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SHORTER PAPER FDI and Wage Spillovers in Indonesian Manufacturing Robert E. Lipsey andFredrik SjOholm City University of New York; Stockholm School of Economics Abstract: This paper examines the effect of foreign direct investment in Indone- sian manufacturing on wages in locally owned Indonesian manufacturing plants. The issue is examined in a cross section of Indonesian manufacturing industries and provinces in one of the few years for which data on worker characteristics were available. Wages in locally owned plants were high in industries and indus- tries within provinces with large foreign presence. Since the foreign plants also pay higher wages than locally owned ones, the two factors together imply that higher foreign presence raises the general wage level in a province and industry. JEL no. F2, ]3 Keywords: Foreign direct investment; spillovers; wages; Indonesia 1 Introduction It is well established that foreign-owned firms pay higher wages than do- mesticallyownedoneswithin hostcountries,withinindustries and regions in these countries, and even after differences in plant characteristics are taken into account.1 The impact of foreign direct investment (FDI) on overall wages depends not only on how high the foreign firm wages are, but also on their effect, if any, on wages in locally ownedfirms. The di- rection of the effect on local firm wages is uncertain. For instance, foreign Remark: The authors wish to thankChris Manning, of the Australian National University, and Denise Eby Konan, of the University of Hawaii, our discussants at meetings of the East Asian Economic Association and the International Trade and Finance Association, as well as Bruce Blonigen, of the University of Oregon and participants at an ICSEAD seminar for suggestions that helped us greatly in revising the paper. This p a p e r was prepared as part of an ICSEAD project on "Foreign Multinational Corporations and Host-Country Labor Markets in Asia." Earlier versions appeared as ICSEAD Working Paper 2001-02 and NBER Working Paper No. 8299. Please address correspondence to Fredrik Sj6holm, Stockholm School of Economics, P.O. Box 6501,S-113 83 Stockholm; e-mail: [email protected] 1 For a survey of the evidence of a foreign wage premium, see Lipsey(2004).
Transcript

SHORTER PAPER

FDI and Wage Spillovers in IndonesianManufacturing

Robert E. Lipsey andFredrik SjOholm

City University of New York; Stockholm School of Economics

Abstract: This p a p e r examines the effect of foreign d i r e c t investment in I n d o n e -sian manufacturing on w a g e s in local ly o w n e d Indonesian manufacturing plants .The issue is e x a m i n e d in a cross sect ion o f Indonesian manufacturing industriesand provinces in one of the few y e a r s for w h i c h data on w o r k e r characteristicswere available. W a g e s in local ly o w n e d plants were high in industries and indus-tries w i t h i n provinces wi th l a r g e foreign presence. Since the foreign plants alsopay h i g h e r w a g e s than local ly o w n e d o n e s , the two factors together i m p l y thath i g h e r foreign presence raises the general wage level in a province and indus t ry .JEL no . F 2 , ]3Keywords: Foreign direct investment ; spi l lovers ; wages; Indonesia

1 Introduction

It is well established that foreign-owned firms pay higher wages than do-mesticallyo w n e d ones w i t h i n host countries, w i t h i n industries and regionsin these countries, and even after differences in p l a n t characteristics aretaken into account.1 The impact of foreign direct investment (FDI) onoverall wages depends not only on how high the foreign firm wages are,but also on their effect, if any, on wages in locally o w n e d firms. The di-rection of the effect on local firm wages is uncertain. For instance, foreign

Remark: The authors wish to t h a n k Chr is Manning, of the Austral ian National University,and Denise Eby Konan, of the University of Hawaii , our discussants at meet ings of the EastAsian Economic Association and the International Trade and Finance Association, as wellas Bruce Blonigen, of the University of Oregon and part icipants at an ICSEAD seminar forsuggestions that helped us greatly in revising the paper. This p a p e r was prepared as partof an ICSEAD project on "Foreign Mult inat ional Corporat ions and Host-Country LaborMarkets in Asia." Earlier versions appeared as ICSEAD Working Paper 2001-02 and NBERWorking Paper No. 8299. Please address correspondence to Fredrik S j6ho lm, StockholmSchool of Economics , P.O. Box 6501, S-113 83 Stockholm; e-mail : [email protected] For a survey of the evidence of a foreign wage premium, see Lipsey (2004).

