nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2022‒02‒14
nine papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Place attachment and preferences for land-based wind power. A discrete choice experiment By Anders Dugstad; Kristine Grimsrud; Gorm Kipperberg; Henrik Lindhjem; Ståle Navrud
  2. Consumers' Preferences for Energy-Efficient Air Conditioners in a Developing Country: A Discrete Choice Experiment Using Eco Labels By Miwa Nakai; Majah-Leah V. Ravago; Yoichi Miyaoka; Kiyoshi Saito; Toshi. H Arimura
  3. The Tart Cherry Market and Purchasing Preferences in the United States By Kilders, Valerie; Lineback, Caitlinn; Malone, Trey; Caputo, Vincenzina; McKendree, Melissa G.S.
  4. Revisiting the solution of dynamic discrete choice models: time to bring back Keane and Wolpin (1994)? By Jack Britton; Ben Waltmann
  5. Information Source and Content – Drivers for Consumers’ Valuation of Fairly Traded Foods By von Grafenstein, Liza; Iweala, Sarah; Ruml, Anette
  6. Is there a diminishing value of urban amenities as a result of the Covid-19 pandemic? By van Vuuren, Aico
  7. Revisiting Identification Concepts in Bayesian Analysis By Jean-Pierre Florens; Anna Simoni
  8. Dynamic Factor Model for Functional Time Series: Identification, Estimation, and Prediction By Sven Otto; Nazarii Salish
  9. Purchasing decisions on alternative fuel vehicles within the agent-based model By Arkadiusz Jędrzejewski; Katarzyna Sznajd-Weron; Jakub Pawłowski; Anna Kowalska-Pyzalska

  1. By: Anders Dugstad; Kristine Grimsrud (Statistics Norway); Gorm Kipperberg; Henrik Lindhjem; Ståle Navrud
    Abstract: Economists have neglected place attachment as a potential explanation for people’s preferences for environmental goods. We conducted the first discrete choice experiment to assess the place attachment concept in the valuation of and response to the place-specific environmental impact from a proposed wind farm in Norway. Place attachment increases required compensation for accepting the wind farm, strengthens resistance, and leads to a higher propensity to systematically choose the status quo option of no wind farm in the discrete choice experiment. This finding suggests that the so-called “not-in-my-backyard” (NIMBY) effect should be recognized as a rational response when people place a high value on local environmental amenities, including place identity and a sense of place.
    Keywords: Place attachment; sense of place; NIMBY (not-in-my-backyard); discrete choice experiment; cultural ecosystem services; wind energy
    JEL: Q40 Q51 Q57
    Date: 2022–01
  2. By: Miwa Nakai; Majah-Leah V. Ravago; Yoichi Miyaoka; Kiyoshi Saito; Toshi. H Arimura
    Abstract: In this paper, we aim to examine consumer behaviour concerning energy-efficient appliances in the context of a developing country. As a case study, we use the Philippines, one of the earliest countries in Southeast Asia to introduce appliance test standards. We conducted face-to-face surveys of potential purchasers of air conditioners (ACs) in Metropolitan Manila, where the percentage of AC owners has increased as a result of economic growth. The survey includes choice experiment questions to estimate preferences for AC attributes, including purchase price, additional functions, country of manufacturer and energy efficiency information. In addition, we examine the types of information on eco labels that encourage consumers to choose an energy-efficient AC, including the default option of an energy efficiency ratio, estimated cost per hour or an energy star rating. Our choice experiment analysis reveals that energy-efficient ACs made by domestic manufacturers with smart functions are more likely to be chosen by consumers. We find that the probability of an energy-efficient AC being chosen can be increased by approximately 15% if the eco label uses an energy star rating rather than an energy efficiency ratio.
