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A note on determinants of Japanese foreign direct investment in Southeast Asia, 2008–2015
Economic Analysis and Policy 62 (2019) 192–196
Contents lists available at ScienceDirect
Economic Analysis and Policy journal homepage: www.elsevier.com/locate/eap
Recent trends in economic research
A note on determinants of Japanese foreign direct investment in Southeast Asia, 2008–2015 Akihiro Kubo Graduate School of Economics, Osaka City University, 3-3-138 Sugimoto, Sumiyoshi-ku, Osaka 558–8585, Japan
article
info
Article history: Received 21 May 2018 Received in revised form 16 March 2019 Accepted 16 March 2019 Available online 25 March 2019 JEL classification: F4 Keywords: Foreign direct investment Currency appreciation Industry-specific panel data Southeast Asia
a b s t r a c t The appreciation of the Japanese yen does not explain why Japanese firms have doubled foreign direct investment (FDI) in Southeast Asia since the late 2000s. This study investigates the effects of exchange rates and other factors on new Japanese FDI in Indonesia, Malaysia, the Philippines, and Thailand, using industry-specific panel data from 2008 to 2015. It is found that new FDI was more strongly correlated with the expectation of consumption demand than with exchange rate movements for Indonesia and Thailand, while the agglomeration of Japanese firms predominantly affected new FDI in Malaysia and the Philippines. © 2019 Economic Society of Australia, Queensland. Published by Elsevier B.V. All rights reserved.
1. Introduction Since the start of the most recent period of appreciation of the Japanese yen, Japanese firms have increased their foreign direct investment (FDI). Traditional trade theories offer two explanations for the relationship between exchange rates and FDI movements in the 1980s and 1990s. One is the acquisition of firm-specific assets, mainly in industrialized countries, due to internalization. The other is the establishment of new production bases in developing countries due to their comparative labor wages. In particular, Japanese manufacturing industries, which had faced declining international competitiveness with rising domestic labor costs, acted to take advantage of a reduction in outward investment costs due to the appreciation of the yen by relocating their production bases overseas. These industries increased FDI, predominantly in China due to its relatively cheap labor costs, allowing firms to recover international competitiveness, particularly in labor-intensive industries such as textiles. However, the traditional theories are not fully consistent with events taking place since the late 2000s. Fig. 1 shows that real exchange rate movements do not explain the doubling of FDI in Indonesia, Malaysia, the Philippines, and Thailand. In addition, Panels B and C of Fig. 1 show that real exchange rate movements almost consistently fail to correlate with new FDI in Malaysia and the Philippines. Recently, Southeast Asian FDI-recipient countries, which were the destination of relocated production bases, are being recognized as new sales markets (Japan External Trade Organization, 2015). Indonesia and Thailand, which are expected to have large consumption demand and are centers of business development among their neighboring countries, have attracted large amounts of FDI year after year. Surprisingly, this trend continued even when yen appreciation stabilized. This paper seeks to provide empirical evidence related to the trend. E-mail address: [email protected]. https://doi.org/10.1016/j.eap.2019.03.003 0313-5926/© 2019 Economic Society of Australia, Queensland. Published by Elsevier B.V. All rights reserved.
A. Kubo / Economic Analysis and Policy 62 (2019) 192–196
193
Fig. 1. The number of Japanese FDIs and real exchange rate movements. Note: The left vertical axis represents the real exchange rate index and the right vertical axis represents the number of new FDIs. Source: International Monetary Fund and Japan’s Ministry of Economy, Trade and Industry.
Many previous studies have empirically investigated the relationship between exchange rate and FDI movements. For example, Caves (1989), Froot and Stein (1991), and Klein and Rosengren (1994) found a significant relationship between the depreciation of the U.S. dollar and inward FDI in the United States, while Stevens (1998) found little evidence of correlation between the two trends. In addition, Blonigen (1997) and Kogut and Chang (1996) examined the relationship between yen appreciation and Japanese FDI in the United States, and suggested that the real exchange rate significantly affected FDI. Baek and Okawa (2001) and Takagi and Shi (2011) are notable examples of studies that examined and confirmed the relationship between yen appreciation and FDI in Asia. To the best of our knowledge, few studies have analyzed recent data in this manner. In this paper, we investigate the effects of the exchange rate and other economic factors on new Japanese FDI in Southeast Asia, using an industry-specific panel data set for new FDI in Indonesia, Malaysia, the Philippines, and Thailand during 2008–2015. The remainder of this paper is organized as follows. Section 2 describes the theoretical relationship between some types of FDI and exchange rate movements while Section 3 presents the estimation methodology and data. Section 4 discusses the estimation results and Section 5 concludes the paper. 2. Some theories concerning FDI and exchange rate movements The effects of exchange rate movements on different types of FDI (e.g., vertical, export-platform, and horizontal) can be different. We summarize the relationships between exchange rates and the various theories of FDI. First, the vertical FDI model seems to be representative of the relationship between a developed (home) country and a developing (host) country that supplies cheaper labor. In this model, the FDI depends on the trade-off between the production costs of intermediate goods in a host country and their costs of import to a home country (e.g., Helpman, 1984). If the labor costs are lower in the host country, the FDI can offset the trade costs by reducing production costs. However, in the case of vertical FDI, the effect of the appreciation of the home currency on the FDI behavior may be insignificant, when the trade costs increase due to the currency appreciation and offset the saved production costs.
