Foreign Plants and Industry Productivity: Evidence from Chile

Transcription

1 Foreign Plants and Industry Productivity: Evidence from Chile Natalia Ramondo The University of Texas-Austin March 1, 2009 Abstract This paper studies the effects of foreign plants on a host industry, bringing new evidence from the Chilean manufacturing sector. Foreign plants are systematically larger than domestic Chilean plants, contribute significantly to output production in the manufacturing sector, and mostly serve the Chilean market. Additionally, industries with more foreign plants presence have more productive domestic plants. These facts are captured by a Melitz-type model that I modify to link foreign plants entry to changes in the productivity distribution of a host industry. Productivity increases due to: the entry of more productive foreign plants; the exit of the least productive domestic plants; the entry of more productive domestic plants; and spillovers from foreign to domestic incumbent plants. I test the model s predictions using a Chilean panel of domestic and foreign plants, and a differencein-difference approach. Results show that foreign ownership is a strong predictor of plant productivity and size advantages, for both all and new plants. Moreover, the evidence suggests that productivity gains for a domestic incumbent plant is positively associated with foreign plants presence in the same industry and geographical region. Regarding plants turnover, I find support for a positive correlation between entry of foreign plants into an industry and the exit probability of less productive domestic plants. However, the evidence on domestic entry is inconclusive. I would like to thank Fernando Alvarez, Robert Lucas, Daniel Paravisini, Ronni Pavan, Andrés Rodríguez-Clare, Robert Shimer, Nancy Stokey, Chad Syverson, Sergio Urzua, and other participants at seminars at the University of Chicago for their comments. I also thank two anonymous referees for their helpful suggestions. All remaining errors are mine. Department of Economics, The University of Texas at Austin. nramondo@mail.utexas.edu. 1

2 1 Introduction Which are the effects of foreign plants on a host industry? Foreign plants carry a direct technological component to a recipient economy that other international flows, including trade flows, do not. Moreover, technologies used by foreign plants seem to be on average better than the ones domestic plants operate. Hence, similarly to the effects of opening an industry to trade, the arrival of foreign plants to an industry is often associated with increases in productivity. But, are these increases mainly due to reallocation of production toward better plants? That is, the entry of more productive plants, and exit of less productive domestic plants? Or, is productivity mainly increasing in the host industry because existing domestic plants get more productive due to spillovers effects from foreign plants? Using a panel of domestic and foreign plants for the Chilean manufacturing sector in the nineties, I bring new evidence on the effects of foreign plants on a recipient industry. In particular, I test for the correlations predicted by a Melitz-type model that links foreign plants entry to changes in productivity, revenues, and market shares, in the host industry. From Melitz (2003) s seminal work, incorporating firm heterogeneity as a source of differences in outcomes related to international decisions has become standard, particularly, if one wants to analyze plant-level data. With fixed costs of exporting, Melitz shows that when an industry opens up to trade, it becomes more productive due to reallocation of production toward more productive firms; exporters are indeed the most productive firms in the industry. The main features of Melitz s model of trade are adapted in the framework presented here to treat foreign plants. Firms are heterogenous in productivity, and compete monopolistically in a differentiated goods sector. I assume that a firm that decides to open a foreign affiliate can take its productivity draw abroad. However, a firm has to pay a multinational entry cost to open a foreign affiliate. Consequently, since a firm must be productive enough to overcome such cost, foreign plants end up being the most productive firms in the home, but also in the host industry. First, the model aims to capture the main characteristics of foreign plants in the Chilean manufacturing sector. As previous empirical studies have also shown, foreign plants are systematically larger than domestic plants, contribute significantly to output production, in spite of being a very small fraction of the total number of plants in the manufacturing sector, and the bulk if their revenues comes from serving the Chilean market. Additionally, industries with stronger foreign plants presence have also more productive domestic plants. Second, the model has testable implications about entry, exit, and productivity, related to the presence of foreign plants. In the model, productivity increases due to: the entry of more productive foreign plants; the exit of the least productive domestic plants; and the entry of more productive domestic plants. These are all effects due to plants turnover, or reallocation effects between plants, the main mechanism behind 2

3 Melitz s model of trade. However, it is worth noting that the turnover mechanism in a model with plants rather than goods mobility across countries is slightly different. Foreign plants produce directly in the host economy, and compete for labor with local firms there. Hence, upon they arrival, they push real wages up. With fixed costs of production, less productive domestic firms are forced to exit the industry. 1 Finally, I add to the model productivity spillovers from foreign to domestic incumbent plants. In this way, I generate increases in productivity within a plant associated with the presence of foreign plants. I then test in the data for the existence of spillovers from foreign to domestic Chilean incumbent plants. As other plant-level studies have found, results for the Chilean manufacturing sector show that foreign plants are overall more productive than domestic plants, by around 15%. This advantage survives for new foreign plants. I find support for a positive correlation between the exit probability of a domestic plant, and foreign plants entry; one extra foreign plant into an industry increases the exit probability of a domestic plant by 3-6 percentage points, depending on the year. I also find support for exit occurring among less productive domestic plants. 2 The model predicts that, by tightening the conditions for entering the industry, the entry of foreign plants should be associated with increases in the average productivity of domestic new-comers. The productivity of domestic new plants should be higher in industries with more foreign plants entry, but, at the same time, market shares should shrink. While I find support for the predicted negative correlation between foreign plants entry and market shares, I do not find strong support for the predicted positive correlation between entry of foreign plants and productivity of new domestic plants; results vary across different time periods. Finally, I find support for positive spillovers from foreign to domestic incumbent plants in the same industry, stronger when both industry and region are considered. Domestic incumbents plants experience significant productivity gains, that range from 1 to 7 percentage points, when more productive foreign plants enter the same industry (and region) where they operate. There is a growing empirical literature that examines international trade and production decisions at the plant-level. One part of the literature addresses the factors that induce firms to engage in international trade or production, linking them to characteristics of the home industry. 3 Other part of the literature evaluates the effects of liberalizing trade and Foreign Direct Investment (FDI) on a recipient country. My contribution is to this latter strand of the literature by bringing new evidence on the effects of foreign plants on the Chilean manufacturing sector. The empirical literature on the effects of foreign plants on host industries has studied firm and establishment level data sets from the United Kingdom, the United States, Morocco, and Venezuela, among 1 In Melitz s model, the real wage is pushed up because the prospect of becoming an exporters makes entry into the industry more attractive, and the entry cost is paid in units of labor. 2 See Aw, Chung, and Roberts (2000), and Pavcnik (2002), for similar results regarding international trade exposure, for Taiwan and Chile, respectively. 3 See Melitz (2003), Helpman, Melitz and Yeaple (2004), Bernard, Eaton, Kortum, and Jensen (2004), among others. 3