    Date: 2022–01
  3. By: Kilders, Valerie; Lineback, Caitlinn; Malone, Trey; Caputo, Vincenzina; McKendree, Melissa G.S.
    Abstract: The overall project goal is to gain a better understanding of consumer demand and preferences for tart cherry products to provide meaningful insights to producers, retailers, and marketers working on the promotion of tart cherry products. To achieve this goal, we conducted a nationwide online survey of 1,235 U.S. consumers in July 2019. We collected a variety of insights on the current tart cherry consumer landscape by asking questions about respondent’s socio-demographics, their consumption, dietary and expenditure habits, their knowledge and awareness of tart cherries and derivate products, as well as respondents’ preferences for local food products and their ethnocentric tendencies. In addition, the survey included two discrete choice experiments on tart cherry juice selection, which were designed to enhance our understanding of (i) what attributes are important to consumers when purchasing tart cherry juice, and (ii) how tart cherry juice performs relative to other juice and soft drink alternatives available in the market. Results suggest that tart cherry consumers systematically differ from non-tart cherry consumers. Our key findings are: 1. Around 56% of respondents consumed either fresh or dried tart cherries and/or tart cherry juice in the last three (3) months. Among those tart cherry consumers almost 50% are 25-44 years old compared to non-consumers, where 40% are 45-64 years old. Tart cherry consumers are also more likely to have children and at least three members in their household, which could indicate that tart cherry consumers tend to be adults with younger children. 2. Those respondents that can be classified as tart cherry consumers consume generally more fruit and fruit derivative products. They also tend to place a higher budget share towards purchasing fruits and vegetables compared to their counterparts. This occurs in conjunction with around 33% of tart cherry consumers following a partially meat and/or animal free diet vs. only 13% of non-tart cherry consumers. 3. The main attributes respondents value more when purchasing tart cherry juice are taste, nutrition, price, safety, and naturalness, with non-consumers putting greater relative importance on all of these attributes than tart cherry consumers except for naturalness. The higher relative importance of nutrition for non-consumers is also reflected in a significantly higher premium they are willing to pay to avoid added sugar in tart cherry juice compared to tart cherry consumers ($0.49 vs. $0.61 per 8 oz bottle). 4. Outside of the main production areas in Michigan and Washington, respondents were uncertain about where tart cherries are produced but are on average willing to pay a premium of around $0.25 per 8 oz bottle for tart cherry juice made in the United States. 5. While non-tart cherry consumers have an overall higher willingness-to-pay (WTP) for different beverage options, the difference in marginal WTP between the juice alternatives is substantially smaller than for tart cherry consumers. Jointly these results demonstrate that existing consumers of tart cherries and non-tart cherry consumers differ from one another in various dimensions. These should be taken into consideration when marketing and promoting tart cherries and their derivative products.
    Keywords: Consumer/Household Economics, Food Consumption/Nutrition/Food Safety
    Date: 2022–01–28
  4. By: Jack Britton (Institute for Fiscal Studies); Ben Waltmann (Institute for Fiscal Studies and IFS)
    Abstract: The ‘curse of dimensionality’ is a common problem in the estimation of dynamic models: as models get more complex, the computational cost of solving these models rises exponentially. Keane and Wolpin (1994) proposed a method for addressing this problem in finite-horizon dynamic discrete choice models by evaluating only a subset of state space points by Monte Carlo integration and interpolating the value of the remainder. This method was widely used in the late 1990s and 2000s but has rarely been used since, as it was found to be unreliable in some settings. In this paper, we develop an improved version of their method that relies on three amendments: systematic sampling, data-guided selection of state space points for Monte Carlo integration, and dispensing with polynomial interpolation when a multicollinearity problem is detected. With these improvements, the Keane and Wolpin (1994) method achieves excellent approximation performance even in a model with a large state space and substantial ex ante heterogeneity.
    Date: 2021–05–28
  5. By: von Grafenstein, Liza; Iweala, Sarah; Ruml, Anette
    Abstract: To learn about the role of information content and source as catalysts to increase consumers’ valuation of fairly traded foods, we conducted an online survey with 2,500 consumers representative of the German population. Within the online survey, respondents were randomly assigned to one of five information treatments or the control group. We employ the contingent valuation approach to measure the willingness-to-pay (WTP) premium for chocolate with the Fairtrade label compared to similar conventional chocolate. To estimate WTP and the outcome which measures the participants’ purchasing intentions, we use ordinary least squares and interval regressions. We find that German consumers are willing to pay a high price premium for a Fairtrade label despite limited knowledge about the certification. This WTP is relatively robust to additional supportive information provision irrespective of the information source. However, the broader measure of behavior, the purchasing intention, can rise due to information provided by a retailer or the government. While a supportive statement by a university does not seem to incentivize the valuation of Fairtrade certified chocolate, we find that an unsupportive (zero effect) statement of the same source can discourage the purchasing intention. Our findings imply that policymakers and scientists need to mind the risk of generalized science communication and create information campaigns to increase purchasing frequency.