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A. Kubo / Economic Analysis and Policy 62 (2019) 192–196
Second, export-platform FDI, which facilitates export of intermediate goods to third countries rather than a home country, has increased recently. The FDI depends on third-country factors such as the accessibility of the third countries, and is not dependent on costs of trade to the home country (e.g., Blonigen et al., 2007; Ekholm et al., 2007). In the case of export-platform FDI, the effect of the appreciation of the home currency on the FDI behavior may be minor because the impact of changes in the bilateral exchange rate may not significantly affect the exports to third countries. Finally, horizontal FDI, where multi-national companies carry out the same economic activities in a host country depends on the trade-off between fixed production costs in the host country and export costs (Markusen, 1984). If the market size of the host country is relatively large, fixed costs can be offset by saving on export costs. In particular, horizontal FDI seems appropriate where a firm in a developed (home) country seeks access to the large market of another developed (host) country. In the case of horizontal FDI, appreciation of the home currency may increase FDI because the reduction in host country fixed costs may be larger than savings on export costs. 3. Estimation and data We estimate the equation for new FDI as follows:
(
JPAV
New FDIi,t = RERt + πi,t
+ GDPtJP + GDPKt + NiJPF ,t −1
)
(1)
where New FDIi,t stands for the number of new Japanese FDIs (project base) in 2-digit Standard Industrial Classification industry (i ) and year (t ).1 As one of the explanatory variables, we employ the log of the real exchange rates (RERt ) that are constructed using the yen–Indonesian rupiah, yen–Malaysian ringgit, yen–Philippine peso, and yen–Thai baht nominal exchange rates, as well as the corresponding consumer price index for each country. An increase in the real exchange rate represents a real appreciation of the Japanese yen. Therefore, we expect a positive correlation between FDI and real exchange rates. To control for Japanese demand in each industry, we include the share rate of Japanese value JPAV JP added by industry (πi,t )2 and the annual growth rate of Japanese real GDP (GDPt ). We expect a positive relationship between these and FDI. We also control for supply-side factors in the host countries. Expectation of future and increased consumption in this region is assumed to be correlated with FDI, so we include the log of GDP per capita (GDPKt ) as the representative variable and expect values to be positive in the equation.3 In addition, we include the previous annual JPF results of local Japanese firms (Ni,t −1 ) to represent the value of each Japanese industrial agglomeration, and expect positive correlations with FDI. The FDI-related data are obtained from Japan’s Ministry of Economy, Trade and Industry.4 Data for nominal exchange rates, consumer price indices, and real GDP are obtained from the International Monetary Fund. The share of Japanese value added by industry is obtained from the Cabinet Office, Government of Japan, and the GDP per capita data from the World Bank. To investigate the effects of other representative variables on expected local demand and the agglomeration effect, for Thailand,5 we re-estimate these equations using industry-level GDP growth or industry-level FDI inflow from abroad per GDP. These data are obtained from the Bank of Thailand. 4. Empirical results Tables 1 and 2 show the estimates for the fixed effect model for the determinants of new Japanese FDI in four Southeast Asian countries. Columns 1–3 of Table 1 report the estimates for all Thai industries from 2008 to 2015. The results for Column 1 seem to be better than the others because inward FDI and value-added growth in each industry are statistically insignificant and have an unexpected sign. In Column 1, the relationship between the number of new FDIs and exchange rate movements, which is one of the greatest concerns here, is significantly positive. Thai GDP per capita and the number of local Japanese firms are also significantly positive, as predicted.6 Regarding the agglomeration effect, the Japanese clusters affect mainly Japanese FDI decision making. On the other hand, while the effect of the share of Japanese value added by industry is significant, Japan’s GDP growth is not. Finally, each fixed effect in this model is significant, as shown by the results of log-likelihood ratio tests. 1 Due to data limitations, we must use data for the short sample period 2008 to 2015, and classify firms into 19 industry groups: Food; Textiles; Lumber and Pulp; Chemicals and Pharmaceuticals; Petroleum; Glass and Ceramics; Iron, Non-ferrous and Metals; General machinery; Electric machinery; Transportation equipment; Other manufacturing; Farming, Forestry, Fishery, and Marine products; Mining; Construction; Transportation; Communications; Wholesale and Retail; Services; Other non-manufacturing. 2 We use share rates (per GDP) to control the time series data. 3 We use GDP per capita rather than GDP or the size of population because this variable is representative for each economic performance as consumption. 4 For further detail regarding this data source, see the website of Japan’s Ministry of Economy, Trade and Industry (http://www.meti.go.jp/english/ statistics/tyo/gaisikei/index.html). 5 Due to data limitations, we cannot perform this estimate for the other countries. 6 High GDP per capita also means high labor costs, so it has a front–back relationship. However, we assume here that the expectation for significant consumption demand outweighs the effect of labor costs.
