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on Discrete Choice Models |
| By: | Tobias Holmsgaard Larsen (Department of Food and Resource Economics, University of Copenhagen); Thomas Lundhede (Department of Food and Resource Economics, University of Copenhagen); Søren Bøye Olsen (Department of Food and Resource Economics, University of Copenhagen) |
| Abstract: | This report summarizes the main results from a choice experiment survey addressing peoples’ willingness to pay (WTP) for improvements in surface water quality as well as groundwater quality. A particular novel focus is on estimating the extent to which WTP is impacted by the time lags and outcome uncertainties that commonly occur in practice when implementing new policies to improve water quality. The survey is conducted across four different case areas in four different countries, involving responses from more than 3000 respondents. Results generally confirm previous findings that people on average have quite high WTP for improvements in water quality, both in relation to surface water and groundwater. In addition, the results show that the WTPs reduce significantly with increasing time lags and outcome uncertainty in relation to the actual water quality improvements. |
| Keywords: | Economic Valuation, Choice Experiment, Water Quality, Outcome Uncertainty, Time Lags |
| JEL: | C83 D60 Q51 Q53 |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:foi:wpaper:2020_12&r=all |
| By: | Khuong, Phuong M.; Scheller, Fabian; McKenna, Russell; Keles, Dogan; Fichtner, Wolf |
| Abstract: | Photovoltaic (PV) has recorded an impressive development in the last years. The increasing economic potential and further technological improvement will continue to reduce the cost of PV. However, it is not yet well adopted by household customers. Adversely, there is lacking empirical evidence for understanding residential PV adoption behaviour, which this study addresses with empirical research. Although a variety of models can be used to explain social acceptance (SA) and willingness to pay (WTP) for renewable energy, they overlook the connection between SA and WTP in the final purchase decision of a decision-maker. Based on a survey of both SA and WTP in the same observation sample of 2039 Vietnamese residents, this study introduces well-established models with a new linking psychological and economic aspects to measure multiple outcomes involving residential PV behaviours to testing hypotheses with no precedent in the literature. The theoretical and integrative moderated mediation models help to understand residential PV behaviour and suggest solutions for development by revealing how different factors affect SA and WTP in different manners. Environmental interest reveals the predictive power within the SA and WTP behaviour models. Meanwhile, PV knowledge drives SA, but not WTP in Vietnam. Attitude and Perceived behavioural control not only impact SA and WTP directly but also mediate the effect of Environmental interest and SA and WTP. Age & Marital status & Children and Place of residence are important covariates that drive in the SA and WTP models, respectively. Lastly, Income is the covariate in the SA model, but the moderator in the WTP model. In practical implications, this study provides evidence that residential PV is a lifestyle product rather than an economical product, but it is not considered as an essential good for household customers. Thereby, suggestions are given to policymakers and stakeholders to promote market development. |
| Keywords: | Developing country,Willingness to pay,Social acceptance,Residential photovoltaic |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:kitiip:46&r=all |
| By: | Diane Coyle; David Nguyen |
| Abstract: | This paper uses a survey representative of the UK online population to assess the willingness to accept loss of certain goods. We had conducted an initial survey in February, focusing on ‘free’ online goods and some potential substitutes and comparators. Consistent with other contingent valuation studies, consumers on average assigned valuations to many of these goods, particularly when benchmarked against revenue figures for the services. Our pilot studies, discussed in a forthcoming paper, also suggested that the actual valuations are not well anchored, but the methodology can give consistent rankings among goods. It is also a useful way to assess changes in valuations. Repeating the survey in May, during the UK, lockdown, we observed significant changes in the valuations of different goods and services, with some large differences by age and gender. In this sense the lockdown has acted as a natural experiment testing for the extent to which digital goods and physical goods are substitutes. These valuation changes may indicate which services are most valuable in a post-pandemic world where more activity takes place online. They also provide important, policy-relevant insights into distributional questions. |
| Keywords: | digital services, valuations, lockdown |