322 Review of World Economics 2004, Vol. 140 (2)

firms m i g h t raise the d e m a n d for labor or increase competition in labormarkets, and thereby, in relatively competitive labor markets, force domes-tic plants to increase wages. Technological externalities--spillovers--fromFDI may increase productivity and, possibly, wages in domestic plants.On the o t h e rh a n d , foreign firms m i g h t recruit the best, presumably h i g h -wage, workers from domestic firms or acquire high-wage local firms. In-flows of foreign firms m i g h t also lead to lower scale of production andlower productivity in domestic firms (Aitken and Harrison 1999). Eitherone of these effects could result in lower wages, on average, in domesticfirms. The impact on overall average wage levels is therefore also uncer-tain.

This paper examines effects on local firm wages--wage spillovers--inthe Indonesian manufacturing sector, with a n important improvement onearl ierstudies. Previous studies did not include any information on workercharacteristics, beyond the distinction between production and n o n p r o -duction workers, but the Indonesian manufacturing census collected in-formation on worker education levels for a b r i e f period in the mid-1990s.We use the best of these data, for 1996, to examine wage spillovers. Weattempt to answer the question as to whether the presence or importanceof foreign-owned firms in a n industry or region caused locally o w n e dfirmsto pay higher wages. From this we draw some inferences a b o u t effects offoreign presence on wage levels as a whole.

2 The Indonesian Manufacturing Sector: Data Sourcesand Description

Our analysis is based on Indonesian manufacturing census data for 1996supplied by the Biro Pusat Statistik (Central Statistical Office). M1 plants inthe manufacturing sector with more than 20 employees were included inthe census. After excluding plants that did not respond to the questionnaire,but instead had t h e i r data estimated by the statistical office, we are left witha sample of 19,594 p l a n t observations. The analysis focuses on the effectof foreign firm presence on domestically owned plants, defined as plantsw i t h o u t any foreign ownership. The sample includes 18,652 domesticallyo w n e d plants.

For Indonesian manufacturing as a whole the foreign shares in 1996were 16 percent of employment and 30 percent ofvalue added, indicating a naverage o u t p u t per employee in foreign operations a r o u n dtwice as high as in

Lipsey/Sj/3holm: FDI and Wage Spillovers in Indonesian Manufacturing 3 2 3

domestically o w n e d plants (Lipsey and Sj6holm 2004).2 T h e foreign shareswere relatively large in Basic Metal Industries, Fabricated Metal Products,and Other Manufactures, but small in such labor-intensive industries asFoods, Beverages, and Tobacco, and Textiles, Apparel, and Leather.

Wages in foreign plants, described in Table 1, were relatively high in allsectors except for white-collar workers in Basic Metal Industries (ISIC 37),and both types of workers in Other Manufactures ( ISIC 39). T h e averagewage in foreign manufacturing plants was about 50 percent higher than inprivate domestic plants within 3-digit industries. Even aftertaking accountof industry, region, plant , and worker characteristics, foreign-owned plantswere found to pay higher wages, by over 10 percent for blue-collar workersand over 20 percent for white-collar workers (Lipsey and Sj6holm 2004:Table 5).

