How much do developing countries benefit from foreign investment? We contribute to this question by comparing the employment and wage practices of foreign and domestic firms in Brazil, using detailed matched firm-worker panel data. In order to control for unobserved worker differences, we examine both foreign acquisitions and divestments and worker mobility, including the joint estimation of firm and worker fixed effects. We find that changes in ownership do not tend to affect wages significantly, a result that holds both at the worker- and firm-levels. However, divestments are related to large job cuts, unlike acquisitions. On the other hand, movers from foreign to domestic firms take larger wage cuts than movers from domestic to foreign firms. Moreover, on average, the fixed effects of foreign firms are considerably larger than those of domestic firms, while worker selection effects are relatively small.
How much do developing countries benefit from foreign investment? This is a question with important implications in terms of how globalization is perceived across the world. In fact, the popular assessment of the international benefits of globalization is perhaps still influenced by the view that multinationals operate “sweatshops” in developing countries. However, a considerable body of academic work indicates that foreign firms pay higher wages than domestic firms in several developing countries ( [
In this paper, we study the case of Brazil, a large developing country which has so far not been examined in the literature about foreign-firm wage differentials. Brazil is also an interesting country to study due to the richness of its data, including a detailed matched employer-employee panel data set that we use here. The quality of the data allows us to make a contribution to the literature (which in most cases uses firm-level data, at least when considering developing countries) also on a methodological level. Specifically, we seek to address the unobserved heterogeneity problem that workers in foreign and domestic firms may be different along dimensions not quantified in the data [
In order to provide a robust contribution to our understanding of the foreign-firm wage premium in developing countries, our paper pursues four different but complementary approaches. First, we examine the evolution of wages as firms change ownership type (domestic or foreign), considering not only the case of acquisitions, when domestic firms become foreign-owned (as in [
Our second approach involves conducting our analysis not only at the firm-level but also at the worker level [
At this point, it is important to clarify the methodological differences between firm-level and worker-level regressions. The firm-level regressions uses “mean-values-variables”, for example, the average wage paid by the firm, the average age and tenure of their workers, etc. The firm-level mobility regressions capture changes in the ownership of the firms. The worker-level regressions use individual worker information, for example, the wage received by a particular worker, his age, tenure, etc. In terms of mobility, in the worker-level regressions we are no longer interested in the effects of the change of ownership of a firm, but the effects of worker mobility who migrated from a domestic firm to a foreign one, or vice versa. Although the specifications of the worker-level and firm-level regressions look similar, the interpretation of their results is completely different, as will be discussed throughout the article.
Third, in order to address such compositional issues in more detail, we also study how job and worker flows evolve as firms change ownership, not only immediately after (i.e. in the first year under new ownership) but also over time. In fact, this aspect strikes us as an important oversight in most of the research about the foreign- firm wage premium, as wages tend to be studied in isolation from employment levels, although the two variables are presumably strongly related.
Finally, we also address the unobserved heterogeneity problem mentioned above by following the same workers as they move across different domestic and foreign firms (Martins 2008). This topic has received attention recently, although the focus has been on FDI spillovers embodied in workers that move from foreign to domestic firms [
To the best of our knowledge, this is one of only two papers that consider both acquisitions and worker mobility while also studying changes from domestic to foreign firms and vice versa. The other paper employing a similar approach is [
In our results, based on a matched sample of about 1350 manufacturing-sector firms, observed from 1995 to 1999, and a total of about 3.3 million worker-years, we find that both acquisitions and divestments do not tend to affect wages significantly. However, although this result holds simultaneously at the firm and the worker- levels, divestments are related to large job cuts, while acquisitions are not followed by significant employment differences. Moreover, movers from foreign to domestic firms take larger wage cuts than movers from domestic to foreign firms (and the latter in many cases see their pay increase or at least not decrease). Finally, when estimating worker and firm fixed effects simultaneously, we find that the fixed effects of foreign firms are on average considerably larger than those of domestic firms. On the other hand, the differences in the worker fixed effects are minor.
The structure of the paper is as follows: Section 2 introduces the data; Sections 3 and 4 describe the firm- and worker-level analysis, respectively; and Section 5 discusses the results.
The main data set used in this paper is RAIS (“Relacao Anual de Informacoes Sociais”, Annual Social Data Report), a Census of all firms and all their formal-sector employees in Brazil conducted by the Ministry of Labour. The data include detailed information about each employee (wages, hours worked, education, age, tenure, gender, worker nationality, etc.) and each firm (industry, region, size, establishment type, etc.) in each year, plus a unique identifier for each employee, each establishment and each firm.1
Although RAIS is particularly rich, it does not include information on (foreign) firm ownership. In order to use such information, we draw on two additional firm-level data sources that we merge in using a common firm identifier. The first data source is CCE (Foreign Capitals Census), a census conducted every five years by the Central Bank of Brazil. These data consider all firms which have at least 50% of their capital owned by foreign investors. Moreover, the census collects detailed information about the foreign ownership structure of firms based in Brazil, including additional data such as exports, imports, location, activity sector, number of employees. We use the information from the 1995 census in order to classify each firm in our sample as domestic or foreign in that first year of our analysis.
The second additional firm-level data source we use is the information compiled by [
When creating our data set, we decided to consider only (manufacturing sector) firms with at least 100 employees in 1995. While the firm size threshold is originally designed to meet our computational constraints, in fact such threshold is not particularly binding. As most foreign firms in Brazil and elsewhere employ 100 or more workers, a rigorous “like-for-like” comparison of domestic and foreign firms would in fact require disregarding smaller firms. Furthermore, in order to ensure we draw on a homogeneous group of firms, we conducted a propensity score matching analysis [
Specifically, we adopted a “nearest-neighbour” matching method, so that each foreign firm was matched to its most “similar” domestic counterpart (in terms of their characteristics in 1995, as indicated by the propensity score). In the construction of this propensity score, we used a large set of covariates, including three-digit industry dummies, state dummies, and quadratics in firm size and the level of exports and in the averages of worker age, gender, schooling and tenure. Moreover, we also imposed a “common support” condition, so that foreign firms which could not be matched (because their propensity score was “too” different―more than 0.01 different―from the propensity score of the “closest” domestic firm) were dropped from the data.2 Finally, after selecting the matched firms in 1995, a total 678 foreign firms and 669 domestic firms, we finally match in their data for 1996 to 1999.
It is due to the richness of the data and/or our computational constraints that we consider in our analysis a period of not more than five years (1995 to 1999). Although this time frame is not particularly long, it is important to underline that this was a period characterized by a large number of mergers and acquisitions in Brazil [
As only a small number of firms exit the data, there is a total of 6337 firm-year observations. Moreover, about 8% of the firms in the data exhibit a change in foreign/domestic ownership-a total of exactly 100 changes, 51 of
which being acquisitions (domestic firms acquired by foreign investors) and the remaining 49 divestments. As to the time distributions of the ownership changes, while the divestments are spread out over the 1996-1999 period, the acquisitions are very strongly concentrated in 1997, which was in fact a ‘boom year’ for such forms of firm entry/expansion [
Given the richness of the data, we consider a large set of firm- and worker-level variables in our analysis. Most of these variables are derived directly from the original data set, but other variables were constructed by us, based on such original variables. The latter group includes worker flow variables, which are created from the worker-level data and then merged back into the firm-level data.
All flow variables (job and workers) are defined in the way that has become standard in the literature [
analyzed. Specifically, the job creation rate is defined as
In terms of worker flows, the hiring rate is
and the churning rate (CRt), a measure of “excessive turnover” [
Before conducting regression analyses, we provide some comparisons from the raw data. We compare three types of firms, the first category (
Variable | Always domestic | Always foreign | |||||
---|---|---|---|---|---|---|---|
Mean | Std. Dev. | N | Mean | Std. Dev. | N | p-test | |
Schooling | 7.551 | 1.978 | 2788 | 9.375 | 2.085 | 3088 | 0.000 |
Experience | 20.447 | 4.827 | 2786 | 17.861 | 3.746 | 3087 | 0.000 |
Tenure | 63.640 | 32.069 | 2788 | 64.943 | 28.302 | 3088 | 0.098 |
Female | 0.185 | 0.195 | 2788 | 0.187 | 0.177 | 3088 | 0.608 |
Foreign worker | 0.006 | 0.016 | 2788 | 0.018 | 0.049 | 3088 | 0.000 |
Firm size | 317.428 | 819.872 | 2788 | 413.229 | 1077.781 | 3088 | 0.000 |
Log avg. hourly pay | 2.045 | 0.556 | 2786 | 2.608 | 0.561 | 3085 | 0.000 |
Change in log pay | 0.007 | 0.257 | 2160 | 0.015 | 0.275 | 2429 | 0.338 |
Foreign firm | 0.000 | 0.000 | 2788 | 1.000 | 0.000 | 3088 | |
Job creation rate | 0.053 | 0.133 | 2164 | 0.060 | 0.152 | 2434 | 0.075 |
Job destruction rate | 0.176 | 0.328 | 2184 | 0.133 | 0.275 | 2445 | 0.000 |
Net job creation rate | −0.124 | 0.381 | 2164 | −0.073 | 0.339 | 2434 | 0.000 |
Job reallocation rate | 0.228 | 0.327 | 2184 | 0.193 | 0.287 | 2445 | 0.000 |
Worker reallocation rate | 0.504 | 0.336 | 2164 | 0.452 | 0.327 | 2434 | 0.000 |
Churning rate | 0.273 | 0.246 | 2164 | 0.258 | 0.249 | 2434 | 0.040 |
1995 | 0.217 | 0.412 | 2788 | 0.208 | 0.406 | 3088 | 0.431 |
1996 | 0.215 | 0.411 | 2788 | 0.207 | 0.405 | 3088 | 0.437 |
1997 | 0.199 | 0.399 | 2788 | 0.201 | 0.401 | 3088 | 0.843 |
1998 | 0.188 | 0.391 | 2788 | 0.195 | 0.396 | 3088 | 0.496 |
1999 | 0.181 | 0.385 | 2788 | 0.189 | 0.392 | 3088 | 0.453 |
Notes: This table describes the characteristics of firms that do not change their domestic/foreign status over the 1995-1999 period. Each firm-year carries the same weight. Schooling refers to the average schooling (measured in years) of the workforce of the firm in each year; experience is defined as Mincer experience; tenure is measured in months; “foreign worker” is a dummy taking value one for workers who are not Brazilian nationals, “firm size” is measured as the (spell-weighted) number of workers in the firm, and pay is measured in 2006 “reais”. Job creation rate and the following job and worker flow rates are defined in the standard way (see main text). “1995”, “1996”, etc., are dummy variables for each year.
