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Does Outward FDI Generate Higher Productivity for Emerging Economy MNEs?—Micro-level Evidence from Chinese Manufacturing Firms

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Outward Foreign Direct Investment of Chinese Enterprises

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Abstract

This chapter investigates whether emerging economy multinational enterprises (EMEs) that undertake outward foreign direct investment (OFDI) become more productive, controlling for the self-selection into the global investment market. Particularly, we focus on the moderating effects of firm heterogeneity on the OFDI-productivity nexus. A theoretical framework incorporating the resource-based views and institutional theory is established and the propensity-score matching and difference-in-difference (DID) approaches are combined to test the framework, utilizing unique data on Chinese manufacturing firms over the sample period 2002–2008. We find that EMEs turn to be generally more productive after they conduct OFDI, but this productivity effect varies depending on the parent firm and investment strategy heterogeneity. Our results suggest that EMEs without state ownership but with stronger absorptive capability gain higher and more sustainable productivity effects and such gains are higher for EMEs investing in OECD than in non-OECD countries. Policy and managerial implications are discussed.

This chapter is published in International Business Review by Li Linjie, Xiaming Liu, Dong Yuan, Miaojie Yu.

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Notes

  1. 1.

    Firm productivity is a component of a country’s production efficiency, which plays an essential role in shaping a country’s GDP growth. Therefore, we choose firm productivity as our dependent variable, to some extent, to shed some light on a country’s growth.

  2. 2.

    Due to space limitation, a summary of country and industry level studies is not included in the table, but available upon request.

  3. 3.

    In fact, the aggregated data on the industrial sector in the annual China’s Statistical Yearbook and China’s Industry Economy Statistical Yearbook are compiled from this data set.

  4. 4.

    When estimating the probability to invest abroad in one year, we would use firms’ production data in the previous year, namely when the previous year is 2001, we would also utilize firms’ production data in 2001. Thus more exactly speaking, the production data utilized in this chapter range from 2001 to 2008.

  5. 5.

    Because the intermediary input variable is missing in 2008, we impute this variable using a conventional method. According to China’s Statistical Yearbook, value added = total output − intermediary input + value added tax payable. We can impute the missing data by the equation, intermediary input = total output − valued added + value added tax payable. Here we assume a firm’s valued-added rate in 2008 equals to that in 2007. Depending on the value-added rate in 2007 and the total output in 2008, we can obtain firms’ value added in 2008, and then firms’ intermediary inputs in 2008 can be straightforwardly derived. Imputing the intermediary input data in 2008 helps extend the sample. If we only utilize the sample 2002–2007, our findings do not change significantly.

  6. 6.

    Considering that the date on which an investment was approved differs from that on which the subsidiary was established, we spared no effort to search the internet (the information from the parent firm’s website is labeled top priority) to confirm the exact date of subsidiary establishment. If the establishment date is unavailable, the year in which the investment was approved is used to approximate the year in which the subsidiary was established.

  7. 7.

    In 2002, the former Ministry of Foreign Trade and Economic Cooperation of China and China’ National Bureau of Statistics jointly developed China’s first Outward Foreign Direct Investment Statistical System.

  8. 8.

    We adopt the perpetual inventory method as the law of motion for real capital and real investment. The nominal and real capital stock constructed following Brandt et al. (2012). We depend on the firm’s own information in the dataset to construct firm’s real depreciation ratio.

  9. 9.

    Here is an implicit assumption, namely, firms which are more productive now would have higher expected return rates, and hence those firms would invest more in that period. Under a few assumptions of production technology, (Pakes, 1996) has verified this implicit assumption.

  10. 10.

    In fact, to alleviate the influence of business cycle and control for the industry heterogeneity, we estimate the propensity score on a year-by-year and industry-by-industry basis.

  11. 11.

