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on Discrete Choice Models |
| By: | Benoit Chèze (IFPEN - IFP Energies nouvelles - IFPEN - IFP Energies nouvelles, EconomiX-CNRS, University of Paris); Charles Collet (CIRED-CNRS); Anthony Paris (EconomiX-CNRS, University of Paris, LEO - Laboratoire d'Économie d'Orleans - UO - Université d'Orléans - Université de Tours - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | This working paper overviews theoretical foundations and estimators derived from econometric models used to analyze stated choices proposed in Discrete Choice Experiment (DCE)surveys. Discrete Choice Modelling is adapted to the case where the variable to be explained is a qualitative variable which cannot be ranked in relation to each other. A situation which occurs in many cases in everyday life as people often have to choose only one alternative among a proposed set of different ones in many fields (early in the morning, just think about how you pick clothes for instance). DCE is a Stated Preference method in which preferences are elicited through repeated fictional choices, proposed to a sample of respondents. Compared to Revealed Preference methods, DCEs allow for an ex ante evaluation of public policies that do not yet exists. |
| Keywords: | Revealed preference theory,Stated Preference / Stated Choice methods,Discrete Choice Modelling,Discrete Choice Experiment |
| Date: | 2021–04–12 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03262187&r= |
| By: | Salma Khedr; Katrin Rehdanz; Roy Brouwer; Hanna Dijkstra; Sem Duijndam; Pieter van Beukering; Ikechukwu C. Okoli |
| Abstract: | Plastic pollution is one of the most challenging problems affecting the marine environment of our time. Based on a unique dataset covering four European seas and eight European countries, this paper adds to the limited empirical evidence base related to the societal welfare effects of marine litter management. We use a discrete choice experiment to elicit public willingness-to-pay (WTP) for macro and micro plastic removal to achieve Good Environmental Status across European seas as required by the European Marine Strategy Framework Directive. Using a common valuation design and following best-practice guidelines, we draw meaningful comparisons between countries, seas and policy contexts. European citizens have strong preferences to improve the environmental status of the marine environment by removing both micro and macro plastic litter favouring a pan-European approach. However, public WTP estimates differ significantly across European countries and seas. We explain why and discuss implications for policymaking. |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2107.03957&r= |
| By: | Levon Barseghyan (Institute for Fiscal Studies); Francesca Molinari (Institute for Fiscal Studies and Cornell University); Matthew Thirkettle (Institute for Fiscal Studies) |
| Abstract: | This paper is concerned with learning decision makers’ preferences using data on observed choices from a ?nite set of risky alternatives. We propose a discrete choice model with unobserved heterogeneity in consideration sets and in standard risk aversion. We obtain su?cient conditions for the model’s semi-nonparametric point identi?cation, including in cases where consideration depends on preferences and on some of the exogenous variables. Our method yields an estimator that is easy to compute and is applicable in markets with large choice sets. We illustrate its properties using a dataset on property insurance purchases. |
| Date: | 2020–06–24 |
| URL: | http://d.repec.org/n?u=RePEc:ifs:cemmap:28/20&r= |
| By: | Victor Aguirregabiria; Jesus Carro |
| Abstract: | In nonlinear panel data models, fixed effects methods are often criticized because they cannot identify average marginal effects (AMEs) in short panels. The common argument is that the identification of AMEs requires knowledge of the distribution of unobserved heterogeneity, but this distribution is not identified in a fixed effects model with a short panel. In this paper, we derive identification results that contradict this argument. In a panel data dynamic logic model, and for T as small as four, we prove the point identification of different AMEs, including causal effects of changes in the lagged dependent variable or in the duration in last choice. Our proofs are constructive and provide simple closed-form expressions for the AMEs in terms of probabilities of choice histories. We illustrate our results using Monte Carlo experiments and with an empirical application of a dynamic structural model of consumer brand choice with state dependence. |
| Keywords: | Identification; Average marginal effects; Fixed effects models; Panel data; Dynamic discrete choice; State dependence; Dynamic demand of differentiated products |
| JEL: | C23 C25 C51 |
| Date: | 2021–07–08 |
| URL: | http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-701&r= |
| By: | Victor Aguirregabiria; Jesus M. Carro |
