ESTIMATION OF POTENTIAL REDUCTIONS IN RECREATIONAL BENEFITS DUE TO SEDIMENTATION1

ABSTRACT: A travel cost model is developed to estimate the potential reductions in recreational benefits from sedimentation in Reelfoot Lake in northwestern Tennessee. In addition to the consumer surplus estimates generated by the model, three other aspects of the study were significant. First, the study applied a relatively untested methodology for deriving the opportunity cost of travel time. The study resulted in a value that is less than one-half of the Water Resource Council's “one-third of the wage rate” rule-of-thumb. Second, water quality perceptions were unsuccessfully incorporated into the model as a demand shifter. This raised questions as to the appropriate manner in which perceptions could be included in a travel cost model. Finally, a simple methodology was outlined by which estimates of the recreational value of Reelfoot Lake could be used to suggest how much cost could be justified for soil erosion control on agricultural land surrounding the lake.     

THE OPPORTUNITY COST OF TIME AND AVERTING EXPENDITURES FOR SAFE DRINKING WATER1

ABSTRACT: A survey of individuals during a Giardia contamination incident provided data to calculate the cost of boiling, hauling, or purchasing water to avoid infection. Three different approaches to the valuation of time were used to assess the implications of the opportunity cost of time for the measurement of averting costs. Mean monthly household averting costs were $33.47 using family income to value time, $13.07 using the minimum wage to value time, and $5.60 using zero opportunity cost of time. Comparisons of the mean costs for different sources and household characteristics indicated the value of time from family income was too high and that the other methods of valuing time were superior.     

Multi-Destination and Multi-Purpose Trip Effects in the Analysis of the Demand for Trips to a Remote Recreational Site

One of the basic assumptions of the travel cost method for recreational demand analysis is that the travel cost is always incurred for a single purpose recreational trip. Several studies have skirted around the issue with simplifying assumptions and dropping observations considered as nonconventional holiday-makers or as nontraditional visitors from the sample. The effect of such simplifications on the benefit estimates remains conjectural. Given the remoteness of notable recreational parks, multi-destination or multi-purpose trips are not uncommon. This article examines the consequences of allocating travel costs to a recreational site when some trips were taken for purposes other than recreation and/or included visits to other recreational sites. Using a multi-purpose weighting approach on data from Gros Morne National Park, Canada, we conclude that a proper correction for multi-destination or multi-purpose trip is more of what is needed to avoid potential biases in the estimated effects of the price (travel-cost) variable and of the income variable in the trip generation equation.     

An Ecoregional Approach to the Economic Valuation of Land- and Water-Based Recreation in the United States

/ This paper describes a framework for estimating the economic value of outdoor recreation across different ecoregions. Ten ecoregions in the continental United States were defined based on similarly functioning ecosystem characters. The individual travel cost method was employed to estimate recreation demand functions for activities such as motor boating and waterskiing, developed and primitive camping, coldwater fishing, sightseeing and pleasure driving, and big game hunting for each ecoregion. While our ecoregional approach differs conceptually from previous work, our results appear consistent with the previous travel cost method valuation studies.KEY WORDS: Recreation; Ecoregion; Travel cost method; Truncated Poisson model     

Wildfire effects on hiking and biking demand in New Mexico: a travel cost study

We use a travel cost model to test the effects of wild and prescribed fire on visitation by hikers and mountain bikers in New Mexico. Our results indicate that net benefits for mountain bikers is $150 per trip and that they take an average of 6.2 trips per year. Hikers take 2.8 trips per year with individual net benefits per trip of $130. Both hikers' and mountain bikers' demand functions react adversely to prescribed burning. Net benefits for both groups fall as areas recover from prescribed burns. Because both visitation and annual recreation benefits decrease to these two types of visitors, this gives rise to multiple use costs associated with prescribed burning. With respect to wildfire, hikers and mountain bikers both exhibit decreased visitation as areas recover from wildfires, however, only hikers indicate an increase in per trip net benefits. Bikers' demand effectively drops to zero. These results differ from previous findings in the literature and have implications for efficient implementation of the National Fire Plan and whether prescribed burning is a cost effective tool for multiple use management of National Forests. Specifically, that fire and recreation managers cannot expect recreation users to react similarly to fire across recreation activities, or different geographic regions. What is cost effective in one region may not be so in another.     