A. Kubo / Economic Analysis and Policy 62 (2019) 192–196
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Table 1 Empirical results, Thailand. Independent variable
Dependent variable: new Japanese FDI All industries
Manufacturing
2008–2015
2010–2015
2008–2015
2010–2015
(1)
(2)
(3)
(4)
(5)
(6)
Real exchange rate
6.993 (2.68) [2.61]***
7.414 (2.98) [2.49]**
2.556 (2.02) [1.26]
12.235 (4.06) [3.02]***
4.455 (1.64) [2.72]***
5.360 (2.44) [2.20]**
Japanese Industry value-added share
2.253 (0.90) [2.51]**
5.636 (1.23) [4.60]***
2.116 (0.92) [2.29]**
3.519 (1.31) [2.68]***
−0.085 (0.86) [−0.10]
0.067 (1.30) [0.05]
Japanese economic growth
−0.037 (0.10) [−0.38]
−0.107 (0.11) [−0.96]
0.137 (0.10) [1.39]
−0.005 (0.19) [−0.02]
−0.018 (0.06) [−0.30]
−0.044 (0.11) [−0.41]
GDP per capita
15.396 (6.07) [2.54]**
20.900 (6.67) [3.13]**
38.475 (11.47) [3.35]***
12.156 (3.83) [3.17]***
20.741 (6.30) [3.29]***
0.031 (0.01) [2.99]***
0.008 (0.01) [0.56]
−0.014 (0.01) [−1.47]
−0.035 (0.01) [−2.49]**
Local industry value-added growth
−0.018 (0.03) [−0.66]
Local Japanese firms
0.025 (0.01) [2.37]**
Local industry inward FDI
−0.279 (0.23) [−1.23]
Likelihood ratio test (Cross-section Chi-square) Observations
76.05***
123.17***
72.91***
71.30***
34.64***
38.45***
152
152
152
114
88
66
Note: ( ) denotes standard errors, [ ] denotes t-value. ***, ** and * indicate that the 1%, 5% and 10% confidence intervals are satisfied, respectively. Table 2 Empirical results, other countries. Independent variable
Dependent variable: new Japanese FDI Indonesia
Malaysia
Philippines
2008–2015 (1)
2010–2015 (2)
2008–2015 (3)
2010–2015 (4)
2008–2015 (5)
2010–2015 (6)
Real exchange rate
13.111 (3.75) [3.49]***
13.681 (5.46) [2.51]**
1.396 (0.81) [1.52]
0.025 (1.19) [0.02]
2.024 (0.94) [2.15]**
2.340 (2.72) [0.86]
Japanese Industry value-added share
1.717 (0.72) [2.37]**
2.006 (0.99) [2.02]**
−0.030
−0.477 (0.31) [−1.37]
−0.103 (0.27) [−0.38]
−0.072
(0.23) [−0.13]
0.102 (0.08) [1.34]
−0.157 (0.18) [−1.04]
0.028 (0.02) [1.22]
−0.108 (0.05) [−2.06]**
−0.006 (0.03) [−0.22]
(0.08) [−1.40]
GDP per capita
14.606 (3.00) [4.43]***
16.598 (6.74) [2.46]**
2.981 (1.56) [1.91]*
−0.580 (2.52) [−0.23]
3.806 (1.85) [2.06]**
3.608 (6.54) [0.55]
Local Japanese firms
0.006 (0.02) [0.40]
−0.035 (0.02) [−2.02]**
0.045 (0.01) [4.87]***
0.021 (0.01) [1.67]*
0.071 (0.02) [3.97]***
0.073 (0.03) [2.93]***
60.72***
75.12***
73.17***
76.40***
38.74***
32.51***
152
114
152
114
152
114
Japanese economic growth
Likelihood ratio test (Cross-section Chi-square) Observations
(0.41) [−0.17]
−0.104
Note: ( ) denotes standard errors, [ ] denotes t-value. ***, ** and * indicate that the 1%, 5% and 10% confidence intervals are satisfied, respectively.
