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on Discrete Choice Models |
| By: | Tensay Meles; L. (Lisa B.) Ryan; Sanghamitra Mukherjee |
| Abstract: | Renewable sources of home heating like heat pump systems are expected to play a vital role in mitigating the adverse effects of carbon-intensive heating systems. Compared to conventional heating systems, heat pump systems are more energy efficient, have low maintenance and operational costs and provide reliable and environmentally friendly home heating. Despite those advantages, the uptake of heat pumps has been low among the Irish population and little is known about the factors that affect their adoption. This paper uses a discrete choice experiment approach to investigate preferences for heat pumps in the residential sector based on nationally representative household survey data from Ireland. We analyse the choice data using a mixed logit model and estimate the marginal willingness to pay for bill savings, environmentally sustainable, installation hassles and increase in home comfort using both models in preferences space and in willingness to pay (WTP) space. Our results show that upfront cost, bill savings, environmental sustainability and installation hassle significantly influence household uptake of heat pumps. The estimated results also reveal the presence of heterogeneous preferences. Furthermore, the results show that households are willing to pay for heat pumps; however, the values might not be large enough to cover the higher upfront costs of, for example, a ground source heat pump. Overall, the study highlights that policy makers should consider the various financial and non-financial factors that influence adoption and heterogeneity in preferences in designing policy intervention aimed at increasing the uptake of heat pumps. |
| Keywords: | Heat-pump system; Choice experiment; Mixed logit model; Willingness to pay |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:ucn:oapubs:10197/11467&r=all |
| By: | Myrto Kalouptsidi; Paul T. Scott; Eduardo Souza-Rodrigues |
| Abstract: | In structural dynamic discrete choice models, unobserved or mis-measured state variables may lead to biased parameter estimates and misleading inference. In this paper, we show that instrumental variables can address such measurement problems when they relate to state variables that evolve exogenously from the perspective of individual agents (i.e., market-level states). We define a class of linear instrumental variables estimators that rely on Euler equations expressed in terms of conditional choice probabilities (ECCP estimators). These estimators do not require observing or modeling the agent's entire information set, nor solving or simulating a dynamic program. As such, they are simple to implement and computationally light. We provide constructive arguments for the identification of model primitives, and establish the estimator's consistency and asymptotic normality. Four applied examples serve to illustrate the ECCP approach's implementation, advantages, and limitations: dynamic demand for durable goods, agricultural land use change, technology adoption, and dynamic labor supply. We illustrate the estimator's good finite-sample performance in a Monte Carlo study, and we estimate a labor supply model empirically for taxi drivers in New York City. |
| Keywords: | dynamic discrete choice, unobserved states, instrumental variables, identification, Euler equations |
| JEL: | C13 C35 C36 C51 C61 |
| Date: | 2020–08–26 |
| URL: | http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-674&r=all |
| By: | Hunt, Priscillia E (RAND); Smart, Rosanna (RAND) |
| Abstract: | A criminal record can severely damage labor market prospects. While public and private organizations have developed a host of policies to encourage employers to hire people with a record, research suggests some of the policies may have negative unintended consequences. To explore ways to mitigate these consequences, we conducted a discrete-choice experiment in the summer of 2017 with a nationally representative sample of employers. Employers indicated their preferences for incentives offered by staffing agencies to hire individuals with one non-violent felony conviction. These incentives include: a replacement guarantee, more detailed work history, provision of transportation to/from job site, and a fee discount. The baseline incentive involved a staffing agency verifying that the ex-offender did not have safety or rule violations in previous companies and a fee discount worth the same amount as the federal Work Opportunity Tax Credit for ex-felons (WOTC). At baseline, less than half (43%) of employers would consider hiring an individual with this incentive. The likelihood of hiring an individual with a record increased from the baseline by 69 percent if a staffing agency also provided a guarantee of a replacement worker in the event the individual was deemed unsuitable. Employers were 53 percent more likely to hire an individual providing a certificate of validated positive previous work performance history. Having consistent transportation increased the probability of being considered for hire by 33 percent, and doubling the fee discount increased the baseline probability by 42 percent. |
