nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2021‒03‒15
nine papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Enhancing the informational nudge of energy labels: Evidence from a DCE in New Delhi By Grover, Charu; Bansal, Sangeeta; Martinez-Cruz, Adan L.
  2. Discrete-Continuous Dynamic Choice Models: Identification and Conditional Choice Probability Estimation By Bruneel-Zupanc, Christophe Alain
  3. Predicting fixed effects in panel probit models By Johannes S. Kunz; Kevin E. Staub; Rainer Winkelmann
  4. Weak Identification in Discrete Choice Models By Frazier, David T.; Renault, Eric; Zhang, Lina; Zhao, Xueyan
  5. Testing Willingness to Pay Elicitation Mechanisms in the Field: Evidence from Uganda By Konrad B. Burchardi; Jonathan de Quidt; Selim Gulesci; Benedetta Lerva; Stefano Tripodi
  6. Allocation Rules for Multi-choice Games with a Permission Tree Structure By David Lowing
  7. Influence and Correlated Choice By Christopher P. Chambers; Yusufcan Masatlioglu; Christopher Turansick
  8. Collaborative tax evasion in the provision of services to consumers: A field experiment By Doerr, Annabelle; Necker, Sarah
  9. Extension of the Lagrange multiplier test for error cross-section independence to large panels with non normal errors By Zhaoyuan Li; Jianfeng Yao

  1. By: Grover, Charu (Shaheed Bhagat Singh College, University of Delhi, India); Bansal, Sangeeta (Centre for International Trade and Development, Jawaharlal Nehru University, India); Martinez-Cruz, Adan L. (CERE - the Center for Environmental and Resource Economics)
    Abstract: India's contribution to global CO2 emissions makes it a priority case for policy makers worldwide. The Indian government is considering the adoption of energy labels for new passenger cars to tackle CO2 emissions. This paper's first aim is to asses New Delhi's car buyers' preferences for cars displaying energy labels. To do so, a discrete choice experiment (DCE) has been designed to document both WTP for energy efficiency (212 USD for one kilometer per liter) and WTP for the best efficiency label (4.93 thousand USD). The informational nudge embedded in a labeling system may not be enough to boost uptake of efficient cars. Thus this paper investigates the potential of combining a labeling system and car driving restrictions. Via a split-sample approach, this paper documents an increase of 2.55 thousand USD in stated WTP for the best efficiency label. This number can be interpreted as reflecting the costs imposed by the driving restrictions on car drivers. Under this interpretation, 2.55 thousand USD fall within the range of estimations reported in previous studies. The results in this paper suggest that a combination of driving restrictions and a labeling system may deliver an increase in energy efficient cars in New Delhi.
    Keywords: Energy labeling system; driving restrictions; willingness to pay; discrete choice experiment; split-sample approach; New Delhi.
    JEL: Q48 Q50
    Date: 2021–03–01
  2. By: Bruneel-Zupanc, Christophe Alain
    Abstract: This paper develops a general framework for models, static or dynamic, in which agents simultaneously make both discrete and continuous choices. I show that such models are nonparametrically identified. Based on the constructive identification arguments, I build a novel two-step estimation method in the lineage of Hotz and Miller (1993) but extended to discrete and continuous choice models. The method is especially attractive for complex dynamic models because it significantly reduces the computational burden associated with their estimation. To illustrate my new method, I estimate a dynamic model of female labor supply and consumption.
    Date: 2021–02–03
  3. By: Johannes S. Kunz; Kevin E. Staub; Rainer Winkelmann
    Abstract: Many applied settings in empirical economics require estimation of a large number of fixed effects, like teacher effects or location effects. In the context of binary response variables, pre-vious studies have been limited to the linear probability model, citing perfect prediction and incidental parameter biases as reasons. We explain why these problems arise and present an appropriate solution for the probit model. In contrast to other estimators, it ensures that pre- dicted fixed effects exist for all units. We illustrate the approach in simulation experiments and an application to health care utilization.
    Keywords: Perfect prediction, Incidental parameter bias, Fixed Effects, Panel data, Binary response, Bias reduction
    Date: 2019–06
  4. By: Frazier, David T. (Department of Econometrics and Business Statistics, Monash University, and the Australian Center for Excellence in Mathematics and Statistics (ACEMS)); Renault, Eric (Department of Economics, University of Warwick.); Zhang, Lina (Department of Econometrics and Business Statistics, Monash University); Zhao, Xueyan (Department of Econometrics and Business Statistics, Monash University)
    Abstract: We study the impact of weak identification in discrete choice models, and provide insights into the determinants of identification strength in these models. Using these insights, we propose a novel test that can consistently detect weak identification in commonly applied discrete choice models, such as probit, logit, and many of their extensions. Furthermore, we demonstrate that when the null hypothesis of weak identification is rejected, Wald-based inference can be carried out using standard formulas and critical values. A Monte Carlo study compares our proposed testing approach against commonly applied weak identification tests. The results simultaneously demonstrate the good performance of our approach and the fundamental failure of using conventional weak identification tests for linear models in the discrete choice model context. Furthermore, we compare our approach against those commonly applied in the literature in two empirical examples: married women labor force participation, and US food aid and civil conflicts.
