Working PapersWorking PapersABSTRACT
We developed an integer programing extreme value (IPEV) model that accounts the integer property of trip data and has the same advantages as the multiple discrete–continuous extreme value choice (MDCEV) model. The proposed model is consistent with utility theory and provides a single structural framework for simultaneously modeling the choice of alternatives and quantity decisions with the constraint of the integer value of consumption. We demonstrate that the proposed model has a closed-form probability expression. Finally, we apply the proposed model to the recreation demand for national parks in Japan. The empirical results suggest that the proposed model provides a better fit for the data than the previous model and that ignoring the integer property of demand might cause an underestimation of the welfare loss.
Keywords: demand analysis, utility theory, integer demand, MDCEV, leisure trip demand
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.
Keywords: Value of time, multiple discrete-continuous models, recreation demand, demand system, welfare analysis
ABSTRACT
Researchers propose using a partial profile design using a subset of attributes in choice experiments (CEs) with a high number of attributes. Previous studies report estimation bias in partial profile CEs with a gno choiceh option. This study considers consistent estimations for partial profile designs. The theoretical analysis shows that the estimated parameters using partial profile CEs with a gno choiceh option are not consistent. This paper proposes a consistent estimator using information about the excluded attributes for a partial profile. The simulation results suggest that the proposed consistent estimator can yield unbiased parameters. Following the theoretical and simulation results, the authors discuss some implications for addressing estimation bias in partial profile CEs.
Keywords: Choice experiments, partial profile, "no choice" option, estimation bias, simulatio
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The demand for recreation exhibits intertemporal substitution, as well as spatial substitution. Inthispaper,we develop a dynamic Kuhn-Tucker model of recreation demand with intertemporal substitution effects, from both theoretical and empirical perspectives. We propose a dynamic extension of the traditional static Kuhn-Tucker model and apply this model to data for the beaches of Southern California. The empirical results suggest that disregarding intertemporal substitution effects may result in an overstatement of welfare loss; however, the difference in the compensating variations of the dynamic models with and without intertemporal substitution effects is relatively small for our dataset.
Keywords: welfare analysis, demand system, dynamic optimization, beach recreation
ABSTRACT
We developed an integer programming approach that takes into account the integral character of recreation behavior data and that has the same advantages as the Kuhn-Tucker continuous demand approach, which is consistent with utility theory, and provides a single structural framework for simultaneously modeling site selection and the participation decision. We then used the local search algorithm and the greedy method to estimate the parameters of the utility function and to calculate welfare changes. The results of our empirical study suggest that the integer programming approach provides a better fit to our data than does the continuous demand approach.Keywords: welfare analysis, demand system, approximate algorithms, beach recreation
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The purpose of this paper is to develop a new attribute-based elicitation method, a repeated dichotomous choice contingent valuation (repeated DCCV). In the field of environmental economics, contingent valuation (CV) has traditionally been used to determine the value of environmental resources. However, it is difficult to estimate preferences for attributes of environmental goods using a dichotomous choice, contingent valuation (DCCV) elicitation format. While the choice experiment (CE) technique is a type of multi-attribute preference-elicitation technique that is widely used in marketing research, there are only a few CE studies of environmental valuation. We develop a repeated DCCV format, whereby respondents are iteratively asked binary choice questions related to some offered profiles with multi-attribute bundles. Estimation using repeated DCCV is compared with that of CE using Monte Carlo simulation and with empirical survey data. The results of the simulation show that although parameters estimated by a repeated DCCV can be significant, it requires a larger sample than CE. The empirical evaluation uses survey data regarding provision of protection against oil spills in Tokyo Bay. Sixteen versions of the questionnaire were prepared, and respondents were asked DCCV questions 8 times in each version. The empirical results show that the parameters estimated by the repeated DCCV method are both significant and slightly different from those estimated by CE.Keywords: Contingent valuation, dichotomous choice, choice experiment, conjoint analysis, environmental valuation