4 others. Most of it analyzes whether foreign plants are more productive than domestic plants, and their contribution to industry productivity growth. Previous studies have found significant differences in productivity between foreign and domestic plants, for different countries and periods. For the United Kingdom, estimates of foreign advantage in labor productivity are between 6% and 22%. Other studies find that the advantage is a multinational effect: British multinational plants are as productive as foreign plants, the advantage ranging from 13% to 22%. However, US plants still survive as the most productive of the UK manufacturing sector, having a productivity advantage between 5% and 28%. 4 This result mirrors the one on Japanese firms in the US. 5 Conversely, a similar test is weak for a panel of Venezuelan plants. 6 Many empirical studies on the effects of foreign firms have been devoted to testing for the presence of spillovers from foreign to domestic plants. However, results are inconclusive. For Venezuela, the correlation between the presence of joint-ventures and productivity growth of domestic plants is negative. 7 For plants in the Moroccan manufacturing sector, for the second half of the eighties, results are similar: the hypothesis that foreign presence accelerates productivity growth of domestic firms within the same industry is rejected. 8 The same negative result is found for the United Kingdom. 9 In contrast, for American plants, FDI flows seem to account for about 14% of productivity growth. 10 Similarly, tests using establishment data for the United Kingdom, find a significant positive correlation between a domestic plant s TFP and the share of activity of foreign affiliates in the same industry. 11 Finally, other studies conclude that in evaluating spillovers, it is important to consider not only the ownership status of the plant (partially versus fully-owned foreign firms), but also its position in the product chain. 12 The importance of domestic plants turnover and reallocation effects in changes in industry productivity has been mainly study in relationship with trade liberalization episodes. Aw, Chung and Roberts (2000) find evidence for Taiwan suggesting that exposure to trade forces the least productive firms to exit. Pavcnik (2002) finds a significant contribution of market share reallocations to productivity growth in tradable sectors after trade liberalization in Chile. I combine both tests on reallocation effects, as found in the empirical trade literature, as well as tests on spillover effects, linked to the presence of foreign plants in a host industry. The paper is organized as follows. Section 2 presents the theory, and its testable implications. Section 3 shortly describes the data, and productivity measures (The Appendix provides more details). Section 4 4 Griffith et al. (2001), Griffith (1999), Girma et al. (2001), Bloom and Van Reenen (2006). 5 Dom and Jensen (1998). 6 Aitken and Harrison (1999). 7 Aitken and Harrison (1999). 8 Haddad and Harrison (1992). 9 Girma et al. (2001). 10 Keller and Yeaple (2003). 11 Haskel, Pereira and Slaughter (2002). 12 Javorcik Smarzynska, B. and Spatareanu, M. (1998) and Smarzynska, B. (2002). 4

5 summarizes the facts on foreign plants in the Chilean manufacturing sector, presents the tests, and main results on the predictions of the theory. Section 5 concludes. 2 The Model I introduce multinational firms in a Melitz-type model to analyze the effects of foreign plants on a host industry. I test the relationships predicted by the model using plant-level Chilean data. I focus on a two-country world, the host economy Home, and the rest of the world Foreign ( ). Plants producing in a differentiated sector are mobile across countries, and trade only occurs in an homogenous good that acts as the numeraire. The key assumption is that firms can replicate productivity abroad after paying an entry cost to set up a foreign affiliate plant. The model links changes in the distribution of industry productivity to plants turnover generated by the arrival of foreign plants. As in a standard Melitz model, aggregate industry productivity increases due to reallocation of production toward more productive plants, both foreign and domestic. I further introduce spillovers to generate within-plant productivity changes for domestic plants: a plant productivity increases with the average productivity of foreign plants in the industry. The model is presented for one industry, and is easily extended to many industries. Each economy produces two types of goods. A freely-traded homogenous consumption good, Q 0, produced with one unit of labor per unit of output. Provided that this good is produced everywhere, wages are equalized across countries, and equal to one. The second good is a CES composite good, denoted by Q, that aggregates a continuum of varieties ω [0, 1], with elasticity of substitution η > 1, and associate price index P. Preferences. The representative consumer supplies L units of labor, and maximizes utility from consumption, given by U = Q 1 µ 0 Q µ, where Q is the composite CES goods, Q 0 is the homogeneous good, and µ [0, 1] is the expenditure share in Q. Expenditure in each good ω is ( ) 1 η p(ω) r(ω) = R, (1) P where R is aggregate expenditure in good Q. In turn, R = µy, where Y is aggregate expenditure in the economy that equals total income. Technology. There is a continuum of firms in the industry, each producing a differentiated good ω. The only-labor production technology is given by l = f + q z, where f > 0 is a fixed cost of production, z is the firm-specific productivity, l are labor requirements, and q is output. Firms are global monopolists 5