    Keywords: Discrete Choice Models ; Weak Instruments ; Weak identification ; Identification Testing Creation date: 2021
  5. By: Konrad B. Burchardi; Jonathan de Quidt; Selim Gulesci; Benedetta Lerva; Stefano Tripodi
    Abstract: Researchers frequently use variants of the Becker-DeGroot-Marschak (BDM) mechanism to elicit willingness to pay (WTP). These variants involve numerous incentive-irrelevant design choices, some of which carry advantages for implementation but may deteriorate participant comprehension or trust in the mechanism, which are well-known problems with the BDM. We highlight three such features and test them in the field in rural Uganda, a relevant population for many recent applications. Comprehension is very high, and 86 percent of participants bid optimally for an induced-value voucher, with little variation across treatments. This gives confidence for similar applications, and suggests the comprehension-expediency trade-off is mild.
    Keywords: willingness to pay, Becker-DeGroot-Marschak, field experiment
    JEL: C90 C93 D44 O12
    Date: 2021
  6. By: David Lowing (Univ Lyon, UJM Saint-Etienne, GATE Lyon Saint-Etienne UMR 5824, F-42023 Saint-Etienne, France)
    Abstract: We consider multi-choice cooperative games with a permission tree structure. Multi-choice games are a generalization of a cooperative transferable utility games in which each player has several activity levels. In addition, a permission tree structure models a situation in which a player needs permission from another player to cooperate. In this framework, the influence of a permission structure on the possibility of cooperation may have several interpretations depending on the context. In this paper, we investigate several of these interpretations and introduce for each of them a new allocation rule that we axiomatically characterize.
    Keywords: Multi-choice games, Multi-choice Permission value, Permission (tree) structures
    JEL: C71
    Date: 2021
  7. By: Christopher P. Chambers; Yusufcan Masatlioglu; Christopher Turansick
    Abstract: As a means for testing for the presence of influence across individuals, we discuss the concept of a stochastic choice function for a group of agents which allows observation of correlation structure (correlated choice rule). We ask when choice behavior is consistent with an underlying unobserved (latent) variable or signal which jointly governs preferences: this hypothesis represents absence of influence. Key is the property of marginality, which demands the independence of any given agents' budgetary choices from the budgets faced by the remaining agents. Marginality permits the construction of well-defined marginal stochastic choice functions. Marginality and non-negativity of an analogue of the Block-Marshack polynomials are equivalent to joint stochastic rationality for small environments. For larger environments, we offer an example of a correlated choice function establishing that each of the marginal stochastic choice functions may be stochastically rational while the correlated choice function is not. Thus, the detection of influence can be aided by studying correlated choice data.
    Date: 2021–03
  8. By: Doerr, Annabelle; Necker, Sarah
    Abstract: We conduct a field experiment with sellers of home-improvement services on two German online markets. We take the role of consumers and vary whether we request an invoice for the delivery of the service. In a market which allows anyone to sell anonymously, a willingness to evade is prevalent. In a market that keeps track of credentials, sellers are only willing to evade when a willingness to collude is signaled. The evasion discount is in most estimates not larger than the tax subsidy for legal demand. Evasion is unlikely to be beneficial for many consumers in our setting.
    Keywords: Collaborative tax evasion,evasion discount,undeclared work,third-party reporting,field experiment
    JEL: H26 C93 E26 J22 O17
    Date: 2021
  9. By: Zhaoyuan Li; Jianfeng Yao
    Abstract: This paper reexamines the seminal Lagrange multiplier test for cross-section independence in a large panel model where both the number of cross-sectional units n and the number of time series observations T can be large. The first contribution of the paper is an enlargement of the test with two extensions: firstly the new asymptotic normality is derived in a simultaneous limiting scheme where the two dimensions (n, T) tend to infinity with comparable magnitudes; second, the result is valid for general error distribution (not necessarily normal). The second contribution of the paper is a new test statistic based on the sum of the fourth powers of cross-section correlations from OLS residuals, instead of their squares used in the Lagrange multiplier statistic. This new test is generally more powerful, and the improvement is particularly visible against alternatives with weak or sparse cross-section dependence. Both simulation study and real data analysis are proposed to demonstrate the advantages of the enlarged Lagrange multiplier test and the power enhanced test in comparison with the existing procedures.
    Date: 2021–03

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