Utility theoretic semi-logarithmic incomplete demand systems in a natural experiment: Forest fire impacts on recreational values and use

This study develops a utility theoretic demand model for an arbitrary number of goods that handles correlation between goods and over time. The bivariate compound Poisson estimator is applied to a semi-logarithmic incomplete demand system to estimate the demand for wilderness recreation and the associated welfare measures both prior to and post a 40,000 acre wilderness fire in Washington. Forest fires can simultaneously affect the environmental qualities of many recreational sites; this highlights the need for a utility theoretic demand system approach for modeling consumer behavior that handles the dynamic behavioral and statistical interdependencies over goods and time. Results suggest an increase in consumer welfare per trip post fire, after an initial period of low values, relative to before the fire.     

Modelling and mapping spatial heterogeneity in forest recreation services

Modelling and spatial mapping of recreation services require attention to both demand and supply factors. This paper combines recreational choice modelling and economic valuation with GIS based techniques to allow an assessment of the spatial diversity of the value of forest recreation services. The data for the analysis is a national study of the car borne recreational use of Danish forest sites. A random utility framework is used and a comparison between the standard fixed coefficient model and a mixed logit model is made. The results show that the different specifications of the random utility models reveal similar preferences for the measured forest attributes in terms of sign and magnitude. The spatial predictions, however, reveal a considerable difference in the spatial pattern of economic benefits from recreation between the two models. These results have implications for current ecosystem service mapping initiatives as they emphasise the need to account for spatial heterogeneity in preferences, and aggregate demand and environmental attributes and infrastructure.     

Augmenting travel cost models with contingent behavior data

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 conditionsbeyond the domain of observed variation in costs or resource attributes. Most importantly, contingent scenarios allow the researcher to imposeexogenously 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 convenience 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.The authors are at the University of Nevada and UCLA, respectively. We gratefully acknowledge the comments of both Scott Shonkwiler and participants in the W133 meetings in Santa Fe, New Mexico and for research material provided by Wayne Gray. The data were provided by Rang Narayanan. Research assistance was provided by Jerry McGraw and Natalie Tucker. Research partially supported by the Nevada Experiment Station. Any errors or omissions remain the authors' responsibility.     

A Systematic Assessment of the Environmental Impacts of Transport Policy

This paper presents an integrated urbanpassenger transport model system for evaluatingthe impact of a large number of interrelatedpolicy instruments on urban travel behaviourand the environment. The model system has fourintegrated modules defining household locationand automobile choices, commuter workplace andcommuting travel choices, non-commuting travelactivity, and worker distributed workpractices. The demand model system, estimatedas a set of discrete and continuous choicemodels, is combined with a set of equilibratingcriteria in each of the location, automobileand commuting markets to predict overall demandfor passenger travel in various socio-economicsegments, automobile classes and geographiclocations. We illustrate the diversity of thesystem by applying the integrated system toPerth (Western Australia), in the context ofassessing their impacts on greenhouse gasemissions. The model system is embedded withina decision support system to make it anattractive suite of tools for practitioners.     

Model Uncertainty in Characterizing Recreation Demand

A Bayesian variable selection procedure is used to control for uncertainty in the specification of a recreational demand model. Specifically, we propose a model that draws on the Bayesian paradigm to integrate the variable selection process into model estimation and to reflect the accompanying uncertainty about which is the best specification in subsequent counterfactual predictions. The advantage of this procedure over previous non-Bayesian approaches is that it overcomes the problem of pre-testing in specification searches. In our application, evaluating demand for recreational lake usage in Iowa, we find clear evidence that site attributes, such as lakes size, handicap facilities and wake restrictions, do impact lake usage. There is also evidence that water quality matters in household recreation choices. Indeed, contrary to Abidoye et?al. (Am J Agricult Econ, 2012), in which only a single functional form is considered, we find clear evidence that water quality matters, with posterior probability of less that 10 % associated with a model without any water quality variables. This suggests that the flexibility that the Bayesian variable selection model affords in capturing the linkage between recreation demand and site characteristics can be important.     

