Does Plant Size Matter? Differential Effects - IA de Investigación especializada en el MIT

¿Importa el tamaño de la planta?? Efectos diferenciales
of Foreign Direct Investment on Wages and
Employment in Indian Manufacturing
Shruti Sharma∗

This paper examines the differential effects, based on the size of the plant, de
industry-level foreign direct investment (FDI) on plant-level employment and
the wages of skilled and unskilled workers in India’s manufacturing sector. On
promedio, there are strong positive differential effects of increased inward-level
FDI for large plants relative to small and average-sized plants in terms of
employment and the average wages of both skilled and unskilled workers. Pequeño
plants experience negative effects from inward FDI, which can be explained
by intra-industry reallocation of output from smaller to larger plants. Después
conducting a regional analysis, I ﬁnd positive spillovers to small plants in Indian
states that receive large and persistent ﬂows of FDI. This suggests that a critical
mass of FDI is necessary for small plants to experience positive spillover effects.

Palabras clave: foreign direct investment, skill, spillovers, wages, workers
JEL codes: D22, F62, J24, J31

I. Introducción

Economic theory and policy has often stressed the important role of foreign
direct investment (FDI) in transforming the productive capacities of an economy
and contributing to the development of human capital. It is posited that increased
globalization, as measured by increased FDI, has greater beneﬁcial effects than
tariff liberalization because of the accompanying transfer of technology and skills to
the domestic economy in the case of the former. Of particular concern are the effects
of spillovers to other domestic players in industries that receive FDI. While most
studies have focused heavily on what factors attract FDI and under what conditions
one observes the spillover effects, the literature on the impacts of such FDI on
employment and wages is less extensive, especially in the developing economy
context and speciﬁcally in the South Asian context.

∗Shruti Sharma: Assistant Professor, Department of Social Sciences, Human Services and Criminal Justice; Borough
of Manhattan Community College, The City University of New York. Correo electrónico: shruti009@gmail.com. I would like to
thank Aradhna Aggarwal, participants at the South Asia Conference on Leveraging FDI for Sustainable Economic
Development at the Copenhagen Business School, colleagues at the economics brown bag seminar at the Indian
Institute of Management in Ahmedabad, the managing editor, and anonymous referees for helpful comments and
suggestions. The usual disclaimer applies.

Asian Development Review, volumen. 35, No. 1, páginas. 52–80
https://doi.org/10.1162/adev_a_00105

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¿Importa el tamaño de la planta?? Differential Effects of Foreign Direct Investment 53

Indian policies have been successful

Most developing economies’ policies are aimed at encouraging more inward
FDI in keeping with growth and development objectives. India has moved to a more
liberalized FDI regime over the past few years, which includes allowing FDI to enter
through the automatic route in most cases while also raising FDI caps for many
sectors. En 2014, India launched its Make in India campaign, which aims to attract
more FDI with a special thrust toward improving domestic production capabilities.
in attracting foreign investors.
According to UNCTAD (2015), FDI in India reached $34 billion in 2014, making it
one of the top 10 global destinations for FDI inﬂows. Sin embargo, little is known about
how this inﬂux has affected wages and employment. An important goal of the Make
in India campaign, which is aligned with India’s National Manufacturing Policy, es
to increase employment in the manufacturing sector in absolute terms. The National
Skill Development Corporation was set up to provide skills to India’s labor force, un
acknowledgment that the development of an economy is contingent on the growth
and development of its human capital. Most studies on FDI in India are focused on
the determinants of inward FDI and are either industry-level studies or case studies.
While the former studies do not take into account important within-industry plant
heterogeneity when estimating the effects of FDI, the latter may be informative but
not statistically robust or generalizable.

This paper focuses on the effects of industry-level FDI on plant-level
employment and the wages of both skilled and unskilled workers in India’s
manufacturing sector. It investigates whether FDI increases plant-level employment
and average wages, and more importantly, whether the change in demand for
workers due to increased FDI inﬂows is skill biased or not. According to traditional
theory, foreign ownership provides host economies with access to knowledge,
cual, if absorbed by domestic workers, enhances the domestic human capital
stock, making it permanently more productive. This impact spills over to domestic
ﬁrms through the training of suppliers, imitation, and labor mobility, while workers
migrate from multinational ﬁrms to domestic ﬁrms and transfer their know-how
to domestic workers through various channels of formal and informal interaction
(Aitken and Harrison 1999, piscina 2013). An improvement in the quality of workers
should lead to an increase in average wages for workers in both domestic and foreign
ﬁrms. Más, if there are complementarities between foreign inputs accompanied
with foreign investment and workers’ skills, an increase in FDI should also lead
to an increase in demand for skilled workers and increase the skill composition at
foreign plants while putting upward pressure on the wage–skill premium. Sin embargo,
spillovers to domestic plants might not occur if inﬂows of FDI are neither large
nor persistent enough to transform the workforce at recipient ﬁrms or create a large
enough supply of skilled workers who can then migrate to smaller domestic ﬁrms.
In such cases, we would see greater poaching of skilled workers from domestic
ﬁrms by foreign ﬁrms as opposed to an increase in the supply of skilled workers.

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54 Asian Development Review

This paper estimates the aforementioned relationship in India by using
plant-level data available from the Annual Survey of Industries (ASI) conducted by
the Ministry of Statistics and Programme Implementation, and industry-level FDI
data from the Department of Industrial Policy and Promotion under the Ministry
of Commerce and Industry, for the years 2000–2006. The main ﬁnding is that with
increased inﬂows of industry-level FDI, large plants experience a greater increase in
the employment of and average wages paid out to both skilled and unskilled workers
relative to small and average-sized plants. The effects are negative for small plants
as far as the employment of production workers is concerned, which suggests that
there are greater market reallocation effects away from small plants with increased
industry-level FDI, causing them to reduce production and employment. Además,
there are negative effects for average-sized and small plants even in terms of average
wages paid out to skilled and unskilled workers, suggesting that there is poaching
of higher-quality production and skilled workers by large plants as industry-level
FDI increases. I also ﬁnd that the differential increase in the employment of
production workers at large plants is biased toward male workers as industry-level
FDI increases. When considering the differential impact on regions, sin embargo, I ﬁnd
that states that are the biggest winners in terms of FDI inﬂows, both in terms of
the quantity and persistence of ﬂows, experience strong spillover effects in the
wage–skill premium and skill composition; eso es, big and small plants alike
experience an increase in relative wages as industry-level FDI increases, también
as a higher composition of skilled workers. This could be because for an industry to
experience positive horizontal spillovers in wages, a critical mass of FDI should
be realized and the inﬂows should persist over a period of time. Only then do
we observe the greater training, movilidad, and imitation that contributes to an
expanded pool of skilled workers in an industry such that plants can beneﬁt from
increased supply and the enhanced skill composition of the workforce. Por ejemplo,
piscina (2013) highlights that higher-skilled former multinational enterprise workers
are better able to transfer technology, while higher-skilled incumbent workers are
better able to absorb the transferred technology. Based on this mode, workers at
multinational enterprises are expected to experience an increase in their skills
only after a certain period of working and training. Además, incumbents are
expected to increase their level of skills only when there is a substantial share of
multinational enterprise workers at their ﬁrms. Además, regions with high levels
of FDI might even have better backward and forward linkages, allowing FDI to ﬂow
over a sustained period of time.

This paper is divided into nine sections. Section II reviews the literature on
the impact of FDI on employment and wages, and the evidence of spillovers. Sección
III presents evidence on regional inequalities in inward FDI in India. The empirical
model is discussed in section IV. A description of the data and measurement of
the variables used in the empirical model can be found in section V. Section VI
discusses the estimation results while robustness checks are presented in section

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¿Importa el tamaño de la planta?? Differential Effects of Foreign Direct Investment 55

VII. A regional analysis of the differential impact of FDI is presented in section
VIII. Section IX concludes.

II. Related Literature and Motivation

In the literature investigating the impacts of FDI, there has been a recent
shift toward plant-level analysis as opposed to industry- or sector-level analysis.
Following Melitz (2003), studies take into account ﬁrm and plant heterogeneity
within industries, which is crucial to understanding the effects of FDI. Earlier
studies investigating the role of FDI on labor focused mainly on the impact of
FDI on labor productivity and whether there were any spillover effects to domestic
plants. Blomstrom and Persson (1983) ﬁnd that an increase in the foreign share in
an industry is correlated with an increase in labor productivity, even at domestically
owned plants within the same industry. This study, sin embargo, does not control
for ﬁxed differences in productivity across industries, which may be a source of
endogeneity bias. Aitken and Harrison (1999) control for industry-level ﬁxed effects
in their study on Venezuela and distinguish between own plant effects and spillover
effects of FDI by considering both plant- and industry-level FDI. They ﬁnd that
while own plant FDI has a positive effect on plant-level productivity, the spillover
effects of FDI are negative, owing mainly to the market reallocation effect. Este
paper follows a similar approach in methodology but mainly considers employment,
skill composition, and wages as outcomes of interest.

There are various other studies that estimate the effects of FDI on
productivity and wages for developed and developing economies. Feenstra and
Hanson (1995) ﬁnd that during the relaxation of the FDI regime in Mexico, el
offshoring of jobs that were relatively unskilled and labor intensive in the United
States but relatively skill intensive in Mexico explained nearly 50% of the increase
in relative wages in Mexico during the early 1980s. This effect was largely driven by
FDI in maquiladoras, which are foreign-owned assembly plants in export processing
zones. The other strand of literature pertains to identifying spillovers. While positive
spillovers of FDI are found for the United States in terms of gains in both total
factor productivity (Keller and Yeaple 2009) and wages (Aitken, harrison, y
Lipsey 1995), these spillover effects are absent for developing economies such as
Mexico and Venezuela (Aitken, harrison, and Lipsey 1995). While my study also
ﬁnds negative spillovers for small plants in India, I ﬁnd that regions receiving large
and persistent FDI inﬂows actually experience positive spillovers. Es posible que
high FDI regions in India mimic a developed economy environment where FDI,
presumably in the presence of strong backward and forward linkages, has been able
to transform domestic capability over time, resulting in increased spillovers.

More recently, piscina (2013) provides evidence of positive spillovers of FDI in
Brazil by using matched employer–employee data to show that as workers migrate
from multinational to domestic ﬁrms there is an increase in the wages of even

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56 Asian Development Review

domestic workers at incumbent ﬁrms. Más, the transfer of technology is greater
the higher the skill level of the worker migrating from the multinational and the
higher the skill level of the worker at the incumbent ﬁrm. Average wages for
incumbent workers at the domestic ﬁrm increase as the share of workers from
multinationals increase at the domestic ﬁrm. In my regional analysis for India, I
show similar effects for small ﬁrms in regions receiving high levels of FDI. Como
highlighted by the mechanism described in Poole (2013), it is likely that there is
a bigger pool of skilled workers in regions that have experienced a large sustained
inﬂow of FDI, allowing for greater instances of knowledge transfers spillover even
to small ﬁrms. Another study of note is by Hijzen et al. (2013), which compares
the effect of FDI on wages across developed and emerging (Brazil and Indonesia)
economías. The authors ﬁnd that there is a positive effect of foreign ownership on
wages, which is mainly driven by the creation of new high-wage jobs.

