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on Discrete Choice Models |
| By: | Selim Mankaï (IAE - UCA - Institut d'Administration des Entreprises - Clermont-Auvergne - UCA - Université Clermont Auvergne, UCA - Université Clermont Auvergne); Sébastien Marchand (CERDI - Centre d'Études et de Recherches sur le Développement International - IRD - Institut de Recherche pour le Développement - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne, UCA - Université Clermont Auvergne); Ngoc Ha Le (UCA - Université Clermont Auvergne) |
| Abstract: | The demand for voluntary insurance against low-probability, high-impact risks is lower than expected. To assess the magnitude of the demand, we conduct a meta-analysis of contingent valuation studies using a dataset of experimentally elicited and survey-based estimates. We find that the average stated willingness to pay (WTP) for insurance is 87% of expected losses. We perform a meta-regression analysis to examine the heterogeneity in aggregate WTP across these studies. The meta-regression reveals that information about loss probability and probability levels positively influence relative willingness to pay, whereas respondents' average income and age have a negative effect. Moreover, we identify cultural sub-factors, such as power distance and uncertainty avoidance, that provided additional explanations for differences in WTP across international samples. Methodological factors related to the sampling and data collection process significantly influence the stated WTP. Our results, robust to model specification and publication bias, are relevant to current debates on stated preferences for low-probability risks management. |
| Abstract: | La demande d'assurance volontaire contre les risques à faible probabilité et à fort impact est plus faible que prévu. Pour l'ampleur de la demande, nous effectuons une méta-analyse des études d'évaluation contingente à l'aide d'un d'estimations obtenues expérimentalement et basées sur des enquêtes. Nous constatons que le consentement à payer (CAP) moyen déclaré à payer (CAP) pour l'assurance est de 87 % des pertes attendues. Nous effectuons une analyse de méta-régression pour examiner l'hétérogénéité de la volonté de payer globale dans ces études. La méta-régression révèle que les informations sur la probabilité des pertes et les niveaux de probabilité influencent positivement la volonté relative de payer, tandis que le revenu moyen et l'âge des personnes interrogées ont un effet positif sur la volonté de payer. le revenu moyen et l'âge des répondants ont un effet négatif. En outre, nous identifions des sous-facteurs culturels, tels que la distance de pouvoir et l'évitement de l'incertitude, qui ont fourni des explications supplémentaires pour les différences de consentement à payer entre les échantillons internationaux. de la volonté de payer dans les échantillons internationaux. Les facteurs méthodologiques liés à l'échantillonnage et à la collecte des données d'échantillonnage et de collecte des données influencent de manière significative le CAP déclaré. Nos résultats, robustes à la spécification du modèle et au biais de publication, sont pertinents pour les débats actuels sur l'acceptation de paiement. de publication, sont pertinents pour les débats actuels sur les préférences déclarées en matière de gestion des risques à faible probabilité. |
| Keywords: | Low probability risks, Contingent valuation, Insurance demand, Stated preferences method, Metaanalysis, Economic experiments |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-04474880&r=dcm |
| By: | Nobuo Koida; Koji Shirai |
| Abstract: | This paper develops a novel characterization for random utility models (RUM), which turns out to be a dual representation of the characterization by Kitamura and Stoye (2018, ECMA). For a given family of budgets and its "patch" representation \'a la Kitamura and Stoye, we construct a matrix $\Xi$ of which each row vector indicates the structure of possible revealed preference relations in each subfamily of budgets. Then, it is shown that a stochastic demand system on the patches of budget lines, say $\pi$, is consistent with a RUM, if and only if $\Xi\pi \geq \mathbb{1}$. In addition to providing a concise closed form characterization, especially when $\pi$ is inconsistent with RUMs, the vector $\Xi\pi$ also contains information concerning (1) sub-families of budgets in which cyclical choices must occur with positive probabilities, and (2) the maximal possible weights on rational choice patterns in a population. The notion of Chv\'atal rank of polytopes and the duality theorem in linear programming play key roles to obtain these results. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.04328&r=dcm |
| By: | Christopher Roth (University of Cologne); Peter Schwardmann (Carnegie Mellon University); Egon Tripodi (Hertie School) |
| Abstract: | While psychotherapy has been shown to be effective in treating depression, take-up remains low. In a sample of 1, 843 depressed individuals, we document that effectiveness concerns are top-of-mind when respondents consider the value of therapy. We then show that the average respondent underestimates the effectiveness of therapy and that an information treatment correcting this misperception increases participants’ incentivized willingness to pay for therapy. Information affects therapy demand by changing beliefs rather than by shifting attention. Our results suggest that information interventions that target the perceived effectiveness of therapy are a potent tool in combating the ongoing mental health crisis. |
