858 resultados para social willingness to pay
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The authors use experimental surveys to investigate the association between individuals' knowledge of particular wildlife species and their stated willingness to allocate funds to conserve each. The nature of variations in these allocations between species (e.g., their dispersion) as participants' knowledge increases is examined. Factors influencing these changes are suggested. Willingness-to-pay allocations are found not to measure the economic value of species, but are shown to be policy relevant. The results indicate that poorly known species, e.g., in remote areas, may obtain relatively less conservation support than they deserve. (JEL Q51, Q57, Q58)
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We surveyed 204 individuals from the general public in Brisbane, Australia, to ascertain the extent to which they liked or disliked 24 species of wildlife (belonging to three classes: mammals, birds and reptiles) present in tropical Australia. We calculated likeability indices for each species. We also asked respondents if they favored the survival of each of these species, and were able to calculate the percentage of respondents favoring survival of each. Using linear regression analysis, we could relate the percentage of respondents favoring survival of each of the species to their indices of likeability. In addition, we compared the mean likeability of species in the three classes (mammals, birds and reptiles) with the respondents' allocation of funds (hypothetical 1,000 Australian dollars) between conservation of species and a human charity. From this, we were able to assess how important stated likeability is for preferences to conserve species by animal class, and reconsidered the hypothesis in the literature that there is likely to be more public support for the survival of mammals than for birds, and more support for the survival of birds than for reptiles.
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Purpose – This paper aims to investigate the manner in which technological innovation in the European electrical-grid sector has developed by focusing, in particular, on the effect of public policy on innovation. To achieve this aim, this paper highlights how technological innovation and development progressed from the 1960s to the 1980s, and contrasts this period with the deregulated/privatization environment. Design/methodology/approach – The paper is based on a series of in-depth multiple company case studies of grid companies, some of their suppliers and other actors in their broader business network. Empirical data were collected through 55 interviews. Findings – The authors find that a phase of mutual collaboration was encouraged in the first period, which led to strong technological innovation with a focus on product quality and the development of functionality. Buyers played a pivotal role in the development of products and posed technical requirements. In contrast, the current role of the buyer has transformed principally into one of evaluating competing bids for specific projects. Today, buyers face increasing pressure to substantially lower CO2 emissions and transform the energy grid system. These goals are difficult to achieve without a new way of thinking about innovation. Research limitations/implications – Models to achieve innovation must not only focus on individual research projects; instead, the innovation should be factored into normal business dealings in the supply chain. Practical implications – We propose that policymakers and regulators need to: accommodate for innovation and address the collaborative elements of innovation when developing policies and regulations. Furthermore, regulators have the option of either developing a strategic vision for the electrical-grid network or incorporating sustainability into the evaluation of electrical grids and, thus, consumers’ willingness to pay. Originality/value – This paper makes a distinctive contribution in the area of innovation for electrical grids. Our paper shows how innovation and the development of new technology for electrical grids changed over time. Furthermore, this paper describes the energy sector in terms of a business network comprising the different actors involved in innovation and development and, thus, their role in the energy supply chain.
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The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household's evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household's optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.
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The current exploratory study was designed to determine the impact that green restaurant practices may have on intention to visit a restaurant and willingness to pay more because of those green practices. The study analyzed a convenience sample of 260 surveys from customers in fast food restaurants and 501 surveys from customers in upscale casual restaurants in the Midwestern United States (U.S.) in order to determine if there were differences in the perception of guests regarding these types of restaurants and their green practices. The findings showed that upscale casual restaurant customers believed they are knowledgeable at a higher level than the fast food restaurant customers about green restaurant practices, have a higher mean rating on the importance of environmental record and recycling in restaurants, and believed that restaurants should use local products when they can. In both groups of customers, there was a positive relationship between green practices utilized at home and customers’ willingness to pay more for green restaurant practices as well as their intention to visit the restaurant using green practices. Management implications are discussed.
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The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household’s evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household’s optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.