This paper derives motivation from Das (2002), who theoretically models the
effect of FDI on relative wages in developing economies. Under certain conditions
in his model, FDI might actually decrease relative wages. One possible channel
is a decline in demand for skilled workers as there is intra-industry substitution
of output from less efﬁcient domestic ﬁrms to more efﬁcient (by assumption)
foreign ﬁrms. The second is through inﬂuencing the occupational choices of
skilled workers and crowding them out from entrepreneurial jobs to equally skilled
wage-based positions at multinationals. This paper empirically ﬁnds that there is an
intra-industry substitution of labor from smaller to larger plants as industry-level
FDI increases. Based on the assumption that size may be a proxy for efﬁciency and
the likelihood of receiving FDI, I believe that this result corroborates with what
El (2002) predicts will happen in the case of a technological gap. If there is an
intra-industry substitution of output from small plants to large plants, we must
also expect intra-industry substitution of labor, with employment declining at
small plants and increasing at large plants. While Das (2002) makes a prediction
about what would happen to relative wages on average, this paper considers the
differential effects on average wages for both skilled and unskilled workers. El
main ﬁnding is that while average wages of both skilled and unskilled workers
increase differentially for large plants, small plants actually experience a decline.
Assuming that the technology gap between foreign plants and domestic plants still
exists, this result is in line with the expectation of the model. De hecho, in Indian
states that are (historically) the largest recipients of FDI, this differential is likely
to be smaller. I ﬁnd that there are positive spillovers to both small and large plants
alike.

III. Inward Foreign Direct Investment in India

Most of the literature on FDI for India has focused on the determinants of
FDI inﬂows. There are also a few studies that focus on the impact of FDI on various

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¿Importa el tamaño de la planta?? Differential Effects of Foreign Direct Investment 57

industria- or ﬁrm-level outcomes. FDI has increased in India since the liberalization
of previous restrictions on FDI in the 1990s and it is now one of the major recipients
of FDI among emerging economies (UNCTAD 2015). In addition to liberalization
at the national level, state-level policy reforms have also increased the ease of doing
business to make it more attractive for foreign investors to operate in India.

In a study that investigates the role of state-level policies that affect inward
FDI, Banga (2003) ﬁnds that there is a differential effect of state-level policies
on sources of FDI. While the removal of restrictions shifts FDI from developed
incentives are more effective for
economies to developing economies, ﬁscal
attracting FDI to developing economies. Además, bilateral investment treaties
play an important role in attracting FDI from developed to developing economies.
Aggarwal (2005) investigates the role of labor market institutions in attracting FDI,
distinguishing between domestic-market-seeking and export-oriented FDI to ﬁnd
that while rigid labor market institutions discourage both kinds of FDI, el efecto
is more pronounced in domestic-market-seeking FDI. Mukherjee (2011) shows that
FDI in India is highly concentrated regionally and examines the state-level factors
that play an important role. Market size, agglomeration effects, and the size of the
manufacturing and services base in a state have a positive and signiﬁcant effect on
FDI inﬂows. Por otro lado, she ﬁnds that taxation policies and labor costs have
a signiﬁcant negative impact on FDI inﬂows. morris (2004) echoes the ﬁndings
that FDI is strongly concentrated regionally and further examines the determinants
of FDI inﬂows, speciﬁcally for Gujarat.

These studies highlight the regional concentration of FDI and the importance
of state-level policies that affect taxes, infrastructure, and labor market institutions,
all of which are instrumental in determining the level of FDI inﬂows. In keeping
with these ﬁndings, I will control for these effects while empirically estimating
the relationship between industry-level FDI and plant-level outcomes. Más, este
study will investigate how the estimated relationship varies for each region. I will
divide the states into three groups according to the amount of FDI received: (i) el
top third, (ii) the middle third, y (iii) the bottom third.

IV. Empirical Estimation

In the estimation exercise, I want to distinguish between the effects of
industry-level inward FDI on employment and wages for large, average-sized, y
small plants. For the baseline speciﬁcation, I will use the log of total sales by the
plant as a measure of size. Data on whether a plant is the recipient of FDI is not
available from the ASI. Sin embargo, there are certain beneﬁts of not using plant-level
FDI for the estimations. Plant-level FDI will generate various endogeneity bias
concerns when studying its impact on plant-level variables. We can assume that
FDI mainly goes to the large plants. I provide empirical evidence using Prowess
data to show this in section V. Prowess data is not suitable for the main analysis

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58 Asian Development Review

because it does not have information on the outcome variables of interest, semejante
as employment and the wages of skilled and unskilled employees. Además,
large ﬁrms that do not receive FDI are most likely the competitors of ﬁrms that do
receive FDI and must adjust their technology and management systems to remain
competitive. These ﬁrms are also more capable of making such adjustments than
smaller ﬁrms in the same industry. Using Prowess data, I will further alleviate
concerns regarding endogeneity by showing in section V that there are not a few
focal ﬁrms in an industry receiving all of the FDI. I use the following speciﬁcation
for my estimation:

ln yit = αi + αrt + α j + β1 ln FDI jt + β2 ln FDI jt × ln sizeit + β3 ln sizeit

+ β4 ln Xit + εit

(1)

where yit is the dependent variable at the plant level varying across time t, ai controls
for the plant ﬁxed effects, art is the region-time ﬁxed effects, and a j represents the
industry ﬁxed effects. The variable ln F DI jt is total FDI in industry j, ln sizeit is the
log of measures of plant-level size captured by ﬁxed assets, and ln Xit is a vector
other plant-level controls.

the plant

The various outcomes of interest are at

level and include
total employment, employment of skilled workers (comprising managerial and
supervisory staff and other skilled employees), employment of production
(unskilled) workers, skill composition, total wages, total average wages, and relative
wages. Consider the impact of an increase in industry-level FDI. The interaction
term in the speciﬁcation considers the level of FDI in the industry and the plant size.
As highlighted above, it is assumed that larger ﬁrms are either direct beneﬁciaries
of FDI or are competing ﬁrms that imitate technologies and adjust to increase
their competitiveness. Por lo tanto, we can expect an increase in production with an
increase in industry-level FDI at larger plants, which also has a positive impact
on total employment. Más, given technology transfers and complementarities
between superior technology and quality (proxied by the skills of workers), podemos
assume that bigger ﬁrms will also experience an increase in relative demand for
skilled workers. Por lo tanto, for all the outcome variables, we should expect β2 >
0. Even in cases where size does not act as a proxy for the presence of foreign
equity and technology in a plant, we can expect the biggest plants to respond most
aggressively to an increase in FDI in the industry by upgrading their own technology
and worker skills (p.ej., increasing wages to retain workers) such that β2 > 0. b 1 en
equation (1) captures the spillover effects and the impact of FDI on small plants
in the industry. If the spread of technological know-how due to the presence of
foreign investors leads to an industrywide increase in economic activity, and if this
know-how is transferred to workers on a persistent basis, leading to an increase in
skill of the workforce in general, we should expect β 1 > 0 for all outcome variables

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¿Importa el tamaño de la planta?? Differential Effects of Foreign Direct Investment 59