Variable | Always domestic | Always foreign | |||||
---|---|---|---|---|---|---|---|
Mean | Std. Dev. | N | Mean | Std. Dev. | N | p-value | |
Schooling | 8.505 | 1.704 | 98 | 9.289 | 1.665 | 140 | 0.000 |
Experience | 18.595 | 3.111 | 98 | 17.956 | 2.983 | 140 | 0.111 |
Tenure | 77.501 | 27.522 | 98 | 77.268 | 30.865 | 140 | 0.952 |
Female | 0.212 | 0.168 | 98 | 0.138 | 0.168 | 140 | 0.001 |
Foreign worker | 0.007 | 0.007 | 98 | 0.008 | 0.012 | 140 | 0.319 |
Firm size | 775.857 | 768.731 | 98 | 689.171 | 693.513 | 140 | 0.365 |
Log avg. hourly pay | 2.517 | 0.449 | 98 | 2.513 | 0.465 | 140 | 0.945 |
Change in log pay | 0.001 | 0.108 | 50 | 0.003 | 0.114 | 139 | 0.882 |
Foreign firm | 0.000 | 0.000 | 98 | 1.000 | 0.000 | 140 |
Job creation rate | 0.045 | 0.093 | 50 | 0.051 | 0.188 | 139 | 0.814 |
---|---|---|---|---|---|---|---|
Job destruction rate | 0.083 | 0.115 | 50 | 0.113 | 0.198 | 140 | 0.313 |
Net job creation rate | −0.038 | 0.172 | 50 | −0.063 | 0.294 | 139 | 0.583 |
Job reallocation rate | 0.128 | 0.119 | 50 | 0.164 | 0.250 | 140 | 0.327 |
Worker reallocation rate | 0.393 | 0.186 | 50 | 0.422 | 0.334 | 139 | 0.562 |
Churning rate | 0.265 | 0.217 | 50 | 0.257 | 0.365 | 139 | 0.880 |
1995 | 0.490 | 0.502 | 98 | 0.000 | 0.000 | 140 | 0.000 |
1996 | 0.490 | 0.502 | 98 | 0.000 | 0.000 | 140 | 0.000 |
1997 | 0.010 | 0.101 | 98 | 0.329 | 0.471 | 140 | 0.000 |
1998 | 0.010 | 0.101 | 98 | 0.336 | 0.474 | 140 | 0.000 |
1999 | 0.000 | 0.000 | 98 | 0.336 | 0.474 | 140 | 0.000 |
Notes: This table describes the characteristics of firms that switch from domestic to foreign status over the 1995-1999 period. The left columns describe these firms while they are domestic owned and the right columns describe these same firms when they are foreign owned. See
Variable | Always domestic | Always foreign | |||||
---|---|---|---|---|---|---|---|
Mean | Std. Dev. | N | Mean | Std. Dev. | N | p-value | |
Schooling | 8.315 | 2.190 | 65 | 9.061 | 2.793 | 38 | 0.136 |
Experience | 19.878 | 3.624 | 65 | 20.406 | 7.592 | 38 | 0.634 |
Tenure | 57.403 | 29.748 | 65 | 57.272 | 43.017 | 38 | 0.986 |
Female | 0.173 | 0.151 | 65 | 0.098 | 0.128 | 38 | 0.011 |
Foreign worker | 0.013 | 0.013 | 65 | 0.013 | 0.054 | 38 | 0.926 |
firm size | 230.923 | 368.663 | 65 | 97.026 | 130.192 | 38 | 0.033 |
Log avg. hourly pay | 2.422 | 0.636 | 65 | 2.480 | 0.639 | 38 | 0.657 |
Change in log pay | 0.044 | 0.244 | 40 | 0.027 | 0.350 | 35 | 0.812 |
Foreign firm | 1.000 | 0.000 | 65 | 0.000 | 0.000 | 38 | |
Job creation rate | 0.025 | 0.050 | 40 | 0.100 | 0.324 | 35 | 0.152 |
Job destruction rate | 0.321 | 0.518 | 40 | 0.577 | 0.749 | 38 | 0.083 |
Net job creation rate | −0.297 | 0.536 | 40 | −0.526 | 0.902 | 35 | 0.178 |
Job reallocation rate | 0.346 | 0.505 | 40 | 0.669 | 0.741 | 38 | 0.027 |
Worker reallocation rate | 0.654 | 0.504 | 40 | 0.824 | 0.762 | 35 | 0.254 |
Churning rate | 0.308 | 0.304 | 40 | 0.098 | 0.581 | 35 | 0.050 |
1995 | 0.385 | 0.490 | 65 | 0.000 | 0.000 | 38 | 0.000 |
1996 | 0.292 | 0.458 | 65 | 0.132 | 0.343 | 38 | 0.064 |
1997 | 0.215 | 0.414 | 65 | 0.158 | 0.370 | 38 | 0.481 |
1998 | 0.108 | 0.312 | 65 | 0.342 | 0.481 | 38 | 0.003 |
1999 | 0.000 | 0.000 | 65 | 0.368 | 0.489 | 38 | 0.000 |
Notes: This table describes the characteristics of firms that switch from foreign to domestic status over the 1995-1999 period. The left columns describe these firms while they are foreign owned and the right columns describe these same firms when they are domestic owned. See
Again, the left-hand-side columns describe those firms before they undergo their change in ownership and the right-hand-side columns describe those firms after the change in ownership. In all tables, the very last column displays the p-value of the test of the equality of the means of each variable across the two subsamples.
Each table describes average worker characteristics of each firm-year, in which all firm-years are weighted equally, regardless of firm size. Besides the standard human capital variables (schooling, experience, gender, tenure), and real wages and real wage growth, we also present information about the workers’ nationality (Brazilian or non-Brazilian). Finally, we also include descriptive statistics about job and worker flows and year dummy variables.
First, when comparing always-domestic and always-foreign firms (
Finally,
Overall, our findings from the descriptive statistics suggest that acquisitions and divestments are different processes, not only in terms of the before-after changes in firm and worker characteristics but also in terms of the type of firms subject to each type of change of ownership (i.e. when comparing the left columns of
In the next section, we extend these comparisons to a regression framework.
Our empirical analysis involves the estimation of wage, size and job and worker flow equations, firstly using data aggregated at the firm level. In the case of wages, the equation we consider, based on equation (12) and the discussion in Appendix C, is:
in which
We also decompose the wage differential between acquisitions and divestments. In fact, there are no ‘a priori’ reasons for the effect of such changes in ownership to be symmetric, i.e. for the effects of divestments to be equal to minus the effect of acquisitions. We carry out this decomposition by considering the following wage equation:
in which all variables take the same meaning as in Equation (1),
and
β3 and β4 are the parameters of interest, indicating the average change in wages for firms that undergo acquisitions or divestments, respectively.
