The Educational Bias in Commuting Patterns: Micro-Evidence for the Netherlands

Groot, S.P.T.; Groot, H.L.F. de; Veneri, Paolo

doi:10.2139/ssrn.2119929

Cited by 11 publications

(19 citation statements)

References 28 publications

(31 reference statements)

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“…But, as one referee pointed out, strictly speaking we look at changes in commuting distances between municipalities. 20 The self-reported average commuting distance in the Netherlands is 17 km over the period 2000(Groot et al 2012. The difference with our data stems largely from within-municipality commutes that are assumed to be zero in our approach.…”

Section: Datamentioning

confidence: 77%

Does new information technology change commuting behavior?

2019

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We estimate the long-run causal effect of information technology, i.e., Internet and powerful computers, as measured by the adoption of teleworking, on average commuting distance within professions in the Netherlands. We employ data for 2 years-1996 when information technology was hardly adopted and 2010 when information technology was widely used in a wide range of professions. Variation in information technology adoption over time and between professions allows us to infer the causal effect of interest using difference-indifferences techniques combined with propensity score matching. Our results show that the long-run causal effect of information technology on commuting distance is too small to be identified and likely to be absent. This suggests that, contrary to some assertions, the advent of information technology did not have a profound impact on the spatial structure of the labor market.

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Section: Datamentioning

confidence: 77%

Does new information technology change commuting behavior?

2019

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“…The level of education is also a key determinant of commuting and higher educated workers are expected to have longer commutes (Groot, Groot, & Veneri, 2012). First, highly educated individuals are more efficient at gathering information and have greater knowledge of alternative opportunities .…”

Section: Individual Characteristicsmentioning

confidence: 99%

The role of job uncertainty in inter‐regional commuting: The case of Italy

Parenti

Tealdi

2019

Growth and Change

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This paper studies the evolution of the determinants of inter‐regional commuting in Italy in the period 1992–2016, during which the labour market has been significantly reformed. To capture the changes in commuting patterns, the analysis of the role of individual, job, firm, and regional characteristics is performed. Specifically, the focus is on the impact of job uncertainty at both micro and macro level, through the analysis of the way the diffusion of temporary contracts has affected the decision to commute for work. The findings suggest that in more recent years workers hired on a temporary contract are more likely to commute to another region. Moreover, the higher the relative share of temporary contracts in the region of residence, the higher the probability of commuting across regions. These findings support the idea that the strong utilisation of (short) temporary contracts represents a push factor, which drives workers away in search of better job opportunities, with potentially negative consequences for poorly performing regions.

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“…Furthermore, dual‐earner households are positively related to commuting time (Flowerdew, ; Green, ; McQuaid and Chen, ), as home location may be chosen to minimize the joint travel, rather than a single trip to work. Home ownership, compared to renting (Deding, Filges, and Van Ommeren, ; Groot, de Groot, and Veneri, ; McQuaid and Chen, ) and car ownership (Pucher and Renne, ; Schwanen, Dieleman, and Dijst, ; Dargay and Clark, ; McQuaid and Chen, ) are two factors that have also been found to be positively related to the length of the commute.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Gender has been found to be related to lower commuting times (Hanson and Hanson, ; Turner and Neimeier, ; Sandow, ; Sandow and Westin, ; Dargay and Clark, ; Groot, de Groot, and Veneri, ; McQuaid and Chen, ), and several explanations have addressed gender differences in commuting behavior. First, it could be that differences in the sociodemographic characteristics of men and women explain the gender gap in commuting distance and time, as higher income and education are positively related to commuting distance.…”

Section: Literature Reviewmentioning

confidence: 99%

Commuting Time and Household Responsibilities: Evidence Using Propensity Score Matching

Giménez-Nadal

Molina

2015

Journal of Regional Science

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The Educational Bias in Commuting Patterns: Micro-Evidence for the Netherlands

Cited by 11 publications

References 28 publications

Does new information technology change commuting behavior?

Does new information technology change commuting behavior?

The role of job uncertainty in inter‐regional commuting: The case of Italy

Commuting Time and Household Responsibilities: Evidence Using Propensity Score Matching

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