We develop a framework to incorporate exchange rates into a differential demand system and apply it to U.S. demand for fresh tomatoes by country of origin. We find evidence of incomplete exchange-rate pass-through involving Mexico. Results indicate that accusations of dumping by American agricultural groups in 1995-1996 coincide with the appreciation of the U.S. dollar against the peso in 1994-1995. Traditional modeling approaches that do not account for exchange-rate effects would not capture the distinction between dumping and changes in relative prices, leading to the conclusion that too many tomatoes were being imported from Mexico.

The treatment of the opportunity cost of travel time in travel cost models has been an area of research interest for many decades. Our analysis develops a methodology to combine the travel distance and travel time data with respondent-specific estimates of the value of travel time savings (VTTS). The individual VTTS are elicited with the use of discrete choice stated preference methods. The travel time valuation procedure is integrated into the travel cost valuation exercise to create a two-equation structural model of site valuation. Since the travel time equation of the structural model incorporates individual preference heterogeneity, the full structure model provides a travel cost site demand model based upon individualized values of time. The methodology is illustrated in a study of recreational birdwatching, more specifically, visits to a ‘stork village’ in Poland. We show that the usual practice of basing respondents’ VTTS on 1/3 of their wage rate is largely unfounded and propose alternatives—including a separate component of the travel cost survey aimed at valuation of respondents’ VTTS or, as a second best, asking if they wish if their journey was shorter and for those who do—use full hourly wage as an indicator of their VTTS.

Early applications of wilderness economic research demonstrated that the values of natural amenities and commodities produced from natural areas could be measured in commensurate terms.To the surprise of many, the economic values of wilderness protection often exceeded the potential commercial values that might result from resource extraction.Here, the concepts and tools used in the economic analysis of wilderness are described, and the wilderness economic literature is reviewed with a focus on understanding trends in use, value, and economic impacts.Although our review suggests that each of these factors is trending upward, variations in research methods plus large gaps in the literature limit understanding of long-run trends.However, as new data on wilderness use, visitor origins, and spatially referenced features of landscapes are becoming increasingly available, more robust economic analysis of both onsite and offsite wilderness economic values and impacts is now becoming possible.

While the demand for forest recreation has been a topic covered in many studies, little attention has been paid so far to seasonal demand. In a forest context, the seasonal analysis is particularly interesting because of inter-temporal change in forest attributes throughout the year which can influence trip-taking behavior. In this paper, the model of seasonal forest visitation is developed to provide a richer understanding of the role played by seasonal fluctuation on a distribution of forest social benefits. The analysis is based on an on-site survey conducted in four forests in Poland. Results show that the most valuable forest trips are those taken in fall and that seasonal trips are separable.

one of the challenges facing many applications of nonmarket valuations is to find data with enough variation in the variable(s) of interest to estimate econometrically their effects on the quantity demanded. a solution to this problem was the introduction of stated preference surveys. These surveys can introduce variation into variables where there is no natural variation and, as a result, natural experiments are not possible. The problem of no or insufficient variation in naturally occurring data to estimate the effects of interest has led to a large literature on stated preference methods. among the methods developed, two can be linked directly to observed behaviour. unlike contingent valuation questions, these approaches key off of actual choices that individuals have made in the past or are contemplating in the future. Consequently, the consistency of these choices with the responses to stated preference questions can be examined. The two methods are those based upon random utility theory and those based upon demand theory. While the two can be linked theoretically in practice, one either adopts a random utility framework or a demand framework. The demand framework, adopted here, is frequently identified as a ‘contingent behaviour’ approach. The contingent behaviour method was proposed by Englin and Cameron (1996). Their paper suggests focusing on the number of trips an individual might make under different situations rather than how a single choice might vary (random utility model) under different situations. The advantage of the contingent behaviour model is that it includes both the intensive and the extensive margin while the random utility approach focuses solely on the intensive margin. as a result, the contingent behaviour approach can capture improvements with the extensive margin as well as quality reductions on the intensive margin. While considerable effort has been expended examining the functional form, parametric specifications and distributional assumptions used in contingent behaviour studies, no effort has been spent examining the role

Reliable estimates of the impacts and costs of biological invasions are critical to developing credible management, trade and regulatory policies. Worldwide, forests and urban trees provide important ecosystem services as well as economic and social benefits, but are threatened by non-native insects. More than 450 non-native forest insects are established in the United States but estimates of broad-scale economic impacts associated with these species are largely unavailable. We developed a novel modeling approach that maximizes the use of available data, accounts for multiple sources of uncertainty, and provides cost estimates for three major feeding guilds of non-native forest insects. For each guild, we calculated the economic damages for five cost categories and we estimated the probability of future introductions of damaging pests. We found that costs are largely borne by homeowners and municipal governments. Wood- and phloem-boring insects are anticipated to cause the largest economic impacts by annually inducing nearly $1.7 billion in local government expenditures and approximately $830 million in lost residential property values. Given observations of new species, there is a 32% chance that another highly destructive borer species will invade the U.S. in the next 10 years. Our damage estimates provide a crucial but previously missing component of cost-benefit analyses to evaluate policies and management options intended to reduce species introductions. The modeling approach we developed is highly flexible and could be similarly employed to estimate damages in other countries or natural resource sectors.