Column 4 reports the estimates for the sample 2010 to 2015, corresponding to the recent substantial investment in Thailand. The number of new Japanese FDIs has a significantly positive relationship with exchange rate movements,
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A. Kubo / Economic Analysis and Policy 62 (2019) 192–196
Japanese industry-level value-added share, and Thai GDP per capita. In particular, the coefficient of GDP per capita is approximately twice as large as that for the period 2008–2015, which also implies that large demand in middle-income countries such as Thailand strongly affects new FDI behavior. Conversely, the number of local Japanese firms has no relationship with new FDI. In addition, although the sample sizes become small, we examine the model for manufacturing industries for the two sample periods 2008–2015 and 2010–2015, and report the results in Columns 5–6. Coefficients of both the real exchange rate and GDP per capita are statistically significant. This result is consistent with Blonigen (1997), suggesting that firmspecific assets, via real exchange rates, may be more important in manufacturing industries than in other industries. However, in Column 6, the number of local Japanese firms has a significant but negative relationship with the FDI. This result may imply that there is an optimal FDI stock and a time lag in the adjustment of recent new investments in Thailand. Table 2 presents the results for new Japanese FDI in the other Southeast Asian countries featured in this study – Indonesia, Malaysia, and the Philippines – for both the sample periods. Columns 1–2 show that the number of new Japanese FDIs is positively correlated with the yen–Indonesian rupiah exchange rate movements, the share of Japanese value added by industry, and Indonesian per capita GDP. However, the number of local Japanese firms has a significant but negative relationship with FDI in 2010–2015, as was observed for Thai manufacturing industries. Columns 3–6 show that new Japanese FDI in Malaysia and the Philippines are affected by the number of local Japanese firms (for both periods), which implies that Japanese industrial agglomeration has played an important role in both countries. However, during 2010–2015, there is no longer a relationship between GDP per capita and new Japanese FDI in Malaysia, while the yen–Philippine peso exchange rate and GDP per capita are not correlated with new Japanese FDI in the Philippines. 5. Concluding remarks This study employed industry-specific panel data analysis to investigate the economic factors affecting Japanese FDI in Southeast Asia from 2008 to 2015. We arrived at some key findings. The relationship between exchange rate movements and new FDI was positive and statistically significant in Indonesia and Thailand. Moreover, expectation for consumption demand more strongly affected new FDI in these countries. This result is consistent with the character of horizontal FDI. Appreciation of the yen may increase FDI because it reduces fixed costs for operations in the host country, which become more likely to be lower than the export costs form Japan, due to the large consumption demand in Indonesia and Thailand. In addition, FDI in Thailand also fits the export-platform model because results show a relatively strong relationship between the FDI and local Japanese firms’ agglomeration, which is assumed to be consistent with the evidence that Thailand is the center of business development in the region. In Malaysia and the Philippines, local Japanese firms’ agglomeration was positively correlated with new FDI, while the relationship between exchange rate movements and new FDI was insignificant. This pattern of FDI seems to be consistent with the vertical model. We can assume that the trade costs for both countries increase due to the appreciation of the yen, and may offset the production cost savings achieved due to the relatively low labor costs. There is an important extension of this study that could be pursued in future research: a representative variable for the third-country effect could be included to examine whether the FDI fits the export-platform model. References Baek, I.M., Okawa, T., 2001. Foreign exchange rates and Japanese foreign direct investment in Asia. J. Econ. Bus. 53 (1), 69–84. Blonigen, B.A., 1997. Firm-specific assets and the link between exchange rates and foreign direct investment. Amer. Econ. Rev. 87 (3), 447–465. Blonigen, B.A., Davies, R.B., Waddell, G.R., Naughton, H.T., 2007. FDI in space: Special Autoregressive relationships in foreign direct investment. Eur. Econ. Rev. 51 (5), 1303–1325. Caves, R.E., 1989. Exchange rate movements and foreign direct investment in the United States. In: Audretsch, D.B., Claudon, M. (Eds.), The Internationalization of US Markets. New York University Press, New York. Ekholm, K., Forslid, R., Markusen, J.R., 2007. Export-platform foreign direct investment. J. Eur. Econom. Assoc. 5 (4), 776–795. Froot, K., Stein, J., 1991. Exchange rates and foreign direct investment: an imperfect capital markets approach. Q. J. Econ. 106 (4), 1191–1217. Helpman, E., 1984. A simple theory of international trade with multinational corporations. J. Political Econ. 92 (3), 451–471. Japan External Trade Organization, 2015. Survey of Japanese-affiliated firms in Asia and Oceania. https://www.jetro.go.jp/ext_images/en/reports/ survey/pdf/2015_01_biz.pdf. (Accessed 21 December 2015). Klein, M., Rosengren, E., 1994. The real exchange rate and foreign direct investment in the United States: relative wealth vs. relative wage effects. J. Int. Econ. 36 (3/4), 373–389. Kogut, B., Chang, S.J., 1996. Platform investments and volatile exchange rates: direct investment in the U.S. by Japanese electronic companies. Rev. Econ. Stat. 78 (2), 221–231. Markusen, J.R., 1984. Multinationals, multi-plant economies, and the gains from trade. J. Int. Econ. 16 (3–4), 205–226. Stevens, G., 1998. Exchange rates and foreign direct investment: a note. J. Policy Model. 20 (3), 393–401. Takagi, S., Shi, Z., 2011. Exchange rate movements and foreign direct investment (FDI): Japanese investment in Asia, 1987–2008. Japan World Econ. 23 (4), 265–272.