Table 1 : Wages in the Indonesian Manufacturing Sector, 1996

Average wagea( 1,000 ruphias)

Blue- White-Sector ISIC Total collar collar

Ratio of average wages

Blue-collar White-collar

Foreign/ Foreign/private private

Total 2,556 2 , 1 3 3 4,637 1.47 1.55Food 31 1,957 1 , 6 5 7 2,933 1.63 2.00Textiles 32 2,298 1 , 9 9 5 4,845 1.32 1.15Wood, Furniture 33 2,183 1 , 9 3 0 3,805 1.15 1.21Paper, Printing 34 3,504 3,025 4,989 1.73 1.15Chemicals 35 3,201 2,408 5,792 1.84 1.74Non-Metallic Minerals 36 2 , 7 6 5 2 , 2 4 3 5,173 2.35 1.61Basic Metal Industries 37 5 , 3 1 4 4,502 8,093 1.12 0.90Fabricated Metals 38 3 , 5 2 2 2 , 8 4 8 6,603 1.49 1.67Other Manufacturing 39 1,888 1 , 6 2 1 4,129 0.93 0.98

a Average wages have been calculated as aggregate averages. Average wages for different own-ership groups, used in the last two columns, have been calculated at a 3-digit level of ISICand aggregated up to a 2-digit level of ISIC u s i n g shares of total blue-collar and white-collaremployees as weights.

2 The foreign share is defined as the share of production or employment in all plants withany foreign ownership. Most foreign-owned plants are joint ventures with a foreign major-ity share. The average foreign share among plants with any foreign ownership is 72 per-cent , 23 percent of the plants have a 100 percent foreign ownership and 18 percent a for-eign minority share.

3 2 4 Review of World Economics 2004, Vol. 140 (2)

The relatively high wages we observe in foreign-owned plants in Indone-sia match the results of o t h e rstudies for a variety of countries summarized inLipsey (2004). Studies on Southeast Asia have f o u n d that foreign firms payhigh wages, a t least partially attributed to their larger size and their highercapital intensities (Manning and Fong 1990). In the case of Indonesia, Hill(1990) and M a n n i n g ( 1998: Ch. 6) observed that foreign and domestic firmsdiffer in several aspects including relatively high wages in the former.3

In contrast to the large literature on wage differences between domesticand foreign firms, studies on wage spillovers to domestically o w n e d firmsare relatively scarce, as is pointed out in G6rg and Greenaway(2002). Aitkene t al. (1996) f o u n d that wages in domestically o w n e d manufacturing plantsin Venezuela tended to be low in sectors with a large foreign presence.Only in the United States was there some evidence of a positive impact offoreign firms' presence on domestic p l a n t wages. Feliciano and Lipsey(1999)confirmed the existence of positive wage spillovers in the United States, butonly in nonmanufacturing industries. Driffield and G i r m a (2003) f o u n dwage spillovers in the United Kingdom, but only for white-collar wages.Figlio and Blonigen (2000: 352, fn. 12) reported that the effect of inwardFDI on aggregate wages in five S o u t h Carolina counties was so large that itcould not have come entirely from the higher wages in the foreign plantsthemselves. It must have involved spillovers to domestically o w n e dplants.

3 Econometric Estimations

In examining the effect of FDI on domestically o w n e d plants' wage levels,we use data only for domestic plants and estimate a n equation of the form:

( FDI, Government owner, Education, )In W = f k, Sector, Location, In X , , (1)

where W is a plant's average wage (separately for blue- and white-collaremployees), Government owner is a d u m m yvariable for public ownership,Education is the education level of the employees (the share of the employeeswith primary, junior, senior, and university education), Sector and Locationare d u m m yvariables for industries and provinces, and X is a vector of plant-specific characteristics such as size, the share of females, and the use of inputs.For descriptive statistics of the variables, see Table A1 in the Appendix.

3 There are exceptions. For instance, Indonesian affiliates o f firms from the Asian newlyindustrialized economies do not always pay high wages (Manning 1993).

