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on Discrete Choice Models |
| By: | Chun Pong Lau |
| Abstract: | In dynamic discrete choice models, some parameters, such as the discount factor, are being fixed instead of being estimated. This paper proposes two sensitivity analysis procedures for dynamic discrete choice models with respect to the fixed parameters. First, I develop a local sensitivity measure that estimates the change in the target parameter for a unit change in the fixed parameter. This measure is fast to compute as it does not require model re-estimation. Second, I propose a global sensitivity analysis procedure that uses model primitives to study the relationship between target parameters and fixed parameters. I show how to apply the sensitivity analysis procedures of this paper through two empirical applications. |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2408.16330 |
| By: | Rubal Dua; Tamara Sheldon (King Abdullah Petroleum Studies and Research Center) |
| Abstract: | Research has shown that when combined in a mobility-on-demand (MOD) framework, automation, carpooling, and electrification have the potential for theoretically large emission reductions. However, there is insufficient research regarding the consumer preferences for and behavioral responses to this vision of transportation in the future. In this paper, we use choice experiment data collected from an online ride-hailing survey to quantify the consumer preferences for these technologies. |
| Keywords: | Ride-hailing, Vehicle Electrification |
| Date: | 2024–03–28 |
| URL: | https://d.repec.org/n?u=RePEc:prc:dpaper:ks--2024-dp06 |
| By: | Jean-Michel Benkert; Shuo Liu; Nick Netzer |
| Abstract: | Response times contain information about economically relevant but unobserved variables like willingness to pay, preference intensity, quality, or happiness. Here, we provide a general characterization of the properties of latent variables that can be detected using response time data. Our characterization generalizes various results in the literature, helps to solve identification problems of binary response models, and paves the way for many new applications. We apply the result to test the hypothesis that marginal happiness is decreasing in income, a principle that is commonly accepted but so far not established empirically. |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2408.14872 |
| By: | Henk Keffert; Nikolaus Schweizer |
| Abstract: | When it comes to structural estimation of risk preferences from data on choices, random utility models have long been one of the standard research tools in economics. A recent literature has challenged these models, pointing out some concerning monotonicity and, thus, identification problems. In this paper, we take a second look and point out that some of the criticism - while extremely valid - may have gone too far, demanding monotonicity of choice probabilities in decisions where it is not so clear whether it should be imposed. We introduce a new class of random utility models based on carefully constructed generalized risk premia which always satisfy our relaxed monotonicity criteria. Moreover, we show that some of the models used in applied research like the certainty-equivalent-based random utility model for CARA utility actually lie in this class of monotonic stochastic choice models. We conclude that not all random utility models are bad. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2409.00704 |
| By: | Te Bao; John Duffy; Nobuyuki Hanaki |
| Abstract: | In the digital age, privacy in economic activities is increasingly threatened. In considering policies to address this threat, it is useful to consider what value, if any, people attach to privacy in their economic activities. This valuation may be influenced by a mixture of concerns including the desire for personal autonomy, concerns about the exposure of confidential information, and the risk of reputational damage due to dishonest or stigmatized behavior. Our focus is primarily on reputational concerns as we assess individuals’ willingness to pay (WTP) to avoid scrutiny of their potentially dishonest behavior in a simple coin flipping task. We gather and analyze data from Japan, China, and the U.S.A. to determine if there are notable differences across these nations in WTP. Our findings reveal that people’s WTP to “avoid the spotlight” is positive and economically sizable across all three countries and is the largest in Japan. |
| Date: | 2024–04 |
| URL: | https://d.repec.org/n?u=RePEc:dpr:wpaper:1238r |
| By: | Kim, Hyunseok |
| Abstract: | South Korea's strategies for deploying battery electric vehicles (BEVs) primarily include providing purchase subsidies and expanding charging infrastructure. An empirical analysis of new vehicle registrations from 2019 to 2022 shows that investing in charging facilities is more costeffective than offering purchase incentives for increasing BEV adoption. To achieve a higher share of BEVs, a stronger policy focus on improving the charging network is necessary to stimulate overall demand for BEVs. |