6 in a variety of the industry good; they charge a mark-up over marginal cost. Profits for a firm with productivity z are given by π(z) = 1 r(z) f (2) η = λ (zp ) η 1 Y f, where λ is a constant. 13 A firm with higher productivity z is larger in terms of revenues, profits, output, and employment. 14 Entry, Exit, and Multinational Plants. There is an unbounded number of potential entrants into the industry with unknown productivity parameter z distributed according to the cumulative distribution function G(z), with support [1, ). An entry cost f e (in terms of labor) must be paid in order to know the firm s productivity. 15 Upon entry, productivity is observed. After observing its productivity draw, a firm has to decide whether to produce and pay the fixed cost of production f each period, or exit. There exists a productivity level z d above which all firms with z z d stay in the industry, produce, and eventually, become multinationals, as described below; all firms with productivity z < z d exit upon entry. The decision rule is simply π d (z) 0 ι d (z) = 1, π d (z) < 0 ι d (z) = 0, where π d (z) denotes profits from serving the domestic market for a firm with productivity z, and ι d (z) is an indicator variable that equals one if the firm stays in the industry. Additionally, a firm has to decide whether to serve the foreign market by opening an affiliate there, or just serve the domestic market. Opening an affiliate abroad entails to build a new plant. The cost of setting up a foreign affiliate is fixed, and given by f m (in terms of labor). A firm with productivity z becomes multinational if profits from operating abroad, denoted by π m (z), net of the the multinational entry cost, f m, are non-negative: π m (z) f m 0 ι m (z) = 1 π m (z) f m < 0 ι m (z) = 0, where ι m (z) is an indicator variable that equals one if the firm becomes multinational. As for the domestic market, there exists a productivity level z m such that for all z z m, firms open affiliates abroad, i.e. 13 λ (µ/η)(η/η 1) 1 η. 14 Labor demanded by a firm with productivity z is given by λ 1 (zp ) η (Y/P ) where λ 1 µ[(η 1)/η] η. 15 Indeed, in this framework, there is no distinction between a plant, a product line, and a firm. 6

7 ι m (z) = 1, and below which they only operate domestically, i.e. ι m (z) = 0. Thus, there are two zero profit conditions that define z d and z m, respectively. The zero-profit condition for domestic firms is: π d (z d ) = 1 η r d(z d ) f = 0, (3) while the zero-profit condition for multinational firms is: π m (z m ) f m = 1 η r m(z m ) f f m = 0. (4) Plants with productivity z z m serve both the domestic and foreign market (by producing there); plants with z d z < z m serve only the domestic market; and plants with z < z d exit immediately after entry. The value of entering an industry for a prospective entrant with productive z is just given by total profits: π(z) = ι d (z) [π d (z) + ι(z)(π m (z) f m )], that is, profits from operating in the domestic market if z z d, and, eventually, profits from operating abroad net of multinational entry costs, if z z m. In equilibrium, with an unbounded mass of potential entrants, the expected value of profits net of the entry cost has to be non-positive. 16 Aggregate income Y is pinned down by the size of labor force L. Free entry conditions in Home and Foreign pin down the mass of (national) entrants into the industry, in each country, denoted by M d. The mass of multinational firms a country has is just proportional to M d. 17 Finally, the number of varieties available to Home consumers is given by the mass of national plus foreign plants operating in the industry. In this paper, the purpose is to derive predictions about the (equilibrium) effects of foreign plants on a host economy. This economy is a small open economy that hosts foreign plants from the (large) rest of the world. In turn, this small economy has itself fewer multinational firms, but foreign firms are a larger fraction of total firms than in the larger economy. As shown by Helpman, Melitz, and Yeaple (2003), the following Assumption ensures a world equilibrium with those characteristics. 18 Assumption 1. Home is smaller than Foreign: L < L. Otherwise, they are identical. I denote by M f the mass of foreign plants the Home economy hosts. In what follows, I assume 1, 16 The free-entry condition is 0 π(z)g(z)dz = z π d d (z)g(z)dz + z m (π m(z) f m)g(z)dz = f e. 17 [1 G(z m)]/[1 G(z d )]M d. 18 Under assumption 1, the world equilibrium has the following characteristics: (1) z d = zd and zm = z m ; (2) foreign affiliates are the most productive plants in their home country, and also in the host country, z d < z m (recall that while firms that only operate in the domestic market pay f, multinational firms pay f + f m); (3) the small country has less domestic firms (and multinational firms) than the large country, both in absolute terms, and relative to its size L; and (4) the small country hosts relatively more foreign affiliates than the large country. 7

