, vol. 50(129), pages 94-112, March.
    10. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    11. Herriges, Joseph A. & Kling, Catherine L. & Phaneuf, Daniel J., 2004. "What's the use? welfare estimates from revealed preference models when weak complementarity does not hold," Journal of Environmental Economics and Management, Elsevier, vol. 47(1), pages 55-70, January.
    12. DeSerpa, A C, 1971. "A Theory of the Economics of Time," Economic Journal, Royal Economic Society, vol. 81(324), pages 828-846, December.
    13. Takuya Satomura & Jaehwan Kim & Greg M. Allenby, 2011. "Multiple-Constraint Choice Models with Corner and Interior Solutions," Marketing Science, INFORMS, vol. 30(3), pages 481-490, 05-06.
    14. 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.
    15. Hanemann, W Michael, 1984. "Discrete-Continuous Models of Consumer Demand," Econometrica, Econometric Society, vol. 52(3), pages 541-561, May.
    16. Wales, T. J. & Woodland, A. D., 1983. "Estimation of consumer demand systems with binding non-negativity constraints," Journal of Econometrics, Elsevier, vol. 21(3), pages 263-285, April.
    17. Douglas M. Larson & Sabina L. Shaikh, 2004. "Recreation Demand Choices and Revealed Values of Leisure Time," Economic Inquiry, Western Economic Association International, vol. 42(2), pages 264-278, April.
    18. Kitamura, Ryuichi, 1984. "A model of daily time allocation to discretionary out-of-home activities and trips," Transportation Research Part B: Methodological, Elsevier, vol. 18(3), pages 255-266, June.
    19. Frank J. Cesario, 1976. "Value of Time in Recreation Benefit Studies," Land Economics, University of Wisconsin Press, vol. 52(1), pages 32-41.
    20. D. A. Hensher & W. E. Hotchkiss, 1974. "Choice of Mode and the Value of Travel Time Savings for the Journey to Work," The Economic Record, The Economic Society of Australia, vol. 50(1), pages 94-112, March.
    21. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
    22. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    23. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 715-719, November.
    24. Chandra R. Bhat & Subodh K. Dubey & Mohammad Jobair Bin Alam & Waleed H. Khushefati, 2015. "A New Spatial Multiple Discrete-Continuous Modeling Approach To Land Use Change Analysis," Journal of Regional Science, Wiley Blackwell, vol. 55(5), pages 801-841, November.
    25. 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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    More about this item

    Keywords

    Value of time; Multiple discrete–continuous models; Recreation demand; Demand system; Welfare analysis;
    All these keywords.

    JEL classification:

    • Q26 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Recreational Aspects of Natural Resources
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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