Recreation demand estimation and valuation in spatially connected systems

Recreation demand models frequently are used to explain outdoor recreation behavior and to estimate willingness to pay for changes in environmental quality at recreation sites. Among the most commonly used recreation demand models are site choice models based on the multinomial logit framework, which account for the spatial relationships between each recreator's home and multiple alternative destinations thereby capturing the substitution possibilities among recreation sites. However, standard applications of this framework typically do not account for the possibility of spatial connections among the sites via movements of the target species, such as fish in connected water bodies in recreational angling applications or terrestrial species in hunting or wildlife viewing applications. In this paper we examine aspects of environmental valuation and natural resource dynamics that generally are addressed separately. Specifically, we show that in such spatially connected systems, a “reduced form” application of the standard site choice modeling approach, using proxy measures of environmental quality rather than direct measures of species abundances, can produce biased estimates of willingness to pay for environmental improvements. Furthermore, we show that under some conditions poorly targeted environmental improvements in spatially connected systems can lead to welfare decreases. In such systems a structural model of recreator site choices and species sorting behavior and population dynamics may be required to fully account for the spatial linkages among sites and the feedback effects between recreators and the target species.     

Environmental diversity in recreational choice modelling

The accuracy of environmental valuation studies relies, to a great extent, on the suitability of the proxy measures used to capture individuals' preferences. While important advances have been achieved in the last years concerning the characterization of the physical background in which recreational choices are made, Travel Cost Method applications have failed to consider the heterogeneity of landscape and the spatial configuration of land use. This paper presents an empirical application to forest recreation in Mallorca (Spain), implementing a random parameter logit model to evaluate in terms of goodness-of-fit, model predictions and welfare measurements the effects of environmental diversity on the recreational site-choice process.     

A spatial analysis of provincial corporate income tax responses: evidence from Canada

Abstract.  Using a model of interdependent tax choices, and accounting for equalization entitlements and general transfers, this paper estimates – making use of a spatial econometric framework – corporate income tax-setting functions for all Canadian provincial governments. The results show that there is a statistically significant positive fiscal interaction among a subset of provinces and between all provinces and the federal government. Provincial corporate income taxes are also found to be negatively related to equalization entitlements, general federal transfers, and the federal corporate income tax. A robustness check on the fiscal relationship between Ontario and Quebec verifies the existence of significant bi-directional fiscal interdependencies. The paper also introduces U.S state corporate income taxes as covariates and examines their interaction with Canadian provinces.     

Predicting land use allocation in France: A spatial panel data analysis

Predictions of future land use areas are an important issue as land use patterns significantly impact environmental conditions (biodiversity, water pollution, soil erosion, and climate change) as well as economic and social welfare. In order to improve the prediction accuracy of aggregated land use share models, we propose in this paper a methodological contribution by controlling for both unobserved individual heterogeneity and spatial autocorrelation. Our model is a land use shares model applied to aggregated data in France. Our dataset is a panel which covers both time series observations from 1992 to 2003 and cross-sectional observations by Département (equivalent to NUTS3 regions). We consider four land use classes: (1) agriculture, (2) forest, (3) urban and (4) other use. We investigate the relation between the areas in land in different alternative uses and economic and demographic factors influencing land use decisions. Based on the comparison of prediction accuracy of different model specifications, our findings are threefold: First, controlling for both unobserved individual heterogeneity and spatial autocorrelation outperforms any other specification in which spatial autocorrelation and/or individual heterogeneity are ignored. Second, accounting for cross-equation correlations does not seem to improve the prediction performances and finally, ignoring individual heterogeneity introduces substantial loss in prediction accuracy.     

DISCRETE CHOICE MODELS WITH MULTIPLE UNOBSERVED CHOICE CHARACTERISTICS*

Since the pioneering work by Daniel McFadden, utility‐maximization‐based multinomial response models have become important tools of empirical researchers. Various generalizations of these models have been developed to allow for unobserved heterogeneity in taste parameters and choice characteristics. Here we investigate how rich a specification of the unobserved components is needed to rationalize arbitrary choice patterns in settings with many individual decision makers, multiple markets, and large choice sets. We find that if one restricts the utility function to be monotone in the unobserved choice characteristics, then up to two unobserved choice characteristics may be needed to rationalize the choices.     