8 and take the perspective of the small host country, Home. I then take as given the mass of foreign plants arriving to Home, M f, as well as the marginal foreign plant zm, i.e. I do not solve for the world equilibrium. Due to the presence of multinational entry costs, and the fact that firms can replicate productivity abroad, foreign affiliates come from the upper tail of their home productivity distribution, and are, on average, more productive than firms that only serve their home market. 2.1 Testable Implications The Melitz-type model presented in the previous section predicts that the overall industry productivity distribution improves with foreign plants entry because production reallocates toward more productive plants, both domestic and foreign. The following are testable implications regarding the various channels through which the model links changes in aggregate productivity to foreign plants entry. First, define the productivity distribution among active domestic (foreign plants as: F s (z) = z z s g(y) 1 G(z s ) dy, for all z z s, s = d, m. Notice that F s is a truncation of G. Therefore, F s first order stochastically dominates G, i.e. F s fosd G, and if z s < z s, F s fosd F s. Further, if z d < z m, F m (z) fosd F d (z). In the appendix, I show that the productivity of the marginal domestic plant increases with foreign plants entry (Proposition 1), and that the size of a plant with productivity z, in terms of profits, revenues, output, and employment, decreases with foreign plants entry (Proposition 2). These two propositions will be used in deriving the testable implications below. Notice that foreign plants produce in the host market, and hence compete for workers there. Given L, real wages have to go up in the host industry. This is different from Melitz s model of trade: there, it is the existence of exporters in an industry that bid up the real wage, and thus creates plants turnover and increases in aggregate productivity. In the model here, even with the (small) country hardly having multinational firms, it is the presence of foreign plants producing in the host industry that creates similar effects to the ones in Melitz s model. Under Assumption 1, the price index for Home when it hosts foreign plants is: P = η [M d z η 1 df d (z) + M f 1 η z d z m ] 1 z η 1 1 η df m (z). (5) Prediction 1. On average, foreign plants are more productive than domestic plants, and larger in 8

9 terms of revenues (and market share), profits, output and employment. 19 Corollary. Foreign new plants are also, on average, more productive, and larger than domestic new plants. 20 The productivity and size advantage for foreign plants in the host economy stems from the fact that the marginal foreign plant is more productive than the marginal domestic plant in the host economy, i.e. z m > z d. It is crucial the assumption on the existence of multinational entry costs along with foreign affiliates that inherit the productivity of their parent firm. 21 The model predicts a positive correlation between foreign ownership and productivity, and size, for all and new plants, in the host economy. Prediction 2. The exit probability for a domestic (incumbent) plant increases with foreign plants entry: G(z < z d ) G(z < z d) < G(z < z d ) G(z < z d), where z d < z d < z d, and z d corresponds to an industry with less foreign plants entry. Trivially, in the closed economy, the exit probability for a domestic incumbent plant is zero. When the economy opens up to foreign plants, the exit probability for a domestic incumbent plant becomes positive, given by G(z < z d ) G(z < zd c) > 0. This is because z d > zd c ; conditions to stay in the industry are more stringent due to tighter competition coming from the arrival of more productive foreign plants. Moreover, the domestic plants that are more likely to exit are the least productive plants in the industry. The model predicts a positive correlation between the exit probability for a domestic (incumbent) plant, and the number of new foreign plants into a host industry. This probability is higher, the lower the productivity of the domestic plant. Prediction 3. New domestic plants are, on average, more productive when there is foreign plants entry into the industry. This prediction is again derived from the fact that the marginal domestic plant is more productive when there is more foreign plants entering the industry, z d z d. Regarding size, because prices decrease with foreign plants entry, we should observe that new domestic plants with the same productivity are smaller in industries with more foreign plants entry, P > P. The size of the marginal plant does not change, r(z d ) = r(z d ) (because f = f ), but plants with z > z d shrink. On average, we should observe smaller new domestic plants. The model predicts a positive (negative) correlation between productivity (size) of new domestic 19 Here, as aggregate expenditure and income Y are fixed, revenues and market shares are the same. 20 Domestic new plants refer to plants that do not exit immediately upon entry (i.e. z z d ). 21 Also, it is sufficient to assume that G(z) = G (z). 9

10 plants, and the number of new foreign plants, across host industries. Prediction 4. A domestic incumbent plant (i.e. with z z d ) shrinks with foreign plants entry, in terms of revenues (and market shares), profits, output, and employment. The testable implication is that the correlation between the size of a domestic incumbent plant, and the number of new foreign plants, across host industries, should be negative Adding Spillovers I extend the model to incorporate spillovers from foreign to domestic plants. In this way, the arrival of foreign plants to a host industry creates increases in aggregate productivity due to within-plant effects, and not only reallocation effects. I model the spillover as the average productivity of foreign plants entering the production function of domestic plants, l = f + q Z where Z m z m = [M f z η 1 df z m(z)] ɛ 1, m and 0 ɛ 1. This expression aims to capture some sort of imperfect access to foreign plants technology, due to learning, or copying. The zero profit condition for domestic plants in equation (3) is modified so as z is replaced by Z m z, π d (zd s) = λ (zs d Z mp ) η 1 Y f = 0 where zd s denotes the productivity of the marginal domestic plant under the presence of spillovers effects. The aggregate price index is given by P s = [ η Md s 1 η z s d (zz m ) η 1 df d (z) + Z 1/ɛ m ] 1 1 η. (6) Prediction 5. Incumbent domestic plants, i.e. z > zd s, experience productivity gains due to foreign plants entry, given by (Z m 1)z. We should observe a positive correlation between productivity gains of incumbent domestic plants and foreign plants entry. However, the effects on domestic plants size are ambiguous: while productivity gains push plants size up, competition effects (i.e. lower prices) act in the opposite direction. If η > 2, then the productivity effect dominates, and the size of incumbent domestic plants increases with foreign plants entry. 22 Finally, notice that z s d < z d, for η > 1. Thus, it might well be that in industries with more foreign plants entry, the exit probability of a domestic plant is decreased rather than increased. 23 That is, the externality effect is stronger than price effects. However, Prediction 2 still holds as long as the [ ] 22 With spillovers, rd s (z) = ηλzη 2 m M d z d s z η 1 df d (z) + Z 1 1 ɛ +1 η 1 η m, while without them, rd (z) = [ ηλ M d z d s z η 1 df d (z) + Z 1 ɛ m ] 1 1 η. 23 In particular, when an industry opens up to foreign plants, it might be that z c d > zs d. 10

