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on Discrete Choice Models |
| By: | Vincent Boucher (CRREP - Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques - ULaval - Université Laval [Québec], CREATE, Centre de Recherche en économie de l'Environnement, de l'Agroalimentaire, des Transports et de l'Énergie - ULaval - Université Laval [Québec]); Yann Bramoullé (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique - AMU - Aix Marseille Université) |
| Abstract: | Heckman and MaCurdy (1985) first showed that binary outcomes are compatible with linear econometric models of interactions. This key insight was unduly discarded by the literature on the econometrics of games. We consider general models of linear interactions in binary outcomes that nest linear models of peer effects in networks and linear models of entry games. We characterize when these models are well defined. Errors must have a specific discrete structure. We then analyze the models' game-theoretic microfoundations. Under complete information and linear utilities, we characterize the preference shocks under which the linear model of interactions forms a Nash equilibrium of the game. Under incomplete information and independence, we show that the linear model of interactions forms a Bayes-Nash equilibrium if and only if preference shocks are iid and uniformly distributed. We also obtain conditions for uniqueness. Finally, we propose two simple consistent estimators. We revisit the empirical analyses of teenage smoking and peer effects of Lee, Li, and Lin (2014) and of entry into airline markets of Ciliberto and Tamer (2009). Our reanalyses showcase the main interests of the linear framework and suggest that the estimations in these two studies suffer from endogeneity problems. |
| Keywords: | Binary Outcomes,Linear Probability Model,Peer Effects,Econometrics of Games |
| Date: | 2020–11 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-03031767&r=all |
| By: | Wong, Stephen D; Walker, Joan L; Shaheen, Susan A |
| Abstract: | Advances in the sharing economy – such as transportation network companies (e.g., Lyft, Uber) and home sharing (e.g., Airbnb) – have coincided with the increasing need for evacuation resources. While peer-to-peer sharing under normal circumstances often suffers from trust barriers, disaster literature indicates that trust and compassion often increase following disasters, improving recovery efforts. We hypothesize that trust and compassion could trigger willingness to share transportation and sheltering resources during an evacuation. To test this hypothesis, we distributed a survey to individuals impacted by the 2017 Southern California Wildfires (n=226) and the 2018 Carr Wildfire (n=284). We estimate binary logit choice models, finding that high trust in neighbors and strangers and high compassion levels significantly increase willingness to share across four sharing scenarios. Assuming a high trust/compassion population versus a low trust/compassion population results in a change of likelihood to share between 30% and 55%, depending on scenario. Variables related to departure timing and routing – which capture evacuation urgency – increase transportation sharing willingness. Volunteers in past disasters and members of community organizations are usually more likely to share, while families and previous evacuees are typically less likely. Significance of other demographic variables is highly dependent on the scenario. Spare seatbelts and bed capacity, while increasing willingness, are largely insignificant. These results suggest that future sharing economy strategies should cultivate trust and compassion before disasters via preparedness within neighborhoods, community-based organizations, and volunteer networks, during disasters through communication from officials, and after disasters using resilience-oriented and community-building information campaigns. |
| Keywords: | Engineering, Evacuations, sharing economy, shared mobility, ridehailing, homesharing, California wildfire |
| Date: | 2020–10–14 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsrrp:qt14z1383w&r=all |
| By: | Tensay Meles; L. (Lisa B.) Ryan |
| Abstract: | Concern about climate change and dependence on fossil fuels is inducing countries to develop and deploy renewable energy technologies. Heat pump systems, which extract heat either from the air, water, or ground sources, are among the viable options for space heating and domestic hot water production in the residential sector. In this paper, we develop an agent-based model to analyze the adoption process of heat pump systems and the underlying diffusion factors. Uniquely, we use a recent nationally representative Irish household survey data to derive parameters for decision rules for technology adoption in the model. In this research, we explore how financial aspects, psychological factors and social networks influence the adoption and diffusion of heat pump systems. We also discuss how individual household socio-demographic characteristics, building characteristics, geographical location of household and policy incentives affect the adoption process. The research should be of interest to policymakers, as we use the model to test the impact of various policies on technology adoption rates. |
| Keywords: | Agent-based model; Heat pump systems; Energy economics; Renewable energy technology adoption; Ireland |
| JEL: | D12 D91 Q41 Q28 |
| Date: | 2020–12 |
| URL: | http://d.repec.org/n?u=RePEc:ucn:wpaper:202030&r=all |
| By: | Michel Grabisch (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics); Christophe Labreuche (Thales Research and Technology [Palaiseau] - THALES); Mustapha Ridaoui (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics) |
| Abstract: | Generalized Additive Independence (GAI) models permit to represent interacting variables in decision making. A fundamental problem is that the expression of a GAI model is not unique as it has several equivalent different decompositions involving multivariate terms. Considering for simplicity 2-additive GAI models (i.e., with multivariate terms of at most 2 variables), the paper examines the different questions (definition, monotonicity, interpretation, etc.) around the decomposition of a 2-additive GAI model and proposes as a basis the notion of well-formed decomposition. We show that the presence of a bi-variate term in a well-formed decomposition implies that the variables are dependent in a preferential sense. Restricting to the case of discrete variables, and based on a previous result showing the existence of a monotone decomposition, we give a practical procedure to obtain a monotone and well-formed decomposition and give an explicit expression of it in a particular case. |
| Keywords: | decomposition,decision making,multichoice game,Generalized Additive Independence |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-03022926&r=all |
| By: | Michel Grabisch (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics); Christophe Labreuche (Thales Research and Technology [Palaiseau] - THALES); Mustapha Ridaoui (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics) |
| Abstract: | Generalized Additive Independence (GAI) models permit to represent interacting variables in decision making. A fundamental problem is that the expression of a GAI model is not unique as it has several equivalent different decompositions involving multivariate terms. Considering for simplicity 2-additive GAI models (i.e., with multivariate terms of at most 2 variables), the paper examines the different questions (definition, monotonicity, interpretation, etc.) around the decomposition of a 2-additive GAI model and proposes as a basis the notion of well-formed decomposition. We show that the presence of a bi-variate term in a well-formed decomposition implies that the variables are dependent in a preferential sense. Restricting to the case of discrete variables, and based on a previous result showing the existence of a monotone decomposition, we give a practical procedure to obtain a monotone and well-formed decomposition and give an explicit expression of it in a particular case. |
| Keywords: | decomposition,decision making,multichoice game,Generalized Additive Independence |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:hal:pseptp:halshs-03022926&r=all |