Moreover, we also find that, when disentangling the wage differences between acquisitions and divestments, there are no significant differences between the two types of ownership change. This result is robust to controlling for worker characteristics (column 6) and to restricting the sample to the last year before ownership change
OLS-1 | OLS-2 | FE-1 | FE-2 | FE-3 | FE-4 | FE-5 | FE-6 | |
---|---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
Schooling | 0.183 (0.005)*** | 0.070 (0.009)*** | 0.070 (0.009)*** | 0.0007 (0.020) | ||||
Experience (years) | 0.057 (0.008)*** | 0.071 (0.017)*** | 0.070 (0.017)*** | 0.131 (0.060)** | ||||
Tenure (months) | 0.003 (0.0008)*** | 0.0004 (0.0009) | 0.0004 (0.0009) | 0.003 (0.005) | ||||
Female (%) | −0.404 (0.036)*** | −0.154 (0.063)** | −0.155 (0.063)** | −0.418 (0.447) | ||||
Foreigners (%) | 0.627 (0.658) | 0.136 (0.569) | 0.138 (0.569) | 3.147 (0.635)*** | ||||
Foreign firm | 0.550 (0.014)*** | 0.288 (0.013)*** | −0.005 (0.026) | −0.003 (0.024) | ||||
D-to-F switch (acquisition) | −0.046 (0.020)** | −0.048 (0.020)** | 0.046 (0.281) | −0.264 (0.159)* | ||||
F-to-D switch (divestment) | −0.064 (0.093) | −0.080 (0.088) | 0.091 (0.301) | −0.167 (0.160) | ||||
Obs. | 6197 | 6197 | 6197 | 6197 | 6197 | 6197 | 139 | 139 |
R2 | 0.411 | 0.64 | 0.845 | 0.851 | 0.845 | 0.852 | 0.959 | 0.982 |
Notes: Dependent variable: Log average real hourly wage. All columns include firm-level controls (size, industry dummies and state dummies) and year dummies. Even columns includes worker-level controls (average of the following characteristics of workers: schooling, experience and its square, tenure and its square; and the share of female workers and of foreign workers). “Foreign firm” is a dummy taking value one if the firm-year is foreign owned (and value zero otherwise). “D-to-F switcher” is a dummy taking value one if the firm was domestic owned in the previous period(s) and is foreign owned in the current period(s) (and value zero otherwise). “F-to-D switcher” is a dummy taking value one if the firm was foreign owned in the previous period(s) and is domestic owned in the current period(s) (and value zero otherwise). All firm-years used in all specifications, except in the final two columns (only firms that switch ownership, domestic or foreign, are observed, and only in the last period before changing and in the first period after changing). All firm-years receive the same weight. Robust standard errors. Significance levels: *: 0.10; **: 0.05; ***: 0.01.
and the first year after that (columns 7 and 8). While there is evidence of a significant wage decrease following an acquisition, the lack of precision of the coefficient for divestments rules out the rejection of the equality of the two effects. It is also interesting to notice that changes in some worker characteristics are very significant in predicting wage changes: for instance, increases in the percentage of foreign workers tend to be associated with (particularly large) increases in wages, while increases in the percentage of female workers tend to be associated with declines in wages.
For the remaining dependent variables that we analyze in Tables 5-9 (firm size, job creation, job destruction, job reallocation, worker reallocation and churning), we consider exactly the same specifications as for wages, except that we do not include the measure of firm size in the list of regressors. In the case of firm size (
The results for net job creation rates (
OLS-1 | OLS-2 | FE-1 | FE-2 | FE-3 | FE-4 | FE-5 | FE-6 | |
---|---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
Schooling | −0.127 (0.015)*** | −0.192 (0.020)*** | −0.189 (0.020)*** | 0.005 (0.106) | ||||
Experience (years) | −0.039 (0.025) | −0.002 (0.040) | −0.001 (0.040) | −0.002 (0.314) | ||||
Tenure (months) | 0.027 (0.002)*** | 0.004 (0.003) | 0.003 (0.003) | 0.028 (0.031) | ||||
Female (%) | −0.614 (0.135)*** | −0.091 (0.160) | −0.091 (159) | 3.304 (1.885)* | ||||
Foreigners (%) | −4.044 (0.428)*** | −2.181 (0.400)*** | −2.179 (0.399)*** | −3.844 (3.725) | ||||
Foreign firm | 0.219 (0.034)*** | 0.091 (0.036)** | 0.487 (0.099)*** | 0.334 (0.094)*** | ||||
D-to-F switch (acquisition) | −0.005 (0.051) | −0.024 (0.047) | −0.082 (0.801) | 0.233 (0.617) | ||||
F-to-D switch (divestment) | −1.199 (0.301)*** | −0.905 (0.266)*** | −1.113 (0.778) | −0.538 (0.653) | ||||
Obs. | 6247 | 6244 | 6247 | 6244 | 6247 | 6244 | 146 | 146 |
R2 | 0.11 | 0.297 | 0.873 | 0.912 | 0.874 | 0.913 | 0.92 |
Notes: Dependent variable: Log firm size (number of workers in each year, weighted by length of spell of each individual). All columns include firm-level controls (industry dummies and state dummies) and year dummies. Even columns includes worker-level controls (average of the following characteristics of workers: schooling, experience and its square, tenure and its square; and the share of female workers and of foreign workers). “Foreign firm” is a dummy taking value one if the firm-year is foreign owned (and value zero otherwise). “D-to-F switcher” is a dummy taking value one if the firm was domestic owned in the previous period(s) and is foreign owned in the current period(s) (and value zero otherwise). “F-to-D switcher” is a dummy taking value one if the firm was foreign owned in the previous period(s) and is domestic owned in the current period(s) (and value zero otherwise). All firm-years used in all specifications, except in the final two columns (only firms that switch ownership, domestic or foreign, are observed, and only in the last period before changing and in the first period after changing). All firm-years receive the same weight. Robust standard errors. Significance levels: *: 0.10; **: 0.05; ***: 0.01.
OLS-1 | OLS-2 | FE-1 | FE-2 | FE-3 | FE-4 | FE-5 | FE-6 | |
---|---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
Schooling | −0.024 (0.006)*** | −0.082 (0.014)*** | −0.081 (0.014)*** | 0.067 (0.150) | ||||
Experience (years) | 0.012 (0.009) | −0.032 (0.024) | −0.031 (0.024) | −0.051 (0.265) | ||||
Tenure (months) | 0.00002 (0.0008) | −0.006 (0.002)*** | −0.006 (0.002)*** | 0.015 (0.024) | ||||
Female (%) | −0.140 (0.054)*** | −0.108 (0.094) | −0.107 (0.094) | 2.649 (1.538)* | ||||
Foreigners (%) | −1.168 (0.235)*** | −0.483 (0.437) | −0.469 (0.433) | −2.340 (3.767) | ||||
Foreign firm | 0.053 (0.011)*** | 0.059 (0.012)*** | 0.146 (0.070)** | 0.104 (0.075) | ||||
D-to-F switch (acquisition) | −0.022 (0.059) | −0.019 (0.059) | 0.195 (0.354) | 0.500 (0.324) | ||||
F-to-D switch (divestment) | −0.418 (0.232)* | −0.417 (0.240)* | −0.572 (0.280)** | −0.187 (0.316) | ||||
Obs. | 4862 | 4859 | 4862 | 4859 | 4862 | 4859 | 136 | 136 |
R2 | 0.023 | 0.127 | 0.401 | 0.472 | 0.403 | 0.475 | 0.58 | 0.661 |
Notes: Dependent variable: Net job creation rate (defined as in the text: the change in firm size divided by the average firm size, if positive, zero otherwise). All columns include firm-level controls (industry dummies and state dummies) and year dummies. Even columns includes worker-level controls (average of the following characteristics of workers: schooling, experience and its square, tenure and its square; and the share of female workers and of foreign workers). “Foreign firm” is a dummy taking value one if the firm-year is foreign owned (and value zero otherwise). “D-to-F switcher” is a dummy taking value one if the firm was domestic owned in the previous period(s) and is foreign owned in the current period(s) (and value zero otherwise). “F-to-D switcher” is a dummy taking value one if the firm was foreign owned in the previous period(s) and is domestic owned in the current period(s) (and value zero otherwise). All firm-years used in all specifications, except in the final two columns (only firms that switch ownership, domestic or foreign, are observed, and only in the last period before changing and in the first period after changing). All firm-years receive the same weight. Robust standard errors. Significance levels: *: 0.10; **: 0.05; ***: 0.01.
OLS-1 | OLS-2 | FE-1 | FE-2 | FE-3 | FE-4 | FE-5 | FE-6 | |
---|---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
Schooling | 0.025 (0.006)*** | 0.062 (0.012)*** | 0.061 (0.013)*** | −0.080 (0.072) | ||||
Experience (years) | −0.003 (0.009) | 0.031 (0.020) | 0.031 (0.020) | 0.114 (190) | ||||
Tenure (months) | −0.002 (0.0009)** | 0.001 (0.002) | 0.002 (0.002) | −0.020 (0.018) | ||||
Female (%) | 0.120 (0.048)** | 0.081 (0.080) | 0.081 (0.079) | −2.548 (1.232)** | ||||
Foreigners (%) | 1.146 (0.231)*** | 0.660 (0.423) | 0.657 (0.421) | 3.095 (2.701) | ||||
Foreign firm | −0.046 (0.009)*** | −0.052 (0.011)*** | −0.118 (0.064)* | −0.075 (0.067) | ||||
D-to-F switch (acquisition) | 0.052 (0.036) | 0.048 (0.037) | 0.860 (0.726) | −0.067 (0.752) | ||||
F-to-D switch (divestment) | 0.336 (0.195)* | 0.269 (0.198) | 10.217 (0.740) | 0.316 (0.712) | ||||
Obs. | 4897 | 4894 | 4897 | 4894 | 4897 | 4894 | 140 | 140 |
R2 | 0.025 | 0.135 | 0.445 | 0.504 | 0.447 | 0.506 | 0.597 | 0.735 |
Notes: Dependent variable: Job destruction rate (defined as in the text: the absolute value of the change in firm size divided by the average firm size, if change is negative, zero otherwise). All columns include firm-level controls (industry dummies and state dummies) and year dummies. Even columns includes worker-level controls (average of the following characteristics of workers: schooling, experience and its square, tenure and its square; and the share of female workers and of foreign workers). “Foreign firm” is a dummy taking value one if the firm-year is foreign owned (and value zero otherwise). “D-to-F switcher” is a dummy taking value one if the firm was domestic owned in the previous period(s) and is foreign owned in the current period(s) (and value zero otherwise). “F-to-D switcher” is a dummy taking value one if the firm was foreign owned in the previous period(s) and is domestic owned in the current period(s) (and value zero otherwise). All firm-years used in all specifications, except in the final two columns (only firms that switch ownership, domestic or foreign, are observed, and only in the last period before changing and in the first period after changing). All firm-years receive the same weight. Robust standard errors. Significance levels: *: 0.10; **: 0.05; ***: 0.01.