también. Sin embargo, if there is a greater market contraction effect on smaller domestic
ﬁrms and there is no transfer of technology, but rather a poaching of skilled workers
from domestic plants to large plants that receive FDI, we should expect β 1 < 0 for the outcome variables. There is a concern that in regions receiving high levels of FDI, even small plants are recipients of inward FDI and so a positive β1 does not capture spillovers but rather the effects of plant-level FDI. In section V, I show that, even in high FDI regions, it is plants that are much larger than the average or median size that receive FDI rather than FDI being more evenly distributed across ﬁrms of different size. Therefore, even in these regions, β 1 continues to capture spillover effects. To control for within-industry plant heterogeneity and unobservable time-invariant characteristics that may inﬂuence the relationship that I am trying to estimate, the speciﬁcation includes plant ﬁxed effects. As stressed by Aitken and Harrison (1999) and Keller and Yeaple (2009), various time-invariant unobservable industry characteristics can cause FDI to ﬂow into certain industries rather than others. To make sure these do not affect my estimation, I control for industry ﬁxed effects. Finally, while year ﬁxed effects would control for any economywide policy that affects all plants equally, from Banga (2003), Morris (2004), Aggarwal (2005), and Mukherjee (2011), we know that there are important regional variations in the distribution of FDI and that state policy plays a crucial role in attracting FDI. The estimation therefore controls for state-year ﬁxed effects, which control for any unobservable changes that were made at the state level that would affect inward FDI and the outcome variable. The standard errors in the estimation are robust and have been clustered at the industry-year level. V. Data and Measurement The main data used to measure the variables in the above speciﬁcation are the plant-level data from the ASI released by the Ministry of Commerce and Industry. The survey is the most comprehensive data set of India’s manufacturing sector and has recently been made available as a panel. This data set is better suited to my analysis than the other commonly used Prowess data set because it contains detailed information on employment and wages of skilled and unskilled workers that the latter is unable to provide. The data include information on various plant characteristics such as ﬁxed assets, working capital, total sales, employment, location, and wages for all categories of workers and employees at the ﬁve-digit National Industrial Classiﬁcation (NIC) industry level. For this study, I have used a strongly balanced panel of 5,425 plants. A strongly balanced panel is considered because the ASI is a combination of a survey and census; thus, if some plants are missing for a few years, we cannot infer the exit or entry of those plants. Instead, it is more likely that these ﬁrms were not surveyed in those years. Outcome variables of interest have been used or calculated from the l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 60 Asian Development Review Table 1. Summary Statistics Mean Standard Deviation Log(Fixed capital) Log(Working capital) Log(Production workers) Log(Total employment) Log(Skilled workers) Log(Male workers) Log(Female workers) Log(Managerial workers) Log(Other workers) Log(Total sales) Skill composition Observations Source: Author’s compilation. 18.96 16.32 4.87 5.13 3.51 4.40 3.27 2.68 3.00 18.53 0.24 36,875 (1.86) (2.80) (1.68) (1.67) (1.65) (1.75) (1.74) (1.61) (1.58) (2.50) (0.16) data set. For instance, skill composition has been calculated as a ratio of skilled employees (supervisory and managerial staff as well as other professionals such as engineers, accountants, and designers) to total workers. Relative average wages have been calculated by taking a ratio of the average wages paid out to a skilled employee to the average wages paid out to a production worker. The estimations use the natural logs of all variables except skill composition, which is a ratio. Summary statistics for these variables are reported in Table 1. A list of all the variables used as well as their deﬁnitions and units of measurement are provided in the Appendix (Table A1). In section IV, it was assumed that larger ﬁrms were more likely to receive FDI. Using Prowess, which includes data on foreign ownership, it was demonstrated that ﬁrms receiving FDI are, on average, much bigger in terms of total sales, ﬁxed assets, and total wages. (As mentioned earlier, Prowess data do not contain information on employment.) Table 2 shows the size distribution of ﬁrms receiving FDI from the Prowess data set in the ﬁrst column, followed by all ﬁrms in the Prowess data set and all plants in the ASI data set in the second and third columns, respectively. This is presented for all plants followed by regions receiving low, medium, and high levels of FDI. Firms that receive FDI have a much higher mean and median than the grouping of all ﬁrms in the Prowess data set. These ﬁndings hold for the entire sample when considered separately for low-FDI, medium-FDI, and high-FDI regions. This analysis adds credibility to using size as a proxy for receiving FDI. Using Prowess data, I also show the distribution of FDI across ﬁrms of different size, which is measured as total sales. This shows that there are not just a handful of focal ﬁrms receiving FDI in order to allay endogeneity concerns with the use of industry-level FDI. Figure 1 shows the distribution for the four industry quartiles, with quartile 1 receiving the smallest amount of FDI and quartile 4 receiving the largest. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 Does Plant Size Matter? Differential Effects of Foreign Direct Investment 61 n o i g e R I D F - h g i H n o i g e R I D F - m u i d e M n o i g e R I D F - w o L s t n a l P l l A l l A I S A l l A I D F l l A I S A l l A I D F l l A I S A l l A I D F l l A I S A l l A I D F s s e w o r P s s e w o r P s s e w o r P s s e w o r P s s e w o r P s s e w o r P s s e w o r P s s e w o r P s w o l F t n e m t s e v n I t c e r i D n g i e r o F d r a w n I n i y t i e n e g o r e t e H l a n o i g e R . 2 e l b a T 8 0 8 5 1 , . 8 6 9 5 5 . 0 1 4 1 3 . 9 8 3 7 6 1 8 9 4 2 , . 2 2 5 1 5 . 0 1 1 9 1 . 5 3 6 8 7 9 4 9 2 , . 3 6 2 2 2 1 , . 0 7 7 4 8 . 3 8 3 4 1 1 , 7 1 3 3 . 6 4 1 2 . 5 0 5 3 . 0 8 . 8 7 4 6 2 . 1 8 1 4 . 9 6 5 6 . 5 6 5 4 . 5 8 0 6 . 9 3 0 8 1 , 2 7 3 5 2 , 2 1 0 3 , 0 0 5 2 1 , . 7 6 3 0 4 . 8 4 9 1 2 . 3 8 0 0 5 8 5 6 7 2 , . 3 6 4 8 2 . 0 4 1 0 1 . 9 4 2 5 4 . 7 9 2 7 7 . 0 5 8 4 5 . 0 2 3 0 7 7 1 0 3 , ) n o i l l i m s R ( s e l a s l a t o T 1 7 5 , 6 5 3 . 0 5 4 5 8 . 8 4 1 4 6 . 1 7 6 3 3 . 3 2 2 1 . 0 1 3 2 . 2 3 6 9 1 , 7 4 2 5 , 4 8 3 . 9 6 3 9 3 . 7 2 1 7 4 . 3 3 5 9 7 0 , 7 1 1 . 8 7 5 0 0 . 1 3 2 1 7 . 7 1 8 6 0 7 4 2 . 0 7 3 , 1 0 3 . 6 3 0 , 1 6 8 . 9 9 1 , 1 0 9 5 , 5 3 5 . 9 1 2 7 1 . 4 6 8 3 . 8 3 4 7 8 8 , 1 0 1 . 5 8 3 0 6 . 3 3 1 8 5 . 5 1 6 1 5 1 9 5 . 8 4 9 0 6 . 1 9 8 7 8 . 9 9 8 7 6 2 , 9 2 0 1 . 6 4 4 3 1 . 9 7 1 9 9 . 8 3 6 0 6 1 , 6 3 3 6 . 8 1 5 0 0 . 2 9 1 7 9 . 4 8 7 4 1 1 , 4 0 2 . 1 4 8 7 7 . 2 1 2 , 1 s n o i t a v r e s b O n a i d e M n a e M 2 4 . 1 5 1 , 1 n o i t a i v e D d r a d n a t S ) n o i l l i m s R ( s e g a w l a t o T ) n o i l l i m s R ( s t e s s a d e x i F 0 4 . 7 1 3 . 4 2 7 9 . 9 3 4 0 3 , 7 0 0 . 4 6 0 2 . 2 4 8 3 . 0 6 6 6 7 2 6 . 3 7 9 . 2 1 9 1 . 3 2 8 1 1 , 6 0 9 . 7 9 2 . 3 2 1 5 . 7 3 3 5 8 , 1 2 5 . 7 4 0 3 . 4 2 0 6 . 6 5 4 4 1 2 2 9 , 2 3 9 8 7 , 6 3 6 4 2 , 4 s n o i t a v r e s b O 4 7 . 5 2 9 7 . 2 1 4 0 . 3 3 0 2 . 8 6 4 . 5 2 5 8 . 0 4 7 2 . 3 6 5 4 . 2 4 9 4 . 0 6 n o i t a i v e D d r a d n a t S n a i d e M n a e M 9 4 0 , 8 0 9 . 2 9 0 7 . 6 6 2 2 8 . 2 4 4 0 8 . 8 6 7 0 8 . 7 8 5 4 8 . 4 8 6 5 9 6 6 9 1 , 3 0 3 . 2 6 2 8 . 1 9 1 5 7 . 1 6 3 4 8 0 , 2 0 2 . 9 7 1 1 . 2 4 2 3 5 . 9 1 4 2 4 1 7 5 . 7 4 8 5 0 . 0 0 5 5 6 . 8 1 8 7 8 3 , 0 2 2 8 . 9 5 3 9 7 . 9 5 1 2 9 . 3 9 4 5 4 3 , 0 4 4 8 . 8 7 2 0 8 . 8 9 0 1 . 0 5 4 0 1 . 1 6 7 0 9 . 5 3 5 0 1 . 2 0 7 2 7 1 , 4 n o i t a i v e D d r a d n a t S s n o i t a v r e s b O n a i d e M n a e M . e e p u r n a i d n I = s R , t n e m t s e v n i t c e r i d n g i e r o f = I D F , s e i r t s u d n I f o y e v r u S l a u n n A = I S A . s n o i t a l u c l a c s ’ r o h t u A : e c r u o S l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 62 Asian Development Review Figure 1. Distribution of Foreign Direct Investment by Firm Size for Industry Quartiles l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l FDI = foreign direct investment, Rs = Indian rupee. Source: Centre for Monitoring Indian Economy. Prowess database. https://www.cmie.com/kommon/bin/sr.php?kall =wcontact&page=prowess. The industry-level FDI data used in this study are from the Department of Industrial Policy and Promotion of the Ministry of Commerce and Industry (National Council of Applied Economic Research 2009). The report compiles statistics released by the Reserve Bank of India for 2000–2006. Using the concordance between the Department of Industrial Policy and Promotion’s sector-level codes and the three-digit level NIC 2004 provided in the 2009 report, as well as concordance tables for three-digit NIC codes for 1998–2004 from the Ministry of Commerce and Industry website, inward FDI ﬂows are reported at the NIC 1998 three-digit level. There are a total of 75 industries considered in the data for the manufacturing sector, with signiﬁcant variation across industries. Section VIII of this paper studies