Estimating the Economic Value of National Parks with Count Data Models Using On-Site,Secondary Data: The Case of the Great Sand Dunes National Park and Preserve

We estimate an individual travel cost model for Great Sand Dunes National Park and Preserve (GSD) in Colorado using on-site, secondary data. The purpose of the on-site survey was to help the National Park Service better understand the visitors of GSD; it was not intended for a travel cost model. Variables such as travel cost and income were estimated based on respondents’ Zip Codes. Following approaches found in the literature, a negative binomial model corrected for truncation and endogenous stratification fit the data the best. We estimate a recreational benefit of U.S. $89/visitor/year or U.S. $54/visitor/24-h recreational day (in 2002 U.S. $). Based on the approach presented here, there are other data sets for national parks, preserves, and battlefields where travel cost models could be estimated and used to support National Park Service management decisions.     

Sensitivity of Whitewater Rafting Consumers' Surplus to Pecuniary Travel Cost Specifications

Considerable research has examined how different ways of accounting for onsite and travel time affect surplus estimates from travel cost models. However, little has been done regarding different definitions of out-of-pocket costs. Estimates of per trip consumer surplus are developed for a zonal travel cost model for outfitted rafting on the Chattooga River. Nine price definitions are used for each of three functional forms. Three price definitions are based on mileage rates times round-trip distance, plus outfitter fees. The remaining six definitions are based on reported spending, using three different sets of expenditures and two methods of imputing prices for zero-visit zones.     

Two-stage vertex analysis method for planning electric power systems with greenhouse gas abatement consideration

This study presents a two-stage vertex analysis (TSVA) method for the planning of electric power systems (EPS) under uncertainty. TSVA has advantages in comparison to other optimization techniques. Firstly, TSVA can incorporate greenhouse gas (GHG) abatement policies directly into its optimization process, and, secondly, it can readily integrate inherent system uncertainties expressed as fuzzy sets and probability distributions directly into its modeling formulation and solution procedure. The TSVA method is applied to a case study of planning EPS and it is demonstrated how the TSVA efficiently identify optimal electricity-generation schemes that could help to minimize system cost under different GHG-abatement considerations. Different combinative considerations on the uncertain inputs lead to varied system costs and GHG emissions. Results reveal that the total electricity supply will rise up along with the time period due to the increasing demand and, at the same time, more non-fossil fuels should be used to satisfy the increasing requirement for GHG mitigation. Moreover, uncertainties in connection with complexities in terms of information quality (e.g., capacity, efficiency, and demand) result in changed electricity-generation patterns, GHG-abatement amounts, as well as system costs. Minimax regret (MMR) analysis technique is employed to identify desired alternative that reflects compromises between system cost and system-failure risk.     

Measuring the Social Recreation Per-Day Net Benefit of the Wildlife Amenities of a National Park: A Count-Data Travel-Cost Approach

In this article, we apply count-data travel-cost methods to a truncated sample of visitors to estimate the Peneda-Gerês National Park (PGNP) average consumer surplus (CS) for each day of visit. The measurement of recreation demand is highly specific because it is calculated by number of days of stay per visit. We therefore propose the application of altered truncated count-data models or truncated count-data models on grouped data to estimate a single, on-site individual recreation demand function, with the price (cost) of each recreation day per trip equal to out-of-pocket and time travel plus out-of-pocket and on-site time costs. We further check the sensitivity of coefficient estimations to alternative models and analyse the welfare measure precision by using the delta and simulation methods by Creel and Loomis. With simulated limits, CS is estimated to be €194 (range €116 to €448). This information is of use in the quest to improve government policy and PNPG management and conservation as well as promote nature-based tourism. To our knowledge, this is the first attempt to measure the average recreation net benefits of each day of stay generated by a national park by using truncated altered and truncated grouped count-data travel-cost models based on observing the individual number of days of stay.     