Lipsey/Sj6holm: FDI and Wage Spillovers in Indonesian Manufacturing 325

FDI, our variable of main interest, is the share of a n industry's valueadded produced in foreign plants. The foreign share is calculated a t severaldifferent levels of the industrial classification, each implying a differentdefinition of a labor market. Equation (1) is first run w i t h o u t the locationvariable, implying that labor markets are countrywide, within industries.Equations with foreign shares measured a t a 2-digit ISIC level i m p l y thata labor market consists of workers throughout Indonesia within a 2-digitindustry. It assumes that workers move freely a m o n g firms and a m o n g the3-digit and 5-digit components of a 2-digit industry, but not from one2-digit industry to another. When the share is calculated a t a 3-digit level,the implication is that workers do not move from one 3-digit subindustryto another, even w i t h i n the same 2-digit industry, but do move a m o n g5-digit industries. The equations with foreign 5-digit ISIC industry sharesassume labor mobility only w i t h i n single 5-digit industries, implying that5-digit industries define labor markets in which foreign and domestic firmscompete for labor.

We w o u l d expect the coefficient for FDI to be positive and statisticallysignificant if FDI leads to higher wages in domestic plants in a n industry.That expectation is strongly confirmed in Table 2, whatever the industrylevel a t which the FDI shares are calculated. While the coefficients for theo t h e r variables are not much affected by the level used for the FDI sharevariable, the FDI coefficient diminishes as the industrial classification be-comes more detailed. One m i g h t expect the opposite result if competitionfor labor were most severe a m o n g firms in the same narrow industry. How-ever, the narrowing of the industry definitions removes any bias from theselection of higher-wage industries by foreign firms, even within 2-digit and3-digit industry groups. The narrowing of the classification may also havethe less desirable effect of reducing the n u m b e r of cases in which foreignand domestic plants, similar in various characteristics, coexist in the sameindustry.

The additional variables all affect wage levels as expected: large plantswith high capitalintensities, large amounts of inputs, with a highly educatedlabor force, and low shares of female workers, pay relatively high wages.Government-owned plants pay low white-collar wages whereas the effecton blue-collar wages is not statistically significant.4

4 Government-owned plants migh t have other objectives than privately owned plants ,which could affect the results. We therefore est imated equation (1) wi thout includinggovernment-owned plants but the resul ts remained robus t .

326 Review of World Economics 2 0 0 4 , V o l . 1 4 0 ( 2 )

Table 2: FDI and Wages in Domestic Plants (average wage per employee asdependent variable)

Regression 1 Regression 2 Regression 3 Regression4 Regression 5 Regression 6

Blue collar White-collar

Constant 5.31 5.67 5.71 4.97 5.22 5.25(116.10)*** (147.22)*** (153.91)*** (87.13)*** (98.04)*** (101.30)***

Below primary - 0 . 3 9 - 0 . 4 0 - 0 . 4 0 - 0 . 3 9 - 0 . 4 1 - 0 . 4 0(12.48)*** (12.86)*** (12.80)*** (5.92)*** (5.96)*** (5.78)***

Junior high 0.28 0.30 0.30 0.37 0.38 0.37(13.94)*** (14.63)*** (14.64)*** (11.73)*** (11.86)*** (11.81)***

Senior high 0.21 0.26 0.26 0.61 0.64 0.64(10.99)*** (13.73)*** (13.60)*** (24.21)*** (25.19)*** (25,09)***

University 0.91 0.96 0.94 1,03 1.10 1.09(7.70)*** (8.91)*** (7.91)*** (27,07)*** (28.86)*** (28.68)***

Energy 0.03 0.03 0.03 0.04 0,05 0.05(9.85)*** (10.05)*** (10.34}*** (9.57)*** (9.68)*** (10,16)***

Inputs 0.15 0.13 0.13 0.13 0.12 0.12(36.28)*** (34.28)*** (33.96)*** (26,68)*** (24.85)*** (24.54)***

Size 0.04 0.05 0.05 0.16 0.16 0.16(9.99)*** (11.12)*** (11.08)*** (26.33)*** (26.72)*** (26.38)***