OLS-1 | OLS-2 | FE-1 | FE-2 | FE-3 | FE-4 | FE-5 | FE-6 | |
---|---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
Schooling | 0.027 (0.006)*** | 0.049 (0.012)*** | 0.048 (0.012)*** | −0.062 (0.061) | ||||
Experience (years) | 0.001 (0.009) | 0.026 (0.018) | 0.026 (0.018) | 0.128 (146) | ||||
Tenure (months) | −0.005 (0.001)*** | −0.004 (0.002)** | −0.004 (0.002)** | −0.022 (0.015) | ||||
Female (%) | 0.100 (0.047)** | 0.065 (0.076) | 0.065 (0.076) | −2.418 (1.124)** | ||||
Foreigners (%) | 1.104 (0.232)*** | 0.782 (0.425)* | 0.780 (0.423)* | 3.388 (2.374) | ||||
Foreign firm | −0.040 (0.009)*** | −0.044 (0.011)*** | −0.112 (0.064)* | −0.078 (0.062) | ||||
D-to-F switch (acquisition) | 0.083 (0.041)** | 0.082 (0.040)** | 0.963 (0.688) | −0.025 (0.683) | ||||
F-to-D switch (divestment) | 0.352 (0.190)* | 0.254 (0.183) | 1.128 (0.691) | 0.163 (0.630) | ||||
Obs. | 4897 | 4894 | 4897 | 4894 | 4897 | 4894 | 140 | 140 |
R2 | 0.027 | 0.143 | 0.465 | 0.506 | 0.468 | 0.508 | 0.638 | 0.801 |
Notes: Dependent variable: Job reallocation rate (defined as in the text: the sum of job creation and job destruction divided by the average firm size). All columns include firm-level controls (industry dummies and state dummies) and year dummies. Even columns includes worker-level controls (average of the following characteristics of workers: schooling, experience and its square, tenure and its square; and the share of female workers and of foreign workers). “Foreign firm” is a dummy taking value one if the firm-year is foreign owned (and value zero otherwise). “D-to-F switcher” is a dummy taking value one if the firm was domestic owned in the previous period(s) and is foreign owned in the current period(s) (and value zero otherwise). “F-to-D switcher” is a dummy taking value one if the firm was foreign owned in the previous period(s) and is domestic owned in the current period(s) (and value zero otherwise). All firm-years used in all specifications, except in the final two columns (only firms that switch ownership, domestic or foreign, are observed, and only in the last period before changing and in the first period after changing). All firm-years receive the same weight. Robust standard errors. Significance levels: *: 0.10; **: 0.05; ***: 0.01.
OLS-1 | OLS-2 | FE-1 | FE-2 | FE-3 | FE-4 | FE-5 | FE-6 | |
---|---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
Schooling | 0.023 (0.005)*** | 0.062 (0.012)*** | 0.062 (0.012)*** | −0.065 (0.099) | ||||
Experience (years) | 0.002 (0.008) | 0.029 (0.018)* | 0.028 (0.018) | 0.029 (0.141) | ||||
Tenure (months) | −0.014 (0.0009)*** | −0.018 (0.002)*** | −0.018 (0.002)*** | −0.035 (0.014)*** | ||||
Female (%) | 0.087 (0.042)** | 0.018 (0.074) | 0.017 (0.074) | −1.258 (1.079) | ||||
Foreigners (%) | 0.882 (0.241)*** | 0.534 (0.400) | 0.526 (0.397) | 2.877 (2.302) | ||||
Foreign firm | −0.050 (0.010)*** | −0.042 (0.010)*** | −0.088 (0.065) | −0.077 (0.049) | ||||
D-to-F switch (acquisition) | 0.095 (0.056)* | 0.096 (0.048)** | 0.087 (0.257) | −0.283 (0.207) | ||||
F-to-D switch (divestment) | 0.488 (0.194)** | 0.301 (0.162)* | 0.568 (0.222)** | 0.225 (0.209) | ||||
Obs. | 4862 | 4859 | 4862 | 4859 | 4862 | 4859 | 136 | 136 |
R2 | 0.041 | 0.313 | 0.509 | 0.599 | 0.514 | 0.601 | 0.627 |
Notes: Dependent variable: Worker reallocation rate (defined as in the text: the sum of hirings and separations divided by the average firm size). All columns include firm-level controls (industry dummies and state dummies) and year dummies. Even columns include worker-level controls (average of the following characteristics of workers: schooling, experience and its square, tenure and its square; and the share of female workers and of foreign workers). “Foreign firm” is a dummy taking value one if the firm-year is foreign owned (and value zero otherwise). “D-to-F switcher” is a dummy taking value one if the firm was domestic owned in the previous period(s) and is foreign owned in the current period(s) (and value zero otherwise). “F-to-D switcher” is a dummy taking value one if the firm was foreign owned in the previous period(s) and is domestic owned in the current period(s) (and value zero otherwise). All firm-years used in all specifications, except in the final two columns (only firms that switch ownership, domestic or foreign, are observed, and only in the last period before changing and in the first period after changing). All firm-years receive the same weight. Robust standard errors. Significance levels: *: 0.10; **: 0.05; ***: 0.01.
such a case, net job creation would already be negative just before divestment, leading to smaller and/or insignificant estimates, which we do not find in these results.
Given that job creation is very small across the firms in our sample, our results about this variable (not reported) are almost always insignificant or indicating very small differences across the two types of firms (slightly larger for foreign firms, but only in specifications without firm fixed effects). Unsurprisingly,
Consistent with the previous tables, we find that job reallocation (the sum of job creation and job destruction) is significantly lower in foreign firms, while “F-to-D” switchers are the main drivers of such effect (
Here we address the unobserved heterogeneity problem by following the same workers as they move across different domestic and foreign firms. Again, this is only possible using matched employer-employee panel data, so that one can trace workers over time and focus, for instance, on those who change employers.
We consider five types of workers: stayers, “movers” through acquisitions, “movers” through divestments, movers from domestic to foreign firms and, finally, movers from foreign to domestic firms. In each table and for each type of mover we present descriptive statistics about the worker and the worker’s firm before and after the movement (left and right columns, respectively). In the case of stayers, we present descriptive statistics separately for stayers in domestic and foreign firms.
We now consider the case of workers that move between firms.
Finally, we consider the case of workers that move from a foreign to a domestic firm (
Variable | Always domestic | Always foreign | |||||
---|---|---|---|---|---|---|---|
Mean | Std. Dev. N | Mean | Std. Dev. N | p-test | |||
Schooling | 7.921 | 3.740 | 883,147 | 8.827 | 3.779 | 1,254,490 | 0.000 |
Experience | 18.782 | 11.120 | 882,008 | 17.239 | 10.088 | 1,254,236 | 0.000 |
Tenure | 67.485 | 69.466 | 883,278 | 71.833 | 72.941 | 1,254,988 | 0.000 |
Female | 0.192 | 0.394 | 883,278 | 0.174 | 0.379 | 1,254,988 | 0.000 |
Foreign worker | 0.005 | 0.069 | 883,278 | 0.010 | 0.097 | 1,254,988 | 0.000 |
Firm size | 2402.242 | 4054.423 | 883,278 | 3197.021 | 5151.050 | 1,254,988 | 0.000 |
New hire | 0.200 | 0.400 | 883,278 | 0.204 | 0.403 | 1,254,988 | 0.000 |
Log avg. hourly pay | 2.131 | 0.841 | 852,499 | 2.355 | 0.845 | 1,227,190 | 0.000 |
Change in log pay | 0.037 | 0.370 | 517,186 | 0.044 | 0.328 | 765,046 | 0.000 |
Foreign firm | 0.000 | 0.000 | 883,278 | 1.000 | 0.000 | 1,254,988 | |
Foreign status switch | 0.000 | 0.000 | 883,278 | 0.000 | 0.000 | 1,254,988 | |
Firm mover | 0.000 | 0.000 | 883,278 | 0.000 | 0.000 | 1,254,988 | |
Job creation rate | 0.063 | 0.170 | 653,049 | 0.072 | 0.166 | 962,365 | 0.000 |
Job destruction rate | 0.092 | 0.146 | 656,934 | 0.079 | 0.152 | 973,334 | 0.000 |
Net job creation rate | −0.029 | 0.249 | 653,049 | −0.008 | 0.250 | 962,365 | 0.000 |
Job reallocation rate | 0.155 | 0.196 | 656,934 | 0.150 | 0.198 | 973,334 | 0.000 |
Worker reallocation rate | 0.381 | 0.251 | 653,049 | 0.411 | 0.279 | 962,365 | 0.000 |
Churning rate | 0.226 | 0.311 | 653,049 | 0.259 | 0.269 | 962,365 | 0.000 |
1995 | 0.256 | 0.437 | 883,278 | 0.224 | 0.417 | 1,254,988 | 0.000 |
1996 | 0.224 | 0.417 | 883,278 | 0.211 | 0.408 | 1,254,988 | 0.000 |
1997 | 0.200 | 0.400 | 883,278 | 0.205 | 0.404 | 1,254,988 | 0.000 |
1998 | 0.165 | 0.371 | 883,278 | 0.181 | 0.385 | 1,254,988 | 0.000 |
1999 | 0.154 | 0.361 | 883,278 | 0.179 | 0.383 | 1,254,988 | 0.000 |
Notes: This table describes the characteristics of workers that do not change their affiliation between domestic or foreign firms over the 1995-1999 period. However, workers may move between firms, provided they are in the same “sector”. Schooling is measured in years; experience defined as Mincer experience; tenure measured in months; “foreign worker” is a dummy taking value one for workers who are not Brazilian nationals, ‘firm size’ is measured in terms of the number of workers in the firm in 31 December of the year, “dismissal without cause” is a dummy variable taking value one if the worker was fired without cause from his/her previous job, “new hire” is a dummy taking value one if the worker is in the first year in the current firm, “reemployed” is a dummy taking value one if the worker left and then returned to the current firm, pay is measured in 2006 “reais”, “foreign firm” is a dummy taking value one for firms owned at least at 50% by foreign investors. Job creation rate and the following job and worker flow rates are defined in the standard way (see main text). “1995”, “1996”, etc., are dummy variables for each year.