Contents lists available at ScienceDirect
Economic Analysis and Policy journal homepage: www.elsevier.com/locate/eap
Recent trends in economic research
A note on determinants of Japanese foreign direct investment in Southeast Asia, 2008–2015 Akihiro Kubo Graduate School of Economics, Osaka City University, 3-3-138 Sugimoto, Sumiyoshi-ku, Osaka 558–8585, Japan
article
info
Article history: Received 21 May 2018 Received in revised form 16 March 2019 Accepted 16 March 2019 Available online 25 March 2019 JEL classification: F4 Keywords: Foreign direct investment Currency appreciation Industry-specific panel data Southeast Asia
a b s t r a c t The appreciation of the Japanese yen does not explain why Japanese firms have doubled foreign direct investment (FDI) in Southeast Asia since the late 2000s. This study investigates the effects of exchange rates and other factors on new Japanese FDI in Indonesia, Malaysia, the Philippines, and Thailand, using industry-specific panel data from 2008 to 2015. It is found that new FDI was more strongly correlated with the expectation of consumption demand than with exchange rate movements for Indonesia and Thailand, while the agglomeration of Japanese firms predominantly affected new FDI in Malaysia and the Philippines. © 2019 Economic Society of Australia, Queensland. Published by Elsevier B.V. All rights reserved.
1. Introduction Since the start of the most recent period of appreciation of the Japanese yen, Japanese firms have increased their foreign direct investment (FDI). Traditional trade theories offer two explanations for the relationship between exchange rates and FDI movements in the 1980s and 1990s. One is the acquisition of firm-specific assets, mainly in industrialized countries, due to internalization. The other is the establishment of new production bases in developing countries due to their comparative labor wages. In particular, Japanese manufacturing industries, which had faced declining international competitiveness with rising domestic labor costs, acted to take advantage of a reduction in outward investment costs due to the appreciation of the yen by relocating their production bases overseas. These industries increased FDI, predominantly in China due to its relatively cheap labor costs, allowing firms to recover international competitiveness, particularly in labor-intensive industries such as textiles. However, the traditional theories are not fully consistent with events taking place since the late 2000s. Fig. 1 shows that real exchange rate movements do not explain the doubling of FDI in Indonesia, Malaysia, the Philippines, and Thailand. In addition, Panels B and C of Fig. 1 show that real exchange rate movements almost consistently fail to correlate with new FDI in Malaysia and the Philippines. Recently, Southeast Asian FDI-recipient countries, which were the destination of relocated production bases, are being recognized as new sales markets (Japan External Trade Organization, 2015). Indonesia and Thailand, which are expected to have large consumption demand and are centers of business development among their neighboring countries, have attracted large amounts of FDI year after year. Surprisingly, this trend continued even when yen appreciation stabilized. This paper seeks to provide empirical evidence related to the trend. E-mail address: [email protected]. https://doi.org/10.1016/j.eap.2019.03.003 0313-5926/© 2019 Economic Society of Australia, Queensland. Published by Elsevier B.V. All rights reserved.
A. Kubo / Economic Analysis and Policy 62 (2019) 192–196
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Fig. 1. The number of Japanese FDIs and real exchange rate movements. Note: The left vertical axis represents the real exchange rate index and the right vertical axis represents the number of new FDIs. Source: International Monetary Fund and Japan’s Ministry of Economy, Trade and Industry.
