foreign ownership and firm productivity in bangladesh...
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Foreign Ownership and Firm Productivity in Bangladesh Garment Sector
Hiau Looi Kee*
May 2005
Abstract
This paper studies the productivity advantage and spillover of FDI firms in Bangladesh garment sector. This is based on a newly collected exclusive firm level data, supported by a unique custom firm level export data. Firm productivity is first estimated from a firm production function, controlling for input endogeneity, selectivity, as well as firm and year fixed effects. Results show that FDI firms are on average 20 percent more productive than domestic firms. Moreover, there are statistical evidence suggesting that productivity spillover occurs such that domestic firms may benefit from the productivity increase in FDI firms. These findings support a more open FDI policy for the Bangladesh garment sector.
__________________________________________* Development Research Group – Trade, the World Bank, 1818 H ST NW (MSN MC3-303), Washington, DC 20433, USA; Tel: (202) 473 4155; Fax: (202) 522 1159; E-mail: [email protected]; I thank the World Bank, CIDA and DFID for providing research funding. The findings, interpretations, and conclusions expressed in this paper are entirely those of the author, and do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent.
Introduction
Conventional wisdoms have it that firms with foreign equity tend to be more productive.
This could be due to the firm specific tangible assets such as exclusive technology and
product designs, or the intangible know-how embodied in foreign equity such as
marketing, networking and sourcing. Such assets may be more readily available in big
multinational corporations (MNC). As such, being part of MNCs allow the local
subsidiaries with foreign equity to gain access to these assets, which in turn make them to
produce more output given the same level of inputs, and thus a higher level of total factor
productivity (TFP) than the solely domestic owned firms. Such hypothesis has some
empirical support based on samples of Venezuela manufacturing firms studied in Aiken
and Harrison (AER, 1999) and Malaysia service sector firms in Kee (forthcoming).
Unlike many developing countries such as Cambodia, Mauritius and Mongolia,
where most of the garment firms are part of some larger multinational corporations in the
form of foreign direction investment, less than 15 percent of Bangladesh garment firms
have foreign equity. This is partly due to the industrial policies of Bangladesh in order to
safe guard quota allocations of garment export to US to the domestic firms.
Furthermore, foreign firms are allowed to invest in Bangladesh garment sector only if
they locate the plants in the export processing zones, and are not competing with the
subcontracting domestic firms supplying to the exporting firms who have quota access.
Thus, almost all FDI firms export all of their products from Bangladesh.
The objective of this paper is to study the potential productivity advantage of FDI
firms operating in Bangladesh. In addition, this paper aims to identify the possible
2
channels by which local firms may benefit from the FDI firms. We focus on the
productivity spillover effects, beyond the physical presence of FDI firms.
The paper first presents an overview of the garment sector, in terms of industry
structure and export performance. The paper proceeds to study the firm export
performance according to a unique custom export data. By dissecting the firms in terms
of the markets they participated, this paper is able to assess the productivity distribution
among Bangladesh garment export. The main part of the paper focuses on estimating
firm productivity by modifying the state of the art technique due to Olley and Pakes
(Econometrica, 1996), to control for firm and year specific biases. We relate the
estimated productivity, which is the level of output not explained by the level of inputs,
to the ownership structure of the firms using between firm panel regression, controlling
for industry, year, location fixed effects. It is shown that firms with foreign equity are on
average 20 percent more productive than otherwise identical domestic firms. The
productivity advantage of FDI firms is robust to age and export destinations. In addition,
we relate the productivity performance of domestic firms to that of FDI firms and show
that there are indeed positive and significant productivity spillovers. For every 10
percent increase in the productivity level of FDI in the industry, productivity of domestic
firms increases by 1.4 percent.
An Overview of Bangladesh Garment Sector
According to data obtained from the Bangladesh Garment Manufacturers and Exporters
Association (BGMEA) Members’ Directory 2004-2005, there are more than 4,000 firms
operating in Bangladesh garment sector, of which 2,800 are in Dhaka area. Almost 65%
of the firms are in the woven industry, 20% in the knitting industry with the sweater
3
industry rounds up the remaining 15%. About 13% of the woven firms also engage in
the knitting industry. These are usually the larger and more productive woven firms.