| Keywords: | employment, choice experiment, stated preference, criminal record |
| JEL: | K14 J78 J24 |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp13520&r=all |
| By: | Anais Lamour (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - INRA - Institut National de la Recherche Agronomique - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement); Subervie Julie (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement) |
| Abstract: | We use primary data from a choice experiment carried out with 207 coffee farmers in Costa Rica, in order to study their willingness to adopt various agroforestry systems under various types of support. We test four adaptation strategies that are based on resistant coffee varieties introduction, timber tree species production and/or shade tree density increase. Revealed preferences suggest that most of the respondents do value the introduction of resistant varieties. They are willing to plant twice the number of trees in their plantations when these are combined with resistant varieties. Conversely, all agroforestry systems requiring timber trees to be planted are chosen significantly less often and on average, their adoption would require a compensation scheme. We moreover find that a large majority of respondents is very responsive to non-monetary rewards, namely a subsidized credit, a free trial of resistant coffee seedlings or technical assistance. We conclude that each of these incentivescould be used as an incentive to induce land use changes |
| Keywords: | Payment for Environmental Services,Non-monetary Incentives,Climate change,Choice Experiment,Coffee,Costa Rica |
| Date: | 2020–07–07 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02892085&r=all |
| By: | Youssef M. Aboutaleb; Moshe Ben-Akiva; Patrick Jaillet |
| Abstract: | This paper introduces a new data-driven methodology for nested logit structure discovery. Nested logit models allow the modeling of positive correlations between the error terms of the utility specifications of the different alternatives in a discrete choice scenario through the specification of a nesting structure. Current nested logit model estimation practices require an a priori specification of a nesting structure by the modeler. In this we work we optimize over all possible specifications of the nested logit model that are consistent with rational utility maximization. We formulate the problem of learning an optimal nesting structure from the data as a mixed integer nonlinear programming (MINLP) optimization problem and solve it using a variant of the linear outer approximation algorithm. We exploit the tree structure of the problem and utilize the latest advances in integer optimization to bring practical tractability to the optimization problem we introduce. We demonstrate the ability of our algorithm to correctly recover the true nesting structure from synthetic data in a Monte Carlo experiment. In an empirical illustration using a stated preference survey on modes of transportation in the U.S. state of Massachusetts, we use our algorithm to obtain an optimal nesting tree representing the correlations between the unobserved effects of the different travel mode choices. We provide our implementation as a customizable and open-source code base written in the Julia programming language. |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2008.08048&r=all |
| By: | Prateek Bansal; Daniel H\"orcher; Daniel J. Graham |
| Abstract: | Crowding valuation of subway riders is an important input to various supply-side decisions of transit operators. The crowding cost perceived by a transit rider is generally estimated by capturing the trade-off that the rider makes between crowding and travel time while choosing a route. However, existing studies rely on static compensatory choice models and fail to account for inertia and the learning behaviour of riders. To address these challenges, we propose a new dynamic latent class model (DLCM) which (i) assigns riders to latent compensatory and inertia/habit classes based on different decision rules, (ii) enables transitions between these classes over time, and (iii) adopts instance-based learning theory to account for the learning behaviour of riders. We use the expectation-maximisation algorithm to estimate DLCM, and the most probable sequence of latent classes for each rider is retrieved using the Viterbi algorithm. The proposed DLCM can be applied in any choice context to capture the dynamics of decision rules used by a decision-maker. We demonstrate its practical advantages in estimating the crowding valuation of an Asian metro's riders. To calibrate the model, we recover the daily route preferences and in-vehicle crowding experiences of regular metro riders using a two-month-long smart card and vehicle location data. The results indicate that the average rider follows the compensatory rule on only 25.5% of route choice occasions. DLCM estimates also show an increase of 47% in metro riders' valuation of travel time under extremely crowded conditions relative to that under uncrowded conditions. |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2007.03682&r=all |