Many previous studies have empirically investigated the relationship between exchange rate and FDI movements. For example, Caves (1989), Froot and Stein (1991), and Klein and Rosengren (1994) found a significant relationship between the depreciation of the U.S. dollar and inward FDI in the United States, while Stevens (1998) found little evidence of correlation between the two trends. In addition, Blonigen (1997) and Kogut and Chang (1996) examined the relationship between yen appreciation and Japanese FDI in the United States, and suggested that the real exchange rate significantly affected FDI. Baek and Okawa (2001) and Takagi and Shi (2011) are notable examples of studies that examined and confirmed the relationship between yen appreciation and FDI in Asia. To the best of our knowledge, few studies have analyzed recent data in this manner. In this paper, we investigate the effects of the exchange rate and other economic factors on new Japanese FDI in Southeast Asia, using an industry-specific panel data set for new FDI in Indonesia, Malaysia, the Philippines, and Thailand during 2008–2015. The remainder of this paper is organized as follows. Section 2 describes the theoretical relationship between some types of FDI and exchange rate movements while Section 3 presents the estimation methodology and data. Section 4 discusses the estimation results and Section 5 concludes the paper. 2. Some theories concerning FDI and exchange rate movements The effects of exchange rate movements on different types of FDI (e.g., vertical, export-platform, and horizontal) can be different. We summarize the relationships between exchange rates and the various theories of FDI. First, the vertical FDI model seems to be representative of the relationship between a developed (home) country and a developing (host) country that supplies cheaper labor. In this model, the FDI depends on the trade-off between the production costs of intermediate goods in a host country and their costs of import to a home country (e.g., Helpman, 1984). If the labor costs are lower in the host country, the FDI can offset the trade costs by reducing production costs. However, in the case of vertical FDI, the effect of the appreciation of the home currency on the FDI behavior may be insignificant, when the trade costs increase due to the currency appreciation and offset the saved production costs.
194
A. Kubo / Economic Analysis and Policy 62 (2019) 192–196
Second, export-platform FDI, which facilitates export of intermediate goods to third countries rather than a home country, has increased recently. The FDI depends on third-country factors such as the accessibility of the third countries, and is not dependent on costs of trade to the home country (e.g., Blonigen et al., 2007; Ekholm et al., 2007). In the case of export-platform FDI, the effect of the appreciation of the home currency on the FDI behavior may be minor because the impact of changes in the bilateral exchange rate may not significantly affect the exports to third countries. Finally, horizontal FDI, where multi-national companies carry out the same economic activities in a host country depends on the trade-off between fixed production costs in the host country and export costs (Markusen, 1984). If the market size of the host country is relatively large, fixed costs can be offset by saving on export costs. In particular, horizontal FDI seems appropriate where a firm in a developed (home) country seeks access to the large market of another developed (host) country. In the case of horizontal FDI, appreciation of the home currency may increase FDI because the reduction in host country fixed costs may be larger than savings on export costs. 3. Estimation and data We estimate the equation for new FDI as follows:
(
JPAV
New FDIi,t = RERt + πi,t
+ GDPtJP + GDPKt + NiJPF ,t −1
)
(1)
where New FDIi,t stands for the number of new Japanese FDIs (project base) in 2-digit Standard Industrial Classification industry (i ) and year (t ).1 As one of the explanatory variables, we employ the log of the real exchange rates (RERt ) that are constructed using the yen–Indonesian rupiah, yen–Malaysian ringgit, yen–Philippine peso, and yen–Thai baht nominal exchange rates, as well as the corresponding consumer price index for each country. An increase in the real exchange rate represents a real appreciation of the Japanese yen. Therefore, we expect a positive correlation between FDI and real exchange rates. To control for Japanese demand in each industry, we include the share rate of Japanese value JPAV JP added by industry (πi,t )2 and the annual growth rate of Japanese real GDP (GDPt ). We expect a positive relationship between these and FDI. We also control for supply-side factors in the host countries. Expectation of future and increased consumption in this region is assumed to be correlated with FDI, so we include the log of GDP per capita (GDPKt ) as the representative variable and expect values to be positive in