Government 0.02 - 0 . 0 3 - 0 . 0 3 - 0 . 1 7 - 0 . 2 0 - 0 . 1 8( 0 . 6 3 ) ( 1 . 0 4 ) ( 0 . 9 1 ) (4,42)*** (5,17)*** (4.76)***

Female share - 0 . 3 2 - 0 . 3 9 - 0 . 3 9 - 0 . 1 5 4 ) . 1 6 0.16(20.16)*** (24.59)*** (24.92)*** (7.15)*** (7,44)*** (7.58)***

FDI--2-digit 1.07 - 1.04 - -(21,83)*** (16.42)***

FDI--3-digit 0.28 - 0.34 -(6.20)*** (5.43)***

FDI- -5-d ig i t - 0.16 - 0.35(7.48)*** (11.46)***

Adjusted R-square 0.31 0.29 0.29 0.32 0.30 0.31N o . o f o b s e r v a t i o n s 17,545 17,545 17,545 13,731 13,731 13,731

*,**,*** significant at the 10, 5, a n d 1 percentlevel, respectively.Note: t-statistics within parentheses are based on White's adjustment for heteroskedasticity.

T h e potential impact on wages from FDI may b e conditioned on ge-ographic proximity, since there are reasons to believe that the Indones ianlabor market shows some degree of regional segmentation. We thereforecalculate an alternative measure of FDI--FDIprovince which is the shareof an industry's output in a province that is produced in foreign plants. 5We w o u l d expect a positive and statistically significant coefficient on FDIprovince if foreign firms affect wages in domestic plants in the same industrywithin the same province. T h e introduction of the province variable alsoreduces the possible biases from the selection of higher wage regions by

5 T h e r e were 2 7 Indonesian provinces in 1 9 9 6 .

Lipsey/Sj6holm: FDI and Wage Spillovers in Indonesian Manufacturing 327

foreign firms. The motivation for such a selectionw o u l d presumably be notthe higher wages, which should discourage investment, but other locationaladvantages of these regions.

Table 3 shows equations for wages in domestic plants where the FDIshare is measured w i t h i n each province. In the first equation of each set,white-collar and blue-collar, the implicit assumption is that labor is mobilea m o n g industries w i t h i n a province, but not across provinces. Therefore,the effect of FDI in any industry is felt in all industries in the same province.The FDI share coefficient a t the province level is positive and statisticallysignificant, and a b o u t the same size as the national FDI share variable a t the2-digit level in Table 2. The next pair of equations, with the FDI share inthe province calculated a t the 2-digit ISIC level, implies that FDI presenceaffects wages only within the same 2-digit industry in the same province.The coefficients for FDI share are again statistically significant, but muchsmaller, t h o u g h one m i g h t expect the effect to be stronger within the same2-digit industry than across all industries in a province. As the industrybreakdown becomes finer, the coefficients on FDI share decrease further,but they are always significant. The last equations, which measure spilloversonly w i t h i n 5-digit industries w i t h i n provinces, i m p l y that a 10 percenthigher foreign share produces a blue-collar local firm average wage 2.4percent higher, and a white-collar wage 3.8 percent higher a m o n g workersin locally o w n e d plants.

The evidence for wage spillovers from foreign-owned plants appearsquite strong. We cannot completely rule out the possibility that there issome bias from foreign firms' choices of industries, provinces, or establish-ments. However, it is likely that our use of different levels of aggregationin constructing the FDI variable and our use of regional measures of FDIwill rule out any possibility that all the effects come from the selection byforeigners of high-wage subindustries or regions. Moreover, the results areconsistent with productivity spillovers from foreign-owned to domesticallyowned plants in Indonesia that have been f o u n d in previous studies basedon cross section data.6

The selection of plants is a more difficult possibility to eliminate. For-eigners m i g h t select, w i t h i n industries and regions, the highest-wage lo-cally o w n e d plants to acquire, and higher wages in the foreign-ownedplants could correspond to lower wages in the remaining domesticallyo w n e d plants. If that were true, foreign ownership w o u l d have no re-