11 externality is not too strong (low ɛ), and consumers have high demand elasticities (high η). Using a panel of plants for the Chilean manufacturing sector in the nineties, I test the correlations predicted by this industry, Melitz-type, model regarding the equilibrium effect of foreign plants on host industries. I analyze whether the presence of foreign plants is correlated with domestic plants turnover, productivity and size. Rather than exploiting an (exogenous) FDI liberalization episode in Chile, the empirical analysis exploits variations in the presence (and entry) of foreign plants across industries (and regions), and across time, in the Chilean manufacturing sector. Results should not be interpreted as causal relationships. 3 Data Description The data are from the Chilean annual survey of manufacturing plants, and has been used before to analyze the effects of trade liberalization in Chile during the eighties, and the dynamics of productivity in relationship with plant turnover. 24 The data set covers the universe of plants of ten or more employees, and includes plant-level data for more than 4,000 manufacturing Chilean plants, each year. The information provided tracks plants over time, including plants entering during the sample period, as wells as plants exiting. 25 The data set spans the period I focus on the period because the variables needed for the analysis are mostly available for this sub-period. A key variable in the following analysis is the ownership status of a plant. Since 1987, the survey includes a question about the ownership structure of the plant, that is, the percentage of foreign control in each year. I consider a plant to be foreign when more than 10% of its nominal capital belongs to non-chilean residents. 26 The ownership data together with the panel structure of the survey enables to track a foreign plant s year of entry into the industry, during the sample period. 27 The Appendix describes in more detail the data and variables, and shows summary statistics (Tables 9 and 8). 24 See Pavcnik (2002), and Levinsohn and Petrin (1999, 2003). 25 The data is at the plant-level, not firm-level. 26 A plant that is more than 50% foreign is considered a majority-owned foreign affiliate. Most foreign plants in the Chilean manufacturing sector are of this type. 27 Moreover, due to the panel structure of the data set, and the availability of the plant ownership status across time, it is possible to record whether a foreign plant s entry is a greenfield project (a new plant), or a Merger and Acquisition (an existing domestic plant). 11

12 3.1 Productivity Measures I present results for two different productivity measures. I consider a labor productivity measure, and a TFP measure constructed as the residual of a production function estimated following Levinsohn and Petrin s method. 28 Consider a production function of the following type (in logs, I skip the time subscripts): log y i = log z i + α l log l i + α k log k i (7) where α l +α k = 1, α l (α k ) is the expenditure share of labor (capital), L i is labor input, and k i is the (real) capital stock, for plant i. 29 I take y i to be real value added for plant i, calculated by subtracting from total revenues r i, the value of raw material used in production m i, fuel f i, and electricity expenditures e i, all in real terms: log y i = log (r i m i f i e i ). I interpret labor input l i as efficiency units of labor, h i L i, where h i is the amount of efficiency units, and L i the number of workers a plant i hires. The available data are the number of employees L i, and (real) total wage payments wh i L i, for plant i. Using the number of employees would overestimate the productivity level of plants that are hiring more efficiency units of labor. 30 Using the wage payments for a plant avoids this problem, and allows to recover the productivity parameter z i up to a constant: log z i α l log w = log y i α l log wh i L i α k log k i. (8) Differences in the underlying efficiency parameter z i across plants should be fully reflected in differences in the right-hand side of Equation (8). 31 Expenditure shares for labor and capital, α l and α k, come from estimating the production function in (7) applying the Levinsohn and Petrin s method. Their method aims to correct for the endogeneity bias that arises due to the correlation between factor usage and unobserved productivity, as well as for the survival bias due to exit of plants. Their method adapts Olley-Pakes s method to deal with the lack of good investment data. Investment levels of a plant are proxied with fuel, electricity and/or raw materials usage. 32 Specifically, I use real fuel and electricity expenditures as proxy variables, and estimate a production function for each two-digit industry. Estimates for α l and α k are used to construct the TFP measure in Equation (8) See Levinsohn and Petrin (1999, 2003). 29 See the Appendix for the construction of this variable. 30 log z i + log h i = log y i α l log L i α k log k i. 31 I exclude the year 2000 when wage payments for a plant are not available. 32 This method turns out to be particularly convenient for the Chilean data. In fact, Levinsohn and Petrin designed it to deal with the Chilean data where one-third of the plants reports zero investment. 33 In the Appendix, I present estimates for α l and α k, by two-digit industry. 12

