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on Discrete Choice Models |
| By: | Benoit Chèze (ECO-PUB - Economie Publique - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, IFPEN - IFP Energies nouvelles - IFPEN - IFP Energies nouvelles, EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique); Maia David (ECO-PUB - Economie Publique - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Vincent Martinet (ECO-PUB - Economie Publique - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | Despite reducing the use of pesticides being a major challenge in developed countries, dedicated agri-environmental policies have not yet proven successful in doing so. We analyze conventional farmers' willingness to reduce their use of synthetic pesticides. To do so, we conduct a discrete choice experiment that includes the risk of large production losses due to pests. Our results indicate that this risk strongly limits farmers' willingness to change their practices, regardless of the consequences on average profit. Furthermore, the administrative burden has a significant effect on farmers' decisions. Reducing the negative health and environmental impacts of pesticides is a significant motivator only when respondents believe that pesticides affect the environment. Farmers who earn revenue from outside their farms and/or believe that yields can be maintained while reducing the use of pesticides are significantly more willing to adopt low-pesticide practices. Policy recommendations are derived from our results. |
| Keywords: | Pesticides,Agricultural practices,Production risk,Discrete choice experiment |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03192158&r=all |
| By: | Tommaso M. Valletti; André Veiga |
| Abstract: | We conduct an experiment where subjects read online news articles and are shown ads for brands next to those articles. Using eye-tracking technology, we measure the attention that each individual devotes to each article and ad. Then, respondents choose between cash or vouchers for the brands advertised. Attention to ads is a predictor both of willingness-to-pay for brands, and brand recall. The main predictors of attention include the type of news and the match between individual political preferences and the media outlet. |
| Keywords: | online-advertising, experiments, attention, e-commerce, targeting |
| JEL: | M37 C91 L86 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_8991&r=all |
| By: | Francesco Cerigioni; Simone Galperti |
| Abstract: | Consistent evidence from various settings shows that individual decisions can depend on the order or emphasis used when presenting the attributes of available options. We introduce a model of such framing effects, which we characterize in terms of observable behavior. We show how strategic use of attribute framing affects competition in markets and outcomes of negotiations. In our framework, attribute framing can also cause choice to depend on the order in which options are listed and phenomena similar to the endowment effect. Finally, we use the model to discuss several approaches to welfare analysis. |
| Keywords: | Attribute, Framing, order, multi-attribute choice, primacy, recency, emphasis, salience |
| JEL: | D01 D11 D90 |
| Date: | 2021–04 |
| URL: | http://d.repec.org/n?u=RePEc:upf:upfgen:1775&r=all |
| By: | Francesco Cerigioni; Simone Galperti |
| Abstract: | Consistent evidence from various settings shows that individual decisions can depend on the order or emphasis used when presenting the attributes of available options. We introduce a model of such framing effects, which we characterize in terms of observable behavior. We show how strategic use of attribute framing affects competition in markets and outcomes of negotiations. In our framework, attribute framing can also cause choice to depend on the order in which options are listed and phenomena similar to the endowment effect. Finally, we use the model to discuss several approaches to welfare analysis. |
| Keywords: | attribute, Framing, order, multi-attribute choice, primacy, recency, emphasis, salience |
| JEL: | D01 D11 D90 |
| Date: | 2021–04 |
| URL: | http://d.repec.org/n?u=RePEc:bge:wpaper:1247&r=all |
| By: | Louise Laage (Department of Economics, Georgetown University) |
| Abstract: | This paper studies a class of linear panel models with random coefficients. We do not restrict the joint distribution of the time-invariant unobserved heterogeneity and the covariates. We investigate identification of the average partial effect (APE) when fixed-effect techniques cannot be used to control for the correlation between the regressors and the time-varying disturbances. Relying on control variables, we develop a constructive two-step identification argument. The first step identifies nonparametrically the conditional expectation of the disturbances given the regressors and the control variables, and the second step uses "between-group" variations, correcting for endogeneity, to identify the APE. We propose a natural semiparametric estimator of the APE, show its square root n asymptotic normality and compute its asymptotic variance. The estimator is computationally easy to implement, and Monte Carlo simulations show favorable finite sample properties. Control variables arise in various economic and econometric models, and we provide variations of our argument to obtain identification in some applications. As an empirical illustration, we estimate the average elasticity of intertemporal substitution in a labor supply model with random coefficients. Classification- C23, C26 |
| Keywords: | Panel Data, Random Coefficients, Endogeneity, Control Variables, Nonparametric Identification |
| Date: | 2021–03–23 |
| URL: | http://d.repec.org/n?u=RePEc:geo:guwopa:gueconwpa~21-21-10&r=all |
| By: | Markus Dertwinkel-Kalt (University of Konstanz); Holger Gerhardt (UniversityofBonn); Gerhard Riener (Heinrich Heine University Düsseldorf); Frederik Schwerter (University of Cologne); Louis Strang (University of Cologne) |
| Abstract: | Many intertemporal trade-offs are unbalanced: while the advantages of options are concen- trated in a few periods, the disadvantages are dispersed over numerous periods. We provide novel experimental evidence for “concentration bias”, the tendency to overweight advantages that are concentrated in time. Subjects commit to too much overtime work that is dispersed over multiple days in exchange for a bonus that is concentrated in time: concentration bias increases subjects’ willingness to work by 22.4% beyond what standard discounting models could account for. In additional conditions and a complementary experiment involving mon- etary payments, we study the mechanisms behind concentration bias and demonstrate the robustness of our findings. |
