Greenfield Hires Preliminary. Do not cite!

Transcription

1 Greenfield Hires Preliminary. Do not cite! Ragnhild Balsvik Doireann Fitzgerald Stefanie Haller July 2017 Abstract We investigate the possibility of short-run spillovers from foreign greenfield entry that work through the labor market. We first show that new hires at foreign-owned entrants are positively selected on observables. Moreover, conditional on observables, new hires to foreign-owned entrants earned a positive wage premium in their previous job, consistent with additional positive selection on unobservables. We do not find evidence that losing workers to a greenfield entrant generates wage spillovers for workers at sending plants. Although new hires at foreign-owned entrants are paid a wage premium, we do not find evidence that foreign entry drive up wages for incumbents in a local labor market. We extend earlier work and confirm evidence consistent with spillovers from multinationals to domestic plants through labor mobility. Keywords: foreign direct investment, greenfield entry, worker selection, spillovers JEL Classification: 1 Introduction Foreign direct investment (FDI) is a major driver of globalisation. Foreign firms setting up new subsidiaries abroad - greenfield entrants - may bring superior technology or organisational capital to their host countries. However the evidence on the impact on domestic firms is mixed (Görg and Greenaway (2004) provides an extensive survey). Here, we investigate the possibility of spillovers from foreign greenfield entry to incumbent plants that work through the labor market. Acknowledgements: We wish to thank Paul Devereux and seminar participants at UCD, ISGEP Pescara, SITT 2017, IEA Dublin and SED Edinburgh for helpful comments and suggestions. All remaining errors are our own responsibility. Norwegian School of Economics, ragnhild.balsvik [at] nhh.no Federal Reserve Bank of Minneapolis and NBER, doireann.fitzgerald [at] gmail.com School of Economics, University College Dublin, stefanie.haller [at] ucd.ie

2 The labor market is a key channel through which greenfield FDI can impact incumbent plants. First, the arrival of a new foreign plant can drive up labor demand at a local level in the short run, forcing incumbents to pay higher wages. This may be good for workers, but bad for incumbent plants. Second, new foreign plants may also poach the best workers from incumbent plants. This could have negative spillovers on incumbents, and on the remaining workers at those plants. Third, in the longer term there may be positive spillovers on incumbents if workers at foreign entrants gain valuable experience. They may eventually bring the benefits of their experience with them after moving to a different employer. We use matched employer-employee data for Norway to provide evidence on the short-run impact of foreign entry on incumbents through the first two channels. This data covers the universe of plants in Norway, and we work with data for the period We also confirm earlier evidence that there are positive spillovers in the longer term through the third channel. This has been shown in earlier work by Balsvik (2011) using the same Norwegian data, but limited to the manufacturing sector. Poole (2013) documents positive spillovers through this channel using data from Brazil, and Stoyanov and Zubanov (2014) do the same using data for Denmark. Following evidence in Balsvik and Haller (2011) that the direction of spillovers on productivity differs by mode of foreign entry, we focus on foreign greenfield entrants rather than plants that are acquired by foreign owners. We first document that new hires at foreign entering plants are positively selected relative to new hires at incumbent plants. Compared to new hires at incumbents, they have more years of education. They are more likely to be making a job-to-job transition and less likely to come from unemployment or out of the labor force. Conditional on a job-to-job transition, they are more likely to have been employed in the same industry in their previous job and to have been employed in another foreign-owned plant. Finally, conditional on worker-level observables, they earned higher wages at their previous job. This evidence of positive selection sets the stage for the possibility that there may be negative spillovers on sending plants from losing workers to foreign entrant plants. We focus on spillovers experienced by workers in incumbent plants in local labor markets which experienced entry. In domestic-owned sending plants, there is no evidence of a negative effect on the wages of co-workers. However in foreign-owned sending plants, we do find evidence of a negative spillover. This may be attributed to the fact that foreign-foreign flows are much greater as a share of separations at foreign incumbents than domestic-foreign flows at domestic incumbents. We also show that conditional on observables, new hires at foreign entrants are paid a substantial premium relative to new hires at incumbents. Although foreign entrants account for a small share of employment, this raises the possibility that wages may be driven up in local labor markets which experience foreign entry. We test for this and do not find any evidence of a positive impact 2

