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Testing the new economic geography’s wage equation: a case study of Japan using a spatial panel model

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Abstract

This paper estimates the parameters of the wage equation of the new economic geography (NEG) using a newly developed spatial panel model. The results show that wage rate variation across different prefectures in Japan can be explained by market potential, which is a key variable in NEG theory, while controlling for variation in labour efficiency. Spatial heterogeneity is particularly important in the context of Japan in part because of its complex physical geography and the spatial distribution of its principal urban centres. The paper considers the challenges associated with representing the spatial relationships between prefectures describing and implementing different approaches to measuring transport costs.

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Notes

  1. The original assumption 1 in full is in Kapoor et al. (2007, p. 100).

  2. The term innovation, was used in the KKP model, but these are often referred to as the error term in econometric textbooks. For the moment, we call them innovations for the convenience of making the direct comparison with the specification of the KKP model.

  3. This issue was discussed with Prof Hiroki Tanaka of Doshisha University, Japan, who was once a researcher for the Economic and Social Research Institute of the Cabinet Office. Prof. Tanaka (personal communication) pointed out that total taxable income is unadjusted nominal data and is not influenced by the change to the System of National Accounts, which makes it more suitable for 30-year panel research that spans the year 1996.

  4. “Annual Report of Rail Transport Statistics, 2008” by Ministry of Land, Infrastructure and Transport, Japan.

  5. “Rail transport in Germany” Wikipedia article 2008.

  6. Where there is no clear empirical evidence to support one approach to intra-area distance calculation over another then both might be implemented to assess the sensitivity of results.

  7. A short description of the index is abstracted in “Appendix”.

  8. “F2601 

    figure a

    ” According to the definition of professional and skilled workers, which was given by the Statistics Bureau of Japan, it includes natural science researchers, social science researchers, medical doctors, chartered accountants, professional electronic engineers, etc.

  9. The t ratio to P value conversion is calculated using the following website. http://www.danielsoper.com/statcalc3/calc.aspx?id=8.

  10. http://www.mhlw.go.jp/english/database/db-slms/dl/slms-04.pdf.

  11. The calculation method was further vindicated by Prof Eiichi Yamaguchi of Doshisha University The original Japanese:

    figure b
    figure c

    .

  12. http://www.stat.go.jp/english/data/kouri/kouzou/pdf/estimation_e.pdf.

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Acknowledgements

Many thanks to Prof. Bernard Fingleton, Prof. Ron Martin, Prof. Eiichi Yamaguchi, and Prof. Hiroki Tanaka for their advice, encouragement and help.

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Authors and Affiliations

  1. Graduate Institute of Urban Planning, National Taipei University, Taiwan 151, University Road, San-shia, New Taipei City, 237-41, Taiwan

    Chian-Yue Wang

  2. Department of Geography, University of Cambridge, UK Downing Place, Cambridge, CB2 3EN, UK

    Robert Haining

Authors
  1. Chian-Yue Wang
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  2. Robert Haining
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Correspondence to Chian-Yue Wang.

Appendices

Appendix

“The survey aims at obtaining a clear picture of the wage structure of employees in major industries, i.e., wage distribution by type of employment, type of work, occupation, sex, age, school career, length of service and occupational career, etc.”Footnote 10 Since wage data are collected following a detailed classification, the nominal wage rate for manufacturing industry per capita per year is calculated as follows:

The nominal wage rate of manufacturing industry per capita per yearFootnote 11 \(=\)  \(\{\)[regular monthly cash income per male worker of manufacturing industry*12 \(+\) Bonus(male worker of manufacturing industry)] * the number of male workers in manufacturing industry \(+\) [regular monthly cash income per female worker of manufacturing industry * 12 \(+\) Bonus(female worker of manufacturing industry)] * the number of female workers in manufacturing industry\(\}\)/[the number of male workers in manufacturing industry \(+\)  the number of female workers in manufacturing industry].

The price index (\(G_s\))

The Regional Difference Index of consumer prices (RDI) is an index that indicates the regional differences of the price level based on the average prices of Japan of goods and services purchased by households nationwide. The RDI is calculated from the result of the retail price survey (RPS) (the trend survey and the structural survey). The items to perform the calculation of the RDI (hereinafter “RDI items”) are the items used in the calculation of the CPI, except for the “imputed rent” and the “items surveyed only in Okinawa-ken” (the calculation method of the RDI of consumer prices is downloadable from the website of the Statistics Bureau, Ministry of Internal Affairs and Communications, Japan).Footnote 12

Fig. 7
figure 7

Japanese prefectures (source: Wikipedia)

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Table 5 Fixed effects and t ratios (Assumed elasticity \(=\) 1.55)
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Wang, CY., Haining, R. Testing the new economic geography’s wage equation: a case study of Japan using a spatial panel model. Ann Reg Sci 58, 417–440 (2017). https://doi.org/10.1007/s00168-016-0804-3

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