Does Outward Foreign Direct Investment Boost Employment in the Home Country? Evidence from China’s Microlevel Data

ABSTRACT

Does outward foreign direct investment (OFDI) create (or transfer) employment in (or from) the home country? To examine this question, we analyze how OFDI with different motivations influences employment in the home country, using micro data from 552 Chinese manufacturing enterprises investing abroad. We use two sets of indices, namely, the absolute employment amount and relative employment amount, and adopt a difference-in-differences methodology. Overall, we find that OFDI increases both the absolute and relative employment amount. In particular, market-seeking OFDI increases the absolute employment amount, but not the relative employment amount. Technology-seeking OFDI significantly promotes both absolute and relative employment amount of the parent firm in the home country, while resource-seeking and efficiency-seeking OFDI have no significant influence on employment at enterprises in the home country. The effect on home-country employment depends on the host country. Finally, investment in developed countries can significantly increase home-country employment, while investment in developing countries does not have a significant influence on home-country employment.

KEY WORDS:

• employment
• motivation of OFDI
• outward foreign direct investment (OFDI)

JEL:

• F41
• E24
• F21

Notes

1. Data source: http://news.163.com/17/1207/04/D51DVENI0001875P.html.

2. Dunning (1998) classified OFDI into resource-seeking OFDI, market-seeking OFDI, strategic asset-seeking OFDI and efficiency-seeking OFDI. In this article, the definitions of resource-seeking OFDI and market-seeking OFDI were the same as those of Dunning. However, our definitions of technology-seeking OFDI and efficiency-seeking OFDI differed from those of Dunning. The difference between Dunning’s concept of strategic-seeking OFDI and our use of the term technology-seeking OFDI as used in this article is that the former refers to the acquisition of strategic assets, including technology, brand, military, petroleum, etc., whereas the latter refers to OFDI that seeks to obtain high-end technologies by investing in overseas high-end equipment sectors and finally acquiring the core competitiveness of enterprises. Dunning’s concept of efficiency-seeking OFDI focuses on improving the efficiency of enterprises, by investing in areas with low labor costs and rich resources. In this article, efficiency-seeking OFDI mainly refers to investment in the sectors that engaged in production, sales, and after-sales.

3. The main purpose of this kind of investment is to study and undertake the advanced overseas technologies. Therefore, we believe that this kind of investment will increase the demand for high-end labor and does not have an obvious impact on low-end technical labor.

4. First, samples that lacked key financial indicators (for instance, gross output, gross fixed assets, sales revenue, and industrial output) were eliminated; second, enterprises with fewer than 10 employees were eliminated; third, eliminate enterprises without specific time of foundation and industrial properties were eliminated; fourth, data from mining industry, power generation, gas, and hydro-power industries as well as supply industry were eliminated, leaving only data from the manufacturing industry.

5. Represented by enterprise’s sales amount divided by total labor.

6. We used the Levinsohn-Petrin Method (2003). In our calculations, industrial added value, capital investment, and intermediate input were deflated in accordance with the price index and fixed-asset price index from the year 2000, while labor input L was represented in the enterprises’ average annual employment numbers. When using enterprise-panel data to estimate TFP, two problems will emerge. The first is the simultaneity problem. Compared to outsiders, enterprises have more information about their productivity, and based on which, they decide how much to invest on factors. The second is the entry and exit of enterprises (entry and exit). Under normal circumstances, the older the enterprise, the stronger its ability to resist risks, and the greater the probability of its survival. Therefore, Olley and Pakes (1996) adopted the semiparametric estimation method to effectively solve the endogenous problem of input elements. The Olley-Pakes method can provide a consistent estimate of the production function at the enterprise level. However, in the actual measurement of the enterprise TFP, it is required that the proxy variable (investment) always has a monotonic relationship with the total output. This means that those samples with zero investment cannot be estimated. Levinsohn and Petrin (2003) developed a new TFP method for this problem. Instead of using the investment amount as a proxy variable, they used the intermediate input index as a proxy variable. Therefore, we chose the Levinsohn-Petrin method to measure enterprise TFP.

7. Helpman, Melitz, and Yeaple (2004) pointed out that only the more productive firms choose to serve the foreign markets, and the most productive among this group will further choose to serve the overseas market via FDI. This conclusion was confirmed by Kelle et al. (2013) and Tanaka (2015).

8. We used the Mahalanobis distance matching to perform match sampling with replacement, so the matching sample was smaller than the experimental group samples.

Additional information

Funding

This work was supported by Ministry of Education of Humanities and Social Science Project (No.19YJC790045; No. 16YJC790023), Fundamental Research Funds for the Central Universities (No.19SZYB09). National Natural Science Foundation of China (No. 71873041; No. 71603060; No. 71573058), Guangdong Province Humanities and Social Sciences Key Research Project&Annual Project of Institute of Studies for the Great Bay Area of Guangdong University of Foreign Studies (No. 2018YGA002), Institute of City Strategy Studies Research Base Project (No. JD201801), Key Grant Projects of Philosophy and Social Sciences Research, Ministry of Education of China (No. 16JZD018), Natural Science Foundation of Guangdong, China (No. 2017A030313422), National Social Science Foundation (No.15ZDC038), Program for Innovative Research Team in University (No. IRT_17R26).