Do Foreign Investors Care About Labor Market Regulations?

This study takes a new look at the regulatory determinants of foreign direct investment (FDI) by asking whether labor market flexibility affects FDI flows across 19 Western and Eastern European countries. The analysis is based on firm-level data on new investments undertaken during the 1998-2001 period. The study employs a variety of proxies for labor market regulations reflecting the flexibility of individual and collective dismissals, the length of the notice period and the required severance payment along with a comprehensive set of controls for the business climate characteristics. The results suggest that greater flexibility in the host country's labor market in absolute terms or relative to that in the investor's home country is associated with larger FDI flows. The findings indicate that as the labor market flexibility in the host country increases from inflexible (e.g., France) to flexible (e.g., United Kingdom), the volume of investment goes up by between 12% and 26%. FDI in services sectors appears to be more sensitive to labor market regulations than investment in manufacturing.


NON-TECHNICAL SUMMARY
While the existing empirical literature on foreign direct investment (FDI) has examined the effect of various regulatory determinants on investment flows, no attention has been paid to one key aspect of government regulations, namely the flexibility of labour markets, despite the fact that both the anecdotal evidence and the theoretical literature suggest it ought to be important. For instance, the lack of flexibility in hiring and laying-off workers is one of the main concerns raised by investors operating in or considering entering transition economies and developing countries.
This study takes a new look at the regulatory determinants of foreign direct investment (FDI) by asking whether labour market flexibility affects FDI inflows across 19 Western and Eastern European countries. The analysis is based on firm-level data on new investments that occurred during the 1999-2001 period. We employ a variety of labour market flexibility measures that capture different aspects of labour laws, along with a comprehensive set of controls for business climate characteristics. Indices of labour market regulations reflect the flexibility of individual and collective dismissals, the length of the notice period, and the required severance payment. The results suggest that greater flexibility in the host country's labour market is associated with a higher probability of investment taking place, as well as with a larger volume of investment. The same holds true for the difference between the labour market regulations in the host and the source country. The data also indicate that foreign investors entering services sectors are more sensitive to labour market regulations than investors in general.

Introduction
While the existing empirical literature on foreign direct investment (FDI) has examined the effect of various regulatory determinants on investment flows, 1 no attention has been paid to one key aspect of government regulations, namely the flexibility of labor markets, despite the fact that both the anecdotal evidence and the theoretical literature suggest it ought to be important. For instance, a recent article in the Financial Times carried a headline stating that "Archaic Labor Laws Stop Europe Working" and argued that in the presence of labor regulations that make it hard to dismiss and to hire workers, companies can neither grow not take advantage of new business opportunities. 2 Similarly, The Economist magazine suggested that increasing labor market flexibility is seen as crucial to the revitalization of the European economy, particularly after the accession of several Central and Eastern European Countries to the European Union. 3 The lack of flexibility in hiring and laying off workers is also one of the main concerns raised by investors operating in or considering entering transition economies and developing countries (Moran 1998, p. 89). This view is further echoed in a theoretical paper by Haaland et al. (2003) who demonstrate a trade-off between FDI incentives and labor market flexibility and conclude that a country with a more flexible labor market (i.e., lower redundancy payments) should find it easier to attract FDI.
This study aims to fill the gap in the literature by testing empirically whether host country's labor market flexibility, in absolute terms or relative to that in the investor's home country, affects the location decisions of multinationals. To the best of our knowledge, the only analysis of this question can be found in a paper by Dewit et al. (2003) who consider the impact of labor laws on aggregate FDI flows within the OECD countries in 1989 and 1998 and find that an unfavorable employment protection differential between a domestic and a foreign location is inimical to FDI. 4 In contrast to the work of Dewit et al. (2003), our analysis is based on firm level data and employs a much more detailed set of proxies for labor market regulations.
One of the advantages of employing firm level data is that we are able to explicitly control for the investing firm's characteristics that affect the investment decision, such as the firm size, previous FDI experience and the nature of business (i.e., manufacturing versus services). We are also able to consider a specification that takes into account unobserved investor characteristics. We use information on new subsidiaries established by the largest 10,000 European companies in 19 Western and Eastern European countries during 1998-2001. The information comes from a commercial database Amadeus compiled by Bureau van Dijk. Western European countries and transition economies of Eastern Europe are well suited for studying this question, as they offer a large variation in terms of labor market regulations. In both Western and Eastern Europe we can find economies with highly inflexible labor markets 1 Wei and Schleifer (2000) examine the consequences of FDI incentives and restrictions on investment flows, Hines (1996) and Devereux and Griffith (1998) the effect of taxation, Javorcik (2004) the impact of intellectual property protection, Keller and Levinson (2002) and Javorcik and Wei (2004) Görg (2002) addresses a similar question using the data on the stock of US outward FDI and focusing only on the level of labor market flexibility in a host country rather than the differential between the home and the host economy.
(France and Poland) as well as countries giving employers relative freedom in hiring and firing decisions (United Kingdom and Bulgaria).
We employ a comprehensive set of labor market flexibility measures along with a large set of controls for business climate characteristics. The former include indices compiled by Djankov et al. (2001) reflecting the flexibility of individual dismissals, the flexibility of collective layoffs, the length of the notice period and the required severance payment, as well as a proxy for the flexibility of hiring and firing practices from the Global Competitiveness Report 2001Report -2002 produced jointly by the Geneva-based World Economic Forum and the Center for International Development at Harvard University. Moreover, we control for the presence of restrictions on FDI inflows, protection of property rights, the level of corporate taxation and the quality of governance. Finally, we include measures of the market size and labor costs.
The results suggest that greater flexibility in the host country's labor market is associated with a higher probability of investment taking place as well as with a larger volume of investment. The same holds true for the difference between the labor market regulations in the host and the source country. When we interact the effect of labor market flexibility with a dummy for services sectors, we find that investors entering these industries are even more sensitive to labor market regulations. We also show that taking into account the presence of transition economies in the sample does not change the results.
The paper is structured as follows. In the next section we discuss the empirical model, the data and the variables definitions. Then we present the empirical results. The last section contains concluding remarks.