3 on wages at incumbent plants. However we do not have a good instrument for foreign entry, so this finding does not have a clear interpretation. Our work is related to several literatures. It is most closely related to the literature documenting spillovers of foreign entry on domestic plants cited above as well as work on the spillovers from labour mobility. It is also related to a literature that documents what happens to workers affected by mass layoffs (Jacobson et al., 1993). Finally, we provide some of the first evidence on the characteristics of new hires at new plants, and of the impact of the birth of new plants on local incumbents through job-to-job transitions from incumbent to entering plants. The remainder of the paper is structured as follows: Section 2 provides a description of the data and descriptive statistics. Section 3 compares newly hired workers in entering and incumbent plants, foreign- and domestic-owned, by labour market status, industry, age, education, tenure and wages. Section 5 investigates whether there are local labor market effects from plant entry. Section 4 documents the effects of losing workers to entering plants on the remaining co-workers. Section 7 concludes. 2 Data and descriptive statistics 2.1 Data and definitions Our data set is based on three different data sources administered by Statistics Norway. The first data source is the register data with annual files of the whole population aged between 16 and 74 with individual identifiers that enable us to follow people over time. The register data contains information about individual characteristics like age, gender, country of birth, years of education, total annual earnings and municipality of residence. In addition, the files include a plant/workplace identifier of the main employer or main job for people in the labour force, as well as the industry and municipality of the workplace, recorded in November of each year. The plant identifiers are linked to a certain activity taking place in a given location, and plant identifiers cannot be changed by the plant or the owner of the plant. Our second source of information is the income tax files where each employer records who they have employed, for how long, and how much they have paid to each of their workers during the year. These data are recorded by job-spell, and in addition to plant and workplace identifiers (which are the same as in the population files), these files also include firm identifiers, i.e., the owners, of plants. Based on these two sources we first construct a plant panel for the years from 1996 to Using the firm identifier of each plant we can link to information about foreign ownership shares from the register of foreign ownership interests in Norwegian firms (the SIFON register). We define plants as foreign-owned if the total foreign ownership share is above 50%. 3

4 From this plant panel, constructed from the plant identifiers in the register data and the income tax files, we drop a plant if it is not observed in both data sources for more than half of its years in the panel. We also drop plants that have many years with missing information about location or missing information about industry affiliation. This drops about 10% of our initial plantyear observations. We further drop workplaces in the public sector, which account for 20% of the remaining sample. 1 We also drop very small plants where all workers are recorded as self-employed or the total wage bill does not exceed 100,000 NOK in 2007 NOK. This drops a further 10% of plant-year observations. The data tell us which individuals are employed by each plant each year, and allow us to follow workers as they transition between plants as well as in and out of the labour force from year to year. Plant identifiers that appear for the first time in our panel are initially defined as entrants. Since our data starts in 1996, to be conservative we do not define entrants before Foreign entrants are entrants that are foreign owned in the entry year. About two thirds of the plant identifiers that appear for the first time in our data from 1998 onwards have only one or two employees in the year of entry. Within the group of new plants with two or more workers, we are concerned about the possibility of classifying as entrants cases where reorganization of an existing plant leads to a new plant identifier even though most of the workers stay on. Also, the possibility of coding mistakes in plant identifiers could lead us to misclassify plants as entrants. We approach this problem by looking for entrants where many of the workers hired by the entrant in its entry year are co-movers, where we define co-movers as workers that are in the same sending plant in year t-1 and end up in the same arriving plant in year t. To do this, we need to identify the plant which sends the largest group of co-movers to the entrant. We then exclude a number of plants from our entrant definition if they have more than two comovers. We define plants as spinouts, and thus not as entrants, if there are more than four comovers that account for more than 50% in the arriving plant and the sending plant does not exit. We define as false entrants, and thus not as entrants, plants where the comovers account for more than 70% of workers in both the sending and the arriving plant. Starting with an initial number of nearly 78,500 new plant identifiers that appear in our final panel, with the exclusions above, we drop close to 6,500 entrants. 2.2 Descriptive Statistics Based on the data cleaning and definitions described above, our dataset contains on average 1.21 million workers in 117,000 plants per year. The plants are located in 160 local labour markets in mainland Norway. Local labor markets are defined by NIBR (Norwegian Institute for Urban and Regional Research) based on commuting patterns. The data cover workers across all sectors 1 We also drop the very few workplaces that are classified as private households and extraterritorial organisations. 4

