nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2022‒04‒18
six papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Climate change and individual behavior By Bernard, René; Tzamourani, Panagiota; Weber, Michael
  2. Make the Difference! Computationally Trivial Estimators for Grouped Fixed Effects Models By Martin Mugnier
  3. Privacy attitudes toward mouse-tracking paradata collection By Henninger, Felix; Kieslich, Pascal J.; Fernández-Fontelo, Amanda; Greven, Sonja; Kreuter, Frauke
  4. Closure operators: Complexity and applications to classification and decision-making By Hamed Hamze Bajgiran; Federico Echenique
  5. Indirect Inference for Nonlinear Panel Models with Fixed Effects By Shuowen Chen
  6. Determining the Acceptable Price Level for Agri-Food Products and the Choice of the Processor By Rembisz, Włodzimierz

  1. By: Bernard, René; Tzamourani, Panagiota; Weber, Michael
    Abstract: This paper studies the causal effect of providing information about climate changeon individuals' willingness to pay to offset carbon emissions in a randomizedcontrol trial. Receiving truthful information about ways to reduce CO2 emis-sions increases individuals' willingness to pay for CO2 offsetting relative to thecontrol group. Individuals receiving information about the behavior of peersreact similarly to those receiving information about scientific research. Individ-uals' responses vary depending on their socio-demographic characteristics andalso along a rich set of prior beliefs and concerns regarding climate change. Ina follow-up survey, we study the endogenous information acquisition of surveyparticipants and show that individuals choose information that aligns with theirviews. Individuals who choose to receive information about climate changehave a higher willingness to pay for CO2 offsets.
    Keywords: Climate change,information treatment,willingness to pay,CO2 compensation,information acquisition
    JEL: D10 D83 D91 Q54
    Date: 2022
  2. By: Martin Mugnier
    Abstract: Novel estimators are proposed for linear grouped fixed effects models. Rather than predicting a single grouping of units, they deliver a collection of groupings with the same flavor as the so-called LASSO regularization path. Mild conditions are found that ensure their asymptotic guarantees are the same as the so-called grouped fixed effects and post-spectral estimators (Bonhomme and Manresa, 2015; Chetverikov and Manresa, 2021). In contrast, the new estimators are computationally straightforward and do not require prior knowledge of the number of groups. Monte Carlo simulations suggest good finite sample performance. Applying the approach to real data provides new insights on the potential network structure of the unobserved heterogeneity.
    Date: 2022–03
  3. By: Henninger, Felix (University of Koblenz-Landau); Kieslich, Pascal J.; Fernández-Fontelo, Amanda; Greven, Sonja; Kreuter, Frauke
    Abstract: Survey participants' mouse movements provide a rich, unobtrusive source of paradata, and offer insight into the response process beyond the observed answers. However, the use of mouse-tracking may require participants' explicit consent that their movements are recorded and analyzed. Thus, the fundamental question arises how this affects the willingness of participants to take part in a survey at all -- if prospective respondents are reluctant to complete the survey if additional measures are collected, paradata collection may do more harm than good. Previous research has found that other paradata collection modes reduce the willingness to participate, and that this decrease may be influenced by the specific motivation provided to participants for collecting the data. However, the effects of mouse movement collection on survey consent and participation have not been addressed so far. In a vignette experiment, we show that willingness to participate in a survey decreased when mouse-tracking was part of the overall consent. However, a larger proportion of the sample was willing to both take part and provide mouse-tracking data when these decisions were combined, compared to an independent opt-in to paradata collection, separated from the decision to complete the study. This indicates that survey practitioners may face a trade-off between maximizing their overall participation rate and maximizing the number of participants that also provide mouse-tracking data. Explaining motivations for paradata collection did not have a positive effect and, in some cases, even reduced participants' willingness to participate.
    Date: 2022–03–16
  4. By: Hamed Hamze Bajgiran; Federico Echenique
    Abstract: We study the complexity of closure operators, with applications to machine learning and decision theory. In machine learning, closure operators emerge naturally in data classification and clustering. In decision theory, they can model equivalence of choice menus, and therefore situations with a preference for flexibility. Our contribution is to formulate a notion of complexity of closure operators, which translate into the complexity of a classifier in ML, or of a utility function in decision theory.
    Date: 2022–02
  5. By: Shuowen Chen
    Abstract: Fixed effect estimators of nonlinear panel data models suffer from the incidental parameter problem. This leads to two undesirable consequences in applied research: (1) point estimates are subject to large biases, and (2) confidence intervals have incorrect coverages. This paper proposes a simulation-based method for bias reduction. The method simulates data using the model with estimated individual effects, and finds values of parameters by equating fixed effect estimates obtained from observed and simulated data. The asymptotic framework provides consistency, bias correction, and asymptotic normality results. An application and simulations to female labor force participation illustrates the finite-sample performance of the method.
    Date: 2022–03
  6. By: Rembisz, Włodzimierz
    Abstract: The purpose of the analysis presented in this paper is to answer why a specific price level of agri-food products is determined and accepted by both the consumer and processor, as well as by the agricultural producer and processor. An answer to this question requires presenting a number of equations and functional relationships based on specific assumptions, which is a formal and analytical method of analysis. This method is based on the assumption that the acceptance involves maximizing the goal function of the processor and the goal function of the consumer and agricultural producer simultaneously, as well as that there are conditions for competitive equilibrium on these markets. The essence of this method is the choice of the processor in terms ofprices on the agri-food market. The importance of the procurement price level forthe choice of the processor is presented in an unusual and new manner by conducting an advanced analysis. The basic result of the analysis is a mechanism to determine the acceptable price level for these entities on the agri-food market. This is determined by introducing the admitting inequalities, which specify the ratio of expectations of these entities to the market equilibrium price. The conclusion is that the price level is mutually acceptable because the goal functions of the entities have been carried out. The analysis is analytical and formal and has a theoretical and cognitive value. It may contribute to the theory of prices in the agri-food sector and the conditions for the choice of the processor.
    Keywords: Agricultural Finance, Consumer/Household Economics, Demand and Price Analysis
    Date: 2021–09–23

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