Most of the garment firms in Bangladesh are locally own, with about 1% of them
operating in the export processing zones (EPZs) in Dhaka and Chittagong. Finally, more
than 63% of EPZ firms have some foreign ownership, from countries such as South
Korea and Hong Kong. The sector as a whole employ 2.1 million workers, with 53,000
workers in the firms with foreign ownership.
Overall, firms in Dhaka are larger and more productive, relative to firms in
Chittagong. In addition, firms in EPZs are the better firms than those out side of the
EPZs. Finally, firms with foreign capital are the most productive of all firms:
On average, FDI firms are larger, they hire more workers given the same number
of machine.
FDI firms are more capital intensive, they use less workers per machine given the
same number of plant capacity. EPZ firms are also more capital intensive relative
to non-EPZ firms.
Given after taking into account the numbers of product variety, FDI firms are still
on average larger in capacity than domestic firms.
76% of the FDI firms are in the woven industry.
Export Performance of Garment Sector
The past few years have witnessed an expansion of Bangladesh garment export to the
world market. In 1998, the total value of garment export from Bangladesh was about
US$3.8 billion, it increased to US$4.2 billion in 2001 and settled at US$3.6 billion in
4
2003. This Information is obtained from the United Nations Comtrade Database
according to the reporting of the Bangladesh government. Figure 1 presents the
breakdown of the aggregate export of the Bangladesh garment sector by destinations, in
1998, 2001 and 2003. In both 1998 and 2001, the share of EU in Bangladesh garment
export was about 50 percent, closely followed by the US at 45 percent, while other
countries, noticeably Canada, made up the remaining 5 percent of aggregate garment
export. In 2003, the importance of EU further increased to 58 percent, while the share of
the US dropped to 37 percent.
Figure 1: Breakdown of Garment Export
Total Garment Exports(HS Catagories 61 & 62)
1874.0
2117.1 2081.7
1689.2
1897.6
1339.5
220.8 201.8 175.1
0.0
500.0
1000.0
1500.0
2000.0
2500.0
1998 2001 2003
Mill
ion
of U
S$
EUUSA
Others
The surprising fall in the garment export to the US could be due to transshipment or
misclassification of goods. Based on US custom data from the US International Trade
5
Commission (USITC), garment export to US from Bangladesh in fact has been steadily
climbing from US$1.5 billion in 1998 to US$1.8 billion in 2003. In 2004, the value of
garment export from Bangladesh further increased to US$1.9 billion, which makes
Bangladesh the 10th largest garment supplier for the US market. Figure 2 presents the
values of garment imports of US from 1998 to 2004 by major exporting countries. In
2004, the top ten garment exporting countries to the US market and their market shares
are China (16%), Mexico (10%), Hong Kong (5.8%), Honduras (4.1%), Vietnam (3.7%),
Indonesia (3.6%), India (3.4%), Dominican Republic (3.1%), Guatemala (2.9%) and
Bangladesh (2.8%).
Figure 2: Breakdown of Major Garment Exporters in the US Market
US Garment Imports(HS Catagories 61 & 62)
0
2000
4000
6000
8000
10000
12000
1998 1999 2000 2001 2002 2003 2004
Mil
lion
of U
S$
BDGCHN
MEXHKG
HONIND
We further use a firm level export data set obtained from the Textile Unit of the
Export Promotion Board (EPB) of Bangladesh to analyze the export performance of the
Bangladesh garment sector. This information is compiled from those firms that applied
6
for Country of Origin Certificates in 2004. This certificate is often requested by the
importing countries to verify the origins of the imported goods in order to grant trade
preferences.
In this firm level data set there are 2387 garment firms exporting in 2004. The total
value of garment export is US$5.7 billion, with more than 400 million dozens of garment
exported. Overall 57 percent of garment export headed to the EU, 20 percent for the US
and the remaining 23 percent went to the other countries such as Canada and Australia.
Table 1 presents the breakdown of garment export volume by destinations.
Table 1: Garment Export by Destination, 2004
Description Quantity (dozen) Value (US$)EU under GSP 319,718,411 3,244,562,889Others 32,044,542 1,306,109,811USA with quota 42,196,576 976,267,029USA without quota 19,785,482 159,150,271Total 413,745,011 5,686,090,000
In terms of the distribution of firms across different markets in 2004, there are 1967
firms exporting under GSP, mainly to the European market, 1039 firms exporting to the
US, of which 709 export under quota allocations, and 1231 firms exporting to other
countries. Figure 3 presents the distribution of firms by export destinations.