the relationship between industry-level FDI and various plant-level employment and wage outcomes for India’s regions. Based on the combined FDI and plant-level data, Indian states have been divided into three groups according to the amount of FDI received: (i) the top third, (ii) the middle third, and (iii) the bottom third. The states in group (i) are Andhra Pradesh, Gujarat, Haryana, Karnataka, Maharashtra, Tamil Nadu, Uttar Pradesh, and West Bengal. The states in group (ii) are Dadar and Nagar Haveli, Delhi, Goa, Jharkhand, Madhya Pradesh, Odisha, Punjab, Rajasthan, and Uttaranchal. The states in group (iii) are Assam, Bihar, Chandigarh, Chhattisgarh, Daman and f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 Does Plant Size Matter? Differential Effects of Foreign Direct Investment 63 Diu, Himachal Pradesh, Kerala, Pondicherry, and others.1 The states that did not receive FDI are not included in the analysis for this section. As mentioned above, Banga (2003), Aggarwal (2005), and Mukherjee (2011) provide evidence on how FDI inﬂows are spatially distributed. Section VIII of this study delves into the consequences that these regional disparities in FDI inﬂows have on employment and the wages of skilled and unskilled workers. VI. Results and Discussion The speciﬁcation in section IV has been estimated for various outcome variables. Table 3 shows how alternate speciﬁcations, especially in terms of various ﬁxed effects, affect the coefﬁcient of interest. The dependent variable in Table 3 is total employment at the plant level. Model 1 only considers the level of FDI (ﬁrm size is proxied by total sales) and it also includes various plant-level controls such as total ﬁxed capital and working capital. Model 1 only controls for plant ﬁxed effects and year ﬁxed effects. The effect of aggregate industry-level FDI on plant-level total employment is negative, but it is not statistically signiﬁcant. Model 2 introduces the interaction term between FDI and plant-level total sales, which is the measure of size being used in this estimation. If we only consider in the interaction term the levels of FDI and total sales, which are two continuous variables, the coefﬁcient is not very informative. It will give the differential effect of FDI on plants that have nonzero total sales relative to plants that have zero total sales. To make this more informative, total sales has been centered around the mean, so we can compare the effect of FDI on plants that are of average size relative to plants that are of below-average size. We ﬁnd that the coefﬁcient on the interaction term is positive and signiﬁcant. This implies that for plants that are larger than the average plant in the sample, an increase in industry-level FDI leads to a bigger increase in total employment relative to plants that are smaller than average. These plants are either receiving FDI or are large enough to compete with plants beneﬁting from FDI, and they are expanding production activity and total employment more than small plants in the same industry. β1 in this model is negative but insigniﬁcant, which can be interpreted as either a lack of industry-level spillovers in terms of employment or simply as small plants not gaining from the increased levels of FDI in their industry. The coefﬁcient β 2 varies from 0.002 to about 0.003. While this may not seem economically signiﬁcant, many industries have seen large percentage increases in FDI. Also, this effect will be bigger the larger the plant is relative to an average-sized plant. In addition, it will vary from industry to industry and region to region. The variations across industries and regions are explored in section VII. Model 3 includes industry ﬁxed effects, which control for any ﬁxed differences across industries that may lead to a higher inﬂow of FDI and affect 1Pondicherry was renamed Puducherry in 2006. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 64 Asian Development Review ) 7 ( ) 6 ( ) 5 ( ) 4 ( ) 3 ( ) 2 ( ) 1 ( l a t o T ( g o L l a t o T ( g o L l a t o T ( g o L l a t o T ( g o L l a t o T ( g o L l a t o T ( g o L l a t o T ( g o L ) t n e m y o l p m e ) t n e m y o l p m e ) t n e m y o l p m e ) t n e m y o l p m e ) t n e m y o l p m e ) t n e m y o l p m e ) t n e m y o l p m e * * 7 3 3 0 0 0 . ) 1 4 1 0 0 0 ( . * * * 8 4 1 0 . ) 0 4 2 0 0 ( . 0 7 3 2 . ) - ( 9 3 7 0 0 . ) - ( s e Y s e Y s e Y o N o N o N * * 5 5 2 0 0 0 . ) 7 2 2 0 0 0 ( . ) 7 1 1 0 0 0 ( . * 1 9 3 0 0 0 − . * * * 1 6 1 0 . * * * 7 8 8 2 . ) 6 0 2 0 0 ( . ) 3 1 2 0 ( . s e Y o N s e Y o N o N o N * * 8 9 2 0 0 . 0 ) 1 4 1 0 0 . 0 ( * * * 5 5 1 . 0 ) 1 4 2 0 . 0 ( 2 3 2 . 2 ) - ( 4 0 1 . 0 ) - ( s e Y s e Y o N o N o N o N * * 0 4 2 0 0 . 0 ) 6 5 2 0 0 . 0 ( ) 7 1 1 0 0 . 0 ( 8 9 3 0 0 . 0 − * * * 3 6 1 . 0 * * * 5 4 0 . 3 ) 8 0 2 0 . 0 ( ) 3 6 2 . 0 ( * * 0 4 2 0 0 . 0 ) 6 5 2 0 0 . 0 ( ) 7 1 1 0 0 . 0 ( 8 9 3 0 0 . 0 − * * * 3 6 1 . 0 * * * 5 4 0 . 3 ) 8 0 2 0 . 0 ( ) 3 6 2 . 0 ( s e Y o N o N s e Y s e Y s e Y s e Y o N o N s e Y s e Y o N ) 5 3 2 0 0 . 0 ( * 0 1 2 0 0 . 0 ) 4 1 1 0 0 . 0 ( * * * 9 6 1 . 0 * * * 6 9 8 . 2 ) 5 0 2 0 . 0 ( ) 2 2 2 . 0 ( 5 7 2 0 0 . 0 − s e Y o N o N s e Y o N o N ) 8 0 2 0 0 . 0 ( 0 5 1 0 0 . 0 − * * * 3 0 2 . 0 * * * 2 6 8 . 2 ) 3 1 1 0 . 0 ( ) 2 2 2 . 0 ( s e Y o N o N s e Y o N o N 9 5 5 3 2 , 3 2 2 0 . 9 5 5 3 2 , 9 0 2 0 . 9 5 5 , 3 2 5 1 2 . 0 9 5 5 , 3 2 3 0 2 . 0 9 5 5 , 3 2 3 0 2 . 0 9 5 5 , 3 2 1 0 2 . 0 9 5 5 , 3 2 0 0 2 . 0 t n e m y o l p m E l a t o T d n a t n e m t s e v n I t c e r i D n g i e r o F . 3 e l b a T ) s e l a s l a t o T ( g o L × ) I D F ( g o L ) I D F ( g o L ) s e l a s l a t o T ( g o L t n a t s n o C E F r a e y - y r t s u d n I E F r a e y - e t a t S s l o r t n o C E F y r t s u d n I E F e t a t S s n o i t a v r e s b O 2 R d e t s u j d A E F r a e Y n e e b s a h ) s e l a s l a t o T ( g o L . l e v e l r a e y - y r t s u d n i I C N t i g i d - e e r h t e h t t a d e r e t s u l c e r a d n a s e s e h t n e r a p n i e r a s r o r r e d r a d n a t S . s t c e f f e d e x ﬁ t n a l p e d u l c n i s l e d o m l l A : s e t o N % 0 1 d n a , % 5 , % 1 e h t t a e c n a c ﬁ i n g i s e t o n e d * d n a , * * , * * * . s t c e f f e d e x ﬁ e h t f o e s u a c e b d e t a l u c l a c e b t o n d l u o c r o r r e d r a d n a t s e h t t a h t s e t a c i d n i ) - ( . n a e m s t i d n u o r a d e r e t n e c . s t c e f f e d e x ﬁ = E F , t n e m t s e v n i t c e r i d n g i e r o f = I D F . s n o i t a l u c l a c s ’ r o h t u A : e c r u o S . y l e v i t c e p s e r , l e v e l l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 Does Plant Size Matter? Differential Effects of Foreign Direct Investment 65 plant-level employment. Model 4 includes state ﬁxed effects in addition to industry ﬁxed effects, which further controls for any ﬁxed differences across states that may be affecting the relationship between inward FDI and plant-level employment. It may be possible, however, that the differences across industries vary over time and β 1 may pick up these changes that are affecting the dependent variable. To control for this, Model 5 includes industry-year ﬁxed effects, which allows us to estimate only the differential effects across big and small plants of industry-level FDI changes. Similarly, differences across states vary across time, especially with respect to state-level policies. As has been highlighted by Banga (2003), Morris (2004), Aggarwal (2005), and Mukherjee (2011), these policies play a very important role in affecting FDI inﬂows. Therefore, Model 6 controls for state-year ﬁxed effects. Model 7 controls for both industry-year ﬁxed effects and state-year ﬁxed effects. The main coefﬁcient of interest β 2 continues to be positive and statistically signiﬁcant across all models. The magnitude also roughly remains the same, though it is largest in Model 7, where we include the most controls. Ideally, we would like to use the speciﬁcation in Model 7 as the baseline because it includes both state-year ﬁxed effects and industry-year ﬁxed effects, but because β 1 is of interest to us in order to estimate the spillover effects to small plants, we use state-year ﬁxed effects and industry ﬁxed effects in all the following estimations. While not presented in Table 3, I also estimated models that include industry- region-year ﬁxed effects to better account for the endogeneity of FDI. Again, the coefﬁcient of the interaction term is what will be better identiﬁed rather than the spillover effects (β 1). The estimation results reveal that the coefﬁcient on the interaction term is robust to this speciﬁcation.2 The speciﬁcation used in all models in Table 4 includes ﬁrm ﬁxed effects, industry ﬁxed effects, and state-year ﬁxed effects. The outcome variables all pertain to employment, starting with total employment at the plant level in Model 1. The effects are not different from those discussed in Table 3, wherein we ﬁnd evidence of a relative increase in total employment at large plants, possibly those that beneﬁt from increased industry-level FDI, and no evidence of spillovers to small plants. Similar effects are found for employment of skilled workers and production workers in Models 3 and 4. Both models show that big plants differentially employ more skilled workers and production workers relative to small plants as industry-level FDI increases. However, Model 3 shows evidence of negative spillovers of production workers to small plants. This can be interpreted as the market contraction effect for small ﬁrms in favor of large ﬁrms due to FDI. As industry-level FDI increases, small plants, which are likely not receiving this FDI nor are productive enough to compete with plants with a foreign presence, experience a decline in market share. Therefore, as their market share and production declines, they experience lower derived demand and less employment 2The results are available from the author upon request. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 66 Asian Development Review ) 7 ( ) 6 ( ) 5 ( f o n o i t i s o p m o C s e e y o l p m E r e h t O r e h t O ( g o L ) s e e y o l p m E l a i r e g a n a M ( g o L ) s e e y o l p m E n o i t i s o p m o C ) s r e k r o W ) s r e k r o W ) t n e m y o l p m E ) 4 ( l l i k S n o i t c u d o r P ( g o L d e l l i k S ( g o L l a t o T ( g o L ) 3 ( ) 2 ( ) 1 ( s r e k r o W d e l l i k S d n a t n e m t s e v n I t c e r i D n g i e r o F . 4 e l b a T * * 3 9 1 0 0 0 . ) 6 4 2 0 0 0 ( . 2 3 2 0 0 0 0 − . ) 5 8 7 0 0 0 0 ( . * * * 3 6 3 0 0 − . ) 9 3 1 0 0 ( . 1 1 5 0 − . s e Y s e Y s e Y ) 0 1 3 0 ( . 6 0 7 2 2 , 5 0 0 0 . * * * 9 5 5 0 0 0 . ) 6 2 3 0 0 0 ( . ) 0 2 1 0 0 0 ( . 1 6 4 0 0 0 − . 9 3 3 0 0 . ) 7 0 2 0 0 ( . * 5 0 0 1 . ) 3 9 5 0 ( . s e Y s e Y s e Y 7 3 8 2 2 , 0 6 0 0 . ) 9 9 2 0 0 . 0 ( * 2 2 2 0 0 . 0 ) 6 2 1 0 0 . 0 ( * * * 3 9 9 0 . 0 1 5 3 0 0 0 . 0 − ) 0 2 2 0 . 0 ( 1 3 2 . 0 − ) 0 9 3 . 0 ( s e Y s e Y s e Y 8 7 3 , 3 2 9 6 0 . 0 5 6 7 0 0 0 . 0 ) 5 3 5 0 0 0 . 0 ( 5 8 7 0 0 0 0 . 0 ) 7 9 1 0 0 0 . 0 ( * * * 2 3 1 0 . 0 − ) 1 6 3 0 0 . 0 ( * * * 7 3 3 . 0 ) 3 6 7 0 . 0 ( s e Y s e Y s e Y 6 0 5 , 3 2 8 1 0 . 0 * * * 2 1 7 0 0 . 0 − * * * 9 5 2 0 0 . 0 ) 2 4 9 0 0 0 . 0 ( ) 0 6 2 0 0 . 0 ( * * * 7 4 1 . 0 * * * 6 5 5 . 2 ) 1 0 2 0 . 0 ( ) 4 8 2 . 0 ( s e Y s e Y s e Y 3 0 5 , 3 2 2 5 1 . 0 * * * 2 7 2 0 0 . 0 ) 0 5 2 0 0 . 0 ( * * * 2 7 8 0 . 0 ) 3 0 1 0 0 . 0 ( ) 9 7 1 0 . 0 ( 6 4 5 . 0 ) 9 8 4 . 0 ( s e Y s e Y s e Y 6 8 4 , 3 2 9 1 1 . 0 * * 5 9 2 0 0 . 0 ) 4 4 2 0 0 . 0 ( ) 9 1 1 0 0 . 0 ( * * * 4 5 1 . 0 * * * 1 4 1 . 3 ) 7 0 2 0 . 0 ( ) 9 5 2 . 0 ( s e Y s e Y s e Y 9 5 5 , 3 2 1 1 2 . 0 ) s e l a s l a t o T ( g o L × ) I D F ( g o L ) s e l a s l a t o T ( g o L E F r a e y - e t a t S s n o i t a v r e s b O 2 R d e t s u j d A E F y r t s u d n I s l o r t n o C t n a t s n o C 8 6 2 0 0 . 0 − * * 1 6 5 0 0 . 0 − ) I D F ( g o L d n u o r a d e r e t n e c n e e b s a h ) s e l a s l a t o T ( g o L . l e v e l r a e y - y r t s u d n i I C N t i g i d - e e r h t e h t t a d e r e t s u l c e r a d n a s e s e h t n e r a p n i e r a s r o r r e d r a d n a t S . s t c e f f e d e x ﬁ t n a l p e d u l c n i s l e d o m l l A : s e t o N . s t c e f f e d e x ﬁ = E F , t n e m t s e v n i t c e r i d n g i e r o f = I D F . y l e v i t c e p s e r , l e v e l % 0 1 d n a , % 5 , % 1 e h t t a e c n a c ﬁ i n g i s e t o n e d * d n a , * * , * * * . n a e m s t i . s n o i t a l u c l a c s ’ r o h t u A : e c r u o S l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 Does Plant Size Matter? Differential Effects of Foreign Direct Investment 67 of production workers. In terms of the composition, however, Model 4 shows that there are no differential effects in terms of bias toward skilled workers. At least compositionally, there is no evidence of complementarities between skilled workers and sophisticated technology that is embodied in FDI, either in terms of differential effects or in terms of spillovers. Models 5 and 6 analyze how the two subcategories of skilled workers (managerial and supervisory staff and other technically skilled employees) are affected by industry-level FDI. The estimations reveal that the differential effects are much larger in the case of other technically skilled employees compared with supervisory and managerial staff. This indicates that there are bigger complementarities between technical skills and FDI than managerial skills and FDI. Alternatively, it could mean that although plants would like to adjust their organizational structures and hire more and better managers as FDI increases, they are unable to do so because of systemic lags in adjustment or rigidities in organizational structures. This could be further exacerbated by the fact that there are supply-side constraints as far as hiring managers is concerned. Table 5 studies the relationship between wages of various worker categories and industry-level inward FDI. Model 1 examines how the total wage bill at the plant level changes with industry-level FDI. Not only do big plants pay out higher total wages than small plants, there are negative spillovers to small plants as industry-level FDI increases. Total wages, however, capture both changes in employment and average wages, and may be a reﬂection of the employment effects observed in Table 4. Model 2, therefore, considers the average wages paid out to workers and whether the positive differential effect for big plants as well as the negative spillover effects to small plants still persist. The dependent variables in Models 3 and 4 are the average wages paid out to skilled workers and production workers, respectively. Again, big plants differentially pay higher average wages to both skilled workers and production workers relative to small plants, while small plants experience negative spillovers as industry-level FDI increases. This implies there is no evidence of the transfer of technology or skills to workers or an upskilling of the labor pool. Bigger plants that are either recipients of FDI or are more aggressively able to compete with plants with FDI poach these workers to stay competitive in the market. There is, however, no differential increase in relative wages or the wage–skill premium. This could be because foreign ﬁrms pay efﬁciency wages to both production and nonproduction workers to elicit more effort. The increase in wages to both categories is perhaps proportional, which is why it does not reﬂect in the measure of the wage–skill premium. Additionally, the measure of skill here does not include education; therefore, it is possible that more educated workers in each of these categories are experiencing a bigger increase in wages than those with less education and training. Unfortunately, I am unable to capture this because of a lack of data. Skilled employees are further classiﬁed into two subcategories—(i) managerial and supervisory staff, and (ii) other skilled employees such as engineers and accountants—in Models 6 and 7, respectively. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 68 Asian Development Review d e l l i k s r e h t O ( g o L l a i r e g a n a M ( g o L e v i t a l e R ( g o L n o i t c u d o r P ( g o L d e l l i k S ( g o L e g a r e v A ( g o L ) e g a w e g a r e v a ) e g a w e g a r e v a ) s e g a w ) e g a w e g a r e v a ) e g a w e g a r e v a ) e g a w ) s e g a W ( g o L ) 7 ( ) 6 ( ) 5 ( ) 4 ( ) 3 ( ) 2 ( ) 1 ( * * 8 2 6 0 0 0 − . * * 4 5 2 0 0 0 . ) 5 5 2 0 0 0 ( . ) 1 0 1 0 0 0 ( . * 2 4 3 0 0 . ) 7 7 1 0 0 ( . * * * 0 5 0 1 . ) 9 6 4 0 ( . s e Y s e Y s e Y 4 3 8 2 2 , 7 4 1 0 . * * * 6 3 8 0 0 . 0 − * * * 8 7 3 0 0 . 0 ) 9 4 2 0 0 . 0 ( ) 9 0 1 0 0 . 0 ( 9 1 8 0 0 . 0 ) 5 8 1 0 . 0 ( * * * 5 3 . 1 1 ) 7 2 4 . 0 ( s e Y s e Y s e Y 0 7 3 3 2 , 6 7 1 . 0 ) 5 9 1 0 0 . 0 ( 3 0 1 0 0 . 0 0 1 1 0 0 . 0 − ) 0 2 8 0 0 0 . 0 ( 8 4 9 0 0 . 0 − ) 9 4 1 0 . 0 ( * * 1 2 9 . 0 ) 9 5 3 . 0 ( s e Y s e Y s e Y 7 5 4 , 3 2 2 3 0 . 0 * * * 2 8 1 0 0 . 0 ) 9 7 1 0 0 . 0 ( ) 8 6 6 0 0 0 . 0 ( * * * 7 7 3 0 . 0 * * 3 9 3 0 0 . 0 − ) 6 1 1 0 . 0 ( * * * 5 3 . 0 1 ) 6 7 1 . 0 ( s e Y s e Y s e Y 1 0 5 , 3 2 3 9 1 . 0 * * * 7 8 2 0 0 . 0 ) 6 6 8 0 0 0 . 0 ( ) 5 1 2 0 0 . 0 ( * * * 2 3 2 0 0 . 0 ) 7 7 6 0 0 0 . 0 ( ) 8 8 1 0 0 . 0 ( * * 3 9 4 0 0 . 0 − * * 0 7 4 0 0 . 0 − * 3 8 2 0 . 0 ) 3 5 1 0 . 0 ( * * * 1 3 . 1 1 ) 4 9 3 . 0 ( s e Y s e Y s e Y 2 6 4 , 3 2 7 3 2 . 0 9 3 1 0 . 0 ) 1 1 1 0 . 0 ( * * * 4 6 . 0 1 ) 3 5 2 . 0 ( s e Y s e Y s e Y 7 5 5 , 3 2 1 6 2 . 0 * * * 3 3 5 0 0 . 0 * * * 3 0 1 0 . 0 − ) 6 0 3 0 0 . 0 ( ) 5 2 1 0 0 . 0 ( * * * 7 6 1 . 0 ) 1 4 2 0 . 0 ( * * * 7 7 . 3 1 ) 8 5 3 . 0 ( s e Y s e Y s e Y 7 5 5 , 3 2 7 3 3 . 0 s e g a W d n a t n e m t s e v n I t c e r i D n g i e r o F . 5 e l b a T ) s e l a s l a t o T ( g o L × ) I D F ( g o L ) I D F ( g o L ) s e l a s l a t o T ( g o L E F r a e y - e t a t S s n o i t a v r e s b O 2 R d e t s u j d A E F y r t s u d n I s l o r t n o C t n a t s n o C d n u o r a d e r e t n e c n e e b s a h ) s e l a s l a t o T ( g o L . l e v e l r a e y - y r t s u d n i I C N t i g i d - e e r h t e h t t a d e r e t s u l c e r a d n a s e s e h t n e r a p n i e r a s r o r r e d r a d n a t S . s t c e f f e d e x ﬁ t n a l p e d u l c n i s l e d o m l l A : s e t o N . s t c e f f e d e x ﬁ = E F , t n e m t s e v n i t c e r i d n g i e r o f = I D F . y l e v i t c e p s e r , l e v e l % 0 1 d n a , % 5 , % 1 e h t t a e c n a c ﬁ i n g i s e t o n e d * d n a , * * , * * * . n a e m s t i . s n o i t a l u c l a c s ’ r o h t u A : e c r u o S l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 Does Plant Size Matter? Differential Effects of Foreign Direct Investment 69 The differential effects are also strong for these categories and there are negative spillovers for the average-sized plant. Putting the results from the employment and wage effects together, we ﬁnd that large plants experience an expansion in employment of both skilled and unskilled workers relative to small plants as industry-level FDI increases, along with a relative increase in the total wage bill and average wages paid out to skilled and unskilled workers. There is no evidence of positive spillovers in terms of wages or employment to average-sized and small plants. Based on