Car ownership, employment, and earnings

Abstract

for many helpful comments. We are especially grateful to Michael Provence for first suggesting the empirical strategy pursued here. This research was supported by a grant from the National Science Foundation, SBR-9709197 and a grant from the Joint Center for Poverty Research. AbstractIn this paper, we attempt to assess whether the positive effects of car ownership on employment outcomes observed in past research are causal. We match state-level data on average car insurance premiums and average per-gallon gas taxes to a nationally representative microdata sample containing information on car ownership and employment outcomes comparable to the those explored in previous research. In OLS regressions that control for observable demographic and human capital variables, we find large differences in employment rates, weekly hours worked, and hourly earnings between those with and without cars. Instrumenting car ownership on insurance and gas tax costs yields estimates of the employment and hours effects of car ownership that are quite close to the OLS estimates. Concerning wages, the IV models yield negative effects of car ownership on wages. This finding is consistent with the hypothesis that employers located in states with high auto maintenance costs must pay compensating differentials to their employees. When we stratify the sample by skill groupings, we find positive significant employment and hours effects for all skill groups, with larger car-employment effects for low-skilled workers and comparable hours effects across skill categories. Again, the IV results for wages yield negative effects that are insignificant for low-and mediumskilled workers and significant for high-skilled workers. JEL Codes: E24, J22, J61, R411 Suburban land use is often governed by zoning laws dictating strict separation of uses --e.g., physical separation of residential from commercial or industrial uses of land --and limiting density through such mechanisms as restrictions on building-height, parking-availability and, for housing, minimum lot sizes (Fischel 1985). Such laws spatially diffuse suburban labor demand, creating multiple employment centers rarely within walking distance of housing and difficult to service by public transit.

Job Accessibility and Employment Probability

“…However, the results showed that the relevant variable was not the time cost to access jobs but rather the car availability in the household. This result agrees with other studies Rice, 2002 andOng andMiller, 2005) and reflects that private transport is sometimes the only option to connect residential places and job opportunities. …”

The Mechanisms of Spatial Mismatch

“…Holzer et al (2003) find that the expansion of the railway system in San Francisco to a predominantly White, high-growth and lowunemployment suburb increases the relative employment of minority workers near the station. Raphael and Rice (2002) show that car ownership increases the employment rate and the number of hours worked but, surprisingly, decreases hourly earnings. Ong and Miller (2005) show that the 'transportation mismatch' (the lack of access to a private automobile) is the most important factor in generating poor labour market outcomes, particularly for disadvantaged neighbourhoods in the Los Angeles metropolitan area.…”

Application of Bayesian Multilevel Models Using Small and Medium Size City in China: The Case of Changchun

“…Income is found to be a determinant for car ownership and use both for work and non-work purposes, which also may be one of the most important factors [49,50]. Yet some researchers claim that the relationship between income and VMT is not significant [38].…”