nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2021‒02‒22
seven papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. On-Demand Transit User Preference Analysis using Hybrid Choice Models By Nael Alsaleh; Bilal Farooq; Yixue Zhang; Steven Farber
  2. Identifying and Estimating Perceived Returns to Binary Investments By Clint Harris
  3. New York, Abu Dhabi, London or Stay at Home? Using a Cross-Nested Logit Model to Identify Complex Substitution Patterns in Migration By Beine, Michel; Bierlaire, Michel; Docquier, Frédéric
  4. Constructing valid instrumental variables in generalized linear causal models from directed acyclic graphs By {\O}yvind Hoveid
  5. Location, Location, Structure Type: Rent Divergence within Neighborhoods By ; Randal Verbrugge
  6. Entropy methods for identifying hedonic models By Arnaud Dupuy; Alfred Galichon; Marc Henry
  7. Flexible transition timing in discrete-time multistate life tables using Markov chains with rewards By Daniel C. Schneider; Mikko Myrskylä; Alyson A. van Raalte

  1. By: Nael Alsaleh; Bilal Farooq; Yixue Zhang; Steven Farber
    Abstract: In light of the increasing interest to transform the fixed-route public transit (FRT) services into on-demand transit (ODT) services, there exists a strong need for a comprehensive evaluation of the effects of this shift on the users. Such an analysis can help the municipalities and service providers to design and operate more convenient, attractive, and sustainable transit solutions. To understand the user preferences, we developed three hybrid choice models: integrated choice and latent variable (ICLV), latent class (LC), and latent class integrated choice and latent variable (LC-ICLV) models. We used these models to analyze the public transit user's preferences in Belleville, Ontario, Canada. Hybrid choice models were estimated using a rich dataset that combined the actual level of service attributes obtained from Belleville's ODT service and self-reported usage behaviour obtained from a revealed preference survey of the ODT users. The latent class models divided the users into two groups with different travel behaviour and preferences. The results showed that the captive user's preference for ODT service was significantly affected by the number of unassigned trips, in-vehicle time, and main travel mode before the ODT service started. On the other hand, the non-captive user's service preference was significantly affected by the Time Sensitivity and the Online Service Satisfaction latent variables, as well as the performance of the ODT service and trip purpose. This study attaches importance to improving the reliability and performance of the ODT service and outlines directions for reducing operational costs by updating the required fleet size and assigning more vehicles for work-related trips.
    Date: 2021–02
  2. By: Clint Harris
    Abstract: I describe a method for estimating agents' perceived returns to investments that relies on cross-sectional data containing binary choices and prices, where prices may be imperfectly known to agents. This method identifies the scale of perceived returns by assuming agent knowledge of an identity that relates profits, revenues, and costs rather than by eliciting or assuming agent beliefs about structural parameters that are estimated by researchers. With this assumption, modest adjustments to standard binary choice estimators enable consistent estimation of perceived returns when using price instruments that are uncorrelated with unobserved determinants of agents' price misperceptions as well as other unobserved determinants of their perceived returns. I demonstrate the method, and the importance of using price variation that is known to agents, in a series of data simulations.
    Date: 2021–01
  3. By: Beine, Michel (University of Luxembourg); Bierlaire, Michel (EPFL, Lausanne); Docquier, Frédéric (LISER)
    Abstract: The question of how people revise their decisions about whether to emigrate, and where to, when facing changes in the global environment is of critical importance in migration literature. We propose a cross-nested logit (CNL) approach to generalize the way deviations from the IIA (independence from irrelevant alternatives)) hypothesis can be tested and exploited in migration studies. Compared with the widely used logit model, the structure of a CNL model allows for more sophisticated substitution patterns between destinations. To illustrate the relevance of our approach, we provide a case study using migration aspiration data from India. We demonstrate that the CNL approach outperforms standard competing approaches in terms of quality of fit, has stronger predictive power, implies stronger heterogeneity in responses to shocks, and highlights complex and intuitive substitution patterns between all possible alternatives. In particular, we shed light on the low degree of substitutability between the home and foreign alternatives as well as on the subgroups of countries that are considered by potential Indian movers as highly or poorly substitutable.
