Demand and Welfare Effects in Recreational Travel Models: A Bivariate Count Data Approach (original) (raw)
Transportation Research Part A: Policy and Practice, 2012
In this paper we present a non-linear demand system for households' joint choice of number of trips and days to spend at a destination. The approach, which facilitates welfare analysis of exogenous policy and price changes, is used empirically to study the e¤ects of an increased CO 2 tax. In the empirical study, a bivariate zero-in ‡ated Poisson lognormal regression model is introduced in order to accommodate the large number of zeroes in the sample. The welfare analysis reveals that the equivalent variation (EV) measure, for the count data demand system, can be seen as an upper bound for the households welfare loss. Approximating the welfare loss by the change in consumer surplus, accounting for the positive e¤ect from longer stays, imposes a lower bound on the households welfare loss. From a distributional point of view, the results reveal that the CO 2 tax reform is regressive, in the sense that low income households carry a larger part of the tax burden.
Environmental and Resource Economics, 1996
This paper proposes contingent behavior survey questions as a valuable supplement to observed data in travel cost models of non-market demand for recreational resources. A set of observed and contingent behavior results for each survey respondent allows the researcher to control for individual heterogeneity by taking advantage of panel data methods when exploring the nature of respondent demands. The contingent scenarios also provide opportunities to (a) test for differences between observed and contingent preferences and/or (b) assess likely demands under conditions beyond the domain of observed variation in costs or resource attributes. Most importantly, contingent scenarios allow the researcher to impose exogenously varying travel costs. Exogenous imposition of travel costs together with panel methods reduces the omitted variables bias that plagues observed-data travel cost models of recreational demand. Using a convemence sample of data for illustrative purposes, we show how to estimate the demand for recreational angling by combining observed and contingent behavior data. We begin with simple naive pooled Poisson models and progress to more theoretically appropriate fixed effects panel Poisson specifications.
A TRAVEL COST ESTIMATION OF CONSUMER SURPLUS IN RECREATIONAL VISITS: A COUNT MODEL APPROACH
Assam Economic Journal , 2022
Recreational services are demanded because they generate benefits. The recreational benefits connected with a destination can be valued based on visitor preferences, which can aid in the formulation of an appropriate Natural Resource Management policy. Environmental and natural resource management studies often attempt to quantify the welfare shift caused by a policy change. In general, welfare is defined as the area under the demand curve; and accordingly, by estimating the demand curve, consumer surplus is obtained, which illustrates the welfare changes connected with an environmental policy change. But unfortunately, conventional markets fail to determine the recreational demand preferences for lack of a proper price mechanism. So the only choice is a non-market method. The Travel Cost Method (TCM) is a well-documented demand based method in environmental literature for measuring such non-marketed recreational benefits. This study attempts to estimate the consumer surplus, in the recreational demand for the Dibru Saikhowa National Park (DSNP), Assam with the help of TCM. In the process, it also seeks to answer the question of whether the existing user charges of DSNP reflect the true recreational demand assigned to the park by its visitors. The findings of the study are expected to be useful for different stakeholders associated with the park's conservation in general and its recreational services in particular, including policy makers.
Truncation and Endogenous Stratification in Various Count Data Models for Recreation Demand Analysis
Journal of Development and Agricultural Economics
This paper extends the truncated and endogenously stratified Poisson and negative binomial models to three alternative discrete distributions, namely the generalized Poisson, geometric, and Borel distributions. Our primary intention here is to demonstrate how improper treatment of the data generates divergent outcomes by applying those distributions to recreation trip data gathered from surveys of visitors to an indigenous horse park in Japan. Our empirical application shows that failure to account for overdispersion, truncation, and endogenous stratification leads to substantial changes in parameter estimates and their standard errors. The parameter on the travel cost tends to be underestimated in absolute value in the standard setups. This results in serious overestimation of the economic benefit that the recreation site offers to society. Even when the endogenous stratification is incorporated, ignoring overdispersion causes the per capita per trip consumer's surplus to be ov...
Augmenting travel cost models with contingent behavior data
Environmental & Resource Economics, 1996
This paper proposes contingent behavior survey questions as a valuable supplement to observed data in travel cost models of non-market demand for recreational resources. A set of observed and contingent behavior results for each survey respondent allows the researcher to control for individual heterogeneity by taking advantage of panel data methods when exploring the nature of respondent demands. The contingent scenarios also provide opportunities to (a) test for differences between observed and contingent preferences and/or (b) assess likely demands under conditions beyond the domain of observed variation in costs or resource attributes. Most importantly, contingent scenarios allow the researcher to impose exogenously varying travel costs.
Since the early 1990s, researchers have routinely used count data models (such as the Poisson and negative binomial) to estimate the demand for recreational activities. Along with the success and popularity of count data models in recreational demand analysis during the last decade, a number of shortcomings of standard count data models became obvious to researchers. This had led to the development of new and more sophisticated model specifications. Furthermore, semi-parametric and non-parametric approaches have also made their way into count data models. Despite these advances, however, one interesting issue has received little research attention in this area. This is related to the fast decay process of the dependent variable and the associated long tail. This phenomenon is observed quite frequently in recreational demand studies; most recreationists make one or two trips while a few of them make exceedingly large number of trips. This introduces an extreme form of overdispersion ...
ARTICLE NO. EE960976 A Structural Equations Approach to Modeling Consumptive Recreation Demand
1996
In this analysis we develop a two equation structural model of a count travel cost model of recreational angling demand and angling success. By modeling the two equations jointly we avoid the difficulties associated with the usual approach which estimates the demand for recreational fishing sites assuming the existence of an exogenous measure of fishing quality. Our analysis explicitly develops the joint log likelihood function that combines the two processes. We estimate our model using full information maximum likelihood methods. Q 1997 Academic Press 1.
A Structural Equations Approach to Modeling Consumptive Recreation Demand
Journal of Environmental Economics and Management, 1997
The usual approach is estimating the demand for recreational fishing assumes that the measure of fishing quality is exogenous to the angler. In contrast here, a likelihood function is developed which combines two Poisson processes to jointly estimate the number of fish caught and recreational fishing trips taken. Dissolved oxygen and turbidity at the lakes in the analysis have significant effects on an individual's catch, and hence fishing demand. Welfare measures are calculated for changes in these environmental variables.
Journal of Applied Economics, 2012
Using count data models that account for zero-truncation, overdispersion, and endogenous stratification, we estimate the value of access to recreational parks. The focus is on the empirical estimation of the proportion of the wage rate that best approximates park visitors' opportunity cost of travel time within the cost of their trip and its effects on estimated consumer surplus. The fraction of hourly earnings that corresponds to the opportunity cost of travel time is endogenously estimated as a function of visitor characteristics, rather than fixed exogenously. In this case, which deals with a relatively remote recreational site, the relevant opportunity cost of time for most visitors appears to represent a smaller fraction of their wage rate than commonly assumed in previous similar studies.