5 of the economy, excluding the public sector, private households and extraterritorial organisations. As we will be comparing workers in foreign entrants to workers in domestic entrants and also to workers in incumbent foreign plants table?? shows the number of plants and their average size for domestic and foreign incumbents and entrants. Table 1: Number of plants and average plant size by type of plant year Incumbents Entrants Domestic Foreign Domestic Foreign Plants Avg. Plants Avg. Plants Avg. Plants Avg. size size size size Avg % of plants The vast majority of plants are incumbents, while 6.6 per cent of incumbents are foreign owned. On average over the period 6.2 percent of plants are entrants, and 4.8 percent of these are foreignowned. As is well-known, foreign-owned incumbent plants are on average much larger - 3 times as large in the present case - than domestically owned incumbent plants. Similarly, foreign entrants are about twice as large as domestic entrants. Tables 12 and 13 in the Appendix show the distribution of incumbents and entrants across sectors and the 20 Norwegian counties, respectively. By and large, entry is proportional to the existing sectoral and regional distribution of activity. In line with the changing structure of economic activity in industrialised economies, we observe less than proportional entry in manufacturing and in wholesale and retail trade, but higher than proportional entry in real estate, renting & business activities, which includes all professional services. In terms of the geographical distribution, foreign-owned plants have a much stronger preference (40 percent compared to about 25 percent of domestic plants) to locate in the Oslo and the surrounding region Akershus. Table 2 shows the distribution of newly hired workers by domestic and foreign incumbents and entrants. Compared to their share in plants, both foreign incumbents and entrants account for 5

6 higher shares of new hires. On average over the period, about 1 percent of new hires is accounted for by foreign entrants. Table 2: Distribution of new hires by type of plant year Incumbents Entrants Total new hires Domestic Foreign Domestic Foreign Avg Comparing new hires across entrants and incumbents In this section we compare new hires at domestic and foreign incumbents with new hires at domestic and foreign entrants, and show that new hires at entrants, in particular new hires at foreign entrants, are positively selected relative to new hires at incumbents. Table 3 shows the previous labour force status and nationality of new hires by employer type. New hires to foreign entrants are about 5 percentage points more likely to have been previously working in another plant in Norway than new hires to domestic incumbents and entrants. They are less likely to have been outside the labour force or unemployed the previous year. In terms of nationality, foreign incumbents and foreign entrants hire slightly higher shares of non-norwegian nationals. However, the share of new non-norwegian nationals is roughly the same across all four types of plants, indicating that foreign entrants do not bring a large share of workers from abroad. 2 Table 4 provides information on the industry and ownership of the previous plant for those new hires that were previously observed in another plant. New hires to both domestic and foreign entrants are more likely to have been employed in the same 2digit NACE sector than new hires at incumbents: the difference between new hires at foreign entrants and new hires at incumbents is about 7 percentage points. Foreign entrants, and also foreign incumbents, are much more likely 2 Note: The data only cover waged or salaried workers, they do not allow us to track persons on consulting contracts. 6

7 Table 3: Previous labour force status and nationality of new hires by type of plant New hire to dom incumbent for incumbent dom entrant for entrant Previous labour force status - in other plant outside labour force unemployed not in data Nationality - Norwegian non-norwegian new non-norwegian Note: New non-norwegian are people not observed in the data in the previous year, i.e. newly registered people. than domestic-owned plants to hire employees that were previously employed at another foreignowned plant. Table 4: plant Sector and ownership of previous plant for previously employed new hires by type of New hire to dom incumbent for incumbent dom entrant for entrant Sector of previous plant - same 2digit sector same NACE letter sector different NACE letter sector Ownership of previous plant - domestic plant foreign plant In Table 5 we compare new hires to incumbent and entrant plants in terms of age, years of education, ability - cognitive scores for men, and - for those who were previously in employment - tenure in their previous plant. New hires to both domestic and foreign entrants are on average years older than new hires to incumbents (column 1). New hires to foreign-owned plants - both incumbents and entrants - have somewhat higher levels of education than new hires to domestic incumbents or entrants (column 2). The difference in years of education between new hires to foreign incumbents and domestic entrants is statistically significant, while the difference between domestic and foreign entrants is not. For men born between 1950 and 1993 the data contains information on cognitive scores from military records measured on a scale from 1 to 9. Results using this score as the dependent variable are shown in column 3 of Table 5. The estimates indicate that foreign entrants on average hire men with higher cognitive scores than all other types 7