Among these firms, 46 percent only supply to one market, 34 percent supply to two
markets, 14 percent to three markets, and 5 percent to all four markets. This is clearly
presented in Figure 4.
Figure 3: Number of Firms in Different Markets
7
Distribution of Firms by M arkets
0
500
1000
1500
2000
2500
US-quota US-no quota EU Other
export destinations
num
ber
of fi
rms
Figure 4: Number of Firms vs. Number of Markets
8
Distribution of Firms by Number of Markets
0
200
400
600
800
1000
1200
1 2 3 4
number of export distinations
num
ber
of fi
rms
Figure 5 presents the choice of export markets of Bangladesh garment exporters
according to the number of export market the firms supply. It is very clear that EU is the
most popular destination, especially among firms that have only one export market.
Among the 1109 firms that only supply one market, nearly 850 firms concentrate on EU
which is about 76 percent. The US market appears to be toughest to break in among this
group of firms, less than 8 percent only export to the US with and without quota.
For firms that supply two markets, both the EU and the others are the favorites.
Together, they account for 80 percent of the markets among the 1640 firms that export to
two markets. The US in quota market is popular for firms that export to more than 2
markets.
Figure 5: Market Choice by Firms with Different Markets
9
Choice of Export Market
0
100
200
300
400
500
600
700
800
900
US-quota US-no quota EU Others
export destinations
num
ber
of fi
rms
one market firms
two market firmsthree market firmsfour market firms
In addition, according to Eaton, Kortum and Kramarz (AER, 2004) who study the
export performance of French firms, the number of markets a firm supplies reflects the
productivity and competitiveness of the firm in the world market. The above distribution
of firms implies that more than 35 percent of Bangladesh garment exporters participate in
world markets widely with at least 3 export destinations, and are thus very competitive.
This is quite evidence in Figure 6, when we plot the unit value of garment export (left
axis) and total export value (right axis) against the number of export destinations. Firms
that export to more destinations tend to have higher average unit values and larger in
size, with the former reflects better quality and the latter indicates greater scale
economies, both signal higher productivity of the firms. The differences in unit values
and total size among firms with different number of markets are statistically significant.
Figure 6: Exporting and Productivity
10
Unit Value, Total Export by Number of Markets
0
5
10
15
20
25
30
35
40
45
1 2 3 4
number of export destinations
unit
valu
e in
US
$
0
1
2
3
4
5
6
7
8
9
tota
l exp
ort i
n m
illio
n of
U
S$
unit value per dozen total value of export
Preliminary Findings Based on Firm Survey
Firm level survey was conducted from the period of November 2004 to April
2005, which covers a stratified random sample of 350 firms, which is about 10% of the
total population of the garment firms currently operating in Bangladesh. After cleaning
up the data to exclude outliers and firms with incomplete information, there are a total of
231 firms in the unbalanced final panel data set of 1026, from 1999 to 2003. In this
unbalanced panel data set, the composition of sub-industries of knitwear, sweaters and
woven is 24%, 8% and 68% respectively. Among the sampled firms, 13% have positive
foreign equity, while the remaining 87% are purely domestic owned. Moreover, 15% of
the sampled firms are in the Dhaka and Chittagong EPZs, 63% in Dhaka and 15% in
Chittagong.
Tables 2-4 and Figures 7-9 present the sample means of the key variables of the
sub-industries of knitwear, sweaters and woven, by foreign versus domestic firms. It is
11
clear that FDI firms are in general larger in sales, in exports, they purchase more material
inputs, including imported materials, they hire more employees, including production
workers. FDI firms also have larger capital stock and investment. All these suggest that
FDI firms are larger in scale and presumably more profitable and productive. To
formally study the productivity superiority of FDI firms, and the possible productivity
spillover to domestic firms, we will need to first estimate firm level productivity for the
firm sample. The estimated firm productivity is then relate to the ownership of the firms,
and the relationship between productivity of domestic and FDI firms in the same sub-
industries will be statistically examined.