6 See Sj6holm (1999a, 1999b), and Blomstr6m and Sj6holm (1999).

328 Rev iew of W o r l d Economics 2 0 0 4 , Vol. 140 (2)

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Lipsey/Sj6holm: FDI and Wage Spillovers in Indonesian Manufacturing

T a b l e 4 : FDI in the Province and Wages in all Plants (average wage inprovince-industry as dependent variable)

329

2-digit of ISIC 3-digit of ISIC 5-digit of ISICVariable Blue-collar White-collar Blue-collar White-collar Blue-collar White-collar

Constant 5.52 4.85 5.53 5.13 5.64 5.30(17.25)*** (7.83)*** (29.95)*** (17.43)*** (52.24)*** (30.46)***

Below primary 0.46 -1.77 0.24 - 1 . 4 7 - 0 . 1 5 - 0 . 7 6( 1 . 4 0 ) (1 .69)* ( 1 . 2 3 ) (2.14)** ( 1 . 1 8 ) (3.70)***

Junior high 0.30 ~ 0 . 0 9 0.23 0.03 0.28 0.28( 0 . 8 5 ) ( 0 . 1 5 ) ( 1 . 1 7 ) ( 0 . 1 2 ) (3.48)*** (1 .82)*

Senior high 0.87 0.62 0.51 0.41 0.32 0.50(4.10)*** ( 1 . 3 6 ) (3.90)*** (1 .83)* (5.37)*** (4.49)***

University 1.41 1.44 1.94 1.09 1.43 1.16(2.34)*** (3.02)*** (3.24)*** (3.94)*** (3.74)*** (8.21)***

FDI 0.22 0.45 0.21 0.33 0.20 0.43(1 .81)* (2.42)*** (2.20)*** (2.39)** (3.96)*** (6.94)***

Energy perworker 0.06 0.03 0.02 0.02 0.03 0.01( 1 . 5 2 ) ( 0 . 9 5 ) ( 1 . 1 6 ) ( 0 . 9 0 ) (3.04)*** ( 0 . 6 3 )

Inputs perworker 0.10 0.19 0.12 0.17 0.13 0.16(3.08)*** (4.16)*** (5.76)*** (5.99)*** (11.73)*** (10.84)***

Size 0.06 0.11 0.10 0.17 0.06 0.15( 1 . 3 8 ) (2.02)** (3.57)*** (4.83)*** (5.40)*** (10.37)***

Female share - 0 . 4 0 0.45 - 0 . 4 2 0.08 - 0 . 3 3 - 0 . 0 8(2.96)*** ( 1 . 3 6 ) (4.80)*** ( 0 . 4 7 ) (7.66)*** ( 0 . 9 7 )

Adjusted R-square 0.47 0.45 0.47 0.43 0.41 0.41Number of observations 197 193 463 450 1,868 1,770

*,**,*** significant at the 10, 5, a n d 1 percent level, respectively.Note: t-statistics within parentheses are based on White's adjustment for heteroskedasticity.

lation to overall (foreign plus domestic) wage levels. That possibility istested in Table 4, in which the dependent variable is the average wagein all plants in a province, within 2-digit , 3-digit , and 5-digit industries.Hence, the estimations include domestic as well as foreign plants to getan estimate of the total wage effect from FDI. At each level, higher for-eign presence means higher wages in general. At the most detailed indus-try level, a 10 percent higher foreign share produces a 2 percent higheraverage blue-collar wage and more than a 4 percent higher white-collarw a g e ,

4 Conclusions

Assuming national labor markets within broad industry groups, we findsignificant spillovers to domestic plant wages within 2-digit industry groups.T h e spillover effect is about the same for blue-collar and white-collar wages.Foreign shares in 3-digit or 5-digit industries seem to show smaller, but still

Lipsey/Sj6holm: FDI and Wage Spillovers in Indonesian Manufacturing

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