| By: | Georges Sfeir; Maya Abou-Zeid; Filipe Rodrigues; Francisco Camara Pereira; Isam Kaysi |
| Abstract: | This study presents a semi-nonparametric Latent Class Choice Model (LCCM) with a flexible class membership component. The proposed model formulates the latent classes using mixture models as an alternative approach to the traditional random utility specification with the aim of comparing the two approaches on various measures including prediction accuracy and representation of heterogeneity in the choice process. Mixture models are parametric model-based clustering techniques that have been widely used in areas such as machine learning, data mining and patter recognition for clustering and classification problems. An Expectation-Maximization (EM) algorithm is derived for the estimation of the proposed model. Using two different case studies on travel mode choice behavior, the proposed model is compared to traditional discrete choice models on the basis of parameter estimates' signs, value of time, statistical goodness-of-fit measures, and cross-validation tests. Results show that mixture models improve the overall performance of latent class choice models by providing better out-of-sample prediction accuracy in addition to better representations of heterogeneity without weakening the behavioral and economic interpretability of the choice models. |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2007.02739&r=all |
| By: | Jacobs, B.J.D.; Fok, D.; Donkers, A.C.D. |
| Abstract: | In modern retail contexts, retailers sell products from vast product assortments to a large and heterogeneous customer base. Understanding purchase behavior in such a context is very important. Standard models cannot be used due to the high dimen- sionality of the data. We propose a new model that creates an efficient dimension reduction through the idea of purchase motivations. We only require customer-level purchase history data, which is ubiquitous in modern retailing. The model han- dles large-scale data and even works in settings with shopping trips consisting of few purchases. As scalability of the model is essential for practical applicability, we develop a fast, custom-made inference algorithm based on variational inference. Essential features of our model are that it accounts for the product, customer and time dimensions present in purchase history data; relates the relevance of moti- vations to customer- and shopping-trip characteristics; captures interdependencies between motivations; and achieves superior predictive performance. Estimation re- sults from this comprehensive model provide deep insights into purchase behavior. Such insights can be used by managers to create more intuitive, better informed, and more effective marketing actions. We illustrate the model using purchase history data from a Fortune 500 retailer involving more than 4,000 unique products. |
| Keywords: | dynamic purchase behavior, large-scale assortment, purchase history data, topic model, machine learning, variational inference |
| Date: | 2020–08–01 |
| URL: | http://d.repec.org/n?u=RePEc:ems:eureri:129674&r=all |
| By: | José Javier Soto Martínez; Luis Gabriel Márquez Díaz; Luis Fernando Macea Mercado |
| Abstract: | Esta investigación examina las preferencias de los usuarios en la escogencia de opciones de estacionamiento en el centro de Cartagena, Colombia. Se emplean modelos de elección discreta, incorporando variaciones sistemáticas de los gustos. Los modelos se estimaron a partir de encuestas de preferencias declaradas (PD), usando como variables explicativas el costo del estacionamiento, el tiempo de acceso desde el parqueadero hasta el destino y el tiempo de búsqueda de estacionamiento. Los resultados indican que el costo es el parámetro más importante a la hora de elección del estacionamiento. Por otra parte, las personas con ingreso alto penalizan menos la tarifa en el proceso de elección, contrario a las personas con vehículos de bajo costo, cuya penalización es mayor. Se estimaron elasticidades y la disposición a pagar por disminuir los tiempos de búsqueda de estacionamiento y de acceso al destino, encontrándose valores entre COP $89/ min – COP $352/min y COP $123/min – COP $489/min, respectivamente. |
| Date: | 2018–12–15 |
| URL: | http://d.repec.org/n?u=RePEc:col:000162:018327&r=all |
| By: | Claire Borsenberger; Helmuth Cremer (TSE - Toulouse School of Economics - UT1 - Université Toulouse 1 Capitole - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Denis Joram; Jean-Marie Lozachmeur (TSE - Toulouse School of Economics - UT1 - Université Toulouse 1 Capitole - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Estelle Malavolti (ENAC - Ecole Nationale de l'Aviation Civile, TSE - Toulouse School of Economics - UT1 - Université Toulouse 1 Capitole - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement) |