    Although there is an argument that the newness of the subsidiary could explain the improvement in firm productivity, our analysis still holds. Frist of all, it’s true that subsidiaries started in different years probably take different technologies, but our estimation results still can show the positive productivity spillover effect through the backward linkage if parent firms benefit from engaging in OFDI. Furthermore, our analysis is to compare the productivity changes of parent firms with their counterfactuals (firms that operate in the same year and industry with the treatment group, but not engage in OFDI) rather than directly compare firms with OFDI in different years. Moreover, our sample ranges from 2002 to 2007 (mainly between 2004 and 2007), and hence technologies used in a given manufacturing industry may be relatively similar during such a short time period. More importantly, our results still hold if we restrict the estimation sample to 2004–2007.

  12. 12.

    The initial value of is set to 2.

  13. 13.

    After sorting the sample by the propensity score, we search the counterfactual observations for the treated group by searching upward and downward. In fact, we find two firms for each treated one. Some other matching methods are also utilized, such as finding out one or four counterfactual observations for each treated firm, but our main results do not change significantly.

  14. 14.

    We adopt firms that never invest abroad in the sample period as the control group. There is an alternative way to choose the control group, i.e., treating firms that just do not invest abroad in the given year as the control group. However, the latter approach inevitably neglects the lagged effect of investing abroad in the previous years. Therefore, our estimation results are based on the former approach.

  15. 15.

    This finding is similar to the conclusion about the productivity effect of exporting by De Loecker (2007).

  16. 16.

    In this table, the number of treated units is less than that of the treated ones after matching. There are several reasons for this situation. First, production information prior to the year when firms started to invest abroad is needed for matching, and firms with missing pre-OFDI information are omitted. Second, firms that cannot be matched are dropped because of the violation of the balance condition hypothesis. Third, when calculating TFP with the augmented Olley-Pakes approach, firms with missing covariates are deleted. These are also the cases for later estimations.

  17. 17.

    By the official definition reported in China Statistical Yearbook (2008), SO-EMEs include firms such as domestic SO-EMEs (code: 110), state-owned joint venture firms(141), and state-owned and collective joint venture firms(143), but exclude state-owned limited corporations (151), based on the registration type.

  18. 18.

    To be accurate, for those that have never invested abroad, we split them based on whether they had R&D prior to that year within each industry for each year.

  19. 19.

    An alternative method to test the role of absorptive capability in moderating the productivity effect of OFDI is to directly split the matched results from Sect. 5.1 into two groups by firms’ pre-OFDI R&D status. But it may overestimate the productivity effect for firms that had pre-OFDI R&D, compared to our approach.

  20. 20.

    Members of OECD countries used in this chapter are restricted to those that had joined OECD before 2009, because of our sample period. For more information about the list of OECD members, please refer to http://www.oecd.org/about/membersandpartners/list-oecd-membercountries.htm.

  21. 21.

    In order to get rid of the mixed effect generated by firms that invest both in OECD countries and in non-OECD countries during the starting year, we drop all the observations of those firms in this section.

  22. 22.

    The detailed results are not reported due to space limitation, but are available upon request.

  23. 23.

    The detailed results are not reported there due to space limitation, but available upon request.

  24. 24.

    In fact, this is to treat OFDI as a component of TFP, and explicitly test whether starting to invest abroad can promote parent firms’ productivity keeping other production factors unchanged.

  25. 25.

    The detailed results are not reported here due to space limitation, but available upon request.

  26. 26.

    The results are available upon request.

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  1. School of Economics, Peking University, Beijing, China

    Wei Tian

  2. Liaoning University, Shenyang, China

    Miaojie Yu

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Tian, W., Yu, M. (2022). Does Outward FDI Generate Higher Productivity for Emerging Economy MNEs?—Micro-level Evidence from Chinese Manufacturing Firms. In: Outward Foreign Direct Investment of Chinese Enterprises. Contributions to Economics. Springer, Singapore. https://doi.org/10.1007/978-981-19-4719-3_5

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