13 Finally, according to the model, more productive plants should be larger in terms of output, revenues, market shares, employment, and profits. I present some of the results using plant-level (real) revenues, and market shares (in the four digit industry). Revenues are total sells at the plant-level, deflated by the industry price index, in each year. Market share is the share of (real) revenues for a plant within the 4-digit industry, in each year. 4 Empirical Results I adopt the following notation. Subscripts denote plant i, in year t, operating in industry k, and region r. Plant revenues are denoted by r itkr, and plant market shares in the industry by r itkr /R tk, where R tk denotes total revenues for industry k, at time t. I denote by T F P the plant productivity measure calculated by using the Levinsohn and Petrin method. 4.1 Aggregate Facts on Foreign Plants I present some facts on foreign plants in the Chilean manufacturing sector, for the period , drawn from the Annual Survey of manufacturing plants. Revenues Value-added Employment Plants Capital Stock Exports Imports Average Table 1: Participation of Foreign Plants in Selected Variables, by year. Importance of Foreign Plants. Table 1 shows the importance of foreign plants in the Chilean Manufacturing Sector. Among roughly 4,300 plants in the Chilean survey of manufacturing plants, each year between 1995 and 2001, only 6% were foreign by the end of the nineties. However, by the 2001, foreign plants accounted for more than 25% of total manufacturing (real) revenues and (real) value-added, more than 15% of industrial employment, and 15% of the capital stock. These plants also accounted for 30% 13

14 of manufacturing exports, and imported inputs. 34 (average) T F P Revenues Value-added Employment Foreign ,757 61, Domestic ,414 9, (average) Wage payments Capital Stock Market share Export share Import share Foreign 10,533 22, % Domestic 2,622 6, % Variables are averages across plants, and period Market share is the ratio of plant to (4-digit) industry revenues. Exports are shares of total revenues. Imports are shares of total value of inputs. Foreign Plants Advantage. Table 2: Foreign and Domestic Plants. Selected Variables. Table 2 shows selected variables, by ownership status, for the period Clearly, foreign plants are, on average, more productive than domestic plant, and larger in terms of revenues, value-added, employment, wage payments, and capital stock. They also command, on average, market shares that are five times higher than the ones for domestic plants. In terms of international trade, even though foreign affiliates in the Chilean manufacturing sector were more open than domestic plants, they were mainly oriented to serve the domestic market. The average foreign plant exported around 21% of its total value of production, and imported 14% of the value of its inputs, while an average domestic plant generated only 6% of its revenues in export markets, and imported 5% of the value of its inputs. In the Appendix, Figure 2 further shows the distribution of (real) revenues (upper panel), and productivity measure T F P (lower panel), for all and new plants, for the period pooled together, by ownership status. Both distributions of revenues and productivity for foreign plants are a shift to the right of the ones for domestic plants. While differences across industries certainly appear in the data (e.g. some industries do not have any foreign plant), the size advantage of foreign plants remains after controlling for industry; however, the productivity advantage is reduced, particularly when all plants are considered. Table 11 in the Appendix shows foreign advantage for selected variables, by industry. Foreign Plants and Industry Productivity. The scatters in Figure 1 show the relationship between average productivity of domestic plants, and the presence of foreign plants, by (4-digit) industry and 34 As Table 10 in the Appendix shows, foreign plants were concentrated in industries such as Food and Beverages, Chemical Products, and Transportation Equipment. These industries concentrated almost 50% of manufacturing revenues, and more than 60% of revenues generated by foreigners in the Chilean manufacturing sector. Foreign plants generated more than 50% of industry revenues in 10% of total (3-digit) industries, and less than 10% of revenues in 30% of all industries. 14

15 year. In the horizontal axis, foreign plants presence is represented by average TFP for all foreign plants in the industry in year t (left panels), average TFP for only new foreign plants in the industry in year t (center panels), and the share of the number of new foreign plants in total plants in the industry in year t (right panels). In the vertical axis, the upper panels show average TFP for domestic incumbent plants (i.e. the ones that survive at least for all the period ), in the industry in year t; the lower panels show average TFP for new domestic plants into the industry in year t. Average TFP for domestic incumbents Average TFP for Foreign Plants Average TFP for domestic incumbents Average TFP for New Foreign Plants Average TFP for domestic incumbents share of New Foreign Plants in total plants Average TFP for new domestic plants Average TFP for Foreign Plants Average TFP for new domestic plants Average TFP for New Foreign Plants Average TFP for new domestic plants share of New Foreign Plants in total plants Figure 1: Foreign Plants and Productivity for Domestic Plants, by industry and year. In general, the correlation between foreign plants presence in an industry, and domestic plants average productivity, both incumbent and new plants, is positive. The scatters that consider only new foreign plants have a spike at zero; several industries, in some years, do not have any foreign new plant. 4.2 Plant-Level Estimation Results The model predicts that foreign plants are more productive than domestic plants, and consequently they are larger in terms of revenues, and market shares. To test this prediction, I run the following regression: log Z itk = β 1 O itk + β 2 T t + β 3 I k + β 4 P i + u itk. (9) 15