| Abstract: | This paper considers an e-commerce market wherein a vertically integrated marketplace competes downstream with a single retailer and upstream with an independent parcel delivery operator. Because of the information collected by the marketplace on customersíhabits and preferences, the integrated parcel delivery operator has lower delivery costs than its competitor. Products are di§erentiated according to the retailer and the parcel operator who delivers them. The representation of product di§erentiation is inspired by the Anderson, De Palma and Thisse (2002) discrete choice model. We study several scenarios each representing a speciÖc policy implemented to regulate the marketplace. The Örst one is a data sharing policy. The integrated marketplace has to share its information with the other delivery operator which in turn will lower this operatorís cost of delivering the marketplaceís product. The second one is vertical separation under which the parcel delivery operator previously owned and managed by the marketplace becomes independent. Finally we consider a full dismantlement scenario under which there is both vertical and horizontal separation. We show that the optimal policy is either complete dismantlement or data sharing. The relative impacts on consumer surplus and total welfare of these two options involve a tradeo§ between the increased competition implied by complete dismantling and the data related delivery cost advantage achieved under data sharing. When this cost advantage is small, completely dismantling dominates, while data sharing is the best policy when the cost advantage is large. |
| Keywords: | E-commerce,delivery operators,vertical integration,platform regulation,data sharing,dismantling |
| Date: | 2020–07–03 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02888790&r=all |
| By: | Amy Finkelstein; Nathaniel Hendren |
| Abstract: | We describe a framework for empirical welfare analysis that uses the causal estimates of a policy’s impact on net government spending. This framework provides guidance for which causal effects are (and are not) needed for empirical welfare analysis of public policies.The key ingredient is the construction of each policy’s marginal value of public funds (MVPF). The MVPF is the ratio of beneficiaries’ willingness to pay for the policy to the net cost to the government. We discuss how the MVPF relates to “traditional” welfare analysis tools such as the marginal excess burden and marginal cost of public funds. We show how the MVPF can be used in practice by applying it to several canonical empirical applications from public finance, labor, development, trade, and industrial organization. |
| JEL: | H0 |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:27640&r=all |
| By: | Douadia Bougherara (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Margaux Lapierre (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Raphaële Préget (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Alexandre Sauquet (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement) |
| Abstract: | Nearly all Agri-Environmental Schemes (AES) offer stable annual payments over theduration of the contract. Yet AES are often intended to be a transition tool, designed totrigger changes in farming practices rather than to support them indefinitely. A decreasingsequence of payments thus appears particularly attractive as a reward structure for AES.The standard discounted utility model supports this notion by predicting that individualsshould prefer a decreasing sequence of payments if the total sum of outcomes is con-stant. Nevertheless, the literature shows that numerous mechanisms, such as increasingproductivity, anticipatory pleasure, and loss aversion, can, by contrast, incline individualsto favor an increasing sequence of payments. To understand the preferences of farmersfor different payment sequences, we propose a review of the mechanisms highlighted bythe literature in psychology and economics. We then test farmers' preferences for stable,increasing or decreasing payments through a choice experiment (CE) survey. In this sur-vey, farmers are offered hypothetical contracts rewarding the planting of cover crops. Toreduce hypothetical bias, the choice cards were designed following repeated interactionswith local stakeholders. One hundred twenty-three French farmers, about 15% of thosecontacted, responded to the survey. Overall, farmers do not present a clear willingnessto depart from the usual stable payments. Nevertheless, 17% declare a preference for in-creasing sequences of payment. Moreover, we find a significant rejection of decreasingpayments by farmers with a lower discount rate or farmers more willing to take risks thanthe median farmer, contradicting the discounted utility model |
| Keywords: | Choice experiment,Cover crops,Farming practices,Sequences of outcomes,Agri-Environmental Schemes,Discounted utility |
| Date: | 2020–07–07 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02892858&r=all |