| Abstract: | In nonlinear panel data models, fixed effects methods are often criticized because they cannot identify average marginal effects (AMEs) in short panels. The common argument is that the identification of AMEs requires knowledge of the distribution of unobserved heterogeneity, but this distribution is not identified in a fixed effects model with a short panel. In this paper, we derive identification results that contradict this argument. In a panel data dynamic logic model, and for T as small as four, we prove the point identification of different AMEs, including causal effects of changes in the lagged dependent variable or in the duration in last choice. Our proofs are constructive and provide simple closed-form expressions for the AMEs in terms of probabilities of choice histories. We illustrate our results using Monte Carlo experiments and with an empirical application of a dynamic structural model of consumer brand choice with state dependence. |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2107.06141&r= |
| By: | Prateek Bansal; Roselinde Kessels; Rico Krueger; Daniel J Graham |
| Abstract: | The COVID-19 pandemic has drastically impacted people's travel behaviour and out-of-home activity participation. While countermeasures are being eased with increasing vaccination rates, the demand for public transport remains uncertain. To investigate user preferences to travel by London Underground during the pandemic, we conducted a stated choice experiment among its pre-pandemic users (N=961). We analysed the collected data using multinomial and mixed logit models. Our analysis provides insights into the sensitivity of the demand for the London Underground with respect to travel attributes (crowding density and travel time), the epidemic situation (confirmed new COVID-19 cases), and interventions (vaccination rates and mandatory face masks). Mandatory face masks and higher vaccination rates are the top two drivers of travel demand for the London Underground during COVID-19. The positive impact of vaccination rates on the Underground demand increases with crowding density, and the positive effect of mandatory face masks decreases with travel time. Mixed logit reveals substantial preference heterogeneity. For instance, while the average effect of mandatory face masks is positive, preferences of around 20% of the pre-pandemic users to travel by the Underground are negatively affected. The estimated demand sensitivities are relevant for supply-demand management in transit systems and the calibration of advanced epidemiological models. |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2107.02394&r= |
| By: | Poulissen, Davey (RS: GSBE other - not theme-related research, ROA / Health, skills and inequality); de Grip, Andries (ROA / Health, skills and inequality, RS: GSBE Theme Learning and Work, RS: SBE - MACIMIDE); Fouarge, Didier (RS: GSBE Theme Learning and Work, RS: GSBE Theme Data-Driven Decision-Making, ROA / Labour market and training); Künn, Annemarie (RS: GSBE Theme Learning and Work, ROA / Labour market and training) |
| Abstract: | Various studies have shown that temporary workers participate less in training than those on permanent contracts. Human resources practices are considered to be an important explanation for this difference. We develop a theoretical framework for employers’ provision of training that explicitly incorporates the costs and benefits associated with training investments in employees with different types of employment contracts. Our framework not only predicts employers to be less willing to invest in temporary workers due to the shorter time horizon associated with such an investment, but it also provides insights into how this willingness depends on characteristics of the training that are related to the expected costs and benefits of the training investment. A discrete choice experiment is used to empirically test the predictions from our theoretical framework. In line with our theoretical framework, we find that employers are less likely to invest in the training of temporary workers. This particularly holds when temporary workers do not have the prospect of a permanent contract with their current employer. Furthermore, we show that employers’ likelihood of investing in temporary workers indeed depends on aspects related to the costs and benefits of training, that is, a financial contribution to the training costs made by employees, a repayment agreement that applies when workers leave the organisation prematurely, and the transferability of the skills being trained. Our findings can be used to increase employers’ willingness to invest in temporary workers. However, similar effects are observed when looking at employers’ willingness to invest in permanent workers, suggesting that it will be difficult to decrease the gap in employers’ willingness to invest between temporary and permanent workers. |
| JEL: | J24 J41 J62 |
| Date: | 2021–05–27 |
| URL: | http://d.repec.org/n?u=RePEc:unm:umaror:2021003&r= |
| By: | Bo E. Honoré (Institute for Fiscal Studies and Princeton); Martin Weidner (Institute for Fiscal Studies and cemmap and UCL) |
