Willingness to Pay for Quality Improvements: Should Revealed and Stated Preference Data Be Combined?

In this article we propose theoretically consistent welfare measurement of use and nonuse values for an improvement in environmental quality with revealed and stated preference data. An analytical model based on the comparative static analysis of the variation function that describes the relationship between recreation demand and dichotomous choice contingent valuation models is estimated. Our results show that revealed and stated data should not be combined under the same assumed preference structure unless the two decisions imply the same change in behavior induced by the quality change. In addition, our results indicate scope effects in willingness to pay measures estimated with stated preference data.     

A regional approach to estimating recreation benefits of improved water quality

Recreation demand and value are estimated with the travel-cost method for fishing, camping, boating, and swimming on a site-specific regional basis. The model regional in that 179 sites are defined for the Pacific Northwest. A gravity model is employed to estimate the number of trips from each origin to its destination in the region, and these data are the basic input in the travel-cost demand curves. The model is illustrated by estimating the recreation benefits that would result from meeting the national environmental goal of “fishable and swimmable” rivers. The main finding is that potential recreation benefits are concentrated in a few select areas, which are accessible to large population centers.     

Addressing onsite sampling in recreation site choice models

Independent experts and politicians have criticized statistical analyses of recreation behavior, which rely upon onsite samples due to their potential for biased inference. The use of onsite sampling usually reflects data or budgetary constraints, but can lead to two primary forms of bias in site choice models. First, the strategy entails sampling site choices rather than sampling individuals—a form of bias called endogenous stratification. Under these conditions, sample choices may not reflect the site choices of the true population. Second, exogenous attributes of the individuals sampled onsite may differ from the attributes of individuals in the population—the most common form in recreation demand is avidity bias. We propose addressing these biases by combining two the existing methods: Weighted Exogenous Stratification Maximum Likelihood estimation and propensity score estimation. We use the National Marine Fisheries Service's Marine Recreational Fishing Statistics Survey to illustrate methods of bias reduction, employing both simulated and empirical applications. We find that propensity score based weights can significantly reduce bias in estimation. Our results indicate that failure to account for these biases can overstate anglers' willingness to pay for improvements in fishing catch, but weighted models exhibit higher variance of parameter estimates and willingness to pay.     

Estimating net benefits of recreation under conditions of excess demand

The public provision of outdoor recreation necessitates the development of nonmarket measures of the value of resources in recreational use. Such values can be used as surrogates for market values in the decision-making process. Another aspect of recreation as a publicly provided good is the absence of a mechanism to eliminate automatically excess demand. The absence of such a mechanism has resulted in conditions of excess demand at many recreation sites.This paper deduces the implications of excess demand for the travel cost method of benefit estimation. We show that when excess demand results in rationing at a particular site, the travel cost method will underestimate the true benefits of the site. The results are important because they help identify the direction of bias of one measure of the benefits from the use of a natural resource.     

Effects of human demand on conservation planning for biodiversity and ecosystem services

Safeguarding ecosystem services and biodiversity is critical to achieving sustainable development. To date, ecosystem services quantification has focused on the biophysical supply of services with less emphasis on human beneficiaries (i.e., demand). Only when both occur do ecosystems benefit people, but demand may shift ecosystem service priorities toward human-dominated landscapes that support less biodiversity. We quantified how accounting for demand affects the efficiency of conservation in capturing both human benefits and biodiversity by comparing conservation priorities identified with and without accounting for demand. We mapped supply and benefit for 3 ecosystem services (flood mitigation, crop pollination, and nature-based recreation) by adapting existing ecosystem service models to include and exclude factors representing human demand. We then identified conservation priorities for each with the conservation planning program Marxan. Particularly for flood mitigation and crop pollination, supply served as a poor proxy for benefit because demand changed the spatial distribution of ecosystem service provision. Including demand when jointly targeting biodiversity and ecosystem service increased the efficiency of conservation efforts targeting ecosystem services without reducing biodiversity outcomes. Our results highlight the importance of incorporating demand when quantifying ecosystem services for conservation planning.     