Table 2: Summary for Knitwear
12
Domestic Firm FDI Firmsales 3050.894 5044.482export 2951.962 5044.482cost 2917.288 4195.379material 2037.68 2888.019imp material 1560.666 2569.798employee 582.9438 996.2333prod worker 501.5181 943.7capital 2033.417 1510.171investment 817.5825 79.3077
Knitwear (Thousands US$)
Figure 7: Summary for Knitwear
Knitwear
30512952 2917
2038
1561
2033
818
5044 5044
4195
2888
2570
1510
79
502583
944996
0
1000
2000
3000
4000
5000
sales export cost material imp material employee prod worker capital investment
US$ Thousands
Domestic Firm
FDI Firm
13
Table 3: Summary for Sweater Industry
Domestic Firm FDI Firmsales 2363.506 3603.465export 2362.946 3603.465cost 2141.488 3350.958material 1435.532 2389.08imp material 564.879 1811.852employee 906.8947 1305.85prod worker 859.6316 1214.75capital 1002.338 4231.342investment 215.6552 344.9167
Sweater (Thousands US$)
Figure 8: Summary for Sweater Industry
Sweaters
2364 2363
2141
1436
565
1002
216
3603 3603
3351
2389
1812
4231
345
860907
12151306
0
500
1000
1500
2000
2500
3000
3500
4000
4500
sales export cost material imp material employee prod worker capital investment
US$ Thousands
Domestic Firm
FDI Firm
14
Table 4: Summary for Woven Industry
Domestic Firm FDI Firmsales 2926.72 13900export 2919.786 13900cost 2587.394 12700material 2015.82 9665.94imp material 1590.774 8393.138employee 600.5773 1893.183prod worker 560.29 1790.3capital 639.5217 5076.089investment 57.77929 315.9224
Woven (Thousands US$)
Figure 9: Summary for Woven Industry
Woven
2927 29202587
20161591
640
58
13900 13900
12700
9666
8393
5076
316560601
17901893
0
2000
4000
6000
8000
10000
12000
14000
sales export cost material imp material employee prod worker capital investment
US$ Thousands
Domestic Firm
FDI Firm
15
Estimating firm productivity
To formally study the overall productivity of firms, we need to estimate firm
production function, taking into account total factor usage per unit of output. In the firm
survey we asked firms to provide the annual increase in the main product price and the
main material input price. The firm level price information allows us to construct firm
level price indexes of output and material, which we use to deflate sales and material
costs to obtain real output and material level. We estimate the following production
function,
,lnlnlnlnln,
itKitMitLitit
ititititit
KMLAYKMLAY KML
where i and t are the indexes for firm and year, respectively. In log, output, Y, is linearly
related to labor, L, materials, M, and capital stock, K. Any part of Y that are not
explained by the three factors of production are attributed to productivity, A, which
varies by firms and years. In other words, if we regress lnY on lnL, lnM and lnK using
ordinary least squares (OLS) estimation, the regression errors are the firms productivity,
lnA.
However, firm’s input choices are likely to be endogenous. How many workers
to hire, how many unit of fabrics to purchase, and how many new machines to set up
each year depends on the productivity of the firms, which is known to the firms, but not
the researchers or economists. Such input endogeneity will bias OLS estimates of labor
and materials upward. In addition, if larger and older firms tend to stay in business
despite low productivity, will younger and smaller firms tend to quit easier, such
entry/exit decision of the firm will bias OLS estimates of capital downward.
16
To address input endogeneity bias and selectivity bias, we follow a 3-step
nonlinear estimation methodology developed by Olley and Pakes (Econometrica, 1996).
Moreover, to control for any factors that are specific to the firms, such as fraudulent
accounting practice, or years, such as economic downturns, that may bias our estimates
that are beyond the Olley-Pakes correction, we also include firm and year fixed effects in
our regressions. We modified the three stage nonlinear estimation of the above
production function due to Olley and Pakes to include firm and year fixed effects.
Furthermore, even that older firms are more likely to stay in business despite temporary
down turn in business, we also control for firm age in the estimation.
To control for input endogeneity, we first regress lnY on lnL, lnM, a full set of
firm and year fixed effects and a 3rd order polynomial function of real investment and
capital, which is used to control for the unobserved productivity. The estimated
coefficients on labor and materials are consistent. Firms’ real investment, I, is obtained
by deflating nominal investment from the firm survey by the GDP deflator of domestic
fixed capital formation of Bangladesh in the respective years. Capital is constructed by
summing real investment over the years using perpetual inventory method with an annual
depreciation rate, of 10 percent:
with initial capital stock being constructed using average between firm’s first year fixed
asset, F, and the infinite sum series of investment prior to the first year, assuming that the
growth rate of investment of 0 and depreciation rate of 10 percent.