| Keywords: | mental health; depression; psychotherapy; beliefs; effectiveness; information policy; |
| Date: | 2024–03–24 |
| URL: | http://d.repec.org/n?u=RePEc:rco:dpaper:500&r=dcm |
| By: | Victor Chernozhukov; Iv\'an Fern\'andez-Val; Sukjin Han; Kaspar W\"uthrich |
| Abstract: | We propose an instrumental variable framework for identifying and estimating average and quantile effects of discrete and continuous treatments with binary instruments. The basis of our approach is a local copula representation of the joint distribution of the potential outcomes and unobservables determining treatment assignment. This representation allows us to introduce an identifying assumption, so-called copula invariance, that restricts the local dependence of the copula with respect to the treatment propensity. We show that copula invariance identifies treatment effects for the entire population and other subpopulations such as the treated. The identification results are constructive and lead to straightforward semiparametric estimation procedures based on distribution regression. An application to the effect of sleep on well-being uncovers interesting patterns of heterogeneity. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.05850&r=dcm |
| By: | Choi, S.; Goyal, S.; Guo, F.; Moisan, F. |
| Abstract: | Social interactions shape individual behaviour and public policy increasingly uses networks to improve effectiveness. It is therefore important to understand if the theoretical predictions on the relation between networks and individual choice are empirically valid. This paper tests a key result in the theory of games on networks: an individual’s action is proportional to their (Bonacich) centrality. Our experiment shows that individual efforts increase in centrality but at a rate of increase that is lower than the theoretical prediction. Moreover, efforts are higher than predicted in some cases and lower than predicted in other cases. These departures from equilibrium have large effects on individual earnings. We propose a model of network based imitation decision rule to explain these deviations. |
| JEL: | C92 D83 D85 Z13 |
| Date: | 2024–01–16 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:2401&r=dcm |
| By: | Patrick Lloyd-Smith (University of Saskatchewan, Department of Agricultural and Resource Economics); Ewa Zawojska |
| Abstract: | Economic analysis of environmental policy projects typically use pre-existing welfare estimates that are then transferred over time to the policy relevant periods. Understanding how stable and predictable these welfare estimates are over time is important for applying these estimates in policy. Yet, revealed preference models of recreation demand have received few temporal stability assessments compared to other non-market valuation methods. We use a large administrative dataset on campground reservations covering ten years to study temporal stability and predictability of recreation demand welfare estimates of lake water quality changes. Based on single-year models, our findings suggest welfare estimates are temporally stable across years in around 50% of the comparisons. Using an event study design, we find evidence that welfare estimates are stable within a year, that is, for weeks after a change in water quality. Our findings further reveal that having two years of data for predicting welfare estimates in subsequent years improves the prediction accuracy by 22% relative to using a single year of data, but further improvements in the prediction accuracy are modest when including additional years of data. Predictions of welfare estimates are not necessarily improved when using data closer in time to the prediction year. We discuss the implications of our results for using revealed preference studies in policy analysis. |
| Keywords: | recreation demand, revealed preferences, temporal stability, prediction accuracy, water quality, welfare estimates |
| JEL: | H41 Q26 Q51 Q53 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:war:wpaper:2024-05&r=dcm |
| By: | Tomohito Aoyama; Nobuyuki Hanaki |
| Abstract: | The random incentive system (RIS) is a standard incentive scheme used to elicit preferences in economic experiments. However, it has been speculated that RIS may not be incentive compatible when participants are concerned about ambiguity, i.e., that the choices observed under RIS do not reflect the underlying preferences. To examine the performance of RIS under ambiguity, we conducted three experiments online and in a laboratory. The results of the experiments suggest that RIS is incentive compatible. We argue that presenting choice situations in isolation may improve the incentive compatibility of RIS. We also argue that using RIS, together with an experimental guideline called Prince, may reduce the observed ambiguity aversion. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:dpr:wpaper:1236&r=dcm |