8 of plants. Column 4 shows that where the workers had been previously employed, both domestic entrants hire new employees with longer tenure in their previous plant than the other types of plants. In Table 6 we examine whether new hires that were previously employed are more likely to have been at the top of the wage distribution in their previous plant - out best proxy for a managerial role. When looking at new hires across all types of previous employers (column 1) new hires to domestic entrants are more likely to be hired from among the top three earners in their previous plant. Columns 2 and 3 suggest that this is true for new hires whether their previous employer was domestically or foreign-owned. Column 3 further shows that new hires to foreign entrants whose previous employer was foreign-owned are also more likely to have been among the top three earners in their previous position, suggesting that foreign entrants are more likely to hire staff for leadership roles from other foreign-owned plants. Table 5: Age, education, cognitive score and tenure in previous plant of new hires by plant type Dependent variable: Age Education Ability a Tenure in men only prev plant (1) (2) (3) (4) New hire to - Domestic Incumbent Omitted category - Foreign Incumbent (0.105) (0.017) (0.013) (0.031) - Foreign Entrant (0.348) (0.049) (0.038) (0.072) - Domestic Entrant (0.126) (0.011) (0.009) (0.030) female (0.042) (0.007) (0.009) constant (0.484) (0.071) (0.065) (0.106) R N Wald p-value FE=FI Wald p-value FE=DE Sample: New hires. Standard errors are adjusted for clustering at the plant level. ( ) p < 0.10,. p < 0.05, p < 0.01 All regressions include year, 3digit industry and labour market region dummies. a Cognitive scores from military records for men born between 1950 and 1993 (scale 1-9). 8

9 Table 6: Position in the wage distribution in previous plant of new hires by plant type Dependent variable: Among top 3 earners in previous plant All plants Domestic Foreign (1) (2) (3) New hire to - Domestic Incumbent Omitted category - Foreign Incumbent (0.001) (0.002) (0.001) - Foreign Entrant (0.005) (0.007) (0.006) - Domestic Entrant (0.002) (0.003) (0.003) female (0.001) (0.001) (0.001) constant (0.013) (0.014) (0.172) R N Wald p-value FE=FI Wald p-value FE=DE Sample: New hires. ( ) p < 0.10,. p < 0.05, p < 0.01 Standard errors are adjusted for clustering at the plant level. All regressions include year, 3digit industry and labour market region dummies. 9

10 Table 7: Wages in year of, year after and year before hire of new hires by plant type Dependent variable: log wage Year of Year after Last year in previous plant hire hire All plants Domestic Foreign (1) (2) (3) (4) (5) (6) New hire to - Domestic Incumbent Omitted category - Foreign Incumbent (0.004) (0.004) (0.004) (0.004) (0.004) (0.005) - Foreign Entrant (0.016) (0.013) (0.013) (0.010) (0.011) (0.014) - Domestic Entrant (0.003) (0.003) (0.003) (0.003) (0.003) (0.008) ln(age) (0.064) (0.061) (0.073) (0.064) (0.070) (0.110) ln(age) (0.009) (0.009) (0.010) (0.009) (0.010) (0.016) ln(education) (0.006) (0.006) (0.005) (0.006) (0.006) (0.011) female (0.002) (0.002) (0.002) (0.002) (0.002) (0.004) ln(tenure prev plant) (0.001) ln(tenure ) (0.007) (0.008) (0.014) <20 hrs/week Omitted category 20-29hrs (0.003) (0.003) (0.004) (0.003) (0.003) (0.007) 30+ hrs (0.004) (0.004) (0.004) (0.003) (0.003) (0.006) ln(plant size) (0.002) (0.001) (0.001) (0.001) (0.001) (0.001) share medium-skilled (0.009) (0.005) (0.007) (0.007) (0.008) (0.014) share high-skilled (0.011) (0.008) (0.010) constant (0.110) (0.109) (0.128) (0.111) (0.122) (0.374) R N Wald p-val FE=FI Wald p-val FE=DE Sample: New hires. Standard errors are adjusted for clustering at the plant 10 level. ( ) p < 0.10,. p < 0.05, p < 0.01 All regressions include year, 3digit industry and labour market region dummies. All variables are measured at the plant in which the worker is employed at the time.