A Spatial Microsimulation Approach to Estimating the Total Number and Economic Value of Site Visits in Travel Cost Modelling

This paper presents a simulation-based modelling approach for simultaneously estimating the total number and aggregate value of recreation-related visits to a small-scale community forest in the West of Ireland. Spatially-referenced simulated individuals from a spatial microsimulation model for Ireland (SMILE) who reside within the geographic extent of the market for recreation at the forest are identified using GIS techniques. A travel cost model, adjusted for truncation and endogenous stratification, is estimated for a sample of visitors to the site and transferred across each individual in the simulated population. The SMILE model and GIS-based network analysis are used to derive the appropriate values for the explanatory variables in the transfer. Each simulated individual’s latent demand for visits to the site is predicted and summed, in order to derive aggregate visits and amenity value estimates. The paper makes two principal contributions. First, it sets out a new approach for modelling the geographic extent of the market for recreation using survey data on reported travel distances and GIS techniques. Second, it develops a new simulation-based modelling approach for predicting total site visits at non-priced open-access recreation sites.     

The complementarity between calls and messages in mobile telephony

This article estimates price elasticities of demand for mobile telephone calls and messages. We use panel data consisting of telephone bills to Portuguese mobile telephony consumers. In order to account for the unobserved individual heterogeneity and data censoring, we estimate a Tobit model for panel data with individual random effects. The demands for calls and messages are inelastic. Calls and messages are found to be complements.     

Modeling Multiple-Objective Recreation Trips with Choices Over Trip Duration and Alternative Sites

Traditionally, recreation demand studies have focused on single-day, single-activity trips, despite anecdotal and empirical evidence that many recreational trips involve overnight stays and multiple purposes. This paper develops a random utility model that explores how visitors choose alternative sites and trip durations for multiple-objective trips. We focus on a recreational activity, beach visits, that appear to have significant proportions of the population taking single and multiple-day trips, and many of the multiple day trips involve multiple objectives. Multiple-duration and multiple-objective issues are incorporated in pricing trip costs. The results of the research suggest that the accepted method for incorporating travel costs into random utility models can lead to biased estimates of the structural utility parameters and, consequently, biased measures of welfare in a multiple-objective trip setting for single- and multiple-day users.     

Applying Intermediate Microeconomics to Terrorism

The authors show how microeconomic concepts and principles are applicable to the study of terrorism. The utility maximization model provides insights into both terrorist resource allocation choices and government counterterrorism efforts, and basic game theory helps characterize the strategic interdependencies among terrorists and governments.     

Using spatial microsimulation to account for demographic and spatial factors in environmental benefit transfer

This paper presents a simulation-based modelling approach for estimating total visitor numbers and amenity values for prospective non-priced open-access outdoor recreation sites. To begin, the geographic extent of the market for recreation at a policy site is estimated using data from a similar study site. The population residing within this geographic area is simulated using a spatial microsimulation model and GIS techniques and an individual-level ‘visitor arrival function’ is then transferred across this simulated population. This allows the latent demand for visits to the policy site by each simulated individual to be predicted and summed, providing an estimate of the total potential demand for recreation at the site. Combining this with an economic value measure of a visit provides an estimate of the potential amenity value of the policy site. The approach is applied to Moyode Wood, a small-scale forest in the West of Ireland, and estimates the potential total economic value of recreation at €0.4 million for the site. The research represents the first time that spatial microsimulation has been used in environmental benefit transfer and shows how it can be used to control for differences in demographic and spatial factors between study and policy sites. It also demonstrates how individual-level single-site travel cost models estimated using on-site survey data can be used to predict demand at alternative policy sites.     

Corruption in space: A closer look at the world's subnations

Corruption levels differ not only between but also within countries. In this paper we analyze spatial interdependencies in corruption levels for a large sample of 1232 subnational regions from 81 countries. Based on a spatial autoregressive model, which controls for country-fixed effects and corrects for spatial autocorrelation in the error term, we find that a subnational region's corruption level is positively correlated with neighboring subnational regions' corruption levels. Extending the core model and allowing for heterogeneous spatial effects, we find that most spillovers among subnational regions occur within national borders. Moreover, in particular high income subnational regions and subnational regions with relative low corruption levels tend to spill in space. This is due to their high degree of connectivity in terms of economic, sociocultural and political exchange with other subnational regions. Our estimation results underline the importance to consider not only a subnational region's own characteristics, but also spatial interdependencies when implementing efficient anti-corruption policies at the local level.     