16 Dependent Variable: T F P itk r itk r itk /R tk (in logs) Ownership Dummy 0.16*** 0.32*** 0.28*** [0.06] [0.06] [0.07] Observations 24,173 29,402 29,309 R The dependent variables are productivity measures, revenues, and market share (in the 4-digit industry), for plant i, in year t, industry k. All regressions with plant, year, and industry (3-digit) fixed effects. Robust standard errors in brackets, clustered by plant. * significant at 10%; ** significant at 5%; *** significant at 1%. Table 3: Foreign Ownership Advantage. All Plants. The variable Z itk stands for productivity and size measures, as described in the previous subsection, for plant i, at time t, operating in industry k. The variable O itk is a dummy variable that equals one if plant i is foreign in year t, and zero otherwise. The coefficient β 1 is expected to be positive. Variables T t, I k, and P i denote year, (3-digit) industry, and plant indicators, respectively. I cluster standard errors by plant to control for possible plant-specific shocks across time. As Prediction 1 states, Table 3 shows that there is a productivity advantage for foreign plants of around 13-16% (first two columns). 35 It is unambiguous that foreign plants are more than 30% larger than domestic plants in terms of revenues, and 28% in terms of market shares in the industry. This estimate is in the range of the productivity advantage found for foreign plants in other countries (e.g., in the United Kingdom, between 6% and 22%). A related prediction is that new foreign plants are also more productive than domestic new plants. To test this prediction, I run an equation similar to the one in Equation (9), considering only plants in their entry year; that is, a plant i that enters the industry in year t (and do not exit in year t + 1). I show two specifications, one with all entering plants, and another one in which I exclude foreign plants that enter the industry by acquiring an existing domestic plant (i.e. only greenfield foreign plants, not Merger and Acquisitions ). I include time and industry indicators. 36 I cluster standard errors by (4-digit) industry to control for industry shocks common to all plants entering the industry. Table 4 shows that there is a productivity advantage for new foreign plants when M&A entry is 35 Results adding a joint-venture dummy (that equals one if foreign ownership is less than 50%) are unchanged. The productivity advantage survives if instead of including year, and industry dummies, I interact year-industry dummies. 36 Since there is one observation per (new) plant, I drop plant-level dummies, P i. 16

17 Dependent Variable: T F P itk r itk r itk /R tk T F P itk r itk r itk /R tk (in logs) Ownership Dummy *** 0.57* 0.32*** 1.90*** 1.37*** [0.20] [0.22] [0.31] [0.11] [0.20] [0.209] with M&A entry no no no yes yes yes Observations 1,200 1,600 1,591 1,429 1,864 1,855 R The dependent variables are productivity measures, revenues, and market share (in the 4-digit industry), for a new plant i, in year t, industry k. All regressions with year, and industry (3-digit) fixed effects. Robust standard errors in brackets, clustered by (4-digit) industry. * significant at 5%; ** significant at 1%. Table 4: Foreign Ownership Advantage. New Plants. included. 37 However, the result is insignificant if only foreign entry through greenfield FDI is considered. As the theory predicts, new foreign plants are more than double the size of their domestic counterparts (1.25), in terms of revenues, and have almost 60% larger market shares. Both magnitudes increase to 1.90 and 137%, respectively, when also M&A foreign entry is included. Table 5 shows results regarding the effects of entry of foreign affiliates into an industry on the exit probability of domestic plants in the same industry. Following Melitz-type s model, I am testing whether the arrival of foreign plants is positive correlated with the exit of the least productive domestic plants (Prediction 2). I run the following linear regression: 38 [ X itk(r) = γ 1 log 1 + M f itk(r) + γ 4 log Z itk(r) log ] [ + γ 2 T t log [ ] 1 + M f itk(r) 1 + M f itk(r) ] + γ 3 log Z itk(r) + γ 5 T t + γ 6 I k + γ 7 P i + γ 8 log Y itk + e itk(r). (10) The variable X itk(r) is a dummy that equals one if the domestic plant i, operating in a (4-digit) industry k (and region r), exits at time t + 1, and zero otherwise. 39 The variable M f itk(r) indicates the number of foreign plants that enters the (4-digit) industry k (and region r) where the domestic plant i operates, at time t, as share of total plants in the industry and region, and it could be zero if there is no foreign 37 The result is robust if year 1995 is excluded. This year shows that 54% of domestic plants that exit reappeared as a foreign plant (see the Appendix). 38 Results are similar under a Probit specification. 39 I exclude plants that enter in year t, and exit in year t

18 plants entry. I further interact this variable with time indicators aiming to capture differential effects of foreign plants entry on domestic exit across time. The reference year is 1995, and the period considered The model predicts that the coefficient γ 1 is positive. I also expect the coefficient γ 2 to be positive. The variable Z itk(r) denotes the productivity measure for plant i, in industry k (and region r), at time t. The exit probability in t+1 should be negatively correlated with productivity in t; hence the coefficient γ 2 should be negative. 40 The model further predicts that domestic plants that exit the industry (and region) upon foreign plants entry should be the least productive plants in the industry. To test this prediction, I add a set of variables that interact foreign plants entry and productivity of a domestic plant in the same industry (and region), at time t; I expect the coefficient γ 4 to be negative. I include time T t, (3-digit) industry I k, and plant P i indicators. I cluster standard errors by (4-digit) industry to control for industry shocks common to all plants entering the industry. Still, as the industry dummies are at the 3-digit level while the explanatory variables on foreign entry into the industry are at the 4-digit level, I should control for factors at the 4-digit industry level that affect the exit probability for a domestic plant, and foreign entry. In order to address this omitted-variable bias, Y itk includes a measure of trade openness for (4-digit) industry k of plant i, at time t, constructed from the plant-level data. 41 Trade openness is expected to increase the probability of exit the industry for a domestic plant; hence, I expect the coefficient γ 8 to be negative. 42 Moreover, as suggested by the evidence in Table 1, one might think that openness affects foreign entry because these plants need to use more intermediate inputs from their home country. Also these plants are the ones exporting a larger fraction of their total sales. Table 5 shows results considering foreign plants entering the same industry k (I and II), and industry k and region r (III and IV), as the ones of domestic plant i, at time t. Moreover, I consider domestic plants that exit the industry (I), and region (III), as well as domestic plants that exit the industry (II), and region (IV) due to a Merger and Acquisition (M&A) by a foreign plant. One issue regarding M&A is that foreign plants tend to buy the most productive domestic plants in the host industry. Hence, one would expect that the exit probability for a more productive domestic plant be higher due to foreign M&A entry. The specifications in Table 5 indicate that the coefficient γ 1 in equation 10 is mostly positive, as predicted by the theory, but not significant for the reference year. However, the effect is significant when 40 This regressor is motivated by the fact that productivity could be modeled as a Markov process (Hopenhayn, 1992), in which case, unlike Melitz s model, exit is endogenous. Plants with low productivity today are more likely to have a low productivity draw tomorrow, and then exit. 41 For each t, and industry k, I compute an average of the ratio of exports plus imports over (twice) total sales across plants. The available data on imports refer to intermediate inputs. 42 Pavcnik (2002) finds that more open industries have a higher domestic plants turnover. 18