11 So far, we have shown that new hires at entrants, especially foreign entrants, are positively selected on observables. Looking at wages can give us an idea of whether there is selection on unobservables. Wages are measured as the log of annual pensionable earnings.table 7 shows that other things equal, new hires at foreign entrants earned significantly higher wages than new hires to both incumbent plants and domestic entrants whether they were previously employed (column 2) or not (column 1). This is also true for those that are still in the same plant in the year after hire (column 3). The premium earned by new hires to foreign entrants relative to comparable new hires to domestic entrants is about log points, that to new hires to foreign incumbents is in the range of log points. New hires to foreign incumbents and to foreign and domestic entrants also earned higher wages than new hires to domestic incumbents in the last year in their previous job (column 4), this is true in particular if they were hired from other foreign-owned plants. 4 Spillovers from labour poaching The evidence presented above shows that new hires at foreign entrants are positively selected relative to new hires at incumbents, both on observables, and on unobservables. The literature has shown that where domestic firms hire new workers from foreign owned plants the co-workers in the hiring plant experience positive wage spillovers (Poole, 2013; Stoyanov and Zubanov, 2014), or the hiring plant experience positive productivity spillovers (Balsvik, 2011). The fact that new hires at foreign entrants are positively selected raises the possibility of negative spillovers at plants these workers separate from. As with positive spillovers from new hires, the impact of negative spillovers from the loss of co-workers may be distributed across workers at the plant experiencing separation, and the owners of that plant. Here we investigate whether the loss of a co-worker to a new plant has a negative effect on the wages of workers who remain. In particular, does this impact differ depending on whether the loss is to a foreign-owned vs a domestic-owned new plant? This means we wish to compare the loss of one or more workers to new plants with the loss of one or more workers to incumbent plants. Let i index a worker, j index a plant, r index a region, k index an industry and t index time ln w rk ijt = α ij + θ r t + φ k t + β X it + γ Z j,t 1 + δ S j,t=1 + ɛ ijt, (1) where the vector X it includes worker characteristics, namely age, tenure, education and indicators for hours worked. The vector Z j,t 1 captures lagged plant characteristics. In particular we include plant size, employment growth, shares of medium- and of high-skilled workers in the plant and the share of female workers. All these variables are included in lags because we want to capture 11

12 preexisting conditions at the plant which might have triggered workers to leave, but not the impact of those workers leaving. The variables of interest are S jt. These are the shares of workers leaving to other plants, namely to domestic incumbents, foreign incumbents, foreign entrants and domestic entrants as well as the share of exiting workers lost to non-employment. To give an example, the share of workers leaving to domestic incumbents is calculated as the share of workers lost between t 1 and t that in t are employed at a domestic incumbent over the total number of workers in the sending plant at date t 1. Losing workers to other plants may be a negative signal. In this case, the direction of causality would be the reverse of what we are interested in. We address this by including the plant-level characteristics above, in particular the lagged change in employment. A further concern is that locations where plants enter may be systematically different from locations where there are no new plants. To this end, equation (1) includes both region-year θ rt and industry-year φ kt fixed effects. To capture within-worker variation over time our specification includes worker-plant fixed effects α ij. Finally, as we want to compare incumbent workers at incumbent plants we exclude from the estimation sample workers that changed plant between t 1 and t as well as workers ever employed in entrant plants, where a plant is considered an entrant in its first three years according to our definition of entrants in Section 2. We are interested in the effects of workers leaving to other plants on the wages in levels as well as growth rates of their co-workers that remain at the sending plant. Results are presented in Tables 8 for wages in levels and 9 for wage growth. In each table column 1 reports the baseline estimates for all workers, column 2 the results for workers at domestic plants, column 3 for workers at foreign-owned plants, column 4 for workers in non-traded sectors and column 5 for workers in traded sectors (mining and manufacturing). We do not find significant effects of workers leaving to different plants - whether incumbents or entrants - on the wages or wage growth of their co-workers who do not change plants. This is likely to be due to the small shares of workers leaving in particular to entrant plants, in the baseline sample in column 1 of Table 8 the share of workers leaving to foreign entrants is 0.3%, that to domestic entrants 2.4%, that to foreign incumbents 7.6%, the largest share is that of workers leaving to domestic incumbents at 27%. Where we do find consistent positive effects is from workers leaving to non-employment. However, while these effects are statistically significant they are tiny in economic terms. 12