| JEL: | D12 D60 I31 C43 |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:nsr:escoed:escoe-dp-2020-10&r=all |
| By: | Max H. Farrell; Tengyuan Liang; Sanjog Misra |
| Abstract: | We propose a methodology for effectively modeling individual heterogeneity using deep learning while still retaining the interpretability and economic discipline of classical models. We pair a transparent, interpretable modeling structure with rich data environments and machine learning methods to estimate heterogeneous parameters based on potentially high dimensional or complex observable characteristics. Our framework is widely-applicable, covering numerous settings of economic interest. We recover, as special cases, well-known examples such as average treatment effects and parametric components of partially linear models. However, we also seamlessly deliver new results for diverse examples such as price elasticities, willingness-to-pay, and surplus measures in choice models, average marginal and partial effects of continuous treatment variables, fractional outcome models, count data, heterogeneous production function components, and more. Deep neural networks are well-suited to structured modeling of heterogeneity: we show how the network architecture can be designed to match the global structure of the economic model, giving novel methodology for deep learning as well as, more formally, improved rates of convergence. Our results on deep learning have consequences for other structured modeling environments and applications, such as for additive models. Our inference results are based on an influence function we derive, which we show to be flexible enough to to encompass all settings with a single, unified calculation, removing any requirement for case-by-case derivations. The usefulness of the methodology in economics is shown in two empirical applications: the response of 410(k) participation rates to firm matching and the impact of prices on subscription choices for an online service. Extensions to instrumental variables and multinomial choices are shown. |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2010.14694&r=all |
| By: | Dietmar Pfeifer; Doreen Strassburger; Joerg Philipps |
| Abstract: | In this paper we review Bernstein and grid-type copulas for arbitrary dimensions and general grid resolutions in connection with discrete random vectors possessing uniform margins. We further suggest a pragmatic way to fit the dependence structure of multivariate data to Bernstein copulas via grid-type copulas and empirical contingency tables. Finally, we discuss a Monte Carlo study for the simulation and PML estimation for aggregate dependent losses form observed windstorm and flooding data. |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2010.15709&r=all |
| By: | LUPPI, FRANCESCA; Rosina, Alessandro (Catholic University of the Sacred Heart); Sironi, Emiliano |
| Abstract: | With the spread of the SARS-CoV-2 pandemic all over Europe during the first months of 2020, most of the European governments imposed restrictive measures to people mobility and physical distance (the lockdown), which severely impacted on the economic activities and performance of many countries. Thus, the health emergency turned rapidly into in an economic crisis. The Covid-19 crisis in Europe increased the uncertainty about the economic recovery and the end of the health emergency. This situation is supposed to have conditioned individuals’ life course path with the effect of inducing people to postpone or to abandon many life plans. This paper aims to explore whether the rise of health emergency due to the Covid-19 has delayed or vanished young people intention to leave the parental home during the 2020 in five European countries: Italy, Germany, France, Spain and UK. Using data from an international survey from the “Youth Project”, carried out by the Toniolo Institute of Advanced Studies, this paper implements ordered logistic models in order to investigate the determinants of a possible revision of the choice of leaving the parental home for a representative sample of 6,000 respondents aged 18 to 34, interviewed between March and April 2020. A special focus has been pointed on the Italian case, because of being the first European country to be strongly hit by the pandemic and because of the already economic vulnerable conditions of its young population. Results reports that Italy is the country with the highest rate of downward revisions of the intentions of leaving the nest. In particular, having negative expectations about changes in the individual’s and family’s future income is a key predictor of the choice of abandoning the purpose of leaving the parental home across Europe. However, the vulnerability of the category of temporary workers arises especially in Italy: young people with precarious jobs seems to be the most prone to negatively revise their intentions of leaving, even compared with those not working. |
| Date: | 2020–11–05 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:9y6s5&r=all |