| Keywords: | Attention, Focusing, Bounded rationality, Intertemporal choice, Future bias, Present bias, Framing |
| JEL: | D01 |
| Date: | 2021–04 |
| URL: | http://d.repec.org/n?u=RePEc:ajk:ajkdps:076&r=all |
| By: | Charles-Cadogan, G. (University of Leicester) |
| Abstract: | Under Bruno De Finetti’s coherence theory of additive probability, the expected value of a sequence of mutually exclusive bets should not expose the bettor to certain loss for any of the bets in the sequence (i.e. no formation of Dutch books). However, decision makers (DMs) are known to have non-additive probability preferences represented in the frequency domain. This conundrum of choice implies that DMs are incoherent. If so, then preference reversal (PR) is more likely to occur. That is, DMs response to choice and valuation procedures (with similar expected value) are more likely to be dissimilar or their preferences may appear to be intransitive. We prove that even when the true states of choice experiments are procedure invariance and transitive preferences, PR will still be observed because of : (1) phase incoherence between paired gambles with the same expected value–when probability cycles are incomplete, and (2) experimenter interference in probability measurement. We introduce a utility coherence ratio for paired gambles, and estimates from simulated phase transition from incoherent states to coherent states in binary choice to illustrate the theory. We find that coherence measures are very sensitive to measurement error, coherent states have higher frequency phase transition, and incoherent states represent momentary lapse in judgment that eventually disappear. So, Dutch books and PR are prevented. |
| Keywords: | preference reversal ; transitivity axiom ; probability phase incoherence ; wavelets ; probability weighting JEL codes: C00 ; C02 ; C44 ; D03 ; D81 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:wrk:wcreta:69&r=all |
| By: | Christopher Dobronyi; Jiaying Gu; Kyoo il Kim |
| Abstract: | We show that the identification problem for a class of dynamic panel logit models with fixed effects has a connection to the truncated moment problem in mathematics. We use this connection to show that the sharp identified set of the structural parameters is characterized by a set of moment equality and inequality conditions. This result provides sharp bounds in models where moment equality conditions do not exist or do not point identify the parameters. We also show that the sharp identifying content of the non-parametric latent distribution of the fixed effects is characterized by a vector of its generalized moments, and that the number of moments grows linearly in T. This final result lets us point identify, or sharply bound, specific classes of functionals, without solving an optimization problem with respect to the latent distribution. |
| Date: | 2021–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2104.04590&r=all |
| By: | Przemys{\l}aw Biecek; Marcin Chlebus; Janusz Gajda; Alicja Gosiewska; Anna Kozak; Dominik Ogonowski; Jakub Sztachelski; Piotr Wojewnik |
| Abstract: | Rapid development of advanced modelling techniques gives an opportunity to develop tools that are more and more accurate. However as usually, everything comes with a price and in this case, the price to pay is to loose interpretability of a model while gaining on its accuracy and precision. For managers to control and effectively manage credit risk and for regulators to be convinced with model quality the price to pay is too high. In this paper, we show how to take credit scoring analytics in to the next level, namely we present comparison of various predictive models (logistic regression, logistic regression with weight of evidence transformations and modern artificial intelligence algorithms) and show that advanced tree based models give best results in prediction of client default. What is even more important and valuable we also show how to boost advanced models using techniques which allow to interpret them and made them more accessible for credit risk practitioners, resolving the crucial obstacle in widespread deployment of more complex, 'black box' models like random forests, gradient boosted or extreme gradient boosted trees. All this will be shown on the large dataset obtained from the Polish Credit Bureau to which all the banks and most of the lending companies in the country do report the credit files. In this paper the data from lending companies were used. The paper then compares state of the art best practices in credit risk modelling with new advanced modern statistical tools boosted by the latest developments in the field of interpretability and explainability of artificial intelligence algorithms. We believe that this is a valuable contribution when it comes to presentation of different modelling tools but what is even more important it is showing which methods might be used to get insight and understanding of AI methods in credit risk context. |
| Date: | 2021–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2104.06735&r=all |
| By: | Raisa Sherif |
| Abstract: | This paper uses a ï¬ eld experiment among adolescents in India to study how interventions to increase one pro-environment activity (namely, recycling single-use plastic carry bags), spill over to other pro-environment activities. I show using lab and ï¬ eld experiments combined with survey data that (i) providing information on the need to recycle does not change recycling behaviour, whereas (ii) providing incentives along with the information leads to higher recycling. There is a positive spillover from the incentive treatment to other pro-environment activities. This positive spillover is observed among subjects who respond to the incentives and increase recycling. Notably, the positive spillover is also observed among those in this treatment who do not respond to the incentives and do not change recycling behaviour. This provides evidence for complementarities among pro-environment behaviours and suggests that interventions may have unaccounted positive effects on non-target environment behaviours. |
| Keywords: | pro-environment behaviours, behavioural interventions, spillovers, willingness to pay, ï¬ eld experiment |
| JEL: | C93 D90 Q50 |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:mpi:wpaper:tax-mpg-rps-2021-03&r=all |