Variable | Domestic ownership | Foreign ownership | |||||
---|---|---|---|---|---|---|---|
Mean | Std. Dev. | N | Mean | Std. Dev. | N | p-value | |
Schooling | 8.347 | 3.778 | 50,816 | 8.844 | 3.694 | 67,515 | 0.000 |
Experience | 18.578 | 10.127 | 50,814 | 19.822 | 10.007 | 67,511 | 0.000 |
Tenure | 88.920 | 77.001 | 50,818 | 107.273 | 79.733 | 67,515 | 0.000 |
Female | 0.184 | 0.387 | 50,818 | 0.130 | 0.337 | 67,515 | 0.000 |
Foreign worker | 0.006 | 0.076 | 50,818 | 0.006 | 0.074 | 67,515 | 0.474 |
Firm size | 1518.361 | 921.666 | 50,818 | 1399.844 | 795.025 | 67,515 | 0.000 |
New hire | 0.157 | 0.364 | 50,818 | 0.030 | 0.171 | 67,515 | 0.000 |
Log avg. hourly pay | 2.421 | 0.785 | 50,240 | 2.441 | 0.790 | 65,401 | 0.000 |
Change in log pay | 0.007 | 0.317 | 22,739 | 0.019 | 0.334 | 64,825 | 0.000 |
---|---|---|---|---|---|---|---|
Foreign firm | 0.000 | 0.000 | 50,818 | 1.000 | 0.000 | 67,515 | |
Foreign status switch | 1.000 | 0.000 | 50,818 | 1.000 | 0.000 | 67,515 | |
Firm mover | 0.000 | 0.000 | 50,818 | 0.000 | 0.000 | 67,515 | |
Job creation rate | 0.066 | 0.126 | 27,978 | 0.063 | 0.215 | 66,933 | 0.038 |
Job destruction rate | 0.107 | 0.154 | 27,978 | 0.071 | 0.124 | 67,515 | 0.000 |
Net job creation rate | −0.041 | 0.232 | 27,978 | −0.008 | 0.266 | 66,933 | 0.000 |
Job reallocation rate | 0.173 | 0.160 | 27,978 | 0.134 | 0.229 | 67,515 | 0.000 |
Worker reallocation rate | 0.392 | 0.207 | 27,978 | 0.335 | 0.292 | 66,933 | 0.000 |
Churning rate | 0.219 | 0.274 | 27,978 | 0.200 | 0.406 | 66,933 | 0.000 |
1995 | 0.449 | 0.497 | 50,818 | 0.000 | 0.000 | 67,515 | 0.000 |
1996 | 0.536 | 0.499 | 50,818 | 0.000 | 0.000 | 67,515 | 0.000 |
1997 | 0.007 | 0.082 | 50,818 | 0.375 | 0.484 | 67,515 | 0.000 |
1998 | 0.008 | 0.087 | 50,818 | 0.330 | 0.470 | 67,515 | 0.000 |
1999 | 0.000 | 0.000 | 50,818 | 0.295 | 0.456 | 67,515 | 0.000 |
Notes: This table describes the characteristics of workers that change their affiliation from domestic to foreign firms over the 1995-1999 period because their firms are acquired and they stay in that firm. Schooling is measured in years; experience defined as Mincer experience; tenure measured in months; “foreign worker” is a dummy taking value one for workers who are not Brazilian nationals, “firm size” is measured in terms of the number of workers in the firm in 31 December of the year, “dismissal without cause” is a dummy variable taking value one if the worker was fired without cause from his/her previous job, “new hire” is a dummy taking value one if the worker is in the first year in the current firm, “reemployed” is a dummy taking value one if the worker left and then returned to the current firm, pay is measured in 2006 “reais”, “foreign firm” is a dummy taking value one for firms owned at least at 50% by foreign investors. Job creation rate and the following job and worker flow rates are defined in the standard way (see main text). “1995”, “1996”, etc., are dummy variables for each year.
Variable | Domestic ownership | Foreign ownership | |||||
---|---|---|---|---|---|---|---|
Mean | Std. Dev | N | Mean | Std. Dev. | N | p-test | |
Schooling | 8.748 | 4.291 | 1949 | 9.867 | 4.152 | 1277 | 0.000 |
Experience | 20.139 | 10.307 | 1948 | 20.295 | 9.944 | 1277 | 0.670 |
Tenure | 70.565 | 66.534 | 1949 | 79.816 | 64.334 | 1277 | 0.000 |
Female | 0.144 | 0.351 | 1949 | 0.104 | 0.306 | 1277 | 0.001 |
Foreign worker | 0.014 | 0.119 | 1949 | 0.012 | 0.108 | 1277 | 0.526 |
Firm size | 182.455 | 124.963 | 1949 | 134.033 | 93.096 | 1277 | 0.000 |
New hire | 0.176 | 0.381 | 1949 | 0.031 | 0.172 | 1277 | 0.000 |
Log avg. hourly pay | 2.577 | 0.829 | 1916 | 2.619 | 0.912 | 919 | 0.220 |
Change in log pay | −0.080 | 0.370 | 1033 | 0.085 | 0.412 | 905 | 0.000 |
Foreign firm | 1.000 | 0.000 | 1949 | 0.000 | 0.000 | 1277 | |
Foreign status switch | 1.000 | 0.000 | 1949 | 1.000 | 0.000 | 1277 | |
Firm mover | 0.000 | 0.000 | 1949 | 0.000 | 0.000 | 1277 | |
Job creation rate | 0.037 | 0.062 | 1228 | 0.063 | 0.237 | 1194 | 0.000 |
Job destruction rate | 0.251 | 0.382 | 1228 | 0.240 | 0.396 | 1277 | 0.453 |
Net job creation rate | −0.215 | 0.410 | 1228 | −0.193 | 0.502 | 1194 | 0.256 |
Job reallocation rate | 0.288 | 0.362 | 1228 | 0.298 | 0.426 | 1277 | 0.512 |
Worker reallocation rate | 0.516 | 0.361 | 1228 | 0.503 | 0.447 | 1194 | 0.416 |
Churning rate | 0.229 | 0.142 | 1228 | 0.184 | 0.434 | 1194 | 0.001 |
1995 | 0.370 | 0.483 | 1949 | 0.000 | 0.000 | 1277 | 0.000 |
1996 | 0.318 | 0.466 | 1949 | 0.090 | 0.286 | 1277 | 0.000 |
---|---|---|---|---|---|---|---|
1997 | 0.180 | 0.384 | 1949 | 0.300 | 0.458 | 1277 | 0.000 |
1998 | 0.132 | 0.339 | 1949 | 0.305 | 0.460 | 1277 | 0.000 |
1999 | 0.000 | 0.000 | 1949 | 0.305 | 0.461 | 1277 | 0.000 |
Notes: This table describes the characteristics of workers that change their affiliation from foreign to domestic firms over the 1995-1999 period because their firms are acquired and they stay in that firm. Schooling is measured in years; experience defined as Mincer experience; tenure measured in months; “foreign worker” is a dummy taking value one for workers who are not Brazilian nationals, “firm size” is measured in terms of the number of workers in the firm in 31 December of the year, “dismissal without cause” is a dummy variable taking value one if the worker was fired without cause from his/her previous job, “new hire” is a dummy taking value one if the worker is in the first year in the current firm, “reemployed” is a dummy taking value one if the worker left and then returned to the current firm, pay is measured in 2006 “reais”, “foreign firm” is a dummy taking value one for firms owned at least at 50% by foreign investors. Job creation rate and the following job and worker flow rates are defined in the standard way (see main text). “1995”, “1996”, etc., are dummy variables for each year.