17
To obtain consistent coefficient estimate of capital, we first estimate the entry/exit
decision of the firms using a Probit regression on a 3rd order polynomial function of
investment, capital and age, controlling for year, region and industry fixed effects. This
regression yields the propensity for a firm to stay in business. We then regress
, constructed using the consistent estimates of and from
the 1st step, on age, capital, and a 3rd order polynomial function of propensity of survival
and . This last-stage nonlinear regression gives us
consistent estimated coefficient on capital, .
Results of the regressions are reported in Table 5. Column (1) of Table 5 shows
the OLS estimation with no correction on endogeneity, selectivity, firm or year fixed
effects. These estimates are likely to be biased. Column (2) shows the within estimates
with firm and year fixed effects. While these estimates are robust to factor such as
location which is specific to a firm and macro economic climates which is specific to a
year, year to year variation of productivity within firm will still bias our estimates.
Column (3) reports the first stage Olley-Pakes procedure, where a 3rd order polynomial
function of investment, capital and age is included, in addition to firm and year fixed
effects, to control for within firm year to year changes in the unobserved firm
productivity. This procedure corrects for input endogeneity, which reduces the upward
bias relative to the OLS estimates. The consistent estimated coefficients for labor and
materials are 0.25 and 0.72, respectively. Without correcting for selectivity, the
estimated coefficient on capital is too low.
18
Table 5: Dependent Variable – log of firm output
(1) (2) (3) (4)OLS Within Olley-Pakes Olley-Pakes
Materials 0.688*** 0.718*** 0.718*** 0.718***(0.037) (0.065) (0.065) (0.065)
Labor 0.283*** 0.240*** 0.250*** 0.250***(0.036) (0.086) (0.088) (0.088)
Capital 0.025*** 0.017 0.013 0.021*(0.008) (0.022) (0.248) (0.011)
Age -0.173 0.032*(0.316) (0.019)
Investment 0.137(0.111)
Endogeneity correction1 No No Yes YesSelectivity correction2 No No No YesFirm fixed effects No Yes Yes YesYear fixed effects No Yes Yes YesObservations 1027 1027 1027 795Notes: Heteroskadasticity corrected white robust standard errors in parentheses. 1A 3rd order polynomial function of age, capital and investment are included. 2A 3rd order polynomial function of propensity to stay in business and the fitted output net of labor and capital are included.
Column (4) controls for selectivity bias by including a 3rd order polynomial
function of the estimated survival probability and the net fitted output. The resulting
estimated coefficient for capital is 0.02. All these coefficients are statistically significant,
and are in line with the estimates in the literature. Finally, with the sum of the estimated
coefficients of labor, capital and material equals to one, the production function in the
garment sector is found be constant returns to scale.
With these estimates, we constructed firm level productivity according to the
following equations:
19
Comparing firm productivity across all firms in all sub-industries and locations
yields some interesting insights in terms of relative productivity of firms. When we
compare different firms across different sub-industries, on average, knitwear firms are
the most productive. An average knitwear firm has 10 percent higher productivity than a
woven firm, and 17 percent more productive than a sweater firm. Figure 10 presents the
distribution of the estimated firm productivity by the three sub-industries. In terms of
locations, productivity of firms located in Dhaka-EPZ is the highest, follow by firms in
Dhaka, Chittagong-EPZ and Chittagong. Figure 11 presents the distribution of firm
productivity by location.
Figure 10: Distribution of firm productivity in different sub-industries
20
Firm Productivity by Sub-industries
2.45
2.5
2.55
2.6
2.65
2.7
2.75
Knitwear Sweater Woven
log
of T
FP
Figure 11: Distribution of firm productivity by location
Firm Productivity by Location
2.58
2.6
2.62
2.64
2.66
2.68
2.7
2.72
2.74
2.76
2.78
Chittagong Chittagong-EPZ Dhaka Dhaka-EPZ Others
Log
of T
FP
21
Comparing firm productivity from year to year within firms also sheds some
interesting new lights. On average, garment firms are 3 percent more productive in 2003
than in 1999. The improvement in productivity is especially clear for the sample of
domestic firms -- on average, domestic firm productivity is 5.5 percent higher in 2003
than in 1999. Figure 12 presents the movement of firm productivity over time in the
different sub-industries. It is clear that most of the improvements are driven by firms in
the Sweater and Woven industries. These results purely reflect the growth in
productivity within a given firm, and thus are not contaminated by the composition of
firms in different industries. Such an increase in productivity within a firm suggests that
there are some exogenous factors pushing firms to be more productive over time. We
explore one such exogenous factors which is the productivity spillover effects of FDI
firms.