13 Table 8: Wage spillovers from co-workers moving to entrant plants - wage levels Dependent variable: log wage Plant sample All Domestic Foreign non-traded traded sectors (1) (2) (3) (4) (5) N workers leaving to Dom Incumb ( ) N leavers j,t 1 Omitted category N workers leaving to for incumb ( ) N leavers j,t ( ) (0.0013) (0.0015) (0.0025) (0.0015) (0.0028) N workers leaving to dom entrant ( ) N leavers j,t ( ) (0.0018) (0.0019) (0.0051) (0.0020) (0.0048) N workers leaving to for entrant ( ) N leavers j,t ( ) (0.0052) (0.0073) (0.0066) (0.0056) (0.0132) N workers leaving to non-empl ( ) N leavers j,t (0.0006) (0.0007) (0.0019) (0.0007) (0.0015) ln(age) (0.0240) (0.0258) (0.0490) (0.0265) (0.0482) ln(tenure) (0.0010) (0.0011) (0.0020) (0.0012) (0.0018) ln(education) (0.0106) (0.0112) (0.0309) (0.0119) (0.0228) <20 hrs/week Omitted category 20-29hrs (0.0023) (0.0025) (0.0056) (0.0026) (0.0051) 30+ hrs (0.0025) (0.0027) (0.0060) (0.0028) (0.0051) ln(plant size) t (0.0016) (0.0016) (0.0034) (0.0017) (0.0035) share med-skilled t ( ) (0.0034) (0.0035) (0.0102) (0.0036) (0.0095) share high-skilled t (0.0056) (0.0058) (0.0145) (0.0057) (0.0179) share females t (0.0041) (0.0043) (0.0125) (0.0044) (0.0115) ln(plantsize) t (0.0008) (0.0009) (0.0019) (0.0009) (0.0020) R N Sample: Workers employed in recent entrants and workers changing jobs are excluded. Standard errors are adjusted for clustering at the plant level. ( ) p < 0.10, p < 0.05, p < All regressions include worker-plant, labour market region-year and industry-year fixed effects. 13

14 Table 9: Wage spillovers from co-workers moving to entrant plants - wage growth Dependent variable: log wage growth Plant sample All Domestic Foreign non-traded traded sectors (1) (2) (3) (4) (5) N workers leaving to dom incumb ( ) N leavers j,t 1 Omitted category N workers leaving to for incumb ( ) N leavers j,t ( ) (0.0015) (0.0017) (0.0031) (0.0016) (0.0032) N workers leaving to dom entrant ( ) N leavers j,t ( ) (0.0020) (0.0021) (0.0062) (0.0022) (0.0051) N workers leaving to for entrant ( ) N leavers j,t (0.0058) (0.0080) (0.0086) (0.0062) (0.0168) N workers leaving to non-empl ( ) N leavers j,t (0.0007) (0.0007) (0.0022) (0.0008) (0.0016) ln(age) (0.0182) (0.0192) (0.0507) (0.0213) (0.0357) ln(tenure) (0.0011) (0.0012) (0.0027) (0.0012) (0.0021) ln(education) (0.0128) (0.0135) (0.0381) (0.0143) (0.0278) <20 hrs/week Omitted category 20-29hrs (0.0020) (0.0022) (0.0055) (0.0022) (0.0044) 30+ hrs (0.0019) (0.0021) (0.0054) (0.0022) (0.0040) ln(plant size) t (0.0012) (0.0013) (0.0028) (0.0013) (0.0028) share med-skilled t ( ) (0.0030) (0.0032) (0.0103) (0.0033) (0.0079) share high-skilled t (0.0046) (0.0049) (0.0129) (0.0049) (0.0132) female share t (0.0035) (0.0037) (0.0107) (0.0038) (0.0093) ln(plantsize) t (0.0011) (0.0012) (0.0024) (0.0011) (0.0028) R N Sample: Workers employed in recent entrants and workers changing jobs are excluded. Standard errors are adjusted for clustering at the plant level. ( ) p < 0.10, p < 0.05, p < All regressions include worker-plant, labour market region-year and industry-year fixed effects. 14