Estimating the benefits of recreation under conditions of congestion

The public provisions of free or below cost outdoor recreation sites has resulted in the use of various methods to evaluate the demand. One method is to use travel cost as a price proxy. However, this mechanism does not take into account problems raised by congestion. This paper shows that the use of the travel cost method will always underestimate the true benefits provided by recreation at a site because of the role of congestion. The results are important because they identify a source of bias in measuring benefits of outdoor recreation and suggest how it may be corrected.     

Estimating the benefits of recreation under conditions of congestion congestion

In a recent issue of J. Environ. Econ. Manag. Wetzel showed that the standard travel cost technique will understate recreation benefits under congested conditions because changes in entry fee lead to lowered congestion levels. This comment indicates that benefit projections derived from the travel cost procedure may theoretically overstate the true value of recreation if rising income levels shift the demand curve upwards but fail to account for the contrary effect of increased congestion. The magnitude and direction of the bias that results from omission of a congestion variable is, however, indeterminate when standard econometric techniques are used to develop benefit projections.     

Relevance of crowding effects in a coastal National Park in Germany: results from a case study on Hamburger Hallig

Coastal environments are popular sites for tourism and faced with an increasing recreational demand. Most of European coastal areas attract numerous visitors annually. In recreation research this management problem can be described in terms of carrying capacity which expresses the ability of a site or region to absorb recreational use without deterioration of natural resources and the quality of the visitor experience. As social aspects of recreation in Europe still have received little attention, the purpose of this study is to examine the applicability of the concept of social carrying capacity in a German coastal national park. The article addresses if the relationship between perceived visitor encounters, crowding perception and visitor characteristics is applicable by using data from an on-site survey (N?=?509) of visitors conducted on Hamburger Hallig, Germany. It examines whether effects of overcrowding are measurable on a popular daytrip destination with established approaches. Results demonstrate that visitors to Hamburger Hallig are characterised by a heterogeneous visitor composition of local residents and domestic tourists with different motivations and who mainly visited the area for hiking or cycling. Study findings show that valuation for reported encounters and perceived crowding differed substantially among origin of visitors and sampling dates. All in all, respondents report a high level of encounter with others and in contrast a very low level of perceived crowding.     

Modelling the responses of wildlife to human disturbance: An evaluation of alternative management scenarios for black-crowned night-herons

The impact of anthropogenic disturbance on wildlife is increasing becoming a source of concern as the popularity of outdoor recreation rises. There is now more pressure on site managers to simultaneously ensure the continued persistence of wildlife and provide recreational opportunities. Using ‘Simulation of Disturbance Activities’, a model designed to investigate the impact of recreational disturbance on wildlife, we demonstrate how a simulation modelling approach can effectively inform such management decisions. As an example, we explored the implications of various design and management options for a proposed recreational area containing a historic breeding bird colony. By manipulating the proximity, orientation and intensity of recreation, we were able to evaluate the impact of recreational activities on the behaviour of black-crowned night-heron nestlings (Nycticorax nycticorax). Using a classification and regression tree (CART) procedure to analyse simulation output, we explored the dynamics of multiple strategies in concert. Our analysis revealed that there are inherent advantages in implementing multiple strategies as opposed to any single strategy. Nestlings were not disturbed by recreation when bird-watching facility placement (proximity and orientation) and type were considered in combination. In comparison, proximity alone only led to a <10% reduction in disturbance. Thus we demonstrate how simulation models based on customised empirical data can bridge the gap between field studies and active management, enabling users to test novel management scenarios that are otherwise logistically difficult. Furthermore, such models potentially have broad application in understanding human-wildlife interactions (e.g. exploring the implications of roads on wildlife, probability of bird strikes around airports, etc.). They therefore represent a valuable decision-making tool in the ecological design of urban infrastructures.     