the equation.3 In addition, we include the previous annual JPF results of local Japanese firms (Ni,t −1 ) to represent the value of each Japanese industrial agglomeration, and expect positive correlations with FDI. The FDI-related data are obtained from Japan’s Ministry of Economy, Trade and Industry.4 Data for nominal exchange rates, consumer price indices, and real GDP are obtained from the International Monetary Fund. The share of Japanese value added by industry is obtained from the Cabinet Office, Government of Japan, and the GDP per capita data from the World Bank. To investigate the effects of other representative variables on expected local demand and the agglomeration effect, for Thailand,5 we re-estimate these equations using industry-level GDP growth or industry-level FDI inflow from abroad per GDP. These data are obtained from the Bank of Thailand. 4. Empirical results Tables 1 and 2 show the estimates for the fixed effect model for the determinants of new Japanese FDI in four Southeast Asian countries. Columns 1–3 of Table 1 report the estimates for all Thai industries from 2008 to 2015. The results for Column 1 seem to be better than the others because inward FDI and value-added growth in each industry are statistically insignificant and have an unexpected sign. In Column 1, the relationship between the number of new FDIs and exchange rate movements, which is one of the greatest concerns here, is significantly positive. Thai GDP per capita and the number of local Japanese firms are also significantly positive, as predicted.6 Regarding the agglomeration effect, the Japanese clusters affect mainly Japanese FDI decision making. On the other hand, while the effect of the share of Japanese value added by industry is significant, Japan’s GDP growth is not. Finally, each fixed effect in this model is significant, as shown by the results of log-likelihood ratio tests. 1 Due to data limitations, we must use data for the short sample period 2008 to 2015, and classify firms into 19 industry groups: Food; Textiles; Lumber and Pulp; Chemicals and Pharmaceuticals; Petroleum; Glass and Ceramics; Iron, Non-ferrous and Metals; General machinery; Electric machinery; Transportation equipment; Other manufacturing; Farming, Forestry, Fishery, and Marine products; Mining; Construction; Transportation; Communications; Wholesale and Retail; Services; Other non-manufacturing. 2 We use share rates (per GDP) to control the time series data. 3 We use GDP per capita rather than GDP or the size of population because this variable is representative for each economic performance as consumption. 4 For further detail regarding this data source, see the website of Japan’s Ministry of Economy, Trade and Industry (http://www.meti.go.jp/english/ statistics/tyo/gaisikei/index.html). 5 Due to data limitations, we cannot perform this estimate for the other countries. 6 High GDP per capita also means high labor costs, so it has a front–back relationship. However, we assume here that the expectation for significant consumption demand outweighs the effect of labor costs.
A. Kubo / Economic Analysis and Policy 62 (2019) 192–196
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Table 1 Empirical results, Thailand. Independent variable
Dependent variable: new Japanese FDI All industries
Manufacturing
2008–2015
2010–2015
2008–2015
2010–2015
(1)
(2)
(3)
(4)
(5)
(6)
Real exchange rate
6.993 (2.68) [2.61]***
7.414 (2.98) [2.49]**
2.556 (2.02) [1.26]
12.235 (4.06) [3.02]***
4.455 (1.64) [2.72]***
5.360 (2.44) [2.20]**
Japanese Industry value-added share
2.253 (0.90) [2.51]**
5.636 (1.23) [4.60]***
2.116 (0.92) [2.29]**
3.519 (1.31) [2.68]***
−0.085 (0.86) [−0.10]
0.067 (1.30) [0.05]
Japanese economic growth
−0.037 (0.10) [−0.38]
−0.107 (0.11) [−0.96]
0.137 (0.10) [1.39]
−0.005 (0.19) [−0.02]
−0.018 (0.06) [−0.30]
−0.044 (0.11) [−0.41]
GDP per capita
15.396 (6.07) [2.54]**
20.900 (6.67) [3.13]**
38.475 (11.47) [3.35]***
12.156 (3.83) [3.17]***
20.741 (6.30) [3.29]***
0.031 (0.01) [2.99]***
0.008 (0.01) [0.56]
−0.014 (0.01) [−1.47]
−0.035 (0.01) [−2.49]**
Local industry value-added growth
−0.018 (0.03) [−0.66]
Local Japanese firms
0.025 (0.01) [2.37]**
Local industry inward FDI
−0.279 (0.23) [−1.23]
Likelihood ratio test (Cross-section Chi-square) Observations
76.05***
123.17***
72.91***
71.30***
34.64***
38.45***
152
152
152
114
88
66
Note: ( ) denotes standard errors, [ ] denotes t-value. ***, ** and * indicate that the 1%, 5% and 10% confidence intervals are satisfied, respectively. Table 2 Empirical results, other countries. Independent variable
Dependent variable: new Japanese FDI Indonesia
Malaysia
Philippines
2008–2015 (1)
2010–2015 (2)
2008–2015 (3)
2010–2015 (4)
2008–2015 (5)
2010–2015 (6)
Real exchange rate
13.111 (3.75) [3.49]***
13.681 (5.46) [2.51]**
1.396 (0.81) [1.52]
0.025 (1.19) [0.02]
2.024 (0.94) [2.15]**
2.340 (2.72) [0.86]
Japanese Industry value-added share
1.717 (0.72) [2.37]**
2.006 (0.99) [2.02]**
−0.030
−0.477 (0.31) [−1.37]