Variable | Domestic ownership | Foreign ownership | |||||
---|---|---|---|---|---|---|---|
Mean | Std. Dev. | N | Mean | Std. Dev. | N | p-test | |
Schooling | 8.559 | 3.541 | 22,729 | 9.586 | 3.554 | 20,899 | 0.000 |
Experience | 15.011 | 9.017 | 22,714 | 15.632 | 8.695 | 20,899 | 0.000 |
Tenure | 51.001 | 50.312 | 22,734 | 38.187 | 52.606 | 20,900 | 0.000 |
Female | 0.264 | 0.441 | 22,734 | 0.096 | 0.294 | 20,900 | 0.000 |
Foreign worker | 0.005 | 0.070 | 22,734 | 0.005 | 0.069 | 20,900 | 0.940 |
Firm size | 2691.429 | 2304.134 | 22,734 | 3132.178 | 3178.156 | 20,900 | 0.000 |
New hire | 0.229 | 0.420 | 22,734 | 0.456 | 0.498 | 20,900 | 0.000 |
Log avg. hourly pay | 2.248 | 0.754 | 21,887 | 2.378 | 0.797 | 20,390 | 0.000 |
Change in log pay | 0.038 | 0.434 | 11,409 | 0.050 | 0.395 | 19,269 | 0.015 |
Foreign firm | 0.000 | 0.000 | 22,734 | 1.000 | 0.000 | 20,900 | |
Foreign status switch | 1.000 | 0.000 | 22,734 | 1.000 | 0.000 | 20,900 | |
Firm mover | 1.000 | 0.000 | 22,734 | 1.000 | 0.000 | 20,900 | |
Job creation rate | 0.076 | 0.132 | 14,513 | 0.250 | 0.408 | 20,162 | 0.000 |
Job destruction rate | 0.062 | 0.119 | 14,664 | 0.092 | 0.156 | 20,364 | 0.000 |
Net job creation rate | 0.013 | 0.203 | 14,513 | 0.157 | 0.487 | 20,162 | 0.000 |
Job reallocation rate | 0.137 | 0.149 | 14,664 | 0.340 | 0.379 | 20,364 | 0.000 |
Worker reallocation rate | 0.470 | 0.231 | 14,513 | 0.625 | 0.429 | 20,162 | 0.000 |
Churning rate | 0.332 | 0.283 | 14,513 | 0.282 | 0.279 | 20,162 | 0.000 |
1995 | 0.355 | 0.479 | 22,734 | 0.026 | 0.158 | 20,900 | 0.000 |
1996 | 0.308 | 0.462 | 22,734 | 0.073 | 0.261 | 20,900 | 0.000 |
1997 | 0.238 | 0.426 | 22,734 | 0.151 | 0.358 | 20,900 | 0.000 |
1998 | 0.083 | 0.275 | 22,734 | 0.337 | 0.473 | 20,900 | 0.000 |
1999 | 0.017 | 0.128 | 22,734 | 0.413 | 0.492 | 20,900 | 0.000 |
Notes: This table describes the characteristics of workers that change their affiliation from domestic to foreign firms over the 1995-1999 period because they move between firms. Schooling is measured in years; experience defined as Mincer experience; tenure measured in months; “foreign worker” is a dummy taking value one for workers who are not Brazilian nationals, “firm size” is measured in terms of the number of workers in the firm in 31 December of the year, “dismissal without cause” is a dummy variable taking value one if the worker was fired without cause from his/her previous job, “new hire” is a dummy taking value one if the worker is in the first year in the current firm, “reemployed” is a dummy taking value one if the worker left and then returned to the current firm, pay is measured in 2006 “reais”, “foreign firm” is a dummy taking value one for firms owned at least at 50% by foreign investors. Job creation rate and the following job and worker flow rates are defined in the standard way (see main text). “1995”, “1996”, etc., are dummy variables for each year.
Variable | Domestic ownership | Foreign ownership | |||||
---|---|---|---|---|---|---|---|
Mean | Std. Dev. | N | Mean | Std. Dev. | N | p-test | |
Schooling | 10.169 | 3.632 | 6665 | 10.496 | 3.478 | 6563 | 0.000 |
Experience | 14.464 | 8.649 | 6665 | 15.179 | 8.253 | 6553 | 0.000 |
Tenure | 46.079 | 55.315 | 6668 | 26.644 | 38.200 | 6563 | 0.000 |
Female | 0.172 | 0.377 | 6668 | 0.119 | 0.324 | 6563 | 0.000 |
Foreign worker | 0.010 | 0.098 | 6668 | 0.007 | 0.083 | 6563 | 0.067 |
Firm size | 1639.543 | 2378.396 | 6668 | 1838.680 | 2382.716 | 6563 | 0.000 |
New hire | 0.330 | 0.470 | 6668 | 0.455 | 0.498 | 6563 | 0.000 |
Log avg. hourly pay | 2.515 | 0.879 | 6341 | 2.444 | 0.921 | 6056 | 0.000 |
Change in log pay | 0.022 | 0.389 | 2876 | −0.025 | 0.508 | 5450 | 0.000 |
Foreign firm | 1.000 | 0.000 | 6668 | 0.000 | 0.000 | 6563 | |
Foreign status switch | 1.000 | 0.000 | 6668 | 1.000 | 0.000 | 6563 | |
Firm mover | 1.000 | 0.000 | 6668 | 1.000 | 0.000 | 6563 | |
Job creation rate | 0.137 | 0.280 | 3834 | 0.094 | 0.176 | 6266 | 0.000 |
Job destruction rate | 0.078 | 0.161 | 3877 | 0.073 | 0.160 | 6395 | 0.130 |
Net job creation rate | 0.059 | 0.355 | 3834 | 0.020 | 0.267 | 6266 | 0.000 |
Job reallocation rate | 0.213 | 0.287 | 3877 | 0.165 | 0.207 | 6395 | 0.000 |
Worker reallocation rate | 0.513 | 0.340 | 3834 | 0.446 | 0.315 | 6266 | 0.000 |
Churning rate | 0.297 | 0.303 | 3834 | 0.277 | 0.302 | 6266 | 0.001 |
1995 | 0.419 | 0.493 | 6668 | 0.026 | 0.158 | 6563 | 0.000 |
1996 | 0.249 | 0.432 | 6668 | 0.196 | 0.397 | 6563 | 0.000 |
1997 | 0.156 | 0.362 | 6668 | 0.230 | 0.421 | 6563 | 0.000 |
1998 | 0.103 | 0.304 | 6668 | 0.232 | 0.422 | 6563 | 0.000 |
1999 | 0.074 | 0.262 | 6668 | 0.316 | 0.465 | 6563 | 0.000 |
Notes: This table describes the characteristics of workers that change their affiliation from foreign to domestic firms over the 1995-1999 period because they move between firms. Schooling is measured in years; experience defined as Mincer experience; tenure measured in months; “foreign worker” is a dummy taking value one for workers who are not Brazilian nationals, “firm size” is measured in terms of the number of workers in the firm in 31 December of the year, “dismissal without cause” is a dummy variable taking value one if the worker was fired without cause from his/her previous job, “new hire” is a dummy taking value one if the worker is in the first year in the current firm, “reemployed” is a dummy taking value one if the worker left and then returned to the current firm, pay is measured in 2006 “reais”, “foreign firm” is a dummy taking value one for firms owned at least at 50% by foreign investors. Job creation rate and the following job and worker flow rates are defined in the standard way (see main text). “1995”, “1996”, etc., are dummy variables for each year.
We now estimate wage equations using data at the worker level. The wage equation we consider here is:
in which
OLS1 | All-FE | Stayers1 | Movers1 | Stayers2 | Movers2 | |
---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | |
Schooling | 0.102 (0.004)*** | 0.013 (0.003)*** | 0.012 (0.003)*** | 0.021 (0.004)*** | −0.004 (0.007) | 0.031 (0.008)*** |
Experience | 0.047 (0.004)*** | 0.030 (0.003)*** | 0.029 (0.003)*** | 0.037 (0.005)*** | 0.022 (0.012)* | 0.033 (0.008)*** |
Experience2/100 | −0.062 (0.005)*** | −0.054 (0.005)*** | −0.054 (0.006)*** | −0.068 (0.008)*** | −0.038 (0.021)* | −0.037 (0.013)*** |
Tenure/10 | 0.041 (0.007)*** | 0.021 (0.002)*** | 0.019 (0.003)*** | 0.027 (0.004)*** | 0.028 (0.010)*** | 0.035 (0.004)*** |
Tenure2/1000 | −0.007 (0.002)*** | −0.008 (0.001)*** | −0.008 (0.001)*** | −0.009 (0.001)*** | −0.014 (0.004)*** | −0.011 (0.002)*** |
Female | −0.418 (0.033)*** | |||||
Foreign worker | 0.304 (0.017)*** | |||||
Foreign firm | 0.099 (0.061) | −0.008 (0.017) | −0.027 (0.024) | 0.040 (0.017)** | −0.044 (0.026)* | 0.078 (0.011)*** |
Obs. | 2,295,926 | 2,295,926 | 2,196,359 | 99,567 | 55,626 | 27,665 |
No. Firms | 1348 | 1348 | 1348 | 1214 | 70 | 1067 |
R2 | 0.523 | 0.939 | 0.941 | 0.902 | 0.963 | 0.92 |
Notes: Dependent variable: log real hourly wage. Worker-level controls are schooling, experience and its square, tenure and its square, a female dummy variable and a foreign worker (non-Brazilian) dummy variable. All columns except (1) include worker fixed effects. “Foreign firm” is a dummy taking value one if the firm-year is foreign owned (and value zero otherwise). “D-to-F mover” is a dummy taking value one if the worker was employed in a domestic firm in the previous periods and is employed in a foreign owned firm in the current period (and value zero otherwise). “F-to-D mover” is a dummy taking value one if the worker was employed in a foreign firm in the previous periods and is employed in a domestic owned firm in the current period (and value zero otherwise). All specifications include year dummies. Robust standard errors, clustered at the firm level. Significance levels: *: 0.10; **: 0.05; ***: 0.01.