the coefﬁcient of log(FDI), which measures the effect of industry-level FDI on averaged-sized to small plants, one can infer that there is no evidence of positive spillovers in terms of wages or employment. In fact, there seem to be negative spillovers to small plants as far as wages of skilled and unskilled workers are concerned, pointing toward the fact that there is probably more poaching than training with increased industry-level FDI. Further, there are negative spillovers to small plants as far as employment of production workers is concerned, likely due to decreased market share from the market reallocation effect of greater industry-level FDI. There also seem to be no relative adjustments in terms of skill composition at large plants as FDI increases; neither is there a relative increase in the demand for skilled workers as reﬂected by the insigniﬁcant effects on the wage–skill premium. It is possible, however, that to ﬁnd stronger effects on spillovers in terms of wage–skill premium or skill composition, we should consider the lagged effects of FDI. I consider this in section VII, which also serves as a robustness check for the results. It could be the case that a critical mass of FDI needs to be achieved before spillover effects are observed. This question will be revisited in section VIII, where I compare regions receiving low, average, and large inﬂows of FDI. In the concluding part of this section, I investigate how the employment and wages of male and female production workers are affected by industry-level inward FDI. There is a different perception about the skills and commitment of male and female production workers, as theorized by Yahmed (2012), such that employers discriminate against female workers. This discrimination is exacerbated as plants globalize and become quality conscious. I ﬁnd that this holds in the context of FDI in India’s manufacturing sector. Table 6 shows that, with an increase in industry-level FDI, large plants differentially increase the employment and average wages paid out to male workers, while the employment of female workers remains unaffected. This leads to a slightly statistically signiﬁcant lower wage for women at large plants relative to small plants. VII. Robustness Checks This section addresses the various endogeneity concerns that can arise when estimating the speciﬁcation in section IV. It is an extension of Table 3, which shows that the estimation is robust to various other speciﬁcations. First, I show that the l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 70 Asian Development Review ) 6 ( e l a m e F r e d n e G ( g o L e l a m e F ( g o L e l a m e F ( g o L e l a M ( g o L ) 5 ( ) 4 ( ) 3 ( ) 2 ( n o i t i s o p m o c ) s e g a w e v i t a l e r ) e g a w e g a r e v a ) r e k r o w ) e g a w e g a r e v a ) 1 ( e l a M ( g o L ) s r e k r o w s r e k r o W e l a m e F d n a e l a M f o s e g a W d n a t n e m t s e v n I t c e r i D n g i e r o F . 6 e l b a T * 2 1 2 0 0 0 . ) 8 2 1 0 0 0 ( . 5 9 1 0 0 0 0 . ) 6 7 3 0 0 0 0 ( . 4 8 5 0 0 0 − . ) 0 9 6 0 0 0 ( . * * 5 8 2 0 . ) 0 1 1 0 ( . s e Y s e Y s e Y 6 6 9 7 , 6 3 0 0 . 0 0 6 0 0 . 0 ) 8 7 3 0 0 . 0 ( * 8 5 2 0 0 . 0 − ) 8 4 1 0 0 . 0 ( 5 0 3 0 . 0 ) 6 5 2 0 . 0 ( 1 8 2 . 0 ) 0 3 3 . 0 ( s e Y s e Y s e Y 8 8 8 , 7 1 1 0 . 0 ) 9 1 4 0 0 . 0 ( 3 5 1 0 0 . 0 ) 3 9 1 0 0 . 0 ( 3 2 3 0 0 . 0 − 3 7 3 0 . 0 ) 5 1 3 0 . 0 ( * * * 4 5 . 0 1 ) 2 9 2 . 0 ( s e Y s e Y s e Y 0 4 9 , 7 2 4 1 . 0 ) 0 4 6 0 0 . 0 ( 9 0 7 0 0 0 . 0 ) 9 8 1 0 0 . 0 ( * 8 1 7 0 . 0 * * * 5 7 5 . 1 ) 4 9 3 0 . 0 ( ) 0 4 5 . 0 ( s e Y s e Y s e Y 4 5 9 , 7 7 5 0 . 0 * * * 5 1 2 0 0 . 0 ) 0 0 2 0 0 . 0 ( ) 0 6 6 0 0 0 . 0 ( * * * 2 2 4 0 . 0 ) 9 1 1 0 . 0 ( * * 0 2 . 0 1 ) 1 9 1 . 0 ( s e Y s e Y s e Y 2 5 1 , 3 2 4 2 2 . 0 * * * 5 4 2 0 0 . 0 ) 7 0 9 0 0 0 . 0 ( ) 6 0 3 0 0 . 0 ( * * * 7 1 1 . 0 * * * 9 0 8 . 2 ) 2 8 1 0 . 0 ( ) 6 2 3 . 0 ( s e Y s e Y s e Y 5 5 1 , 3 2 9 2 1 . 0 ) s e l a s l a t o T ( g o L × ) I D F ( g o L ) s e l a s l a t o T ( g o L E F r a e y - e t a t S s n o i t a v r e s b O 2 R d e t s u j d A E F y r t s u d n I s l o r t n o C t n a t s n o C 8 9 2 0 0 . 0 − * * 9 3 4 0 0 . 0 − * * * 2 1 1 0 . 0 − ) I D F ( g o L l a t o T ( g o L . l e v e l r a e y - y r t s u d n i I C N t i g i d - e e r h t e h t t a d e r e t s u l c e r a d n a s e s e h t n e r a p n i e r a s r o r r e d r a d n a t S . s t c e f f e d e x ﬁ t n a l p e d u l c n i s l e d o m l l A : s e t o N . y l e v i t c e p s e r , l e v e l % 0 1 d n a , % 5 , % 1 e h t t a e c n a c ﬁ i n g i s e t o n e d * d n a , * * , * * * . n a e m s t i d n u o r a d e r e t n e c n e e b s a h ) s e l a s . s t c e f f e d e x ﬁ = E F , t n e m t s e v n i t c e r i d n g i e r o f = I D F . s n o i t a l u c l a c s ’ r o h t u A : e c r u o S l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 Does Plant Size Matter? Differential Effects of Foreign Direct Investment 71 Table 7. Robustness Checks (1) Log(Total (2) Log(Total (3) Log(Total (4) Log(Total Lagged Log(FDI) Log(FDI) × Log(Total ﬁxed capital) Log(Total sales) Lag(Log(FDI)) × Log(Total sales) −0.00685*** (0.00218) employment) employment) employment) employment) −0.00582** −0.00348 (0.00267) (0.00216) 0.00210*** (0.000767) 0.203*** (0.0114) Log(Total ﬁxed capital) Log(FDI) 0.0985*** (0.0168) Log(FDI) × Lag(Log(Total sales)) Lag(Log(Total sales)) Lag(Log(FDI)) × Lag(Log(Total sales)) 0.141*** (0.0224) 0.00360*** (0.00128) 0.151*** (0.0142) 0.200*** (0.0186) −0.00676** (0.00317) 0.00369*** (0.00126) 0.0876*** (0.0232) Constant Controls Industry FE State-year FE Observations Adjusted R2 1.834*** (0.275) Yes Yes Yes 23,559 0.211 3.165*** (0.310) Yes Yes Yes 20,024 0.198 0.0234 (0.350) Yes Yes Yes 20,262 0.118 FDI = foreign direct investment, FE = ﬁxed effects. Notes: All models include plant ﬁxed effects. Standard errors are in parentheses and are clustered at the three-digit NIC industry-year level. Log(Total sales) has been centered around its mean. ***, **, and * denote signiﬁcance at the 1%, 5%, and 10% level, respectively. Source: Author’s calculations. estimation is robust to different measures of size. Model 1 in Table 7 considers ﬁxed assets as a measure of size instead of total sales. The estimation results are not affected by this change. Another important concern is the endogeneity of FDI inﬂows. As mentioned in section IV, one can expect FDI to ﬂow into productive industries, which may lead to an endogeneity bias in the estimates. A few ways in which we control for that in Table 3 is by including industry ﬁxed effects and by showing that the estimation is robust when industry-year ﬁxed effects are included. I further show that the estimation is robust by considering lagged FDI in Model 2. The differential effect is positive, signiﬁcant, and of a greater magnitude, showing that the effects of FDI only increase over time. Another important endogeneity bias that the speciﬁcation possibly suffers from is the reverse causality that may exist between size and the various outcome variables. Bigger plants may employ more workers, pay higher wages, and have a higher skill composition. In 0.197*** (0.0190) 0.0901*** (0.0257) 0.00345** (0.00151) 2.246*** (0.398) Yes Yes Yes 19,960 0.113 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 72 Asian Development Review Model 3 of Table 7, I use lagged total sales and ﬁnd that the main result still holds. Model 4 of Table 6 considers the lagged effects of both FDI and total sales, and ﬁnds that the results are robust to this speciﬁcation as well. VIII. Regional Heterogeneity While the estimation exercise so far has estimated the effect of FDI on plant- level employment and wages, it is important to understand how these effects differ across regions. Banga (2003), Aggarwal (2005), and Mukherjee (2011) highlight the regional FDI disparities in India that are driven by differences in state policies, infrastructure, and labor market institutions. Based on a ranking of the states in these studies and data from the Department of Industrial Policy and Promotion, I have divided the states into three groups according to the amount of FDI received: (i) the top third, (ii) the middle third, and (iii) the bottom third. I estimate the relationship for each of these regions and the models now contain only plant ﬁxed effects, industry ﬁxed effects, and year ﬁxed effects. The outcome variables considered are total employment, skill composition, and relative wages (wage–skill premium). The results are shown in Table 8. The estimates reveal that in states that receive the largest FDI, group (i), there are no differential effects of FDI between big plants and average-sized plants. There are only negative spillovers in terms of total employment to small plants owing to market reallocation effects. This is also the case in group (ii). In group (iii), however, while there are no differential effects of FDI between big and small plants, there are strong spillover effects for both kinds of plants. Models 8 and 9 show higher skill composition and higher relative wages at average-sized plants as industry-level FDI increases. Since these are regions where FDI inﬂows are large and persistent, there is stronger evidence of spillovers. It is possible that a certain critical mass of FDI inﬂows has to be achieved before skilled workers gain from the transfer of technology and knowledge induced by foreign investment. Further, the transfer takes place over time, which is why there is evidence of spillovers only in regions that have historically been and continue to be the biggest recipients of FDI inﬂows. There may be a concern that it is likely that average-sized plants in high-FDI regions might be recipients of FDI, in which case one cannot interpret the coefﬁcient on log(FDI) as spillovers. Therefore, I estimated all speciﬁcations with size centered around the 25th percentile in order to measure the effects of FDI on this group of plants. While not included in this paper, I ﬁnd that the results continue to be robust for this speciﬁcation.3 This ﬁnding is further highlighted in Table 9 in which three states are considered: (i) Maharashtra, a state with a very high level of FDI; (ii) Madhya Pradesh, a state that receives an average amount of FDI; and (iii) Assam, a state 3The results are available from the author upon request. