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Labor mobility within Japanese regional labor markets and spillover effects

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Abstract

This paper re-estimates the regional job-matching function using annual panel data covering 47 Japanese prefectures from 1987 to 2013, controlling for spillovers and agglomeration effects across prefectures, in addition to prefecture-level labor market determinants and prefecture and time fixed effects. The estimates reveal that the number of job matches rises together with rising stocks of unemployed and vacancies within and across prefectures suggesting significant spillover effects. A model comparison shows that the spatial spillovers are best captured using a contiguity weight matrix and are restricted to the local labor markets. Finally, the estimates of the matching function in different periods indicate that job seekers have substantially shifted their job-search behavior over time.

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Notes

  1. In case a unit has no neighboring connections, a value of zero was assigned to the weighted average values of the neighboring units.

  2. \(\rho \in \left[{w}_{\mathrm{min}}^{-1}, 1\right]\) as the spatial weight matrix is row-standardized, which ensure the non-singularity of \({(I-\rho W)}^{-1}\). \(\lambda \in \left[{w}_{\mathrm{min}}^{-1}, 1\right]\) because the spatial weight matrix is row-standardized. The parameters estimation rests on a concentrated maximum likelihood approach. The spatial correlation parameters are optimized.

  3. The inclusion of the spatial autocorrelation in the regression models is motivated by potential latent influences not captured by the explanatory variables and that are spatially influencing the dependent variable. Other motivations arise from spatial heterogeneity modeling, externalities, and model uncertainty (see LeSage and Pace (2009), pp 25–31).

  4. Source: www.stat.go.jp.

  5. A worker is defined as: a regular work (without fixed term of employment contract or employment contract term exceeds 4 months), causal worker (employment contract of 1–4 months), and seasonal worker (seasonal labor demand).

  6. Data on total commuting time of workers and commuting time by gender from 1981 to 2011.

  7. Proximities are defined as those in the distance weight matrix.

  8. We construct the contiguity weight matrix using a Japan prefectures level’s coordinates map obtained in a shapefile from www.stats-japan.com.

  9. The measurements for the shortest roads and highways weight matrix that interconnects different prefectures’ were generated using Google Maps, Map Data ©2017. This is accurate enough to provide an approximate estimate of the distances traveled.

  10. Hausman test suggests that fixed effects estimation is preferred to random effects. Chi2 = 29.35, p val = 1.8e−06.

  11. A Lagrangean multiplier test was run for the OLS, with an agglomeration variable to check for the significance of the fixed effects, following the example set by Honda (1985). The null hypothesis that fixed effects should be discarded is rejected. LM-test = 51.99, p val = 2.2e−16.

  12. We run the same verification with spatial models using the remaining spatial weight matrices and similar results are found.

  13. This applies to all the spatial models with the different spatial weight matrices.

  14. H0 = {Magnitude effects of unemployment variable are equal between spatial and non-spatial fixed effects model}. F test = 7.1, p val = 0.0073.

    H0 = {Magnitude effects of vacancies variable are equal between spatial and non-spatial fixed effects model}. F test = 0.4, p val = 0.59.

  15. The choice of the subsamples lengths was established by estimating the matching function and examining it changes over different periods of time.

  16. Higashi (2018) did not find a significant spillover effects at the prefecture level and over similar timeframe.

  17. This may not be the case, however, if the data generating process was the SDM model, as the direct and indirect effects depend on the spatial multiplier matrix \({(I-\rho W)}^{-1}\).

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  1. Osaka University, Suita, Japan

    Nasser Dine Mohamedou

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  1. Nasser Dine Mohamedou
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Mohamedou, N.D. Labor mobility within Japanese regional labor markets and spillover effects. JER 73, 625–645 (2022). https://doi.org/10.1007/s42973-020-00059-3

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