OLS1 | All-FE | Stayers1 | Movers1 | Stayers2 | Movers2 | |
---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | |
Schooling | 0.092 (0.002)*** | 0.013 (0.003)*** | 0.012 (0.004)*** | 0.022 (0.004)*** | −0.004 (0.007) | 0.033 (0.007)*** |
Experience | 0.047 (0.002)*** | 0.030 (0.003)*** | 0.029 (0.003)*** | 0.038 (0.005)*** | 0.022 (0.012)* | 0.035 (0.008)*** |
Experience2/100 | −0.062 (0.003)*** | −0.053 (0.005)*** | −0.053 (0.006)*** | −0.068 (0.008)*** | −0.039 (0.021)* | −0.038 (0.013)*** |
Tenure/10 | 0.038 (0.004)*** | 0.021 (0.003)*** | 0.020 (0.003)*** | 0.028 (0.004)*** | 0.028 (0.009)*** | 0.033 (0.004)*** |
Tenure2/1000 | −0.007 (0.0009)*** | −0.009 (0.001)*** | −0.008 (0.001)*** | −0.009 (0.001)*** | −0.015 (0.004)*** | −0.011 (0.001)*** |
Female | −0.350 (0.016)*** | |||||
Foreign worker | 0.317 (0.017)*** | |||||
Foreign firm | 0.127 (0.041)*** | −0.011 (0.017) | −0.026 (0.023) | 0.037 (0.019)* | −0.052 (0.027)* | 0.066 (0.012)*** |
Obs. | 2,295,926 | 2,295,926 | 2,196,359 | 99,567 | 55,626 | 27,665 |
No. Firms | 1348 | 1348 | 1348 | 1214 | 70 | 1067 |
R2 | 0.585 | 0.939 | 0.941 | 0.903 | 0.964 | 0.922 |
Notes: Dependent variable: log real hourly wage. Worker-level controls are schooling, experience and its square, tenure and its square, a female dummy variable and a foreign worker (non-Brazilian) dummy variable. All columns except (1) include worker fixed effects. “Foreign firm” is a dummy taking value one if the firm-year is foreign owned (and value zero otherwise). “D-to-F mover” is a dummy taking value one if the worker was employed in a domestic firm in the previous periods and is employed in a foreign owned firm in the current period (and value zero otherwise). “F-to-D mover” is a dummy taking value one if the worker was employed in a foreign firm in the previous periods and is employed in a domestic owned firm in the current period (and value zero otherwise). All specifications include year dummies. Robust standard errors, clustered at the firm level. Significance levels: *: 0.10; **: 0.05; ***: 0.01.
results including firm-level controls
Moreover, when decomposing such premium in the wage difference driven by acquisitions or divestments and the wage difference driven by worker mobility, we find that the wage difference in the first case is virtually zero while the difference from mobility is about 4% (columns 3 and 4). These differences hold when using only observations from the period immediately before or immediately after the change in firm status (columns 5 and 6). Moreover, all results are robust to controlling for firm characteristics (
As before, in the firm-level analysis, we are also interested in decomposing the foreign firm effect into changes from domestic to foreign and vice versa. In order to do this, we now estimate new individual-level wage equations as follows:
in which all variables are defined in the same way as in Equation (5), while
and
Unlike before, the overall difference between foreign and domestic firms is driven by both stayers and movers: movers that switch from a foreign to a domestic firm take a significant pay cut of about 9%, while the wage difference for switchers from domestic to foreign firms is about 7% (columns 3 and 4). When considering only workers-year observed immediately before or after the change in firm type, the coefficients either are not significant or only domestic-to-foreign movers increase their pay. All these results are generally robust to the inclusion of firm-level controls―see
Finally, we estimate wage equations including simultaneously worker and firm fixed effects [
in which all variables are defined as before and
As it is well known in the literature, the estimation of these models relies on workers that move between firms, a process which we have documented in some detail in this section. In practical terms, we pursue the methods discussed in [
OLS1 | All-FE | Stayers1 | Movers1 | Stayers2 | Movers2 | |
---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | |
Schooling | 0.101 (0.004)*** | 0.019 (0.007)*** | 0.017 (0.007)** | 0.022 (0.006)*** | −0.002 (0.008) | 0.036 (0.011)*** |
Experience | 0.045 (0.004)*** | 0.025 (0.004)*** | 0.023 (0.004)*** | 0.036 (0.008)*** | 0.028 (0.010)*** | 0.028 (0.011)*** |
Experience2/100 | −0.061 (0.005)*** | −0.039 (0.007)*** | −0.037 (0.008)*** | −0.056 (0.011)*** | −0.044 (0.019)** | −0.009 (0.019) |
Tenure/10 | 0.026 (0.009)*** | 0.012 (0.002)*** | 0.011 (0.002)*** | 0.014 (0.004)*** | 0.013 (0.008) | 0.025 (0.004)*** |
Tenure2/1000 | −0.003 (0.002) | −0.005 (0.0008)*** | −0.005 (0.0009)*** | −0.005 (0.001)*** | −0.008 (0.003)*** | −0.008 (0.002)*** |
Female | −0.453 (0.035)*** | |||||
Foreign worker | 0.284 (0.019)*** | |||||
F-to-D mover | −0.073 (0.063) | −0.091 (0.013)*** | −0.065 (0.017)*** | −0.086 (0.015)*** | −0.043 (0.086) | −0.019 (0.026) |
D-to-F mover | 0.008 (0.050) | −0.038 (0.017)** | −0.034 (0.021) | −0.045 (0.026)* | −0.088 (0.081) | 0.065 (0.019)*** |
Obs. | 1,459,828 | 1,59,828 | 1,386,945 | 72,883 | 50,477 | 21,600 |
No. Firms | 1311 | 1311 | 1309 | 1112 | 69 | 948 |
R2 | 0.501 | 0.945 | 0.946 | 0.926 | 0.969 | 0.946 |
Notes: Dependent variable: log real hourly wage. Worker-level controls are schooling, experience and its square, tenure and its square, a female dummy variable and a foreign worker (non-Brazilian) dummy variable. All columns except (1) include worker fixed effects. “Foreign firm” is a dummy taking value one if the firm-year is foreign owned (and value zero otherwise). “D-to-F mover” is a dummy taking value one if the worker was employed in a domestic firm in the previous periods and is employed in a foreign owned firm in the current period (and value zero otherwise). “F-to-D mover” is a dummy taking value one if the worker was employed in a foreign firm in the previous periods and is employed in a domestic owned firm in the current period (and value zero otherwise). All specifications include year dummies. Robust standard errors, clustered at the firm level. Significance levels: *: 0.10; **: 0.05; ***: 0.01.