19 Dependent Variable: X itk X itkr (I) (II) (III) (IV) log 1 + M f itk(r) [0.88] [0.87] [0.49] [0.47] log Z i,t,k,(r) -0.01* -0.01* -0.01* -0.01* [0.01] [0.01] [0.01] [0.01] log Z i,t,k,(r) log 1 + M f i,t,k,(r) * -0.23* [0.25] [0.26] [0.15] [0.13] log Open itk [0.01] [0.01] [0.01] [0.01] T 96 log 1 + M f i,96,k,(r) 0.97* 1.01** [0.57] [0.48] [0.55] [0.59] T 97 log 1 + M f i,97,k,(r) 0.91* 0.89* [0.49] [0.50] [0.26] [0.26] T 98 log 1 + M f i,98,k,(r) [0.50] [0.44] [0.59] [0.43] T 99 log 1 + M f i,99,k,(r) [3.39] [3.04] [1.14] [0.82] Observations 18,559 18,559 18,559 18,559 R The dependent variable X itk(r) is a dummy variable that equals one if the domestic plant i exits at time t + 1 the (4-digit) industry k (I-II), and region r (III-IV); and equals zero otherwise. (I) and (III) include domestic plants that exit the industry (and region); (II) and (IV) also include also domestic plants that exit because of M&A. All regressions with year, (3-digit) industry, and plant fixed effects. Robust standard errors in brackets, clustered by (4-digit) industry. * significant at 10%; ** significant at 5%; *** significant at 1%. : M f itk(r) is number of new foreign plants into the (4-digit) industry k (and region r in V-VIII) of plant i, at time t, as share of total plants in the industry k (and region r). : log Z itk(r) is T F P for a plant i, at time t in industry k (and region r). : Open itk is a measure of openness for industry k of plant i, at time t. Table 5: Effect of Foreign Plants Entry on the Exit Probability of Domestic Plants. 19

20 foreign entry into the same industry as the one of the domestic plant is considered (I-II) for some of the subsequent years (the coefficient γ 2 in 10). A 10% increase in the share of new foreign plants in 1996 and 1997 increases the exit probability of a domestic plant in the same industry, the next period, by 3-5 percentage points, with respect to the reference year. As expected, the correlation between the probability of exit at time t + 1, and plant s productivity at time t (the coefficient γ 3 ), is negative: a 10% higher productivity in year t translates into 0.1 percentage points lower probability of exit in year t + 1, when foreign entry into the same industry or industry and region is considered. Moreover, the coefficient γ 4 on the interaction between foreign plants entry and domestic plant productivity is negative, and significant when foreign entry into industry and region is considered (III-IV). That is, the entry of foreign plants into an industry and region is associated with higher exit probability among less productive domestic plants there. The inclusion of domestic plants that exit the industry (and region) due to M&A by foreign plants do not seem to weaker the results. The result that exiting plants are on average the least productive plants in the industry, and industry productivity improves through turnover is consistence with other studies in the literature, particularly, regarding trade liberalization episodes. For instance, Pavcnik (2002) finds evidence of increases in industry productivity from reallocating resources from less to more efficient producers, in sectors exposed to liberalized trade: exiting plants are 8% less productive than incumbents. Aw, Chen, and Roberts (1997) find that exiting plants are less productive than survivors, for the manufacturing sector in Taiwan, and this is an important channel through which industry productivity increases. Moreover, entry of (heterogenous) new plants contributes to the overall productivity growth in an industry. I turn next to test the correlation between foreign entry and productivity of new domestic plants. Regarding entry, the theory suggests that the arrival of foreign plants to an industry should increase the productivity of domestic plants entering the same industry (Prediction 3). As competition in the industry gets tighter, the marginal domestic plant has to be more productive to survive. Thus, new domestic plants need higher productivity draws to stay in the industry, and start producing. However, tighter competition compresses their market shares. To test this prediction, I run the following regression: [ ] [ ] log Z itk(r) = λ 1 log 1 + M f i,t 1,k,(r) +λ 2 T t log 1 + M f i,t 1,k,(r) +λ 3 T t +λ 4 I k +λ 5 log Y itk +v itk(r). (11) The variable Z itk(r) denotes productivity, or market shares, for a new domestic plant i, at time t, in industry k (and region r). 43 The variable M f i,t 1,k,(r) denotes the number of foreign plants entering the same (4-digit) industry k (and region r) as plant i, at time t 1, as share of total plants in the industry (and region). I include similar interactions between time indicators and foreign plants entry 43 I exclude plants that enter at time t and exit at time t