| Abstract: | This paper builds on Bonhomme (2012) to develop a method to systematically construct moment conditions for dynamic panel data logit models with fixed effects. After introducing the moment conditions obtained in this way, we explore their implications for identification and estimation of the model parameters that are common to all individuals, and we find that those common model parameters are estimable at root-n rate for many more dynamic panel logit models than has been appreciated by the existing literature. In the case where the model contains one lagged variable, the moment conditions in Kitazawa (2013, 2016) are transformations of a subset of ours. A GMM estimator that is based on the moment conditions is shown to perform well in Monte Carlo simulations and in an empirical illustration to labor force participation. |
| Date: | 2020–07–09 |
| URL: | http://d.repec.org/n?u=RePEc:ifs:cemmap:38/20&r= |
| By: | Andrew Chesher (Institute for Fiscal Studies and University College London); Adam Rosen (Institute for Fiscal Studies and Duke University) |
| Abstract: | This paper demonstrates the use of bounds analysis for empirical models of market structure that allow for multiple equilibria. From an econometric standpoint, these models feature systems of equalities and inequalities for the determination of multiple endogenous interdependent discrete choice variables. These models may be incomplete, delivering multiple values of outcomes at certain values of the latent variables and covariates, and incoherent, delivering no values. Alternative approaches to accommodating incompleteness and incoherence are considered in a unifying framework afforded by the Generalized Instrumental Variable models introduced in Chesher and Rosen (2017). Sharp identication regions for parameters of interest defined by systems of conditional moment equalities and inequalities are provided. Almost all empirical analysis of interdependent discrete choice uses models that include parametric specifications of the distribution of unobserved variables. The paper provides characterizations of identified sets and outer regions for structural functions and parameters allowing for any distribution of unobservables independent of exogenous variables. The methods are applied to the models and data of Mazzeo (2002) and Kline and Tamer (2016) in order to study the sensitivity of empirical results to restrictions on equilibrium selection and the distribution of unobservable payoff shifters, respectively. Confidence intervals for individual parameter components are provided using a recently developed inference approach from Belloni, Bugni, and Chernozhukov (2018). The relaxation of equilibrium selection and distributional restrictions in these applications is found to greatly increase the width of resulting confidence intervals, but nonetheless the models continue to sign strategic interaction parameters. |
| Date: | 2020–06–01 |
| URL: | http://d.repec.org/n?u=RePEc:ifs:cemmap:25/20&r= |
| By: | Eunjung Cho; Youngsang Cho |
| Abstract: | Global concern regarding ultrafine particles (UFPs), which are particulate matter (PM) with a diameter of less than 100nm, is increasing. These particles-with more serious health effects than PM less than 2.5 micrometers (PM2.5)-are difficult to measure using the current methods because their characteristics are different from those of other air pollutants. Therefore, a new monitoring system is required to obtain accurate UFPs information, which will raise the financial burden of the government and people. In this study, we estimated the economic value of UFPs information by evaluating the willingness-to-pay (WTP) for the UFPs monitoring and reporting system. We used the contingent valuation method (CVM) and the one-and-one-half-bounded dichotomous choice (OOHBDC) spike model. We analyzed how the respondents' socio-economic variables, as well as their cognition level of PM, affected their WTP. Therefore, we collected WTP data of 1,040 Korean respondents through an online survey. The estimated mean WTP for building a UFPs monitoring and reporting system is KRW 6,958.55-7,222.55 (USD 6.22-6.45) per household per year. We found that people satisfied with the current air pollutant information, and generally possessing relatively greater knowledge of UFPs, have higher WTP for a UFPs monitoring and reporting system. The results can be used to establish new policies response to PM including UFPs. |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2107.03034&r= |
| By: | Stéphane Bonhomme (Institute for Fiscal Studies and University of Chicago); Martin Weidner (Institute for Fiscal Studies and cemmap and UCL) |
| Abstract: | Economists are often interested in estimating averages with respect to distributions of unobservables. Examples are moments of individual fixed-effects, average partial effects in discrete choice models, and counterfactual simulations in structural models. For such quantities, we propose and study posterior average effects (PAE), where the average is computed conditional on the sample, in the spirit of empirical Bayes and shrinkage methods. While the usefulness of shrinkage for prediction is well-understood, a justification of posterior conditioning to estimate population averages is currently lacking. We show that PAE have minimum worst-case bias under local misspecification of the parametric distribution of unobservables. This provides a rationale for reporting these estimators in applications. We introduce a measure of informativeness of the posterior conditioning, which quantifies the bias of PAE relative to parametric model-based estimators, and we study other robustness properties of PAE for estimation and prediction. As illustrations, we report PAE estimates of distributions of neighborhood effects in the US, and of permanent and transitory components in a model of income dynamics. |