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Urban problems have several features that make them inherently dynamic. Large transaction costs all but guarantee that homeowners will do their best to consider how a neighborhood might change before buying a house. Similarly, stores face large sunk costs when opening, and want to be sure that their investment will pay off in the long run. In line with those concerns, different areas of Economics have made recent advances in modeling those questions within a dynamic framework. This dissertation contributes to those efforts.
Chapter 2 discusses how to model an agent’s location decision when the agent must learn about an exogenous amenity that may be changing over time. The model is applied to estimating the marginal willingness to pay to avoid crime, in which agents are learning about the crime rate in a neighborhood, and the crime rate can change in predictable (Markovian) ways.
Chapters 3 and 4 concentrate on location decision problems when there are externalities between decision makers. Chapter 3 focuses on the decision of business owners to open a store, when its demand is a function of other nearby stores, either through competition, or through spillovers on foot traffic. It uses a dynamic model in continuous time to model agents’ decisions. A particular challenge is isolating the contribution of spillovers from the contribution of other unobserved neighborhood attributes that could also lead to agglomeration. A key contribution of this chapter is showing how we can use information on storefront ownership to help separately identify spillovers.
Finally, chapter 4 focuses on a class of models in which families prefer to live
close to similar neighbors. This chapter provides the first simulation of such a model in which agents are forward looking, and shows that this leads to more segregation than it would have been observed with myopic agents, which is the standard in this literature. The chapter also discusses several extensions of the model that can be used to investigate relevant questions such as the arrival of a large contingent high skilled tech workers in San Francisco, the immigration of hispanic families to several southern American cities, large changes in local amenities, such as the construction of magnet schools or metro stations, and the flight of wealthy residents from cities in the Rust belt, such as Detroit.
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I denna uppsats skattas betalningsviljan hos besökarna på Peace & Love-festivalen år 2011. Med hjälp av enkätdata baserad på avslöjade och uttalade preferenser presenteras en regressionsanalys med olika oberoende variabler som karaktäriserar en festivalbesökare. Total budget är den beroende variabeln i regressionsanalysen och tolkas i uppsatsen som ekvivalent med besökarnas betalningsvilja. Analysen visar att män i genomsnitt spenderar 301 kronor mer än kvinnor, att turister i genomsnitt spenderar 1 124 kronor mer än en icke-turist samt att den genomsnittliga besökaren har en betalningsvilja på 4 183 kronor. Ett skattat konsumentöverskott har också värderats, vilket uppgick till 743 kronor per person och cirka 37 miljoner kronor totalt för de 50 000 festivalbesökarna. Uppsatsen tar inte hänsyn till de ekonomiska effekter som festivalen har på Borlänge som stad.
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Seagrass meadows (Zostera marina) are an important ecosystem in the coastal environment of the Baltic Sea. This study employs a discrete choice experiment to value a set of non-market benefits provided by seagrass meadows in the Gulf of Gdańsk, Poland. The benefits valued in this study are a reduction of filamentous algae in the water and on the beach; access to seagrass meadows for boaters and divers; and improved water clarity. Results show significant willingness to pay for each attribute and differences of value estimates across different groups of survey respondents. It is discussed how to link choice attributes and estimated values with established ecosystem benefit categories in order to facilitate value transfer.
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In this dissertation I study the development of urban areas. At the aggregate level I investigate how they may be affected by climate change policies and by being designated the seat of governmental power. At the household level I study with coauthors how microfinance could improve the health of urban residents. In Chapter 1, I investigate how local employment may be affected by electricity price increases, which is a likely consequence of climate change policies. I outline how previous studies that find large, negative effects may be biased. To overcome these biases I develop a novel estimation strategy that blends border-pair regressions with the synthetic control methodology. I show the conditions for consistent estimation. Using this estimator, I find no effect of contemporaneous price changes on employment. Consistent with the longer time-frame for manufacturing decisions, I do find evidence for negative effects from perceived permanent price shocks. These estimates are much smaller than previous research has found. National capital cities are often substantially larger than other cities in their countries. In Chapter 2, I investigate whether there is a causal effect from being a capital by studying the 1960 relocation of the Brazilian capital from Rio de Janeiro to Brasília. Using a synthetic controls strategy I find that losing the capital had no significant effects on Rio de Janeiro in terms of population, employment, or gross domestic product (GDP). I find that Brasília experienced large and significant increases in population, employment, and GDP. I find evidence of large spillovers from the public to the private sector. Chapter 3 investigates how microfinance could increase the uptake of costly health goods. We study the effect of time payments (micro-loans or micro-savings) on willingness-to-pay (WTP) for a water filter among households in the slums of Dhaka, Bangladesh. We find that time payments significantly increase WTP: compared to a lump-sum up-front purchase, median WTP increases 83% with a six-month loan and 115% with a 12-month loan. We find that households are quite patient with respect to consumption of health inputs. We find evidence for the presence of credit and savings constraints.
