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Age structure of the workforce in growing and declining industries: evidence from Hong Kong


Industry-specific human capital reduces the incentive for older workers to leave declining industries and raises the incentive for younger workers to join growing industries. Using the industry restructuring experience of Hong Kong, we find that a 1% increase in employment share of an industry is associated with a 0.60-year decrease in the average age of its workforce. The relationship is more pronounced among less educated workers, who have less general human capital, and male workers, who are more committed to the labor force, than among well educated workers and female workers.

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  1. Figures reported in this paragraph are based on authors’ calculations using records from the Hong Kong population censuses and by-censuses. See Section 2 below for more details of the data.

  2. See also MacDonald and Weisbach (2004) for a theoretical model of technology-specific human capital investment. They argue that technology change tends to depreciate older workers’ skills and turn them into has-beens. The entry of younger workers, who can better grasp new technology, puts a downward pressure on the price of what older workers produce.

  3. See Suen (2000) for a similar approach applied to estimating the differential impacts of immigration.

  4. Unpaid family workers refer to individuals who live with the family and do work (not domestic work) as part of the family enterprise in return for food and lodging. They are workers, and are different with home-makers. In any case, such workers represent a very small fraction of the total workforce.

  5. Details of the recoding are shown in Table 10.

  6. This is consistent with Devereux’s (2005a, Devereux (2005b)b) findings for the USA.

  7. The estimated slope is − 0.89 (\(\hbox{s.e.} = 0.44\)) when observations are weighted by their employment shares. The relationship between employment growth in 1976–1981 and industry-specific unemployment rate in 1981 is similar.

  8. We classify workers into three education groups: primary and below, secondary, and college and above. The sample size is not three times as large as the sample size shown in columns 1 and 2 because some of the cells are too small to give a meaningful measure of the relative wage of young workers.

  9. Evans (1999) analyzes the cyclical structure of occupational upgrading and downgrading.

  10. Although we have eight one-digit industries and ten one-digit occupations, the number of industry-occupation cells is not 80. Some occupations do not appear in all industries. For example, the occupation “market-oriented agricultural and fishery workers” only appears in agriculture-related industries. There are also some industry-occupation cells with very small cell size. The number of individuals in the data files working in the “agricultural products” industry with the occupation of “managers or professionals,” for instance, is often below ten. We record the employment share of an industry-occupation cell in any 1 year as “missing” if there are fewer than 30 individuals in that cell.


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We thank Zhigang Li, Hon-Kwong Lui, James Vere, Junsen Zhang, three anonymous referees, and participants in the 2007 APEA, CEA and CES conferences for their comments on this paper. Part of this research is funded by the Hong Kong Institute of Economics and Business Strategy. We gratefully acknowledge its support.

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Correspondence to Jun Han.

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Responsible editor: Junsen Zhang



Table 10 Recoding the industry variables according to the codebook of census data

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Han, J., Suen, W. Age structure of the workforce in growing and declining industries: evidence from Hong Kong. J Popul Econ 24, 167–189 (2011).

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  • Industry-specific human capital
  • Industry upgrading
  • Sectoral shifts

JEL Classification

  • J10
  • J23
  • J24