| By: | Maes, Sebastiaan (University of Antwerp); Malhotra, Raghav (University of Leicester) |
| Abstract: | Welfare e ects of price changes are often estimated with cross-sections ; these do not identify demand with heterogeneous consumers. We develop a theoretical method addressing this, utilizing uncompensated demand moments to construct local approximations for compensated demand moments, robust to unobserved preference heterogeneity. Our methodological contribution offers robust approximations for average and distributional welfare estimates, extending to price indices, taxable income elasticities, and general equilibrium welfare. Our methods apply to any cross-section; we demonstrate them via UK household budget survey data. We uncover an insight: simple non-parametric representative agent models might be less biased than complex parametric models accounting for heterogeneity. |
| Keywords: | nonparametric welfare analysis ; individual heterogeneity ; Hicksian demand ; compensating variation ; exact consumer surplus ; deadweight loss ; price indices JEL codes: C14 ; C31 ; D11 ; D12 ; D63 ; H22 ; I31 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:wrk:wcreta:84&r=dcm |
| By: | Enzo Brox; Riccardo Di Francesco |
| Abstract: | The fear of social stigma and discrimination leads many individuals worldwide to hesitate in openly disclosing their sexual orientation. Due to the large costs of concealing identity, it is crucial to understand the extent of anti-LGB sentiments and reactions to coming out. However, disclosing one's sexual orientation is a personal choice, complicating data access and introducing endogeneity issues. This paper tackles these challenges by using an innovative data source from a popular online video game together with a natural experiment. We exploit exogenous variation in the identity of a playable character to identify the effects of disclosure on players' revealed preferences for that character. Leveraging detailed daily data, we monitor players' preferences for the character across diverse regions globally and employ synthetic control methods to isolate the effect of the disclosure on players' preferences. Our findings reveal a substantial and persistent negative impact of coming out. To strengthen the plausibility of social stigma as the primary explanation for the estimated effects, we systematically address and eliminate several alternative game-related channels. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.03649&r=dcm |
| By: | Jiawei Fu |
| Abstract: | Understanding causal mechanisms is essential for explaining and generalizing empirical phenomena. Causal mediation analysis offers statistical techniques to quantify mediation effects. However, existing methods typically require strong identification assumptions or sophisticated research designs. We develop a new identification strategy that simplifies these assumptions, enabling the simultaneous estimation of causal and mediation effects. The strategy is based on a novel decomposition of total treatment effects, which transforms the challenging mediation problem into a simple linear regression problem. The new method establishes a new link between causal mediation and causal moderation. We discuss several research designs and estimators to increase the usability of our identification strategy for a variety of empirical studies. We demonstrate the application of our method by estimating the causal mediation effect in experiments concerning common pool resource governance and voting information. Additionally, we have created statistical software to facilitate the implementation of our method. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.04131&r=dcm |
| By: | Malani, Anup (University of Chicago); Kinnan, Cynthia (NBER); Conti, Gabriella (University College London); Imai, Kosuke (Harvard University); Miller, Morgen (University of Chicago); Swaminathan, Shailender (Sai University); Voena, Alessandra (Stanford University); Woda, Bartosz (Amazon) |
| Abstract: | Universal health coverage is a widely shared goal across lower-income countries. We conducted a large-scale, 4-year trial that randomized premiums and subsidies for India's first national, public hospital insurance program, RSBY. We find roughly 60% uptake even when consumers were charged premiums equal to the government's cost for insurance. We also find substantial adverse selection into insurance at positive prices. Insurance enrollment increases insurance utilization, partly due to spillovers from use of insurance by neighbors. However, many enrollees attempted to use insurance but failed, suggesting that learning is critical to the success of public insurance. We find very few statistically significant impacts of insurance access or enrollment on health. Because there is substantial willingness-to-pay for insurance, and given how distortionary it is to raise revenue in the Indian context, we calculate that our sample population should be charged a premium for RSBY between INR 500-1000 rather than a zero premium to maximize the marginal value of public funds. |
| Keywords: | health insurance, adverse selection, spillovers, marginal value of public funds |
| JEL: | D1 I13 |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16861&r=dcm |