Figure 12: Productivity Growth of Domestic Firms by Sub-industries
22
Productivity Growth of Domestic Firmsby sub-industries
2.4
2.45
2.5
2.55
2.6
2.65
2.7
2.75
1999 2000 2001 2002 2003
KnitwearSweater
Woven
Are FDI firms more productive?
We relate the firm level productivity, Ait, to the ownership of the firms. As shown in
Figure 13, on average, productivity of firms with foreign equity are about 20 percent
higher than purely domestically owned firms.
Figure 13: Productivity of Firms with Different Ownerships
23
Productivity vs Firm Ownership
0
2
4
6
8
10
12
14
16
18
20
Domestic firms FDI firms
tota
l fac
tor
prod
ucti
vity
(in
unit
of o
utpu
t)
What could have explained the 20 percent productivity advantage of FDI firms?
Column (1) of Table (6) regress the estimated lnTFP of firms on a FDI indicator
variable, controlling for industry, year and location fixed effects. This is to isolate the
effect of foreign ownership from the influences of sub-industries, investment climate of
the locations, and the macro economic shock in each year. Given that ownership seldom
change within firms in our sample, between-firms variation in foreign ownership is used
to identify the effect of FDI dummy on productivity. The result shows that a FDI firm is
still about 20% more productive than a domestic firm in the same industry, location and
year. This shows that the effect of foreign equity on firm productivity is independent on
the location of the firms, the sub-industry of the firms and the macro economic
fluctuations. Columns (2) and (3) further include age and export destinations of the
firms in both the between and the OLS regressions. It is clear that FDI firms do have a
24
higher level of productivity, even after we take into account the export destinations and
thus the potential demand shocks of the firms, as well as the experience of the firms as
proxied by age. Moreover, the OLS results show that firms export to US tend to be more
productive, which concurs our previous finding using firm export data from EPB.
Columns (4) to (6) repeat the exercise by using the actual foreign equity share in
the regressions instead of a FDI dummy variable. The results are strikingly similar. This
could be because most of the FDI firms in Bangladesh garment sector have 100 percent
foreign equity, only 7 FDI firms are jointly venture firms with foreign equity no less than
25 percent.
Thus overall there is convincing and statistical significant evidence suggesting
that FDI firms are more productive than otherwise identical domestic firms operating in
Bangladesh. This result is robust after taking into account the effects of locations, sub-
industries, macro fluctuation, export destinations and experience.
Table 6: Dependent Variable – log of TFP
25
(1) (2) (3) (4) (5) (6)Between Between OLS Between Between OLS
FDI dummy variable 0.194* 0.181* 0.245***(0.111) (0.098) (0.088)
Foreign equity share 0.208* 0.194* 0.256***(0.114) (0.101) (0.089)
Age 0.001 0.000 0.001 0.000(0.003) (0.001) (0.003) (0.001)
Export share of US 0.234 0.229*** 0.237 0.234***(0.166) (0.063) (0.166) (0.064)
Export share of EU 0.144 0.130** 0.144 0.132**(0.160) (0.053) (0.160) (0.053)
Region fixed effects Yes Yes Yes Yes Yes YesYear fixed effects Yes Yes Yes Yes Yes YesIndustry fixed effects Yes Yes Yes Yes Yes YesObservations 1027 1013 1013 1027 1013 1013Notes: Asymptotic standard errors in parentheses in Columns (1), (2), (4) and (5). Heteroskadasticity corrected white robust standard errors in parentheses in Columns (3) and (6). Total number of firms in the unbalanced panel is 232 in Columns (1) and (4), and 227 for the rest . Dependent variable is constructed based on Column (4) of Table 5.
Productivity Spillover: Can Domestic Firms Benefit from FDI Firms?
Many countries provide special incentives such as tax holidays or subsidies, and
import duty exemptions to attract FDI, with the assumptions that the presence of FDI will
benefit domestic economy through the some unmeasured “spillover effects.” To date,
there is evidence of “vertical” spillover effects through the contact of domestic upstream
suppliers to the downstream FDI firms (Javorcik, AER, 2004), evidence of “horizontal”
spillover effects however have been quite elusive.