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Stated-preference valuation techniques are often used to assess consumers' willingness-to-pay for food items produced in farming systems that adopt a sustainable use of pesticides (SUP). We propose an innovative valuation methodology in which dichotomous-choice contingent valuation is used to estimate the demand curve (price-quantity relationship) for such food items where price means price premium for the SUP output, quantity is the probability of choosing SUP and the conventional food product is kept available in the market at the current market price. This methodology can be used to evaluate market differentiation as a policy option to promote the SUP. The methodology is tested with data from a sample of urban consumers of fruits and vegetables in Portugal. The estimated demand curve is used to define the price level maximizing the total premium revenue for the SUP sector as a whole. This optimal level of the price premium is €77.55 (or 163% of the value of the monthly basket of fruits and vegetables at current prices). Adopting the optimal price premium will decrease the number of consumers of SUP food by 54%. The reduction is even higher for low income consumers (80%) leaving them more exposed to the risks of pesticide use.
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Conservation of the seven lagoons of the Palavas complex (southern France) has been severely impaired by nutrient over-enrichment during at least four decades. The effluents of the Montpellier wastewater treatment plant (WWTP) represented the main nutrient input. To improve the water quality of these lagoons, this WWTP was renovated and upgraded and, since the end of 2005, its effluents have been discharged 11 km offshore into the Mediterranean (total investment €150 M). Possibilities of ecosystem restoration as part of a conservation programme were explored by a focus group of experts. Their tasks were: (i) to evaluate the impact of the reduction of the nutrient input; (ii) if necessary, to design additional measures for an active restoration programme; and (iii) to predict ecosystem trajectories for the different cases. Extension of Magnoliophyta meadows can be taken as a proxy for ecosystem restoration as they favour the increase of several fish (seahorse) and bird (ducks, swans, herons) species, albeit they represent a trade-off for greater flamingos. Additional measures for active ecosystem restoration were only recommended for the most impaired lagoon Méjean, while the least impaired lagoon Ingril is already on a trajectory of spontaneous recovery. A multiple contingent valuation considering four different management options for the Méjean lagoon was used in a pilot study based on face-to-face interviews with 159 respondents. Three levels of ecosystem restoration were expressed in terms of recovery of Magnoliophyta meadows, including their impact on emblematic fish and avifauna. These were combined with different options for access (status quo, increasing access, increasing access with measures to reduce disturbance). The results show a willingness of local populations to pay per year about €25 for the highest level of ecological restoration, while they were only willing to allocate about €5 for additional footpaths and hides.
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El objetivo de este trabajo es la determinación de los beneficios económicos que obtendrían los hogares de zonas residenciales en la ciudad de Medellín (Colombia) por la reducción del ruido por tráfico vehicular. Para tal propósito se utilizó el método de valoración contingente en combinación con información de percepción de calidad acústica de los hogares. Este enfoque permitió estimar la disponibilidad a pagar esperada por la reducción de un decibel en los niveles de ruido a los cuales están expuestos los hogares. Los resultados demuestran que si se aplica para la ciudad un programa, política o proyecto que logre una reducción generalizada de 5 decibeles en el ruido por tráfico vehicular los beneficios económicos agregados ascienden a 397 millones de pesos colombianos al año. El estudio concluye que estos resultados generan conocimiento importante para hacer más efectiva la toma de decisiones en el marco de políticas regionales con respecto a la gestión de la reducción del ruido por tráfico vehicular.