| Keywords: | Electric vehicle, purchase, subsidy, public spending, sustainable mobility, impact analysis, South Korea |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:kdifoc:302800 |
| By: | Eduardo Dávila (Yale University); Andreas Schaab (University of California - Berkeley) |
| Abstract: | This paper shows that it is possible to define an unambiguous notion of the direct effect of a parameter perturbation on the value of an optimization problem’s objective away from an optimum for problems with linearly homogeneous constraints. This notion of the direct effect relies on reformulating the optimization problem using shares as choice variables, and has the interpretation of holding choice variables — when formulated as shares — fixed. This short paper contains one formal “non-envelope†theorem and four applications to i) consumer demand, ii) cost minimization, iii) planning in exchange economies, and iv) planning in production economies. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cwl:cwldpp:2405 |
| By: | Francisco Blasques (Vrije Universiteit Amsterdam); Noah Stegehuis (Vrije Universiteit Amsterdam) |
| Abstract: | This paper proposes a score-driven model for filtering time-varying causal parameters through the use of instrumental variables. In the presence of suitable instruments, we show that we can uncover dynamic causal relations between variables, even in the presence of regressor endogeneity which may arise as a result of simultaneity, omitted variables, or measurement errors. Due to the observation-driven nature of score models, the filtering method is simple and practical to implement. We establish the asymptotic properties of the maximum likelihood estimator and show that the instrumental-variable score-driven filter converges to the unique unknown causal path of the true parameter. We further analyze the finite sample properties of the filtered causal parameter in a comprehensive Monte Carlo exercise. Finally, we reveal the empirical relevance of this method in an application to aggregate consumption in macroeconomic data. |
| Keywords: | observation-driven models, time-varying parameters, causal inference, endogeneity, instrumental variables |
| JEL: | C01 C22 C26 |
| Date: | 2024–02–29 |
| URL: | https://d.repec.org/n?u=RePEc:tin:wpaper:20240016 |
| By: | Magali Aubert (UMR MoISA - Montpellier Interdisciplinary center on Sustainable Agri-food systems (Social and nutritional sciences) - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - IRD - Institut de Recherche pour le Développement - CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement); Geoffroy Enjolras (UGA - Université Grenoble Alpes) |
| Abstract: | In a search of higher income and lower dependence on intermediaries in the food chain, family farms are increasingly adopting short food supply chains (SFSCs). The purpose of this paper is to investigate the role of farm entrepreneurs and their family in defining the implementation of SFSCs. We use the 2010 Exhaustive Agricultural Census of French farms and implement a logit model. The results underline the fact that young and educated farm entrepreneurs are more likely to promote SFSCs. The presence of the family on the farm as well as the involvement of family members play a key role in the choice of SFSCs. However, the marital status of a farm entrepreneur and the involvement of their spouse have no specific influence. This research sheds new light on the key role played by families in supporting productive and marketing strategies of farms. |
| Keywords: | family-run management, short food supply chains, farming |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04669456 |
| By: | Klein, Nicholas J. (Conrell University); Brown, Anne (University of Oregon); Howell, Amanda; Smart, Michael J. (Rutgers University) |
| Abstract: | How and why do zero-car households seek car access? We used a national online survey of 830 American adults and interviews with twenty-nine low- and moderate-income travelers about their car access behaviors to answer this question. We validated our findings with the 2017 National Household Travel Survey. Respondents got rides, borrowed cars, and used ride-hail to access grocery trips, social/recreational activities, and medical care. While most interviewees intend to purchase a vehicle in the future, they also desire better transit, suggesting that households without cars do not necessarily prefer car ownership. |
| Date: | 2024–09–13 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:4ngtr |