Spatially induced disparities in users' and non-users' WTP for water quality improvements—Testing the effect of multiple substitutes and distance decay

Costs and benefits of water restoration projects are not necessarily evenly spread out over the entire area affected by the project. The physical distribution of benefits is, therefore, an important parameter when conducting economic analyses of water restoration projects. Two particularly relevant spatial issues relate to 1) the location of the population relative to the location of the waterbody, and 2) the availability and characteristics of substitute water bodies.Based on a contingent valuation (CV) study of the demand for restoring Odense River in Denmark a spatial demand model which accounts for travel time both to the river subject for valuation and to potential substitute sites is estimated. It is concluded that the spatial distribution of benefits is unlikely to be homogeneously determined by a one-dimensional spatial model. Moreover, the results suggest that the effect of spatial issues on preferences varies between users and non-users. For non-users the spatial impacts from potential substitutes significantly reduce demand for improvements in Odense River. This indicates that focus on estimation of distance decay effects may be an important tool in relation to ensuring proper geographical delimitation of the population in a given context.     

A NEW THEORY OF DEMAND AND SUPPLY AND EMERGENCE OF INTERNATIONAL TRADE FROM DOMESTIC TRADE

Abstract. In the paper a fixed learning cost is introduced into a framework with consumer-producers and transaction costs. The fixed learning cost yields a rate of return on the investment in individual specific learning and training which is increasing in its rate of utilization. Division of labor can avoid duplicated learning costs and generate economies of specialized learning. The tradeoff between economies of specialization and transaction costs can be used to explain concurrent increases in the extent of the market, aggregate demand, productivity, trade dependence, the degree of market integration, the degree of production concentration, diversity of economic structure, variety of different professions, each person's level of specialization, and the extent of endogenous comparative advantage and the emergence of international trade from domestic trade. This model explains demand and supply as two sides of the level of division of labor which is determined by a transaction cost coefficient. Hence, the demand law may not hold even for normal goods owing to complicated interdependencies between the level of specialization and demand and between the level of specialization and prices of traded goods. The extended version of this model with the CES function is used to endogenize variety of consumption in addition to the endogenization of individuals'level of specialization.     

The impact of license regulation on the number of recreation trips: is it worth considering?

A two-stage nonlinear least-squares model (2NLS) with an endogenous treatment effect on recreation trips describes the behavior of recreationists with and without a fishing/hunting license. The proposed 2NLS is applied to the derivation of the policy-relevant average gains in the presence of an endogeneity bias to a license fee implementation program regulated by states. Recreationists who purchased a license are likely to recreate more than are the nonlicensed holders because the regulation may reduce congestions at sites where licensee visit often. The license regulation has a greater impact on the use of natural resources after controlling observed and unobserved confounders which might be correlated with the probability of being a license holder and with the final outcome, the number of recreation trips. We confirm that the individual without a permit regards the recreation trip as less valuable than does the individual having a license permit. We also found that the likelihood of purchasing a license among young adult recreationists is not at the level the states may desire. In addition, the number of trips demanded is more responsive to the nontransportation-related implicit travel cost than to the transportation-related implicit travel cost, although travel implicit costs are price inelastic.      

CAN RECREATION VALUES FOR A LAKE CONSTITUTE A MARKET FOR BANKED AGRICULTURAL WATER?

This paper presents estimates of the recreational use value to prevent the loss of a western lake threatened by diversions of upstream waters that supply it. The recreation demand model used to estimate recreation-related values is the popular repeated nested multinomial logit model. The model is specified to allow an individual to choose when to visit various sites during the season, because site choice is likely to be influenced by water levels that change over the course of the season. The values are compared to agricultural values in order to assess whether the potential recreation demand side of a market for a water bank exists.