15 5 Labour market market effects of entry As documented in Section 3, new foreign entrants pay considerably higher wages than even foreign incumbents. This suggests that entry of foreign-owned plants may have implications for the wage setting at competing plants in the same region or industry. estimating the following regressions. We investigate this possibility by The first specification tries to get at whether the incidence of domestic or foreign entry in a local labour market region or region-industry affects wages in other plants in the same cell. Again, let i index a worker, j a plant, r a region, k an industry and t time. We estimate lnw rk ijt = α ij + θ t + β X it + γ Z jt + δ τ entry (k)r t τ + ɛ ijt, (2) where the dependent variable lnw rk ijt is the log of wages for worker i who is employed in plant j at time t, where the plant is located in region r and operates in industry k. The variable of interest, entry r t τ, represents two dummy variables, one which is equal to one if there is at least one foreign entrant in the (industry-)region and a second which is equal to one if there is at least one foreign entrant in the (industry-)region. The regions are the 160 local labour-market regions identified as commuting zones by Statistics Norway. Industries are defined at the NACE 3-digit level. In terms of worker characteristics, X it, we include the logs of age, tenure and years of education as well as dummy variables capturing hours worked. Plant covariates Z jt include plant size (log(employment)) and the shares of medium- and high-skilled workers at the plant, respectively. α ij is a worker-plant fixed effect and γ t a set of year dummies. The coefficients on entry (k)r t τ capture within-worker-plant changes that are associated with entry in the same (industry- )region. Note that we do not have a good instrument for entry, so we are relying on the timing of entry for identification. In a second specification we also assess whether it is the number of entrants that matters. So here entry (k)r t τ represents two variables which count the number of domestic and foreign entrants in an (industry-)region, respectively. We exclude workers that are ever employed in entrants from these regressions, where a plant is considered an entrant in its first three years according to our definition of entrants in Section 2. The results for the specification with two lags 3 on the entry variables are presented in Table 10. There are no significant effects from the incidence of either foreign or domestic at the labourmarket region level (column 1), the same is true for the number of entrants (column 2). the industry-region level the results indicate a negative effect from the incidence of foreign entry 3 The estimates on the second lags are strongest; they are statistically significant and of similar size also if included without other lags. At 15

16 Table 10: Local labour market effects from entry Dependent variable: log wage Entry variables at region level industry-region level for entry t ( ) ( ) for entry t ( ) ( ) ( ) dom entry t ( ) ( ) dom entry t ( ) ( ) N for entrants t ( ) ( ) N for entrants t ( ) ( ) N dom entrants t ( ) ( ) N dom entrants t ( ) ( ) ( ) ln(age) ( ) ( ) ( ) ( ) ln(tenure) ( ) ( ) ( ) ( ) ln(education) ( ) ( ) ( ) ( ) <20 hrs/week Omitted category 20-29hrs ( ) ( ) ( ) ( ) 30+ hrs ( ) ( ) ( ) ( ) ln(plant size) ( ) ( ) ( ) ( ) share med-skilled ( ) ( ) ( ) ( ) share high-skilled ( ) ( ) ( ) ( ) share females ( ) ( ) ( ) ( ) ( ) ( ) R N Sample: Workers employed in entrants are excluded. ( ) p < 0.10, p < 0.05, p < 0.01 Standard errors are adjusted for clustering at the region-year level. All regressions include worker-plant fixed effects and year dummies. 16

17 and a positive effect from the incidence of domestic entry two years ago (column 3). Column 4 confirms these effects for the number of entrants. However, while these effects are significant from a statistical point of view which is not surprising given the large number of observations, from an economic point of view they are negligible. 6 Spillovers to domestic plants In this section we assess whether there are spillovers to co-workers when workers with experience at multinational plants are hired at domestic plants. This is the traditional direction of stipulated in the literature and confirmed in Balsvik (2011) for Norway and Poole (2013) for Brazil. Here we follow the specification in Poole (2013). In particular, we estimate ln w ijt = δ M Sij M + δ D Sij D + β X it + γ Z jt + λ j + ψ i + θ t + ɛ ijt, (3) where Sjt M is the share of the domestically owned plants workforce with experience in a multinational establishment. As a separate term, Sjt D captures the share of the domestically owned plants workforce hired from another such plant (with no previous experience at a multinational plant). Poole (2013) finds stronger effects for workers in high-skilled industries, we also test for this possibility. Results are reported in Table 11. The results in column 1 are for workers in all domesticallyowned plants. Like Poole (2013) we do find a significant positive effect on the wages of workers staying in domestic plants from having a higher share of workers with previous experience at a multinational plant Sij M as well as previous experience at another domestic plant Sij D as co-workers. As indicated in the last row of the table the effect is significantly stronger from workers with multinational experience. In columns 2 and 3 we check whether there are differences for plants with high shares of high-skilled versus plants with lower shares. We define plants as high-skill intensive plants if their mean share of high-skill workers (defined as workers with a BA degree or higher) over their time in the sample is above 0.2 (the sample mean over all plants is 0.198). While we do find that the effects from both workers with multinational experience and workers with experience from another domestic plant are somewhat higher in plants defined as high-skill intensive, the difference between the two shares are of similar magnitudes in the two types of plants. 17