| By: | Koen Jochmans (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - 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 concerns the analysis of network data when unobserved node-specific heterogeneity is present. We postulate a weighted version of the classic stochastic block model, where nodes belong to one of a finite number of latent communities and the placement of edges between them and any weight assigned to these depend on the communities to which the nodes belong. A simple rank condition is presented under which we establish that the number of latent communities, their distribution, and the conditional distribution of edges and weights given community membership are all nonparametrically identified from knowledge of the joint (marginal) distribution of edges and weights in graphs of a fixed size. The identification argument is constructive and we present a computationally-attractive nonparametric estimator based on it. Limit theory is derived under asymptotics where we observe a growing number of independent networks of a fixed size. The results of a series of numerical experiments are reported on. |
| Keywords: | Heterogeneity, Network, Random graph, Sorting, Stochastic block model |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04672521 |
| By: | Yaojun Zhang; Lanpeng Ji; Georgios Aivaliotis; Charles C. Taylor |
| Abstract: | This paper proposes three types of Bayesian CART (or BCART) models for aggregate claim amount, namely, frequency-severity models, sequential models and joint models. We propose a general framework for the BCART models applicable to data with multivariate responses, which is particularly useful for the joint BCART models with a bivariate response: the number of claims and aggregate claim amount. To facilitate frequency-severity modeling, we investigate BCART models for the right-skewed and heavy-tailed claim severity data by using various distributions. We discover that the Weibull distribution is superior to gamma and lognormal distributions, due to its ability to capture different tail characteristics in tree models. Additionally, we find that sequential BCART models and joint BCART models, which incorporate dependence between the number of claims and average severity, are beneficial and thus preferable to the frequency-severity BCART models in which independence is assumed. The effectiveness of these models' performance is illustrated by carefully designed simulations and real insurance data. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2409.01908 |
| By: | Yuyu Chen; Seva Shneer |
| Abstract: | We introduce a class of super heavy-tailed distributions and establish the inequality that any weighted average of independent and identically distributed super heavy-tailed random variables stochastically dominates one such random variable. We show that many commonly used extremely heavy-tailed (i.e., infinite-mean) distributions, such as the Pareto, Fr\'echet, and Burr distributions, belong to the class of super heavy-tailed distributions. The established stochastic dominance relation is further generalized to allow negatively dependent or non-identically distributed random variables. In particular, the weighted average of non-identically distributed random variables stochastically dominates their distribution mixtures. Applications of these results in portfolio diversification, goods bundling, and inventory management are discussed. Remarkably, in the presence of super heavy-tailedness, the results that hold for finite-mean models in these applications are flipped. |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2408.15033 |
| By: | Zanoni, Wladimir; Duryea, Suzanne; Paredes, Jorge |
| Abstract: | In this study, we investigate the extent and mechanisms of gender-based discrimination in urban Ecuador's hiring practices, a critical issue for understanding persistent gender disparities and informing policy. Using an artifactual field experiment with 392 recruiters evaluating observationally equivalent male and female job candidates, we uncover a significant preference for female candidates. Our results show that women were preferred by a margin of 15%, despite equivalent productivity assessments between genders. This suggests that hiring decisions are influenced by factors beyond assessed productivity differentials. We hypothesize that social norms advocating for gender equality significantly drive these preferences, and demonstrate that the preference for women aligns with the observed trend of narrowing the employment gender gap in survey data. |
| Keywords: | Gender discrimination;Occupational Segregation;labor market;Stereotyping |
| JEL: | J16 J71 C93 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:13705 |
| By: | Kandhra, Diya; MacCurdy, Dwight; Lipman, Timothy PhD |