This paper assesses the impact that the routine application of Ontario's forest management planning process has on the revenue generation of sport fishing tourism sites. The analysis employs a hedonic pricing model to examine jointly these effects on revenue for three tourism experiences. These tourism experiences offer different degrees of remoteness, and as a consequence, require different levels of effort and cost to visit. Modelling the relationship between price and attributes of sites such as remoteness permits the analysis to forecast the revenue generation potential of sport fishing tourism sites under a range of forest management schemes. The results show that the extent of forest harvesting had no statistical relationship with prices charged for fishing packages at road-, boat-, or train-accessible sites and a negative but small impact on the prices charged for fishing packages at sites accessible by float plane.

Sudden oak death (SOD), caused by the non-indigenous forest pathogen Phytophthora ramorum, causes substantial mortality in coast live oak (Quercus agrifolia) and several other oak species on the Pacific Coast of the United States. Quasi-experimental hedonic models examine the effect of SOD on property values with a dataset that spans more than two decades including a decade of transactions before and after the invasion. The long study period allows for a unique contribution to the hedonic literature on natural hazards by studying the dynamic response of property values to an invasive species. The findings suggest property discounts of 2 to 5 percent for homes near infested oak woodlands, which are long lasting because of the continually dying oaks in the woodlands. Greater discounts of 5 to 8 percent occur if dying oaks are on the properties of homeowners, which are transitory because dying oaks are removed from homeowner properties. We compare recent hedonic modeling approaches including quasi-experimental, with spatial fixed-effects for a) communities, and b) parcels ‘repeat sales’, and spatial lag and error models to address bias from homeowner preferences, correlated with the price of a house and the proximity of a house to a SOD infection, which are not observed by the analyst.

This paper examines heterogeneity in the preferences for OHV recreation by applying the random parameters Poisson model to a data set of off-highway vehicle (OHV) users at four National Forest sites in North Carolina. The analysis develops estimates of individual consumer surplus and finds that estimates are systematically affected by the random parameter specification. There is also substantial evidence that accounting for individual heterogeneity improves the statistical fit of the models and provides a more informative description of OHV riders.

While convenient and often used, on-site surveys are biased by the fact that users who visit the site more often are proportionately more likely to be sampled. This so-called avidity or size biased sampling results in over-estimating the visitation patterns of the average user. This analysis develops a rule of thumb method that may easily be applied by recreation site managers to visitation data collected on-site in order to infer behavior of the average user of the site. The key assumption that drives the derivation is that the visitation data of users is logarithmically distributed. To evaluate the methodology, we analyze several data sets of recreational users assuming that they reflect the populations of users and from these construct hypothetical on-site samples.

A difference-in-difference (DID) hedonic property price model examines the property value damage from the pathogen P. ramorum in Marin County, California. The mortality of tanoaks and coast live oaks in Marin County was first observed in late 1998, and the mortality continues throughout the central and north coast of California to this day. The pathogen's growth on the foliage and branches of a variety of tree and shrub species, the ability to spread aerially, and the broad geographic range of the host species makes this disease a serious threat to many forest ecosystems. We determine the property value damage in the geographically diverse and affluent Marin County from coast live oak mortality with a spatial DID model of parcel transactions from 1983-2008, combining knowledge of the year of invasion and several indicator of sudden oak death damage. This study is the first to make use of the DID model to look at the damages of an invasion that spans a decade, with findings for each year of the invasion, with the hedonic property price model. There are several indicators of sudden oak death damages that include: 1) proximity to coast live oak

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.

This analysis examines the demand for a system of regional parks in Sicily (Italy). The analysis utilizes conventional count data methods that do not account for correlation across parks as well as a new model that allows for cross-site correlation and dispersion. In this model, the degree of dispersion and cross-site correlation is shown to evolve as individual grow older. Older individuals exhibit less dispersion and/or cross-site correlation.

A difference-in-difference (DID) hedonic property price model examines the property value damage from the pathogen P. ramorum in Marin County, California. The mortality of tanoaks and coast live oaks in Marin County was first observed in late 1998, and the mortality continues throughout the central and north coast of California to this day. The pathogen’s growth on the foliage and branches of a variety of tree and shrub species, the ability to spread aerially, and the broad geographic range of the host species makes this disease a serious threat to many forest ecosystems.

In large areas of the arid western United States, much of which are federally managed, fire frequencies and associated management costs are escalating as flammable, invasive cheatgrass (Bromus tectorum) increases its stronghold. Cheatgrass invasion and the subsequent increase in fire frequency result in the loss of native vegetation, less predictable forage availability for livestock and wildlife, and increased costs and risk associated with firefighting. Revegetation following fire on land that is partially invaded by cheatgrass can reduce both the dominance of cheatgrass and its associated high fire rate. Thus restoration can be viewed as an investment in fire-prevention and, if native seed is used, an investment in maintaining native vegetation on the landscape. Here we develop and employ a Markov model of vegetation dynamics for the sagebrush steppe ecosystem to predict vegetation change and management costs under different intensities and types of post-fire revegetation. We use the results to estimate the minimum total cost curves for maintaining native vegetation on the landscape and for preventing cheatgrass dominance. Our results show that across a variety of model parameter possibilities, increased investment in post-fire revegetation reduces long-term fire management costs by more than enough to offset the costs of revegetation. These results support that a policy of intensive post-fire revegetation will reduce long-term management costs for this ecosystem, in addition to providing environmental benefits. This information may help justify costs associated with revegetation and raise the priority of restoration in federal land budgets.

An important consideration in managing fire-prone forests is the intertemporal impacts of forest fires. This analysis examines these impacts in a forest recreation setting by fitting a combined stated and revealed data set to explicitly model the effects of forest regrowth following a fire on recreation economic values. The results are particularly useful as they provide clear measures of the time path of recovery of forest amenity values following a fire.