Biodiversity on Swedish pastures: estimating biodiversity production costs

This paper estimates the costs of producing biological diversity on Swedish permanent grasslands. A simple model is introduced where biodiversity on pastures is produced using grazing animals. On the pastures, the grazing animals create a sufficient grazing pressure to lead to an environment that suits many rare and red-listed species. Two types of pastures are investigated: semi-natural and cultivated. Biological diversity produced on a pasture is estimated by combining a biodiversity indicator, which measures the quality of the land, with the size of the pasture. Biodiversity is, in this context, a quantitative measure where a given quantity can be produced either by small area with high quality or a larger area with lower quality. Two areas in different parts of Sweden are investigated. Box-Cox transformations, which provide flexible functional forms, are used in the empirical analysis and the results indicate that the biodiversity production costs differ between the regions. The major contribution of this paper is that it develops and tests a method of estimating biodiversity production costs on permanent pastures when biodiversity quality differs between pastures. If the method were to be used with cost data, that were more thoroughly collected and covered additional production areas, biodiversity cost functions could be estimated and used in applied policy work.     

Valuing nature-based recreation in public natural areas of the Apalachicola River region, Florida

As more people visit natural areas for tourism and recreation purposes, it is becoming increasingly important to understand the value they place on these natural resources. Specifically, tourists to Florida have been increasingly interested in visiting natural areas, forests, parks, and preserves-highlighting the importance of this new and growing phenomenon. We analyze visitors' demand for nature-based recreation in the Apalachicola River region of Florida using the travel cost method. The results from a count data regression model reveal that on average visitors would pay 74.18 dollars per visit-day for nature-based recreation resulting in a total economic value of 484.56 million dollars attributable to nature-based recreation in the Apalachicola River region. Results of this study provide useful information for natural resources management in the region and a rationale to preserve Florida's unique ecosystems.     

Cost‐Effective Placement of Best Management Practices in a Watershed: Lessons Learned from Conservation Effects Assessment Project

This article reviews the key, cross‐cutting findings concerning watershed‐scale cost‐effective placement of best management practices (BMPs) emerging from the National Institute of Food and Agriculture Conservation Effects Assessment Project (CEAP) competitive grants watershed studies. The synthesis focuses on two fundamental aspects of the cost‐effectiveness problem: (1) how to assess the location‐ and farmer‐specific costs of BMP implementation, and (2) how to decide on which BMPs need to be implemented and where within a given watershed. Major lessons learned are that (1) data availability remains a significant limiting factor in capturing within‐watershed BMP cost variability; (2) strong watershed community connections help overcome the cost estimation challenges; (3) detailing cost components facilitates the transferability of estimates to alternative locations and/or economic conditions; and (4) implicit costs vary significantly across space and farmers. Furthermore, CEAP studies showed that (5) evolutionary algorithms provide workable ways to identify cost‐effective BMP placements; (6) tradeoffs between total conservation costs and watershed‐scale cost‐effective water quality improvements are commonly large; (7) quality baseline information is essential to solving cost‐effectiveness problem; and (8) systemic and modeling uncertainties alter cost‐effective BMP placements considerably.     

Estimating recreational trout fishing damages in Montana's Clark Fork River basin: summary of a natural resource damage assessment

This paper summarizes a natural resource damage assessment for the State of Montana. Mining wastes have caused significant reductions in trout stocks in a 145-mile stretch of Montana's Silver Bow Creek and Clark Fork River. To estimate economic damages from decreases in catch rates, we develop and estimate an individual-based utility-theoretic model of where and how often an angler will fish as a function of travel costs, catch rates, and other influential characteristics of the site and individuals. The model includes resident and nonresident anglers who currently fish in Montana, and allows them to have different preferences. Demand parameters and expected catch rates are simultaneously estimated. The value of time is endogenously estimated as a proportion of the wage rate. Catch rates are linked to trout stocks through a stock-catch function. Collection of the angler data involved a three-step process: anglers were intercepted at 26 study sites, a subsample of anglers was selected to reflect the population trip-taking proportions to the study sites, and these anglers received follow-up surveys through the fishing season. Avidity weights are used to correct for the higher level of avidity inherent in intercept samples.     