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 Does Plant Size Matter? Differential Effects of Foreign Direct Investment 73 n o i g e R I D F - h g i H n o i g e R I D F - m u i d e M n o i g e R I D F - w o L ) 9 ( e v i t a l e R ( g o L ) 8 ( l l i k S ) 7 ( ) 6 ( l a t o T ( g o L e v i t a l e R ( g o L ) 5 ( l l i k S ) 4 ( ) 3 ( l a t o T ( g o L e v i t a l e R ( g o L ) 2 ( l l i k S ) 1 ( l a t o T ( g o L ) s e g a w e g a r e v a n o i t i s o p m o c ) t n e m y o l p m e ) s e g a w e g a r e v a n o i t i s o p m o c ) t n e m y o l p m e ) s e g a w e g a r e v a n o i t i s o p m o c ) t n e m y o l p m e I D F f o s t c e f f E l a n o i g e R . 8 e l b a T * * * 0 1 2 0 0 . * * 2 3 1 0 0 0 . ) 5 8 3 0 0 0 ( . 1 6 4 0 0 0 0 − . ) 4 6 5 0 0 0 0 . 6 8 2 0 0 0 0 − . ) 4 5 1 0 0 0 ( . 8 4 2 0 0 . ) 3 7 2 0 0 0 0 ( . 2 4 4 0 0 0 − . ) 4 8 2 0 0 ( . * * * 8 9 3 1 − . s e Y s e Y 1 8 1 4 1 8 1 0 0 . ) 6 7 3 0 ( . ) 3 9 4 0 0 0 ( . * * * 7 4 4 0 . ) 5 1 8 0 0 ( . s e Y s e Y 9 8 1 4 1 , 1 1 0 0 . * * 7 8 4 0 0 . 0 ) 3 9 4 0 0 . 0 ( * * * 5 6 2 0 . 0 − ) 9 2 2 0 0 . 0 ( * * * 1 0 1 . 0 * * * 4 7 8 . 4 ) 5 5 3 0 . 0 ( ) 3 0 3 . 0 ( s e Y s e Y 7 1 2 , 4 1 2 5 1 . 0 5 8 2 0 0 . 0 ) 1 0 4 0 0 . 0 ( 6 0 2 0 0 . 0 ) 5 6 1 0 0 . 0 ( 4 8 3 0 . 0 − ) 6 9 2 0 . 0 ( 4 4 5 . 0 ) 9 8 4 . 0 ( s e Y s e Y 0 5 1 , 5 1 1 0 . 0 ) 5 9 8 0 0 0 . 0 ( 0 4 3 0 0 0 . 0 ) 8 8 3 0 0 0 . 0 ( * * * 3 1 2 0 . 0 − ) 7 5 6 0 0 . 0 ( 7 0 1 . 0 ) 8 0 1 . 0 ( s e Y s e Y 6 6 1 , 5 3 2 0 . 0 ) 7 9 4 0 0 . 0 ( 5 1 1 0 0 . 0 ) 4 6 1 0 0 . 0 ( * * * 9 9 1 . 0 * * * 6 9 2 . 4 ) 8 2 3 0 . 0 ( ) 4 8 3 . 0 ( s e Y s e Y 7 7 1 , 5 5 0 2 . 0 4 1 1 0 0 . 0 − * * * 8 0 2 0 . 0 − 5 2 3 0 0 0 . 0 ) 8 4 5 0 0 . 0 ( 8 4 1 0 0 . 0 ) 4 5 1 0 0 . 0 ( 3 2 1 0 . 0 − ) 6 6 2 0 . 0 ( 1 8 1 . 0 ) 1 4 4 . 0 ( s e Y s e Y 6 8 8 , 3 8 0 0 . 0 0 2 2 0 0 0 . 0 ) 2 2 1 0 0 . 0 ( 9 7 9 0 0 0 0 0 . 0 ) 2 9 3 0 0 0 . 0 ( * * 0 7 1 0 . 0 − ) 2 3 7 0 0 . 0 ( * 0 7 1 . 0 ) 5 3 9 0 . 0 ( s e Y s e Y 2 0 9 , 3 6 2 0 . 0 * * * 5 5 1 0 . 0 − ) 8 8 4 0 0 . 0 ( 9 9 9 0 0 0 . 0 ) 9 7 1 0 0 . 0 ( * * * 5 9 1 . 0 * * * 5 5 0 . 4 ) 5 2 3 0 . 0 ( ) 8 8 3 . 0 ( s e Y s e Y 4 1 9 , 3 0 2 2 . 0 ) s e l a s l a t o T ( g o L ) s e l a s l a t o T ( g o L × ) I D F ( g o L ) I D F ( g o L s n o i t a v r e s b O 2 R d e t s u j d A E F y r t s u d n I s l o r t n o C t n a t s n o C . s t c e f f e d e x ﬁ = E F , t n e m t s e v n i t c e r i d n g i e r o f = I D F d n u o r a d e r e t n e c n e e b s a h ) s e l a s l a t o T ( g o L . l e v e l r a e y - y r t s u d n i I C N t i g i d - e e r h t e h t t a d e r e t s u l c e r a d n a s e s e h t n e r a p n i e r a s r o r r e d r a d n a t S . s t c e f f e d e x ﬁ t n a l p e d u l c n i s l e d o m l l A : s e t o N . y l e v i t c e p s e r , l e v e l % 0 1 d n a , % 5 , % 1 e h t t a e c n a c ﬁ i n g i s e t o n e d * d n a , * * , * * * . n a e m s t i . s n o i t a l u c l a c s ’ r o h t u A : e c r u o S l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 74 Asian Development Review ) 9 ( e v i t a l e R ( g o L m a s s A ) 8 ( l l i k S s e t a t S n a i d n I s u o i r a V n i t n e m t s e v n I t c e r i D n g i e r o F . 9 e l b a T h s e d a r P a y h d a M a r t h s a r a h a M ) 7 ( ) 6 ( l a t o T ( g o L e v i t a l e R ( g o L ) 5 ( l l i k S ) 4 ( ) 3 ( l a t o T ( g o L e v i t a l e R ( g o L ) 2 ( l l i k S ) 1 ( ) l a t o T ( g o L ) s e g a w e g a r e v a n o i t i s o p m o c ) t n e m y o l p m e ) s e g a w e g a r e v a n o i t i s o p m o c ) t n e m y o l p m e ) s e g a w e g a r e v a n o i t i s o p m o c ) t n e m y o l p m e 9 7 1 0 0 0 . 4 7 1 0 0 0 . ) 1 3 1 0 0 ( . 1 1 2 0 0 0 − . ) 6 4 4 0 0 0 ( . 9 4 1 0 0 0 − . ) 0 5 6 0 0 0 ( . 3 4 6 0 0 . ) 4 0 1 0 ( . * * * 9 0 3 3 . ) 3 3 2 1 ( . s e Y s e Y 3 3 4 4 3 0 0 . ) 4 2 2 0 0 0 ( . 9 4 1 0 0 − . ) 7 7 3 0 0 ( . * 8 9 4 0 . ) 3 8 2 0 ( . s e Y s e Y 5 3 4 7 5 0 0 . * * 2 6 1 0 . 0 ) 7 2 1 0 . 0 ( ) 2 4 7 0 0 . 0 ( 3 0 2 0 . 0 ) 3 3 1 . 0 ( * * * 5 8 4 . 3 ) 0 5 0 . 1 ( 7 8 1 0 . 0 − s e Y s e Y 6 3 4 9 0 3 . 0 * * 8 2 2 0 . 0 2 7 3 0 0 . 0 ) 2 0 1 0 . 0 ( ) 8 1 3 0 0 . 0 ( 4 2 6 0 . 0 − ) 2 3 5 0 . 0 ( 2 2 9 . 1 ) 1 5 3 . 1 ( s e Y s e Y 1 8 9 9 1 0 . 0 4 4 2 0 0 0 . 0 − ) 3 6 1 0 0 . 0 ( 5 1 4 0 0 0 . 0 − ) 0 0 7 0 0 0 . 0 ( 4 4 1 0 0 . 0 − ) 2 3 1 0 . 0 ( * * 3 1 4 . 0 ) 2 8 1 . 0 ( s e Y s e Y 1 8 9 9 3 0 . 0 * * * 5 0 3 0 . 0 − ) 0 1 7 0 0 . 0 ( 2 3 1 0 0 . 0 ) 9 3 3 0 0 . 0 ( * * * 5 9 1 . 0 * * * 5 3 9 . 3 ) 8 6 5 0 . 0 ( ) 0 6 9 . 0 ( s e Y s e Y 1 8 9 7 4 2 . 0 * * * 4 6 1 0 . 0 ) 8 2 6 0 0 . 0 ( 5 8 3 0 0 . 0 − ) 1 8 2 0 0 . 0 ( * 1 2 9 0 . 0 ) 2 2 5 0 . 0 ( * 6 1 2 . 1 − ) 1 2 6 . 0 ( s e Y s e Y 7 8 4 , 3 1 2 0 . 0 * * 2 8 2 0 0 . 0 ) 6 1 1 0 0 . 0 ( 5 5 4 0 0 0 . 0 − ) 7 4 5 0 0 0 . 0 ( 5 3 4 0 0 . 0 − ) 2 0 1 0 . 0 ( 7 4 2 . 0 − ) 4 5 1 . 0 ( s e Y s e Y 8 8 4 , 3 0 3 0 . 0 * * * 1 9 2 0 . 0 − ) 6 3 7 0 0 . 0 ( * * 6 1 1 0 . 0 ) 3 7 4 0 0 . 0 ( 1 9 7 0 0 . 0 * * * 1 5 9 . 5 ) 1 5 7 0 . 0 ( ) 6 6 8 . 0 ( s e Y s e Y 8 9 4 , 3 3 9 1 . 0 ) s e l a s l a t o T ( g o L ) s e l a s l a t o T ( g o L × ) I D F ( g o L ) I D F ( g o L s n o i t a v r e s b O 2 R d e t s u j d A E F y r t s u d n I s l o r t n o C t n a t s n o C . s t c e f f e d e x ﬁ = E F , t n e m t s e v n i t c e r i d n g i e r o f = I D F d n u o r a d e r e t n e c n e e b s a h ) s e l a s l a t o T ( g o L . l e v e l r a e y - y r t s u d n i I C N t i g i d - e e r h t e h t t a d e r e t s u l c e r a d n a s e s e h t n e r a p n i e r a s r o r r e d r a d n a t S . s t c e f f e d e x ﬁ t n a l p e d u l c n i s l e d o m l l A : s e t o N . y l e v i t c e p s e r , l e v e l % 0 1 d n a , % 5 , % 1 e h t t a e c n a c ﬁ i n g i s e t o n e d * d n a , * * , * * * . n a e m s t i . s n o i t a l u c l a c s ’ r o h t u A : e c r u o S l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 Does Plant Size Matter? Differential Effects of Foreign Direct Investment 75 with a very low level of FDI. Maharashtra experiences an increase in both skill composition and relative wages through spillovers to even average-sized plants as industry-level FDI increases. In fact, there is no differential effect of FDI based on size. In Madhya Pradesh, these spillovers are present for relative wages but not for skill composition or total employment. In Assam, on the other hand, these spillovers are absent. While these tables help give an aggregate sense of the relationship between FDI and various labor outcomes, I further test for whether one observes these when considering a speciﬁc industry. I chose an industry that belongs to the highest quartile in terms of inward FDI and is spread across various regions, Basic Chemicals (NIC 241). Table 10 includes four panels. The ﬁrst panel shows the result for the entire industry and the next three show the results for regions receiving low, average, and high levels of FDI, respectively. All panels echo the results obtained throughout the paper, which is that while there is an intra-industry reallocation of labor from large to small plants in regions with high levels of FDI, there are also positive spillovers to small plants in terms of higher average wages for both production workers and skilled employees, as well as an increase in relative wages for skilled workers. IX. Conclusion In this paper, I investigate the impact of industry-level FDI on plant-level employment and wages for both skilled and unskilled workers. The expectation is that given the nature of FDI, which typically embodies superior technology, increased inﬂows should be accompanied by a transfer of technology to plants and workers, further enhancing the skills and wages of workers. Such a transfer is expected to have positive (spillover) effects, even to those plants that do not receive FDI through the training of workers and labor mobility, and to lead to imitation among plants within an industry. My hypothesis is that the effects of industry-level FDI in terms of spillovers will be differential based on the size of the plant. My empirical analysis, which covers 5,425 plants in India’s manufacturing sector, conﬁrms this hypothesis. Larger plants experience a differential increase in total employment as well as average wages paid out to both skilled and unskilled workers relative to average-sized and small plants. However, small plants experience negative spillovers in terms of employment of production workers and average wages paid out to both skilled and unskilled workers. This suggests that there are strong market reallocation effects as foreign ownership of plants increases in an industry. Further, increased industry- level FDI is associated with a relative increase in demand for male blue-collar workers at large plants relative to average-sized and small plants, while the demand for female blue-collar workers remains unaffected. While there is evidence of an increase in skilled workers, there are no differential compositional changes at big l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 76 Asian Development Review ) 8 ( ) 7 ( ) 6 ( ) 5 ( e v i t a l e R ( g o L e g a r e v A ( g o L e g a r e v A ( g o L e g a r e v A ( g o L ) 4 ( l l i k S ) 3 ( ) 2 ( ) 1 ( d e l l i k S ( g o L n o i t c u d o r P ( g o L l a t o T ( g o L ) s e g a w e g a r e v a ) s e g a w d e l l i k s ) s e g a w n o i t c u d o r p ) s e g a w n o i t i s o p m o c ) s r e k r o w ) s r e k r o w ) t n e m y o l p m e t n e m t s e v n I t c e r i D n g i e r o F f o s t c e f f E e s i W - n o i g e R . 