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on Discrete Choice Models |
| By: | Robert Duval Hernández |
| Abstract: | Using a special module of the 2015 Mexican Labour Force Survey with information on workers' preferences for jobs with social security coverage, I estimate that 80 per cent of informal workers in large urban areas would prefer to work in a job that provides them with such coverage. A discrete choice econometric model which distinguishes between wanting a formal job and the probability of getting one shows that schooling increases the chances of being hired in formal employment and of having higher earnings in it. |
| Keywords: | informal work, Labour market, Labour market segmentation, rationing, Informality |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:unu:wpaper:wp-2020-151&r=all |
| By: | Johan A Elkink (School of Politics and International Relations, University College Dublin); Sarah Parlane (School of Economics, University College Dublin); Thomas Sattler (Universite de Geneve) |
| Abstract: | Most existing studies of referendums examine voter turnout and their vote choice separately. Our theoretical model suggests that this is problematic. The model predicts that voters who generally prefer one of the two possible referendum outcomes, but who are relatively uncertain about the consequences of their preferred option, tend to abstain from voting. Greater uncertainty about a referendum option not only reduces its value, but also, for more "distant" voters, the value of participating. Uncertainty, thus, has a double effect: potential supporters of one referendum option are less likely to vote; and citizens who vote are less likely to support this option. We use data from the ‘Brexit’ vote to show how individual assessments of uncertainty about the two-options affect turnout and the vote. Our empirical analyses provide support for our theoretical model. |
| Keywords: | referendums, turnout, uncertainty, European integration, electoral behavior and Brexit |
| Date: | 2020–11–12 |
| URL: | http://d.repec.org/n?u=RePEc:ucd:wpaper:202012&r=all |
| By: | Beairsto, Jeneva; Tian, Yufan; Zheng, Linyu; Zhao, Qunshan; Hong, Jinhyun |
| Abstract: | Worldwide bike-sharing systems are growing in popularity as an alternative, environmentally friendly mode of transportation. As cities seek to further develop bike-sharing programs, it is important to consider how systems should expand to simultaneously address existing inequalities in accessibility, and best serve demand. In this paper, we determine ideal locations for future bike-sharing stations in Glasgow, Scotland, by integrating demand modelling with accessibility considerations. We began by analyzing the spatio-temporal trends of bike-sharing usage, and assessed the spatial equity of access to stations in Glasgow. To identify important determinants of bike-sharing demand, we ran an ordinary least squares regression model using bike sharing trip data from Nextbike Glasgow. We then quantifiably measured the level of spatial accessibility to stations by applying the two-step floating catchment area (2SFCA) methodology and ran a GIS weighted overlay analysis using the significant determinants of station demand. Lastly, we combined the demand and accessibility results to determine where new stations should be located using a maximum covering location problem (MCLP) that maximized the population served. Our results show that distance from transit stations, distance from downtown, employment rates, and nearby cycling lanes are significant factors affecting station-level demand. Furthermore, levels of spatial access were found to be highest primarily in the centre and eastern neighbourhood of Glasgow. These findings aided in determining areas to prioritize for future station locations, and our methodology can easily be applied to other bike-share programs with adjustments according to varying aims for system expansion. |
| Date: | 2020–11–24 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:apyfn&r=all |
| By: | Stefan Hubner |
| Abstract: | This paper develops a method to use data from singles in a non–parametric collective household setting. We use it to test the controversial assumption of preference stability between singles and couples. Our test allows for unobserved heterogeneity by defining finite-dimensional types of households according to their revealed preference relations. We show how to derive a test statistic by constructing hypothetical matches of heterogeneous individuals into different types of households using tools from stochastic choice theory. We strongly reject the preference–stability hypothesis based on consumption data from the Dutch LISS, the Russian RLMS, and the Spanish ECPF panels. |
| Date: | 2020–12–02 |
| URL: | http://d.repec.org/n?u=RePEc:bri:uobdis:20/735&r=all |