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The impact of offshoring on temporary workers: evidence on wages from South Korea

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Abstract

Trade literature has found that the impact of globalization on the domestic labor market depends, among other factors, on the sourcing country’s income level, the education level of domestic workers, and the occupations involved. This paper investigates another factor that might determine the effects of globalization on the domestic labor market: the worker’s contract type (i.e. permanent vs. temporary contract). We pay particular attention to wages and examine whether the contract type influences the impact of offshoring. Individual-level wage data from the Korean Labor & Income Panel Study during 1999–2007, linked to industry-level offshoring data from the World Input–Output Database are used to answer this question. Even after controlling for individual worker and employer characteristics, industry, and occupation, we find that South Korean manufacturing workers’ wages increase as offshoring increases, but this impact is significantly weaker for temporary workers. Thus, our findings support public concern that globalization exacerbates inequality and shows that one potential channel of growing inequality is the contract type.

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Notes

  1. See Yi (2003) and Kohler and Smolka (2011).

  2. The literature on trade and wage debate goes back to the 1990s. Please see Feenstra (2004) for the surveys.

  3. See Goldberg and Pavcnik (2005) for Columbia, Menezes-Filho and Muendler (2011) and Kovak (2013) for Brazil, and Topalova (2010) for India.

  4. European countries where legislation protecting permanent workers is particularly strong and unemployment rates are high have adopted a policy of relaxing systems of employment protection by allowing firms greater freedom to create temporary jobs. This policy creates so called dual labor markets with relatively weakly protected temporary workers and well-protected permanent workers. Blanchard and Landier (2002) and Cahuc and Postel-Vinay (2002) suggest that such reforms may not lower unemployment. Also, the extent to which temporary jobs act as stepping stones to permanent jobs is unclear (Booth et al. 2002; Autor and Houseman 2010).

  5. Jung (2009) finds that firms facing global competition are more likely to hire temporary workers than those restricted to the domestic market. Hur (2003) suggests that lower tariffs due to the FTA would increase the proportion of temporary workers.

  6. It is not unusual for the employer to force the employee to retire in his or her early 50s in Korea, so the retired workers would have no choice but to accept low-paying temporary jobs. Gender inequality in favor of male workers has long been an issue in the Korean labor market.

  7. Labor unions do not exist for 75 % of wage workers in Korea.

  8. The OECD average was 2.199 and Korea's index was 3.036, which made it the third-strictest country among OECD countries in 1997. The OECD average was 2.251 and Korea's index was 2.369 in 2007.

  9. A similar argument is used in Baumgarten et al. (2013). See also Grossman (2013).

  10. Another potential source of correlation is measurement error of offshoring. However, as noted in Schwörer (2013), Timmer (2012) and Görg and Görlich (2012), such concerns are mitigated by the use of the WIOD, which provides a far more reliable measure of offshoring than the method based on input–output tables generally used in the literature.

  11. More than 80 % of workers do not experience a change in their contract type. We will also report the regression results using the whole sample.

  12. More details on the endogeneity issue are discussed in the empirical strategy section.

  13. The National Statistics Office started collecting data on job contract type from 2002 and the data has been publicly available from 2004.

  14. Details about the data are in the data section and the “Appendix”.

  15. There are some yearly changes, but the difference between temporary and permanent workers is persistent.

  16. Financial benefits include severance package, incentives, overtime compensation, and paid vacation.

  17. Besides this technical reason, we want to exclude the possibility of an abnormal year affecting our results because the Asian Financial Crisis (1997–1998) severely affected the Korean economy. For a similar reason, we excluded 2008 (the Great Recession) data as well.

  18. Note that earnings for non-wage workers such as self-employed and family business have many missing values.

  19. We will also report the regression results with the dropped 20 % included.

  20. It is notable that the observation for the size of employer is significantly lower. We checked whether it affects our regression results and confirmed that our regression results without the size are consistent with our main results.