Using revealed preferences to estimate the Value of Travel Time to recreation sites

The opportunity Value of Travel Time (VTT) is one of the most important elements of the total cost of recreation day-trips and arguably the most difficult to estimate. Most studies build upon the theoretical framework proposed by Becker (1965) by using a combination of revealed and stated preference data to estimate a value of time which is uniform in all activities and under all circumstances. This restriction is relaxed by DeSerpa's (1971) model which allows the value of saving time to be activity-specific. We present the first analysis which uses actual driving choices between open access and toll roads to estimate a VTT specific for recreation trips, thereby providing a value which conforms to both Becker's and DeSerpa's theoretical models. Using these findings we conduct a Monte Carlo simulation to identify generalizable results for subsequent valuation studies. Our results indicate that 3/4 of the wage rate provides a reasonable approximation of the average VTT for recreation trips, while the commonly implemented assumption of 1/3 of the wage rate generates downward biased results.     

The value of time in recreation benefit studies

This paper examines the role of time costs—both on-site and travel—in models describing recreation behavior, and draws implications for the travel-cost approach to recreation site benefit estimation. The analysis shows that both recreation and travel time are costly. The latter can be valued in terms of its scarcity value, but the former may be most appropriately valued in terms of the “alue of travel time saved.” Although there are cases in which on-site time costs need not be explicitly considered in recreation benefit models, it is not clear such cases are the rule rather than the exception. Suggestions are made for measuring on-site and travel time costs.     

Effects of Tourists on Behavior and Demography of Olympic Marmots

Abstract:  If changes in animal behavior resulting from direct human disturbance negatively affect the persistence of a given species or population, then these behavioral changes must necessarily lead to reduced demographic performance. We tested for the effects of human disturbance on Olympic marmots ( Marmota olympus ), a large ground-dwelling squirrel that has disappeared from several areas where recreation levels are high. We assessed the degree to which antipredator and foraging behavior and demographic rates (survival and reproduction) differed between sites with high recreation levels (high use) and those with little or no recreation (low use). Compared with the marmots at low-use sites, marmots at high-use sites displayed significantly reduced responses to human approach, which could be construed as successful accommodation of disturbance or as a decrease in predator awareness. The marmots at high-use sites also looked up more often while foraging, which suggests an increased wariness. Marmots at both types of sites had comparable reproductive and survival rates and were in similar body condition. Until now, the supposition that marmots can adjust their behavior to avoid negative demographic consequences when confronted with heavy tourism has been based on potentially ambiguous behavioral data. Our results support this hypothesis in the case of Olympic marmots and demonstrate the importance of considering demographic data when evaluating the impacts of recreation on animal populations.     

A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting

● A novel deep learning framework for short-term water demand forecasting. ● Model prediction accuracy outperforms other traditional deep learning models. ● Wavelet multi-resolution analysis automatically extracts key water demand features. ● An analysis is performed to explain the improved mechanism of the proposed method. Short-term water demand forecasting provides guidance on real-time water allocation in the water supply network, which help water utilities reduce energy cost and avoid potential accidents. Although a variety of methods have been proposed to improve forecast accuracy, it is still difficult for statistical models to learn the periodic patterns due to the chaotic nature of the water demand data with high temporal resolution. To overcome this issue from the perspective of improving data predictability, we proposed a hybrid Wavelet-CNN-LSTM model, that combines time-frequency decomposition characteristics of Wavelet Multi-Resolution Analysis (MRA) and implement it into an advanced deep learning model, CNN-LSTM. Four models - ANN, Conv1D, LSTM, GRUN - are used to compare with Wavelet-CNN-LSTM, and the results show that Wavelet-CNN-LSTM outperforms the other models both in single-step and multi-steps prediction. Besides, further mechanistic analysis revealed that MRA produce significant effect on improving model accuracy.     

Static modeling of dynamic recreation behavior: Implications for prediction and welfare estimation

This paper examines the consequences of using a static model of recreation trip-taking behavior when the underlying decision problem is dynamic. Specifically we examine the implications for trip forecasting and welfare estimation using a panel dataset of Lake Michigan salmon anglers for the 1996 and 1997 fishing seasons. We derive and estimate both a structural dynamic model using Bellman's equation, and a reduced-form static model with trip probability expressions mimicking those of the dynamic model. We illustrate an inherent identification problem in the reduced-form model that creates biased welfare estimates, and we discuss the general implications of this for the interpretation of preference parameters in static models. We then use both models to simulate trip taking behavior and show that although their in-sample trip forecasts are similar, their welfare estimates and out-of-sample forecasts are quite different.     