    Keywords: Consumer/Household Economics, Food Consumption/Nutrition/Food Safety, Institutional and Behavioral Economics, Labor and Human Capital
    Date: 2021–12
  6. By: van Vuuren, Aico (Department of Economics, School of Business, Economics and Law, Göteborg University)
    Abstract: We investigate whether the Covid-19 pandemic decreased the willingness to pay for urban amenities such as restaurants, cinemas and theaters. We do this by using a hedonic pricing model in combination with a time-gradient difference-in-difference approach. We use a data set that contains virtually all apartments for sale in the larger Stockholm area. We use a very detailed and exible definition of density of urban amenities based on the exact location of these amenities and the walking distance from the apartments to these amenities. We find a decrease of 1.9 percent of apartments that we label as amenity rich.
    Keywords: Covid-19; urban economics; amenities
    JEL: R00 R23 R30
    Date: 2022–01
  7. By: Jean-Pierre Florens (TSE - Toulouse School of Economics - UT1 - Université Toulouse 1 Capitole - Université Fédérale Toulouse Midi-Pyrénées - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Anna Simoni (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique)
    Abstract: This paper studies the role played by identification in the Bayesian analysis of statistical and econometric models. First, for unidentified models we demonstrate that there are situations where the introduction of a non-degenerate prior distribution can make a parameter that is nonidentified in frequentist theory identified in Bayesian theory. In other situations, it is preferable to work with the unidentified model and construct a Markov Chain Monte Carlo (MCMC) algorithms for it instead of introducing identifying assumptions. Second, for partially identified models we demonstrate how to construct the prior and posterior distributions for the identified set parameter and how to conduct Bayesian analysis. Finally, for models that contain some parameters that are identified and others that are not we show that marginalizing out the identified parameter from the likelihood with respect to its conditional prior, given the nonidentified parameter, allows the data to be informative about the nonidentified and partially identified parameter. The paper provides examples and simulations that illustrate how to implement our techniques.
    Keywords: Minimal Sufficiency,Exact Estimability,Set identification,Dirichlet Process,Capacity functional,Nonparametric models.
    Date: 2021
  8. By: Sven Otto; Nazarii Salish
    Abstract: A functional dynamic factor model for time-dependent functional data is proposed. We decompose a functional time series into a predictive low-dimensional common component consisting of a finite number of factors and an infinite-dimensional idiosyncratic component that has no predictive power. The conditions under which all model parameters, including the number of factors, become identifiable are discussed. Our identification results lead to a simple-to-use two-stage estimation procedure based on functional principal components. As part of our estimation procedure, we solve the separation problem between the common and idiosyncratic functional components. In particular, we obtain a consistent information criterion that provides joint estimates of the number of factors and dynamic lags of the common component. Finally, we illustrate the applicability of our method in a simulation study and to the problem of modeling and predicting yield curves. In an out-of-sample experiment, we demonstrate that our model performs well compared to the widely used term structure Nelson-Siegel model for yield curves.
    Date: 2022–01
  9. By: Arkadiusz Jędrzejewski; Katarzyna Sznajd-Weron; Jakub Pawłowski; Anna Kowalska-Pyzalska
    Abstract: We develop an empirically grounded agent-based model to explore the purchasing decisions of mutually interacting agents (consumers) between three types of alternative fuel vehicles. We calibrate the model with recently published empirical data on consumer preferences towards such vehicles. Furthermore, running the Monte Carlo simulations, we show possible scenarios for the development of the alternative fuel vehicle market depending on the marketing strategies employed.
    Keywords: Agent-based model; Diffusion; Alternative fuel vehicles
    Date: 2022

This nep-dcm issue is ©2022 by Edoardo Marcucci. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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