IMPACTS OF ALTERNATIVE FARM POLICIES ON RURAL COMMUNITIES

The purpose of this study was to describe an LP/IO model for evaluating the economic impacts of alternative farm policies on rural communities and demonstrate its capabilities by analyzing the impacts of three farm policies on a rural community in Texas. Results indicate that in the noncrop sector, two groups of industries are most affected by farm policy. The first group relates to production directly (agricultural services, banking and credit, and nondurable manufacturing) and the second group relates to households (retail trade and services). Farm policies which reduce production but increase net returns cause losses for the first group while benefitting the second group. Both groups are made worse off by farm policies which reduce agricultural production and the value of output.Agricultural and Food Policy, Community/Rural/Urban Development,

ESTIMATION OF THE NONMARKET BENEFITS OF AGRICULTURAL LAND RETENTION IN EASTERN CANADA

We assess the nonmarket value for retention of farmland in the Moncton area of New Brunswick. We examine a number of factors explaining household external values for farmland preservation and expand on previous work by Beasley et al., Bergstrom et al., and Halstead. Our findings indicate that the marginal external benefit of preserving farmland in general in this region is small compared to the market price and that spatial embedding is not automatic in contingent valuation studies.Land Economics/Use,

THE ENDOWMENT EFFECT AND WTA: A QUASI-EXPERIMENTAL TEST

This paper reports a test of the endowment effect in an economic analysis of localized air pollution. Regression techniques are used to test the significance of perceived property rights on household WTP for improved air quality versus WTA compensation to forgo an improvement in air quality. Our experiment contributes to the research into the WTP/WTA divergence by providing a new basis for supporting the existence of an endowment effect. Our results are in contrast to recent work by Shogren et al. which supports the substitution proposition of Hanemann while rejecting the endowment effect.Contingent valuation, Endowment effect, Property rights, Substitution effect, Environmental Economics and Policy,

MEASURING USE VALUE FROM RECREATION PARTICIPATION: COMMENT

Resource /Energy Economics and Policy,

A NOTE ON NONLINEARITY BIAS AND DICHOTOMOUS CHOICE CVM: IMPLICATIONS FOR AGGREGATE BENEFITS ESTIMATION

It is a generally known statistical fact that the mean of a nonlinear function of a set of random variables is not equivalent to the function evaluated at the means of the variables. However, in dichotomous choice contingent valuation studies a common practice is to calculate an overall mean (or median) by integrating over offer space (numerically or analytically) an estimated logit or probit function in which sample mean values for the concomitant variables are used. We demonstrate this procedure to be incorrect and we statically test the procedure against the correct method for nonlinear models. Using data resulting in a well-behaved logit model, we reject the hypothesis of congruence between the two means. Such a finding should be considered in future single response dichotomous choice CVM studies, particularly when aggregation is of interest.Research Methods/ Statistical Methods,

Modeling Demand for Outdoor Recreation Settings with Choice Based Data Accounting for Exogenous and Endogenous Stratification

Estimating regional demand models by pooling different samples without correcting for such differences causes model misspecification as each sample belongs to a different population. Weighted regression using Pseudolikelihood to account for differences in sample population with adjustment for heteroskedasticity improves efficiency but the estimates are biased. We estimate regional demand for National Forest settings types in the southeastern states of U.S using weighted and unweighted regression. Using estimation of demand for National Forests as a case study, we resolve problems relating to inference about the data generating process when different samples are pooled together. We show that though efficiency of weighted estimates improves after correcting for heteroskedasticity, they still remain biased as the weights interact with covariates to explain part of model misspecification. In this paper, we show that it is best to use unweighted regression including interactions with weights as covariates.exogenous stratification, endogenous stratification, choice based data, outdoor recreation, Environmental Economics and Policy, Q000, Q500,

Measuring the Contribution of Water and Green Space Amenities to Housing Values: An Application and Comparison of Spatially-weighted Hedonic Models