Economies of scale in global iron-making

In this paper, we investigate the presence of economies of scale in the global iron-making industry for integrated steel plants, iron making being the first stage in the steel-making process. Iron making depends on basic commodities, such as iron ore, coke and various forms of energy, required in the operation of the blast furnace, which can be classified as essential inputs and used in fixed proportions to produce iron. A generalized Leontief cost function is estimated using panel data for 69 integrated plants, such a specification being appropriate for technologies with essential inputs that are used in fixed proportions in production. A significant scale effect is observed due to the existence of fixed costs and a linear dependence of the cost function on production. Under a simple linear cost function, a rough estimate of the breakeven scale of plant, where costs equal revenue, is 4.5 Mt per year. Competitiveness, as measured by the ratio of plant average cost per tonne to best practice cost per tonne, can be shown to be positively related to the scale of production as well as the cost of essential inputs. Therefore, low-cost producers are also often producers with low raw material costs and production levels below the estimated breakeven scale of operation. Labor costs, although significant, are comparatively less important as a driver towards low costs.     

Using Count Data and Ordered Models in National Forest Recreation Demand Analysis

This research addresses the need to improve our knowledge on the demand for national forests for recreation and offers an in-depth data analysis supported by the complementary use of count data and ordered models. From a policy-making perspective, while count data models enable the estimation of monetary welfare measures, ordered models allow for the wider use of the database and provide a more flexible analysis of data. The main purpose of this article is to analyse the individual forest recreation demand and to derive a measure of its current use value. To allow a more complete analysis of the forest recreation demand structure the econometric approach supplements the use of count data models with ordered category models using data obtained by means of an on-site survey in the Bussaco National Forest (Portugal). Overall, both models reveal that travel cost and substitute prices are important explanatory variables, visits are a normal good and demographic variables seem to have no influence on demand. In particular, estimated price and income elasticities of demand are quite low. Accordingly, it is possible to argue that travel cost (price) in isolation may be expected to have a low impact on visitation levels.     

Who Visits a National Park and What do They Get Out of It?: A Joint Visitor Cluster Analysis and Travel Cost Model for Yellowstone National Park

Yellowstone National Park visitor data were obtained from a survey collected for the National Park Service by the Park Studies Unit at the University of Idaho. Travel cost models have been conducted for national parks in the United States; however, this study builds on these studies and investigates how benefits vary by types of visitors who participate in different activities while at the park. Visitor clusters were developed based on activities in which a visitor participated while at the park. The clusters were analyzed and then incorporated into a travel cost model to determine the economic value (consumer surplus) that the different visitor groups received from visiting the park. The model was estimated using a zero-truncated negative binomial regression corrected for endogenous stratification. The travel cost price variable was estimated using both 1/3 and 1/4 the wage rate to test for sensitivity to opportunity cost specification. The average benefit across all visitor cluster groups was estimated at between $235 and $276 per person per trip. However, per trip benefits varied substantially across clusters; from $90 to $103 for the “value picnickers,” to $185–$263 for the “backcountry enthusiasts,” $189–$278 for the “do it all adventurists,” $204–$303 for the “windshield tourists,” and $323–$714 for the “creature comfort” cluster group.     

Wave energy vs. other energy sources: A reassessment of the economics

The large scatter in the predictions of wave energy costs, which is caused in part by the simplifications assumed by existing models, is a hindrance for the development of this promising renewable. In this context, the main objective of this paper is to reassess the cost of wave energy taking into account a number of elements that are usually overlooked, or not considered simultaneously. This analysis has been performed in relation to the European context. The direct and indirect costs of a wave farm are examined, and a value for each is presented. The levelized cost (€/MWh) of wave energy is then calculated for different scenarios in order to compare the profitability of wave energy with that of other energy sources. After that, a sensitivity analysis is carried out to identify the main parameters affecting the total cost, considering in particular the effect on the levelized cost of considering: (i) the cost reductions arising from economies of scale and technological effects; (ii) an O&M cost variable throughout the useful life of the farm; and (iii) the externalities. In sum, this work sets the basis for a thorough economic comparison of wave energy with other sources of energy.     