Static modeling of dynamic recreation behavior: Implications for prediction and welfare estimation

This paper examines the consequences of using a static model of recreation trip-taking behavior when the underlying decision problem is dynamic. Specifically we examine the implications for trip forecasting and welfare estimation using a panel dataset of Lake Michigan salmon anglers for the 1996 and 1997 fishing seasons. We derive and estimate both a structural dynamic model using Bellman's equation, and a reduced-form static model with trip probability expressions mimicking those of the dynamic model. We illustrate an inherent identification problem in the reduced-form model that creates biased welfare estimates, and we discuss the general implications of this for the interpretation of preference parameters in static models. We then use both models to simulate trip taking behavior and show that although their in-sample trip forecasts are similar, their welfare estimates and out-of-sample forecasts are quite different.     

Assessing the Conservation Value of New Zealand's Offshore Islands

New Zealand has over 500 offshore islands. Many consist of relatively pristine wilderness and contain a disproportionately large amount of New Zealand's biological wealth. Increased demand for recreation has increased the pressure to develop these areas. Although the New Zealand public has shown widespread support for the preservation and safeguarding of both wilderness areas and endangered species, economic values attached to the benefits of preservation are not known. Using a telephone survey, we found evidence that the public attaches significant value to the conservation of Little Barrier Island. The results show that these values are influenced by different levels and sources of prior information.     

Ecological research for integrated coastal zone management: Introduction

Two Special Features on integrated coastal zone management, especially along the Mediterranean Sea, result from a MeDCOAST conference held in Hammamet (Tunisia). 20–25 October 2001. In this first Special Feature some papers are presented on ecological and biological research related to integrated coastal zone management. All over Europe coastal environments are threatened by human activities such as urbanization, industrial development, fisheries, aquaculture, recreation and tourism. Research has to be developed that can be applied to similar case studies in different countries. Methods of monitoring are necessary and baseline data have to be available in order to judge the significance of changes in the abjotic and biotic environment. Examples of studies included in this Special Feature are mainly from southern banks of the Mediterranean Sea but there is also an example from Estonia and one from the Canary Islands.     

Congestion and economic valuation: A reconsideration

The topic of congestion in the use of travel cost demand models has received a considerable amount of attention. A number of extensions of the original Wetzel article have extended the question raised in that article. The purpose of this paper is twofold. The first purpose is to raise the general issue of the use of short-run or long-run demand curves for policy analysis. The second purpose is to make some brief specific comments about certain sections of the extensions and corrections offered to the original Wetzel article.     

Simultaneous estimation of jointly dependent recreation participation function

The purpose of this paper is to develop and estimate a simultaneous model of recreation participation. The logic of the model is that participation in one activity (for example, boating) is influenced by and influences participation in other activities (for example, fishing). For the empirical part of our paper we have used the simultaneous logit model developed by P. Schmidt and R. P. Strauss (Econometrics43, 745–755, 1975). For the application, we have applied the simultaneous logit model to participation in summer recreational activities in Rhode Island. Our results show that simultaneous equation models tend to forecast better, but that the specification bias from excluding the endogenous variables tends to be small.     

Forecasting New Zealand Mudsnail invasion range: model comparisons using native and invaded ranges.

Evaluations of the potential distribution of invasive species can increase the efficiency of their management by focusing prevention measures. Generally, ecological models are built using occurrence data from a species' native range to predict the distribution in areas that the species may invade. However, historical and geographical constraints can limit a species' native distribution. Genetic Algorithm for Rule-set Production (GARP), an ecological niche modeling program, was used to predict the potential distribution of the invasive, freshwater New Zealand mudsnail, Potamopyrgus antipodarum, in Australia and North America. We compared the strength of the predictions made by models built with data from the snail's native range in New Zealand to models built with data from the locations invaded by the species. A time-series analysis of the Australian models demonstrated that range-of-invasion data can make better predictions about the potential distribution of invasive species than models built with native range data. Large differences among the model forecasts indicate that uncritical choice of the data set used in training the GARP models can result in misleading predictions. The models predict a large expansion in the range of P. antipodarum in both Australia and North America unless prevention measures are implemented rapidly.