| Abstract: | To better understand inequities in EV charging costs, we compared charging costs at public EV DCFC stations to the cost for single-family housing (SFH) residents charging at home for three California electric utility service areas, the Sacramento Municipal Utility District (SMUD), San Diego Gas and Electric Company (SDG&E) and Pacific Gas and Electric Company (PG&E), and for three specific urban areas - Sacramento, San Diego, and San Jose. We used a combination of observed pricing data from PlugShare, a crowd-sourced database of public EV charging, and public DCFC pricing data from electric vehicle service provider (EVSP) websites, as well as electric utility tariff information from their respective websites. |
| Keywords: | Engineering |
| Date: | 2024–09–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsrrp:qt9dn2j441 |
| By: | Senst, Benjamin |
| Abstract: | For large organisations with numerous organisational units, it can be challenging to keep track of individual events. In a joint project by Data Science for Social Good Berlin e.V. and the Data Science Hub of the German Red Cross, social services were processed over several phases between summer 2022 and summer 2024 using new technologies such as web scraping, data engineering, and natural language processing, and their implementation in various user applications was tested. More than 600, 000 web documents were collected and more than 30, 000 offers were identified. The results of this automated method were compared with the existing data set. Web scraping and subsequent processing are suitable for at least supplementing the previous approach. Web scraping, NLP, and data engineering offer large organisations the opportunity to effectively gain an overview of local events. |
| Date: | 2024–09–06 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:3pd4s |
| By: | Zhaoxin Liu (Vrije Universiteit Amsterdam); Erik Ansink (Vrije Universiteit Amsterdam) |
| Abstract: | Reducing meat consumption has become a global policy target due to rising environmental, health, and animal welfare concerns. We provide novel evidence on how price change in real life affects grocery shopping behavior in the Netherlands. We focus on price-induced behavioral response among major meat categories (beef, pork, and poultry), fish, and the emerging product category of plant-based meat substitutes (PBMS). Our analysis is based on detailed weekly transaction data from approximately 1, 500 products in 884 stores from several retail chains between 2015 and 2018. The own- and cross-price elasticities are estimated via a Quadratic Almost Ideal Demand System model, where we instrument the endogenous prices by the average prices from nearby stores. Our results show that all animal products have inelastic own-price elasticities, except for pork (-2.1). PBMS have a significant positive own-price elasticity (1.52), which we explain by the increasing variety of high-quality PBMS products. We also show that PBMS are price complements for beef, poultry, and fish. This study contributes to the policy discussions on a carbon meat tax and the protein transition by providing key statistics on price elasticities. |
| Keywords: | Consumer demand, meat, fish, plant-based meat substitutes, price elasticity |
| JEL: | Q1 D1 D4 |
| Date: | 2024–07–11 |
| URL: | https://d.repec.org/n?u=RePEc:tin:wpaper:20240046 |
| By: | Sastry, Kartik; Taylor, David; Leamy, Michael |
| Abstract: | Electrification of the transportation sector provides the means to significantly reduce greenhouse gas emissions from internal combustion engine vehicles (ICEVs). However, for electric vehicles (EVs) to remain a viable alternative to ICEVs, solutions must be developed to meet the associated growth in power demand (for charging) without stressing the power distribution infrastructure. One potential solution to this challenge is to control the EV charging load through smart charging. The objectives of the proposed research effort are to (i) clearly define the smart charging problem, (ii) complete a comprehensive literature review, (iii) develop and document fundamental models needed to analyze EV charging and grid impact, and (iv) develop mathematical algorithms for solving the smart-charging problem defined in (i). View the NCST Project Webpage |
| Keywords: | Engineering, Physical Sciences and Mathematics, Electric vehicles, smart charging, convex optimization, grid impact |
| Date: | 2023–06–30 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt0v64f30n |
| By: | Moamar Sayed Mouchaweh; Amro Elshurafa (King Abdullah Petroleum Studies and Research Center) |
| Abstract: | The digitalization of power systems can contribute to a smoother energy transition by, for example, maximizing the use of renewable energy (RE; i.e., minimizing curtailment), peak shaving, and relaxing grid congestion. Collectively, these and other benefits play an important role in creating an affordable, sustainable, and reliable supply. |
| Date: | 2024–07–07 |
| URL: | https://d.repec.org/n?u=RePEc:prc:dpaper:ks--2024-dp24 |