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on Discrete Choice Models |
| By: | Andrea Craig (Department of Economics, University of Windsor) |
| Abstract: | Public transportation infrastructure projects are major government investments that potentially affect not only travel mode choices, but residential location. To analyze the impacts of public transportation projects, accounting for households' residential location decisions, I develop a discrete choice model of commute mode and residential location. In this model, households have heterogeneous preferences for neighbourhood characteristics and commute costs. I estimate this model using microdata from Vancouver and commute times calculated with geographic information system (GIS) data. The mean-income household's willingness to pay to reduce commute time is fourteen dollars per hour and there is significant heterogeneity in this value across household income. Using the estimated model, I simulate households' residential and commute mode decisions under a proposed public transportation infrastructure project. |
| Keywords: | residential choice, commute mode choice, public transportation, counterfactual simulation |
| JEL: | R21 R41 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:wis:wpaper:1904&r=all |
| By: | Lee, Sanghoon (University of British Columbia); Lee, Seung Hoon (Georgia Institute of Technology); Lin, Jeffrey (Federal Reserve Bank of Philadelphia) |
| Abstract: | The limitations of GDP as a measure of welfare are well known. We propose a new method of estimating the well-being of nations. Using gross bilateral international migration flows and a discrete choice model in which everyone in the world chooses a country in which to live, we estimate each country’s overall quality of life. Our estimates, by relying on revealed preference, complement previous estimates of economic well-being that consider only income or a small number of factors, or rely on structural assumptions about how these factors contribute to wellbeing. |
| Keywords: | International migration; quality of life; GDP |
| JEL: | D63 F22 I31 J61 |
| Date: | 2019–08–27 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:19-33&r=all |
| By: | Omotesho, O.A.; Adenuga, A.H.; Nurudeen, A.S.; Olaghere, I.L. |
| Keywords: | Production Economics, Demand and Price Analysis |
| Date: | 2019–09 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaae19:296040&r=all |
| By: | Liang Chen |
| Abstract: | This paper considers panel data models where the conditional quantiles of the dependent variables are additively separable as unknown functions of the regressors and the individual effects. We propose two estimators of the quantile partial effects while controlling for the individual heterogeneity. The first estimator is based on local linear quantile regressions, and the second is based on local linear smoothed quantile regressions, both of which are easy to compute in practice. Within the large T framework, we provide sufficient conditions under which the two estimators are shown to be asymptotically normally distributed. In particular, for the first estimator, it is shown that $N |
| Date: | 2019–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1911.01824&r=all |