−0.103 (0.27) [−0.38]
−0.072
(0.23) [−0.13]
0.102 (0.08) [1.34]
−0.157 (0.18) [−1.04]
0.028 (0.02) [1.22]
−0.108 (0.05) [−2.06]**
−0.006 (0.03) [−0.22]
(0.08) [−1.40]
GDP per capita
14.606 (3.00) [4.43]***
16.598 (6.74) [2.46]**
2.981 (1.56) [1.91]*
−0.580 (2.52) [−0.23]
3.806 (1.85) [2.06]**
3.608 (6.54) [0.55]
Local Japanese firms
0.006 (0.02) [0.40]
−0.035 (0.02) [−2.02]**
0.045 (0.01) [4.87]***
0.021 (0.01) [1.67]*
0.071 (0.02) [3.97]***
0.073 (0.03) [2.93]***
60.72***
75.12***
73.17***
76.40***
38.74***
32.51***
152
114
152
114
152
114
Japanese economic growth
Likelihood ratio test (Cross-section Chi-square) Observations
(0.41) [−0.17]
−0.104
Note: ( ) denotes standard errors, [ ] denotes t-value. ***, ** and * indicate that the 1%, 5% and 10% confidence intervals are satisfied, respectively.
Column 4 reports the estimates for the sample 2010 to 2015, corresponding to the recent substantial investment in Thailand. The number of new Japanese FDIs has a significantly positive relationship with exchange rate movements,
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Japanese industry-level value-added share, and Thai GDP per capita. In particular, the coefficient of GDP per capita is approximately twice as large as that for the period 2008–2015, which also implies that large demand in middle-income countries such as Thailand strongly affects new FDI behavior. Conversely, the number of local Japanese firms has no relationship with new FDI. In addition, although the sample sizes become small, we examine the model for manufacturing industries for the two sample periods 2008–2015 and 2010–2015, and report the results in Columns 5–6. Coefficients of both the real exchange rate and GDP per capita are statistically significant. This result is consistent with Blonigen (1997), suggesting that firmspecific assets, via real exchange rates, may be more important in manufacturing industries than in other industries. However, in Column 6, the number of local Japanese firms has a significant but negative relationship with the FDI. This result may imply that there is an optimal FDI stock and a time lag in the adjustment of recent new investments in Thailand. Table 2 presents the results for new Japanese FDI in the other Southeast Asian countries featured in this study – Indonesia, Malaysia, and the Philippines – for both the sample periods. Columns 1–2 show that the number of new Japanese FDIs is positively correlated with the yen–Indonesian rupiah exchange rate movements, the share of Japanese value added by industry, and Indonesian per capita GDP. However, the number of local Japanese firms has a significant but negative relationship with FDI in 2010–2015, as was observed for Thai manufacturing industries. Columns 3–6 show that new Japanese FDI in Malaysia and the Philippines are affected by the number of local Japanese firms (for both periods), which implies that Japanese industrial agglomeration has played an important role in both countries. However, during 2010–2015, there is no longer a relationship between GDP per capita and new Japanese FDI in Malaysia, while the yen–Philippine peso exchange rate and GDP per capita are not correlated with new Japanese FDI in the Philippines. 5. Concluding remarks This study employed industry-specific panel data analysis to investigate the economic factors affecting Japanese FDI in Southeast Asia from 2008 to 2015. We arrived at some key findings. The relationship between exchange rate movements and new FDI was positive and statistically significant in Indonesia and Thailand. Moreover, expectation for consumption demand more strongly affected new FDI in these countries. This result is consistent with the character of horizontal FDI. Appreciation of the yen may increase FDI because it reduces fixed costs for operations in the host country, which become more likely to be lower than the export costs form Japan, due to the large consumption demand in Indonesia and Thailand. In addition, FDI in Thailand also fits the export-platform model because results show a relatively strong relationship between the FDI and local Japanese firms’ agglomeration, which is assumed to be consistent with the evidence that Thailand is the center of business development in the region. In Malaysia and the Philippines, local Japanese firms’ agglomeration was positively correlated with new FDI, while the relationship between exchange rate movements and new FDI was insignificant. This pattern of FDI seems to be consistent with the vertical model. We can assume that the trade costs for both countries increase due to the appreciation of the yen, and may offset the production cost savings achieved due to the relatively low labor costs. There is an important extension of this study that could be pursued in future research: a representative variable for the third-country effect could be included to examine whether the FDI fits the export-platform model. 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