This study estimates the influence of proximity to water bodies and park amenities on residential housing values in Knox County, Tennessee, using the hedonic price approach. Values for proximity to water bodies and parks are first estimated globally with a standard ordinary least square (OLS) model. A locally weighted regression model is then employed to investigate spatial non-stationarity and generate local estimates for individual sources of each amenity. The local model is able to capture the variability in the quality of water bodies and parks across the county, something a conventional hedonic model using OLS cannot do.Land Economics/Use,

Determinants of Demand for Participation in Wildlife Hunting: A County level Analysis

We developed an economic demand model of wildlife hunting and found that sociodemograpahic and ecological characteristics of county are its strong predictors. Result shows that the hunting is not popular among younger generation; and promoting hunting clubs and lease-hunting, recruiting young hunters could be effective policy considerations for retaining/promoting hunting.Wildlife hunting, License sales, Demand model, Resource /Energy Economics and Policy, Q21, Q26, L83,

A PROPOSED METHODOLOGY FOR ESTIMATING ECOREGIONAL VALUES FOR OUTDOOR RECREATION IN THE UNITED STATES

This paper provides a methodology for the estimation of recreational demand functions and values using an ecoregional approach. Ten ecoregions in the continental US were defined based on similarly functioning ecosystem characters. The individual travel cost method was employed to estimate the recreational demand functions for activities such as motorboating and waterskiing, developed and primative camping, coldwater fishing, sightseeing and pleasure driving, and big game hunting for each ecoregions. Estimates of per trip net income value range from $12.93 to$218.38 while per day estimates range from $4.31 to$109.19. While our ecoregional approach differs conceptually from previous work, our results appear consistent with the previous travel cost method valuation studies. (Missing tables 1,2,3,4,5 and 6)Recreation, ecoregion, travel cost method, truncated poisson model, Resource /Energy Economics and Policy,

Valuing National Forest Recreation Access: Using a Stratified On-Site Sample to Generate Values Across Activities for a Nationally Pooled Sample

The Forest Service controls vast quantities of natural resources including timber, wildlife, watersheds, air sheds, and ecosystems. For many of these resources, recreation is one of the primary uses of the natural asset. Recreation visits taken to National Forests are not "purchased" in the same type of market as other goods (e.g., timber, grazing, or housing). The price of, and ultimately benefit received from, recreation to National Forests cannot be estimated via traditional market prices and quantities. Alternate methods must be employed to estimate the value of recreation access. We use on-site survey data from the Forest Service's National Visitor Use Monitoring database (2000-2003) and stated preference demand estimation methods to model annual recreation trip-taking behavior to National Forests. We then use these models to derive estimates of per-visit net economic benefits across regions and activities. In 2000, the FS began conducting systematic research into recreation visitation levels on National Forest lands under the National Visitor Use Monitoring Project (NVUM). From 2000 to 2003 NVUM has collected data from 120 National Forests providing information on the number of annual visits, primary activity, local area expenditures, satisfaction with facilities, and limited demographic information. These data were collected using an on-site stratified random sampling scheme resulting in over 90,000 completed surveys. Using the NVUM data we estimate the net economic value (NEV) of recreation on National Forest lands. The dataset used to estimate these values contains 73,655 observations. Using a truncated negative binomial estimator, weighted by a composite factor that adjusts for the stratified, on-site nature of the data, we have estimated a series of pooled, multi-site recreation demand models and calculated net economic values for recreational visits to the National Forests for each of fourteen activities and four RPA regions (Pacific, Rocky Mountain, Northern, and Southern) on a per visit per individual value and for a per activity day per individual basis. Our results indicate that for most models and specifications, adjusting for the choice based sampling frame by using a truncated, weighted, stratified, negative binomial estimator, as well as accounting for regional and activity differences, reduces the estimate of the average per day and per activity day values. Forest managers and others involved in managing, planning, and administering resources used for recreation often need an estimate of the economic value of the resource. For many of these resources non-market analysis must be used to generate this information. For forest recreation, many of the values currently available come from secondary sources or from small samples. The values estimated using NVUM represent an improvement over many of the currently available forest recreation values because of the unique nature of the large-scale, stratified random sample.Resource /Energy Economics and Policy,