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This paper analyzes the strategic behavior behind stated preferences in contingent valuation (CV) surveys. CV is one of several methods used to assess the value of environmental goods. It uses survey data in which respondents are asked about their willingness to pay (WTP) or willingness to accept compensation (WTA) for the environmental goods in question. Economic models of dichotomous choice with follow-up open-ended questions are developed. While respondents can report their preferences freely in the open-ended (OE) format, they must make a choice between "yes" or "no" to the offered payment scheme in a dichotomous choice (CE) format. Theoretical analysis shows that truth telling is the optimal strategy for the first DC question, but free-riding is optimal for the follow-up OE question. Furthermore, the strategic downward bias in follow-up responses is affected by the number of players and by the payment offered. We use experimental CV survey data of stated preferences for protecting the landscape of the Kushiro Wetland National Park in Hokkaido, Japan. Experimental results of this CV survey show that the WTP estimated by follow-up OE responses is significantly lower than the WTP estimated by DC responses, and that the payment offered has a positive effect on follow-up OE responses. These empirical results are compatible with results from theoretical analysisKeywords: strategic behavior, contingent valuation, incentive compatibility, experimental survey analysis
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The purpose of this paper is to estimate the environmental value of recycled wood wastes using conjoint analysis. A comparison of the pair-wise rating method and the choice experiment elicitation method is made. An empirical study of recycled water-cleaning filters made from wood wastes shows that recycling has significant value as estimated by both pair-wise rating and choice experiments. However, the estimated marginal willingness to pay for recycling differs somewhat between the two methods. It may be that profile design effects appear in our survey.
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This paper estimates the environmental value of the ecosystem in the Kushiro wetland using data from choice experiments (CE). CE asks individuals to pick from a set of resource management alternatives. The results are as follows: (1) The average willingness to pay is 16,414 yen/year/household and the aggregate willingness to pay is 36 billion yen/year, when all the land around the wetland (151,361 ha) is protected for the ecosystem. (2) Cost benefit analysis shows that the optimal protection area is in the range between Q4 (91,361 ha) and Q5 (151,361 ha). This means that it is important in terms of social welfare to protect not only the wetland itself, but also the forest around the wetland. (3) The internal scope insensitivity hypothesis is rejected.Keywords
conjoint analysis, choice experiment, wetland ecosystem, environmental valuation
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The economic theory of the scope test and of transaction value in stated preference (SP) data is analyzed. Scope tests are applied to several contingent valuation studies to determine whether willingness to pay (WTP) is derived from consumption or from transaction value. Although the scope insensitivity hypothesis is rejected, WTP may be overestimated due to the inclusion of transaction value. A choice experiment (CE) is analyzed, to estimate the effects of transaction value in SP data. The empirical results show that the WTP is overestimated due to the inclusion of transaction value.Keywords
transaction value, scope test, choice experiment, stated preference
ABSTRACT
A NOAA panel recommended that "no-answer" options be explicitly included in referendum-style contingent valuation (CV) surveys. However, excluding the resulting no-vote (NV) responses would mean not only losing the choice preference information of these respondents, it could also cause sample selection bias. This would be true if NV respondents' preferences differed from other respondents in the sample. This paper analyzes the incentive effects of NV options in double-bounded CV. If initial bids affect follow-up NV responses, there is a systematic difference between initial NV responses and follow-up NV responses. To analyze these effects we use a bivariate ordered probit model; this combines an ordered probit and a bivariate probit model.
Our empirical analysis uses data from a Yakusima World Heritage Site CV survey. Following the NOAA panel, we consider many CV survey design issues. These include conservative survey design, the double-bounded referendum elicitation method, the willingness to pay format, door-to-door in-person interviews, scope issues, and NV options. After extensive pilot surveys, a final CV survey was administered nationally in July 1997, resulting in 821 complete responses. The double-bounded data is analyzed using a bivariate ordered probit model. The empirical results demonstrate a strategic downward bias of 322 yen for the "strong scenario" when excluding the NV option, and 1,763 yen when the NV option is included. The NV option may strengthen strategic downward bias in double-bounded CV surveys.
Kuriyama, K., Y. Shoji, and T. Tsuge. (2023) The integer programing extreme value (IPEV) model: An application for estimation of the leisure trip demand. NRE Discussion Papers No. 2023-01, Natural Resource Economics, Division of Natural Resource Economics, Graduate School of Agriculture, Kyoto University.