  21. International globalization trends often serve as an instrument for a specific country's globalization activities. In Autor et al. (2014), for example, U.S. imports from China are instrumented by world-wide imports from China and Menezes-Filho and Muendler (2011) use imports into Brazil's export destinations from elsewhere around the world as instruments for Brazil's exports to those destinations. See also Görg and Görlich (2012), who use world offshoring activities as instruments for German offshoring activities.

  22. It should be noted that some firm characteristics that influence wages cannot be controlled due to the limitations of the data. For example, Amiti and Davis (2012) show that the wage impact of trade liberalization could vary depending on the firm's global engagement (i.e. whether import-competing firms or exporting firms). Only recently, researchers have managed to exploit micro-level data and construct employee-employer linked datasets (Hummels et al. 2014), but they are not publicly available.

  23. These categories are public officers, professionals (such as physicists), pseudo-professionals (such as airplane technicians and nurses), administrative workers, service workers, sales workers, agricultural or fishing related workers, craft workers (such as automobile mechanics), pseudo-craft workers (such as drywall installers), and laborers (such as truck drivers).

  24. If an individual is nested under an industry, the standard errors should be clustered at the higher industry level, but about 80 % of individuals switched industries during the sample period. Clustering at the industry level only produces similar results.

  25. We don't report the estimates on the control variables to save space.

  26. The major topics change annually.

  27. http://www.kli.re.kr/klips/en/datadown/lst.eklips-0500. The dataset is freely available after registering for a membership in KLI.

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Acknowledgments

This work was supported by National Research Foundation of Korea Grant, funded by the Korean Government (NRF-2013S1A3A2054749). We thank to anonymous referees for the valuable comments. All remaining errors are our own.

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Authors and Affiliations

  1. Department of Economics, Korea University, 5-1 Anam-dong, Sungbuk-gu, Seoul, 136-701, Korea

    Hongshik Lee

  2. Department of Economics, Fogelman College of Business and Economics, University of Memphis, Memphis, TN, USA

    Joonhyung Lee

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Correspondence to Hongshik Lee.

Appendix: Korean Labor and Income Panel Study (KLIPS)

Appendix: Korean Labor and Income Panel Study (KLIPS)

The Korean Labor & Income Panel Study (KLIPS) is a longitudinal survey of households and individuals residing in urban areas. The data provides information on economic status, income expenditures, education, job training, and social activities of households and individuals. This survey was initially designed to perform two-stage stratified sampling: once the enumeration districts (EDs) were randomly sampled, the households were proportionally selected within the EDs. During the initial survey, 19,025 EDs (10 % of the total population) were selected, including 1,100,032 households, and 5,000 households were finally chosen within the selected EDs for the initial survey in 1998. Despite the low attrition rate, the Korea Labor Institute (KLI) has continued to replace vanished households with new ones to maintain the number of observations. The survey targets household members aged 15 and over, and questionnaires for individuals are different for employed and unemployed workers. Both questionnaires include personal characteristics such as age, gender, education, marital status, life satisfaction, and economic status. For employed workers, the survey provides general information on working environment such as wages and working hours. For unemployed workers, the unemployment status such as unemployment duration, job-seeking activities, and reservation wages is mainly investigated. From the 3rd wave (2000), KLIPS initiated an additional in-depth survey on certain topics (i.e. youth, health, education, etc.), which means that detailed cross section data related to specific topics are provided as well.Footnote 26 KLI provides a general introduction to the dataset, and the dataset is available on the website.Footnote 27

See Fig. 4 and Table 8.

Fig. 4
figure 4

The composition of Korean workers. Source: National Statistics Office

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Table 8 Definition and source of variables
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Lee, H., Lee, J. The impact of offshoring on temporary workers: evidence on wages from South Korea. Rev World Econ 151, 555–587 (2015). https://doi.org/10.1007/s10290-015-0215-z

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