To study whether such effects exists in Bangladesh’s garment sector, we first
relate the estimated TFP of the domestic firms to the presence of FDI firms in the sub-
industries. Presence of FDI firms in sub-industry j, FPjt, is captured by the share of
employment of FDI firms collectively in the sub-industries in a given year, adjusted by
26
the percentage of foreign ownership of FDI firms, FSit, for all firm i in sub-industry j.
This measure of the influence of FDI firms has been used in the literature (Aitken and
Harrison, AER, 1999).
In addition, we further relate the estimated TFP of domestic firms to the TFP of
FDI firms in the same sub-industry and year. In order to capture the economic influence
of the productivity of FDI firms, we weight the TFP of FDI firms with the share of
foreign equity and the share of employment in the industry. Weighting by capital or
output would not change the results.
Given that both the presence of FDI in the industry and the productivity of FDI
firms in the industry do not vary within each firm observation, and are specific to each
industry-year, we have aggregate variables in micro unit, which will artificially deflate
the standard errors of the firm level panel regression (Moulton, RESTAT, 1990). We
correct for such problem nonparametrically by clustering the standard errors of the
regressions by industry-year.
Table 7 presents the regression results. Column (1) shows that controlling for
firm and year fixed effects, productivity of domestic firms increases with the presence of
FDI firms in the sub-industry. However, while the effect is positive, it is not statistically
27
significant. This is quite in line with the finding of the previous literature, and is robust
to the inclusion of other control variables such as age and export destinations in Column
(2). The more interesting result is presented in Columns (3) where we find positive and
significant effects of the productivity spillover of FDI firms on the domestic firms in the
same sub-industry. For every 10 percent increase in the productivity of FDI firms, the
productivity level of domestic firms in the same sub-industry improves by 1.4 percent.
This result is robust to controlling for export shares and age of the firms as shown in
Column (4).
Columns (5) to (8) repeat the same exercise, but instead of using log of TFP as
dependent variable, we use the level of TFP. This is closer to the usual notion of
productivity (Olley and Pakes, Econometrica, 1996). In these specifications, both the
presence of FDI firms and the productivity of FDI firms have positive and statistically
significant effects on the productivity of domestic firms in the same sub-industry.
Overall, there are sufficient statistically evidence suggesting that domestic firms
may benefit from the productivity growth of FDI firms in their sub-industries. Thus, not
only are FDI firms more productive than domestic firms, productivity growth of FDI
firms may spillover to the domestic economy to benefit the domestic firms.
Table 7: Foreign Productivity Spillover
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Dependent Variable ltfp ltfp ltfp ltfp tfp tfp tfp tfp(1) (2) (3) (4) (5) (6) (7) (8)Within Within Within Within Within Within Within Within
FDI share in industry 0.332 0.354 8.790* 8.967**(0.224) (0.223) (4.156) (4.167)
Productivity of FDI 0.142** 0.150** 0.251** 0.253** in industry (0.063) (0.063) (0.097) (0.097)
Age -0.005*** -0.006*** -0.0678** -0.117***(0.002) (0.001) (0.024) (0.024)
Export share of US 0.000 0.000 -0.010 -0.011(0.001) (0.001) (0.043) (0.043)
Export share of EU -0.001 -0.001 -0.016 -0.015(0.001) (0.001) (0.038) (0.038)
Firm fixed effects Yes Yes Yes Yes Yes Yes Yes YesYear fixed effects Yes Yes Yes Yes Yes Yes Yes YesObservations 878 878 878 878 878 878 878 878Notes: Both FDI presense and productivity are specific to industry and year. To correct for correlation of errors within industry-year, we cluster the standard errors in parentheses for each sub-industry-year. Sample consists of an unbalanced panel of 196 wholely domestic owned firms.
Conclusions
This paper studies the relationship between foreign equity and firm productivity of
Bangladesh garment sector. Firm productivity is measured by the total factor
productivity (TFP), which is the level of output that is not explained by inputs, reflects
efficiency in production of the firms. Using between firm variations, we show that FDI
firms on average are 20 percent more productive than domestic firms in the same sub-
industry and location. Furthermore, there is statistically significant evidence suggesting
that domestic firms may benefit from the productivity spillover from the FDI firms. For
every 10 percent increase in FDI firm productivity, the productivity of domestic firms
improve by 1.4 percent. The findings of this paper support a more open FDI policy in
Bangladesh garment sector.
References
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