18 Table 11: Wage spillovers from new co-workers with experience at foreign-owned plants Dependent variable: log wage Plant sample All High-skill Low-skill (1) (2) (3) Sij M (0.0087) (0.0121) (0.0106) Sij D (0.0037) (0.0059) (0.0037) ln(age) (0.0200) (0.0324) (0.0256) ln(tenure) (0.0007) (0.0012) (0.0010) ln(education) (0.0093) (0.0181) (0.0118) <20 hrs/week Omitted category 20-29hrs (0.0022) (0.0035) (0.0032) 30+ hrs (0.0024) (0.0036) (0.0034) ln(plant size) (0.0014) (0.0023) (0.0017) share med-skilled (0.0031) (0.0055) (0.0038) share high-skilled (0.0052) (0.0065) (0.0127) share females (0.0039) (0.0055) (0.0056) R N S M ij S D ij p-value Sample: Domestic (Norwegian-owned) plants. ( ) p < 0.10, p < 0.05, p < Standard errors are adjusted for clustering at the plant level. Regressions include worker, plant, and year fixed effects. 18

19 7 Conclusion We use matched employer-employee data for Norway to provide evidence on the short-run impact of foreign entry on incumbent plants through the labor market. We first document that new hires at foreign entering plants are positively selected relative to new hires at incumbent plants on observables. Conditional on worker-level observables, new hires at entrants earned higher wages at their previous job than new hires at incumbents, suggesting selection on unobservables also. This evidence of positive selection sets the stage for the possibility that there may be negative spillovers on sending plants from losing workers to foreign entrant plants. We do not find evidence of wage spillovers to co-workers in sending plants. We also show that conditional on observables, new hires at foreign entrants are paid a substantial premium relative to new hires at incumbents. Although foreign entrants account for a small share of employment, this raises the possibility that wages may be driven up in local labor markets which experience foreign entry. We test for this and do not find any evidence of a positive impact on wages at incumbent plants. We confirm earlier evidence consistent with positive spillovers for remaining workers at plants that hire workers with experience at foreign-owned plants extending the analysis from manufacturing to the economy as a whole. 19

20 References Balsvik, Ragnhild (2011) Is mobility of labour a channel for spillovers from multinationals to local domestic firms? Review of Economics and Statistics 93(1), Balsvik, Ragnhild, and Stefanie A. Haller (2011) Foreign firms and host-country productivity: does the mode of entry matter? Oxford Economic Papers 63(1), Görg, Holger, and David Greenaway (2004) Much ado about nothing? Do domestic firms really benefit from foreign direct investment? The World Bank Research Observer 19(2), Jacobson, Louis S, Robert J LaLonde, and Daniel G Sullivan (1993) Earnings Losses of Displaced Workers. American Economic Review 83(4), Poole, Jennifer P. (2013) Knowledge Transfers from Multinational to Domestic Firms: Evidence from Worker Mobility. The Review of Economics and Statistics 95(2), Stoyanov, Andrey, and Nikolay Zubanov (2014) The distribution of the gains from spillovers through worker mobility between workers and firms. European Economic Review 70(C),

21 Appendix Table 12: Distribution of plant types sectors incumbents entrants NACE letter sector Domestic Foreign Domestic Foreign Agriculture Fishing Mining Manufacturing Utilities Construction Wholesale & retail trade Hotels, bars & restaurants Transport, storage & communication Financial intermediation Real estate, renting & business activities Other community, social & personal services

22 Table 13: Distribution of plant types across counties incumbents entrants Domestic Foreign Domestic Foreign East Ostfold Akershus Oslo Hedmark Oppland Buskerud Vestfold Telemark South Aust-Agder Vest-Agder West Rogaland Hordaland Sogn of Fjordane More og Romsdal Trondelag (Centre North) Sor-Trondelag Nord-Trondelag North Nordland Troms Finnmark