0 1 e l b a T 1 8 8 0 0 . * * * 6 4 3 0 . ) 3 2 5 0 0 ( . * * 5 1 1 0 0 − . ) 5 0 5 0 0 ( . * * 2 0 1 0 0 − . ) 9 0 4 0 0 0 ( . * * 1 4 2 0 . ) 2 2 8 0 0 ( . s e Y 6 5 7 5 3 0 0 . ) 9 4 3 0 0 0 ( . * * * 6 4 3 0 . ) 6 4 4 0 0 ( . s e Y 6 5 7 4 4 2 0 . * * * 6 3 2 0 − . * * 7 8 1 0 . ) 3 3 5 0 0 ( . 0 1 2 0 0 − . ) 6 4 6 0 0 ( . 2 6 8 0 0 0 − . . d e u n i t n o C ) 2 7 1 0 0 ( . 2 6 3 0 . ) 4 8 2 0 ( . 9 8 3 4 6 0 . ) 7 5 9 0 0 0 ( . 7 2 2 0 . ) 4 5 1 0 ( . 9 8 2 0 7 0 . * * * 8 5 2 . 0 ) 2 6 1 0 . 0 ( 7 3 1 0 0 . 0 ) 3 1 6 0 0 . 0 ( ) 1 6 8 0 . 0 ( 5 0 1 . 0 s e Y 7 5 7 5 5 1 . 0 * * * 3 2 4 . 0 ) 4 8 3 0 . 0 ( 4 2 1 0 . 0 ) 2 3 1 0 . 0 ( 5 3 1 . 0 − ) 2 1 2 . 0 ( 0 9 7 9 3 . 0 n o i g e R I D F - w o L s t n a l P l l A * * * 5 9 2 . 0 ) 7 9 3 0 . 0 ( * 3 0 1 0 . 0 − ) 6 1 5 0 0 . 0 ( * * 8 6 2 . 0 ) 1 0 1 . 0 ( s e Y 9 5 7 4 5 2 . 0 ) 3 1 6 0 0 . 0 ( * * * 9 2 5 0 0 . 0 − * * * 2 5 8 0 . 0 ) 4 0 1 0 0 . 0 ( ) 4 6 1 0 . 0 ( s e Y 7 5 7 2 3 0 . 0 8 6 5 0 0 . 0 ) 3 9 4 0 . 0 ( ) 4 4 5 0 0 . 0 ( ) 6 0 8 0 . 0 ( 2 2 1 . 0 s e Y 6 5 7 9 2 1 . 0 6 2 7 0 0 . 0 − * * * 2 4 2 . 0 − * * 6 9 2 . 0 ) 9 5 9 0 . 0 ( 7 3 9 0 0 . 0 − ) 2 8 4 0 0 . 0 ( * * 9 3 2 . 0 ) 0 6 6 0 . 0 ( 0 9 1 3 6 . 0 0 3 2 0 . 0 ) 2 6 1 0 . 0 ( 2 3 7 0 0 . 0 − ) 7 9 3 0 0 . 0 ( 8 8 8 0 . 0 ) 7 7 7 0 . 0 ( 0 9 7 3 1 . 0 * * * 6 5 2 . 0 − ) 8 2 4 0 . 0 ( * * 1 5 2 0 . 0 − ) 5 9 9 0 0 . 0 ( * * 9 8 6 . 0 ) 0 0 2 . 0 ( 9 8 0 8 4 . 0 * * * 2 9 1 . 0 − ) 3 2 3 0 . 0 ( * * * 2 2 3 0 . 0 ) 2 3 6 0 0 . 0 ( * 0 0 3 . 0 − ) 4 2 1 . 0 ( s e Y 7 5 7 7 9 0 . 0 9 2 1 0 . 0 ) 2 1 1 . 0 ( ) 3 9 1 0 . 0 ( 1 2 2 . 0 ) 2 0 3 . 0 ( 0 9 7 5 4 . 0 * * 3 6 3 . 0 − * * * 0 5 2 . 0 − ) 3 9 4 0 . 0 ( * * * 1 4 2 0 . 0 ) 5 8 5 0 0 . 0 ( 8 0 5 0 . 0 − ) 1 5 1 . 0 ( s e Y 9 5 7 3 3 2 . 0 ) 2 5 9 0 . 0 ( 6 1 2 0 0 . 0 ) 7 3 1 0 . 0 ( * * 2 3 3 . 0 − 8 4 3 . 0 ) 2 9 1 . 0 ( 0 9 6 1 5 . 0 ) s e l a s l a t o T ( g o L ) s e l a s l a t o T ( g o L × ) I D F ( g o L ) I D F ( g o L s n o i t a v r e s b O 2 R d e t s u j d A E F e t a t S ) s e l a s l a t o T ( g o L ) s e l a s l a t o T ( g o L × ) I D F ( g o L ) I D F ( g o L s n o i t a v r e s b O 2 R d e t s u j d A l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 Does Plant Size Matter? Differential Effects of Foreign Direct Investment 77 ) 8 ( ) 7 ( ) 6 ( ) 5 ( e v i t a l e R ( g o L e g a r e v A ( g o L e g a r e v A ( g o L e g a r e v A ( g o L ) 4 ( l l i k S ) 3 ( ) 2 ( ) 1 ( d e l l i k S ( g o L n o i t c u d o r P ( g o L l a t o T ( g o L ) s e g a w e g a r e v a ) s e g a w d e l l i k s ) s e g a w n o i t c u d o r p ) s e g a w n o i t i s o p m o c ) s r e k r o w ) s r e k r o w ) t n e m y o l p m e . d e u n i t n o C . 0 1 e l b a T ) 1 0 6 0 0 ( . 7 3 1 0 0 . 5 1 1 0 . * * * 2 0 3 0 . ) 7 2 6 0 0 ( . 1 0 3 0 0 . ) 8 5 1 0 0 ( . 7 3 4 0 0 − . ) 4 0 2 0 0 ( . 8 9 2 0 − . ) 6 5 2 0 ( . 4 1 1 3 2 0 0 . * * * 9 6 1 0 . ) 1 6 1 0 0 ( . 2 5 3 0 0 0 . ) 1 3 8 0 0 0 ( . 7 6 5 0 0 − . ) 7 7 1 0 ( . 1 5 5 1 1 0 0 . ) 5 6 3 0 ( . 4 1 1 1 1 3 0 . * * * 6 0 4 0 . ) 9 9 2 0 0 ( . 0 3 7 0 0 0 − . ) 6 2 8 0 0 0 ( . 3 4 3 0 . ) 0 3 2 0 ( . 1 5 5 9 1 2 0 . * * * 8 8 1 . 0 ) 5 0 3 0 . 0 ( 4 6 1 0 . 0 ) 1 4 1 0 . 0 ( 4 5 2 . 0 − ) 6 4 2 . 0 ( 4 1 1 2 4 1 . 0 * * * 7 3 2 . 0 ) 1 3 3 0 . 0 ( 8 0 1 0 . 0 − ) 2 0 6 0 0 . 0 ( * * 0 0 4 . 0 ) 1 1 1 . 0 ( 1 5 5 7 3 1 . 0 n o i g e R I D F - m u i d e M * * * 8 9 1 . 0 ) 8 2 5 0 . 0 ( 0 8 1 0 . 0 ) 0 0 2 0 . 0 ( 8 1 1 . 0 − ) 3 5 3 . 0 ( 5 1 1 0 5 3 . 0 2 1 1 0 . 0 ) 1 5 1 0 . 0 ( * * 7 3 1 0 . 0 − ) 5 9 3 0 0 . 0 ( * * 4 3 2 . 0 ) 3 1 7 0 . 0 ( 4 1 1 1 3 0 . 0 n o i g e R I D F - h g i H * * * 8 4 3 . 0 ) 7 3 3 0 . 0 ( 8 9 1 0 0 0 . 0 ) 5 4 8 0 0 . 0 ( 9 5 5 0 . 0 ) 0 1 2 . 0 ( 2 5 5 3 1 2 . 0 ) 7 4 7 0 0 . 0 ( 6 6 2 0 0 . 0 − ) 2 5 2 0 0 . 0 ( * 9 5 1 0 . 0 − 0 6 4 0 . 0 ) 3 8 3 0 . 0 ( 1 5 5 9 2 0 . 0 ) 9 9 7 0 . 0 ( * * * 5 0 5 0 . 0 − 7 1 1 . 0 − * * * 2 6 2 . 1 ) 1 3 1 0 . 0 ( ) 8 5 2 . 0 ( 4 1 1 0 1 2 . 0 * * 6 5 3 0 . 0 ) 1 4 1 0 . 0 ( * * * 6 6 2 . 0 − ) 3 8 9 0 0 . 0 ( * * * 1 7 5 . 0 − ) 4 5 1 . 0 ( 1 5 5 3 3 1 . 0 ) 5 7 7 0 . 0 ( 3 2 2 0 . 0 ) 2 8 1 0 . 0 ( 6 6 7 0 . 0 ) 0 2 3 . 0 ( 4 1 1 9 7 2 . 0 * * * 0 7 1 . 0 − ) 9 6 3 0 . 0 ( * * * 4 7 4 0 . 0 ) 5 2 8 0 0 . 0 ( * * * 0 8 7 . 0 − ) 6 6 1 . 0 ( 1 5 5 1 6 0 . 0 ) 8 5 7 0 . 0 ( 8 4 1 0 . 0 ) 0 3 1 0 . 0 ( 1 5 3 . 0 ) 9 3 2 . 0 ( 5 1 1 6 7 4 . 0 * * 7 7 2 0 . 0 ) 2 5 3 0 . 0 ( * * * 0 6 2 . 0 − ) 0 0 1 0 . 0 ( 8 1 2 . 0 − ) 2 9 2 . 0 ( 2 5 5 0 7 1 . 0 ) s e l a s l a t o T ( g o L ) s e l a s l a t o T ( g o L × ) I D F ( g o L s n o i t a v r e s b O 2 R d e t s u j d A ) s e l a s l a t o T ( g o L ) s e l a s l a t o T ( g o L × ) I D F ( g o L ) I D F ( g o L s n o i t a v r e s b O 2 R d e t s u j d A * * 3 9 1 . 0 − * * 9 7 2 . 0 − ) I D F ( g o L . s t c e f f e d e x ﬁ = E F , t n e m t s e v n i t c e r i d n g i e r o f = I D F d n u o r a d e r e t n e c n e e b s a h ) s e l a s l a t o T ( g o L . l e v e l r a e y - y r t s u d n i I C N t i g i d - e e r h t e h t t a d e r e t s u l c e r a d n a s e s e h t n e r a p n i e r a s r o r r e d r a d n a t S . s t c e f f e d e x ﬁ t n a l p e d u l c n i s l e d o m l l A : s e t o N . y l e v i t c e p s e r , l e v e l % 0 1 d n a , % 5 , % 1 e h t t a e c n a c ﬁ i n g i s e t o n e d * d n a , * * , * * * . n a e m s t i . s n o i t a l u c l a c s ’ r o h t u A : e c r u o S l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 78 Asian Development Review plants; neither is there evidence of an increase in the relative wage–skill premium at large plants. While this may suggest that an increase in industry-level FDI in India is not skill biased in its demand for workers nor does it contribute to an increasing pool of skilled workers, analysis at the regional level provides a better picture of the actual effects. Analyzing the effects of industry-level FDI on different regions reveals that even average and small-sized plants in regions that receive the largest inﬂows of FDI experience an increase in both the wage–skill premium and the skill composition of workers. This indicates that perhaps a critical mass of FDI is required to inﬂuence the demand for skilled workers at plants and to contribute to the pool of skilled workers in an industry. The above ﬁndings are important for understanding the effects of a liberalized FDI policy. If the inﬂows of FDI into an industry are low and not sustained over time, we should expect to observe greater intra-industry reallocation of output from domestic ﬁrms to multinational ﬁrms. 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Yahmed, Sarra Ben. 2012. “Gender Wage Gaps Across Skills and Trade Openness.” AMSE Working Papers. Appendix Variable Fixed capital Working capital Production workers Skilled workers Total employment Male workers Female workers Managerial workers Other workers Total sales Skill composition Other skilled composition Table A1. Glossary Description Unit Total value of ﬁxed assets Current assets minus current liabilities Unskilled workers Technical, supervisory, and managerial employees Total number of people employed Male workers Female workers Workers in managerial and supervisory roles Nonmanagerial, nonsupervisory, or nontechnically skilled employees Gross sale value Ratio of skilled workers to production workers Ratio of technically skilled workers to managerial and supervisory workers Rs Rs - - - - - - - Rs - - Rs Rs Rs Continued. Foreign direct investment Wages Average wage Total foreign direct investment received Total amount paid out in wages by the plant Total wages / Total employment l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 80 Asian Development Review Table A1. Continued. Variable Description Unit Skilled average wage Total amount paid out in wages to skilled employees / Number of skilled employees Production average wage Total amount paid out in wages to production workers / Number of production workers Relative wages Ratio of total wages paid to skilled workers to those paid to production workers Relative average wages Managerial average wage Ratio of skilled average wages to production average wages Total amount paid in wages to managerial workers / Number of managerial and supervisory workers Other skilled average wage Total amount paid in wages to technically skilled employees / Male average wage Total amount paid out in wages to males / Number of male Number of technically skilled employees workers Female average wage Total amount paid out in wages to females / Number of female workers Gender relative wages Female composition Lagged Log(FDI) Lag(Log(Total sales)) Ratio of female average wage to male average wage Ratio of female workers to male workers Log of foreign direct investment of the previous year Log of total sales of the previous year Rs Rs Rs Rs Rs Rs Rs Rs - - - - FDI = foreign direct investment, Rs = Indian rupee. Source: Author’s compilation. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 5 1 5 2 1 6 4 3 9 4 9 a d e v _ a _ 0 0 1 0 5 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3
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