    Keywords: international migration, discrete choice modelling, independence from irrelevant alternatives, cross-nested logit, migration aspirations
    JEL: C25 F22 J61
    Date: 2021–02
  4. By: {\O}yvind Hoveid
    Abstract: Unlike other techniques of causality inference, the use of valid instrumental variables can deal with unobserved sources of both variable errors, variable omissions, and sampling bias, and still arrive at consistent estimates of average treatment effects. The only problem is to find the valid instruments. Using the definition of Pearl (2009) of valid instrumental variables, a formal condition for validity can be stated for variables in generalized linear causal models. The condition can be applied in two different ways: As a tool for constructing valid instruments, or as a foundation for testing whether an instrument is valid. When perfectly valid instruments are not found, the squared bias of the IV-estimator induced by an imperfectly valid instrument -- estimated with bootstrapping -- can be added to its empirical variance in a mean-square-error-like reliability measure.
    Date: 2021–02
  5. By: ; Randal Verbrugge
    Abstract: Housing rents are a large share of household budgets and make a large contribution to overall inflation. Rent inflation rates for different types of housing units sometimes diverge, even in the same neighborhoods. We estimate during 2013 to 2016 apartment rents outpaced rents for detached housing in the United States by 0.76 percentage points annually after controlling for location effects. These rent dynamics imply a segmented housing market. They also suggest rent indexes need to be based on data structurally representative of their measurement objective. In particular, indexes based on professionally managed apartment complexes mismeasure the rents for housing generally. Even indexes based on careful geographical sampling, such as the Consumer Price Index’s Owners’ Equivalent Rent component, may be biased by using an unrepresentative mix of apartments and houses.
    Keywords: rental housing; price measurement; owners’ equivalent rent
    JEL: E30 R21 R31
    Date: 2020–02–09
  6. By: Arnaud Dupuy; Alfred Galichon; Marc Henry
    Abstract: This paper contributes to the literature on hedonic models in two ways. First, it makes use of Queyranne's reformulation of a hedonic model in the discrete case as a network flow problem in order to provide a proof of existence and integrality of a hedonic equilibrium and efficient computation of hedonic prices. Second, elaborating on entropic methods developed in Galichon and Salani\'{e} (2014), this paper proposes a new identification strategy for hedonic models in a single market. This methodology allows one to introduce heterogeneities in both consumers' and producers' attributes and to recover producers' profits and consumers' utilities based on the observation of production and consumption patterns and the set of hedonic prices.
    Date: 2021–02
  7. By: Daniel C. Schneider (Max Planck Institute for Demographic Research, Rostock, Germany); Mikko Myrskylä (Max Planck Institute for Demographic Research, Rostock, Germany); Alyson A. van Raalte (Max Planck Institute for Demographic Research, Rostock, Germany)
    Abstract: Discrete-time multistate life tables are attractive because they are easier to understand and apply in comparison to their continuous-time counterparts. While such models are based on a discrete time grid, it is often useful to calculate derived magnitudes, like state occupation times, under assumptions that posit that transitions take place at other times, such as mid-period. Unfortunately, currently available models allow only a very limited set of choices about transition timing. We propose to utilize Markov chains with rewards as an intuitive and general way of modelling the timing of transitions. Combining existing discrete-time models with the rewards methodology results in an estimation strategy that features easy parameter estimation, flexible transition timing, and little theoretical overhead. We illustrate the usefulness of rewards- based multistate life tables with SHARE data for the estimation of working life expectancy using different retirement transition timings. We also demonstrate that, for the single-state case, the rewards-based multistate life tables match traditional life table methods exactly. We provide code to replicate all results of the paper, as well as R and Stata packages for general use of the method proposed.
    JEL: J1 Z0
    Date: 2021

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