Uncertainty in exhaustible natural resource economics: The irreversible sunk costs of Hotelling

According to Pindyck (2007) there are three important aspects of uncertainly in environmental economics: (1) the benefits and costs of environmental policy tend to be highly non-linear, (2) environmental policy tends to involve important irreversibilities, where investment in pollution abatement can impose an irreversible, sunk cost on society, and where certain pollutants can stay in the environment forever and build up to cause even more future harm in which case investment in abatement can cause an irreversible, sunk benefit to society, and (3) environmental policy involves long time horizons and yet the discount rate society should use is uncertain for determining the net present value of costs and benefits of pollution abatement. These same uncertainties also affect non-renewable, exhaustible, natural resource economics and in particular the use of the Hotelling rule: (1) the costs, benefits and transversality conditions of using the Hotelling rule can be highly non-linear, (2) the Hotelling rule involves important sunk cost irreversibilities, which will be explained here, and (3) the Hotelling rule can involve long time horizons with uncertain discount rates. All three of these problem make it extremely difficult for a market to use in any way the Hotelling rule, yet by the sheer number of articles in non-renewable natural resource economics, one would believe that it is the basis of all resource markets. In this article, we concentrate on the sunk cost irreversibilities of using the Hotelling rule. The idea of the Hotelling rule is to optimally store a non-renewable resource, but the optimization is highly dependent on the actual reserves that are available to extract. However, reserves of underground exhaustible resources are often unobservable at the beginning stages of extraction which makes using the Hotelling Rule difficult.     

External cost internalisation of urban transport: a case study of Dublin

Transport users do not currently pay all costs associated with their transport activities and in particular do not pay the costs they impose on the environment. Case studies on Dublin, Amsterdam, Brussels and London have been conducted to evaluate how best to meet the requirement of the European Commission in its fair and efficient pricing aims in the transport sector, i.e. where transport users are made to pay all costs they impose. The paper presents the results of Do Nothing (DN) and Do Something (DS) scenarios for 2005 where in the latter case each transport user pays for all costs they impose including pollution, noise, accidents etc. The Dublin results, from an economics model used in the study, are examined in detail; the findings are compared with those of parallel studies conducted in the other cities to demonstrate the international relevance of this work. The comparison between the DN and DS scenarios indicates that taxes on all transport modes should be increased substantially, particularly in the morning and evening peak periods. As a result of the price increases, travel demand is reduced. A practical example where transport users could be made to pay for all their costs is road use pricing, i.e. charging individuals for the use of road space. The taxation levels suggested in the DS scenario have been used in a road use pricing trial in Dublin, the results of which were published in O'Mahony, Geraghty and Humphreys (Transportation 27, 269-283, 2000), to see if the reductions in the travel requirements of individuals proposed by the economics model are in fact true. The principles of the work presented in this paper are not only relevant to environmental impact management in the transport sector but can also be applied to other sectors.     

Application of a hurdle negative binomial count data model to demand for bass fishing in the southeastern United States

This paper identifies factors that influence the demand for a bass fishing trip taken in the southeastern United States using a hurdle negative binomial count data model. The probability of fishing for a bass is estimated in the first stage and the fishing trip frequency is estimated in the second stage for individuals reporting bass fishing trips in the Southeast. The applied approach allows the decomposition of the effects of factors responsible for the decision to take a trip and the trip number. Calculated partial and total elasticities indicate a highly inelastic demand for the number of fishing trips as trip costs increase. However, the demand can be expected to increase if anglers experience a success measured by the number of caught fish or their size. Benefit estimates based on alternative estimation methods differ substantially, suggesting the need for testing each modeling approach applied in empirical studies.