OLS1 | All-FE | Stayers1 | Movers1 | Stayers2 | Movers2 | |
---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | |
Schooling | 0.092 (0.003)*** | 0.019 (0.007)*** | 0.017 (0.007)** | 0.023 (0.006)*** | −0.002 (0.008) | 0.039 (0.010)*** |
Experience | 0.045 (0.002)*** | 0.025 (0.004)*** | 0.023 (0.005)*** | 0.037 (0.008)*** | 0.028 (0.011)*** | 0.031 (0.011)*** |
Experience2/100 | −0.060 (0.003)*** | −0.039 (0.008)*** | −0.037 (0.008)*** | −0.057 (0.011)*** | −0.045 (0.019)** | −0.015 (0.019) |
Tenure/10 | 0.025 (0.005)*** | 0.012 (0.002)*** | 0.012 (0.002)*** | 0.014 (0.004)*** | 0.013 (0.008)* | 0.023 (0.004)*** |
Tenure2/1000 | −0.004 (0.001)*** | −0.005 (0.0009)*** | −0.005 (0.0009)*** | −0.005 (0.001)*** | −0.008 (0.003)*** | −0.008 (0.001)*** |
Female | −0.383 (0.018)*** | |||||
Foreign worker | 0.303 (0.018)*** | |||||
F-to-D mover | −0.077 (0.052) | −0.087 (0.013)*** | −0.043 (0.014)*** | −0.088 (0.016)*** | −0.021 (0.099) | −0.023 (0.026) |
D-to-F mover | −0.025 (0.044) | −0.041 (0.018)** | −0.030 (0.021) | −0.056 (0.027)** | −0.089 (0.085) | 0.034 (0.019)* |
Obs. | 1,459,828 | 1,459,828 | 1,386,945 | 72,883 | 50,477 | 21,600 |
No. Firms | 1311 | 1311 | 1309 | 1112 | 69 | 948 |
R2 | 0.566 | 0.945 | 0.946 | 0.927 | 0.969 | 0.947 |
Notes: Dependent variable: log real hourly wage. Worker-level controls are schooling, experience and its square, tenure and its square, a female dummy variable and a foreign worker (non-Brazilian) dummy variable. All columns except (1) include worker fixed effects. “Foreign firm” is a dummy taking value one if the firm-year is foreign owned (and value zero otherwise). “D-to-F mover” is a dummy taking value one if the worker was employed in a domestic firm in the previous periods and is employed in a foreign owned firm in the current period (and value zero otherwise). “F-to-D mover” is a dummy taking value one if the worker was employed in a foreign firm in the previous periods and is employed in a domestic owned firm in the current period (and value zero otherwise). All specifications include year dummies. Robust standard errors, clustered at the firm level. Significance levels: *: 0.10; **: 0.05; ***: 0.01.
(large) group of workers and their firms amongst whom there are connections via worker mobility. In our case, this first group accounts for about 95% of the entire data. Under the assumption that mobility is exogenous (and normalizing worker fixed effects so that their sum is equal to zero), one can then estimate the two sets of fixed effects.
Our results indicate a considerable degree of dispersion across either worker or firms-see
Overall, the results provide strong support of more generous wage policies offered by foreign firms, as the average fixed effect of the latter is approximately 0.22 log points higher than the average firm fixed effect of domestic firms. On the other hand, the results suggest that worker selection issues across domestic and foreign firms are also relevant but of less importance, as their difference is only 0.067 log points, or less than one fourth
of the average difference documented from the firm fixed effects. However, a caveat to be considered in this analysis is that there is considerable dispersion in the firm fixed effects, implying that many foreign firms do pay lower wages than similar domestic firms.
How much do developing countries benefit from foreign investment? We contribute to this question by comparing the employment and wage practices of foreign and domestic firms in Brazil, using detailed matched firm- worker panel data. In order to control for unobserved worker differences, we examine not only acquisitions (when foreign investors acquire domestic firms) but also divestments (when domestic investors acquire foreign firms). Moreover, we also consider the wage implications of worker mobility, from foreign to domestic firms and vice versa. Throughout our analyses we also pay particular attention to employment levels at the different types of firms and to the differences between the firm- and worker-levels.
We find that both types of acquisitions (domestic to foreign or vice versa) do not tend to affect wages significantly, a result consistent with the literature [
One possible implication of this result is that, in general, the comparability of acquisition and the divestment wage results may need to be considered carefully. For instance, the wage changes of stayers involved in acquisitions may be more “representative” than the wage changes of workers involved in divestments. This would be the case if the new owners following a divestment tend to offer lower pay to a greater share of their workforce, prompting a larger number of workers to leave, when compared to the case of foreign acquisitions. A complementary interpretation involves the reassignment of workers in divested firms to other firms of the same holding group of the new owner.
We also find that, while movers from foreign to domestic firms typically take (large) wage cuts when they move, movers from domestic to foreign firms tend to either take lower wage cuts or to maintain or even to increase their pay ([
Moreover, such findings are reinforced by our novel estimates of worker and firm fixed effects. Although this analysis indicated considerable dispersion of both types of fixed effects―an interesting finding that merits further research―, the fixed effects of foreign firms are, on average, considerably higher than those of domestic firms. On top of that, our results also suggest that worker selection issues are not particularly important, as the difference of the average worker fixed effects across domestic and foreign firms are relatively small.
From a methodological point of view, the findings in our paper underline the importance of considering employment issues when studying changes in ownership, particularly when one wants to address wage differentials. We also present evidence that the related theme of worker mobility can be particularly illuminating from the point of view of the assessment of the role of foreign firms in labour markets. From the point of view of the debate of the effects of globalization, our results suggest that foreign firms play a positive role in the labour market of Brazil and, perhaps, other developing countries.
Finally, our results support the hypothesis that the employment and compensation practices differ considerably between domestic and foreign firms in Brazil. The evidence presented throughout the article, 1) evidence of higher job destruction rates when the firm ownership changes nationality from domestic to foreign; and 2) evidence of higher wage reductions when a worker migrates from a foreign firm to national one-point to the fact that, under similar conditions, foreign firms are relatively less prone to implement staff and wages cuts. So, it is possible to infer that foreign firms would contribute to reduce employment instability in Brazil.
We thank Alex Hijzen, Francis Kramarz, Robert Lipsey, Robert Lensink, Eduardo P. Ribeiro, Fredrik Sjöholm, Jan Svejnar, Eric Strobl, Katherine Terrell, Richard Upward and conference/workshop participants at the Universities of Nottingham, Michigan, and Ghent, at Central European University (CAED), and at IPEA (Brasilia) for their feedback. We also thank IPEA, Gustavo Costa and Fernando Freitas for logistical and computational support and Martins gratefully acknowledges the British Academy (research grant SG-44044). The data used in this paper are confidential but the authors’ access is not exclusive.
Let
The idea behind a difference-in-differences (DID) estimator is that we can use an untreated comparison group to identify temporal variation in the outcome that is not due to the treatment. However, in order to achieve identification of the general DID estimator we need to assume that the average outcomes for the treated and control groups would have followed parallel paths over time. This is known as the time invariance assumption
where
If assumption (10) holds, the DID estimate of the average treatment effect on the treated can be obtained by the sample analogs of
The expression above simply states that the impact of the program is given by the difference between participants and nonparticipants in the before-after difference in outcomes.
The time invariance assumption can be too stringent if the treated and control groups are not balanced in covariates that are believed to be associated with the outcome variable [
In the following model,
where D is as before and represents the eligibility-specific intercept, τtcaptures time or aggregate effects and equals 0 for the “before” period and 1 for the “after” period, and Z is a vector of covariates included to correct for differences in observed characteristics between individuals in treatment and control groups.
This estimator controls for both differences in the Z s and for time-specific effects, but it does not impose common support on the distribution of the Z‘s across the cells defined by the D-in- D approach (namely, before and after, and treatment and control). In our case, we minimize problems of common support by drawing on a particularly homogeneous sample across domestic and foreign firms.9
RAIS (“Relaca˜o Anual de Informa¸coes Sociais”, Annual Social Information Report) is an administrative report filed by all tax registered Brazilian establishments. Since the information may be used for investigation about labor legislation compliance, firms that do not comply with it do not file in RAIS. Thus, this data set can be considered a census of the formal Brazilian labor market (State-owned enterprises, public administration and non-profit organizations are also required to file the report.) Firms that do not provide accurate information will be committing an offense sanctioned by law, a threat that is likely to lead to very high standards of data quality.
RAIS covers the whole country and is carried out annually. The information is collected every year in the first quarter, referring to the previous year. Every tax registered enterprise receives a unique tax number (CNPJ). This number is composed by a specific firm part and a complement for each unit (local plant or establishment) that the firm operates.
The main variables available from the survey at the establishment level are:
• Geographic location: State, metropolitan region, county;
• Activity sector: CNAE (National Economic Activity Classification); sector Level (10 categories); activity (42 categories); sub-activity (about 560 categories);
• Establishment Size: number of workers, number of wage earners, number of owners;
• Establishment Type: Private enterprise, private foundation, State-owned enterprise, State foundation, joint public-private enterprise, non-governmental organization, government, nonprofit enterprise, notary.
At the employee level, the following information is available (although we did not obtain access to all variables listed):
• Occupation: occupation classes (CBO-Brazilian Occupation Classification system?about 350 categories); subgroup (84 categories); group (11 categories);
• Personal Characteristics: schooling (9 classes), age, gender, nationality.
• Contract Information: month of admission, month of separation, December wage rate (13th monthly salary), average yearly wage, tenure, separation cause (fired with/without fair reason, separation with/without fair reason, retiring, transfer to other units or firm), contract type (work card, civil service, isolated worker, temporary worker), contract status (in activity or paid leave, leave without paid, occupation accident, military service, ma- ternity leave, sick leave, inactive), admission type (first placement in firm, re-employment, transferred), contract hours (exclusive overtime).
As some other matched employer-employee panels, RAIS is based on worker spells, defined by an occupation-establishment-contract group in each year. In other words, if a worker changes his/her occupation or establishment or contract type in a given year, there will be one separate observation for each case.
With the establishment identification number (CNPJ) it is possible to follow all establishments that file the RAIS survey. Moreover, with the worker’s national insurance number, it is possible to follow all workers that remain in the formal sector and to match the worker’s characteristics with those of the establishment. Therefore, we can create a panel that matches workers to their establishments and follow each of them over time. It was using the firm identification numbers that we have merged the three data sets described in this appendix.