| Date: | 2020–10–09 |
| URL: | http://d.repec.org/n?u=RePEc:ifs:cemmap:49/20&r= |
| By: | Philipp Strack; Dmitry Taubinsky |
| Abstract: | We study identification of time inconsistency when an agent at time 0 makes an advance commitment, and later at time 1 can revise their choice after possibly receiving additional information. Roughly speaking, we prove that the only data that reject time-consistent expected utility maximization is a time-0 choice that is always strictly dominated at time 1. This holds for rich choice sets; if the complete ranking of alternatives is observed in every period and state; when it is natural to assume additional properties like concavity; and with supplementary cardinal information. However, time inconsistency can be point identified from willingness to pay for different alternatives in both periods, if utility from money is plausibly additively-separable and independent of time-1 information. |
| JEL: | C9 D0 D9 |
| Date: | 2021–06 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:28961&r= |
| By: | Raffaella Giacomini (Institute for Fiscal Studies and cemmap and UCL); Toru Kitagawa (Institute for Fiscal Studies and cemmap and University College London); Alessio Volpicella (Institute for Fiscal Studies and Queen Mary University of London) |
| Abstract: | Uncertainty about the choice of identifying assumptions is common in causal studies, but is often ignored in empirical practice. This paper considers uncertainty over models that impose different identifying assumptions, which, in general, leads to a mix of point- and set-identified models. We propose performing inference in the presence of such uncertainty by generalizing Bayesian model averaging. The method considers multiple posteriors for the set-identified models and combines them with a single posterior for models that are either point-identified or that impose non-dogmatic assumptions. The output is a set of posteriors (post-averaging ambiguous belief) that are mixtures of the single posterior and any element of the class of multiple posteriors, with weights equal to the posterior model probabilities. We suggest reporting the set of posterior means and the associated credible region in practice, and provide a simple algorithm to compute them. We establish that the prior model probabilities are updated when the models are ``distinguishable" and/or they specify different priors for reduced-form parameters, and characterize the asymptotic behavior of the posterior model probabilities. The method provides a formal framework for conducting sensitivity analysis of empirical findings to the choice of identifying assumptions. In a standard monetary model, for example, we show that, in order to support a negative response of output to a contractionary monetary policy shock, one would need to attach a prior probability greater than 0.05 to the validity of the assumption that prices do not react contemporaneously to the shock. The method is general and allows for dogmatic and non-dogmatic identifying assumptions, multiple point-identified models, multiple set-identified models, and nested or non-nested models. |
| Date: | 2020–07–06 |
| URL: | http://d.repec.org/n?u=RePEc:ifs:cemmap:33/20&r= |
| By: | Julian Hinz (Bielefeld University, Kiel Institute for the World Economy, Kiel Centre for Globalization); Amrei Stammann (Ruhr-University Bochum); Joschka Wanner (University of Potsdam, Kiel Institute for the World Economy) |
| Abstract: | We study the role and drivers of persistence in the extensive margin of bilateral trade. Motivated by a stylized heterogeneous firms model of international trade with market entry costs, we consider dynamic three-way fixed effects binary choice models and study the corresponding incidental parameter problem. The standard maximum likelihood estimator is consistent under asymptotics where all panel dimensions grow at a constant rate, but it has an asymptotic bias in its limiting distribution, invalidating inference even in situations where the bias appears to be small. Thus, we propose two different bias-corrected estimators. Monte Carlo simulations confirm their desirable statistical properties. We apply these estimators in a reassessment of the most commonly studied determinants of the extensive margin of trade. Both true state dependence and unobserved heterogeneity contribute considerably to trade persistence and taking this persistence into account matters significantly in identifying the effects of trade policies on the extensive margin. |
| Keywords: | dynamic binary choice, extensive margin, high-dimensional fixed effects, incidental parameter bias correction, trade policy |
| JEL: | C13 C23 C55 F14 F15 |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:pot:cepadp:36&r= |