Model and Estimation Issues
The basic question we seek to answer is whether labor market flexibility affects the flow of foreign direct investment across countries. In doing so we also consider a number of other potential determinants of location choice, as suggested by the existing literature. 5 We employ two empirical strategies to address this question. First, we focus on the location of foreign subsidiaries ignoring the size of investment. We estimate a fixed effect logit model where the dependent variable takes on the value of one if firm i has invested in country c, and zero otherwise. For each firm the number of observations is equal to the number of possible destination countries in the sample. To control for unobservable firm characteristics, firm specific fixed effects (d i ) are used. On the right hand side, we include the index of the host country's labor market flexibility (Flexibility c ) or the difference in the labor market flexibility between the host and the source country (Flexibility ic = Flexibility c -Flexibility i ) as well as other controls for host country characteristics (X c ). Since our prior is that more flexible labor market regulations in the host country (in absolute terms or relative to the source country) are associated with a greater likelihood of foreign investment, we expect β > 0.
Then we focus on the size of investment and estimate the following equation (2) where the volume of investment undertaken by firm i in country c is regressed on the characteristics of firm i and its home country (X i ), variables specific to destination country (X c ) and the proxy for labor market regulations (Flexibility c or Flexibility ic ). Again we expect δ to be positive. The number of observations for each firm is equal to the number of potential investment destinations, with the FDI volume equal zero for countries in which firm i does not have any investments. To avoid losing all observations for which FDI volume takes on the value of zero, we add one before taking the logarithm of the variable. Given that most firms have subsidiaries only in some of the 19 possible destination countries considered and some firms have no subsidiaries at all, in a large number of cases the dependent variable is equal to zero. Therefore, we employ the Tobit model, as using OLS would lead to inconsistent estimates.
The choice of the model is determined by the data availability. As explained below, our data set contains a comprehensive listing of the existing subsidiaries of firms included in the sample, but the information on the volume of investment is available only for a subset of them. The logit specification allows us to maximize the sample coverage, while the Tobit regression enables us to examine the determinants of the investment volume. We view the two approaches as complementary.

FDI Data
The data used in this study come from the commercial database Amadeus compiled by Bureau van Dijk, which contains comprehensive information on approximately 5 million companies operating in 35 European countries. In addition to the standard financial statements, Amadeus includes complete information on the ownership structure of firms, which allows us to identify the ownership stakes held by each company in entities located in other countries. We are thus able to construct a unique data set containing detailed information about European firms and all of their domestic and foreign subsidiaries.
We focus our attention on the largest 10,000 firms operating in Europe (with the size measured by the value of total assets in 1999) and their subsidiaries located in 14 Western European and 5 Central and Eastern European countries, including Bulgaria, the Czech Republic, Hungary, Poland and Ukraine. The choice of host countries is driven by two considerations: by the fact that information on the size of investment is available only for European subsidiaries and by our decision to restrict the analysis to subsidiaries established between 1998 and 2001. We construct the data set on new subsidiaries by comparing the subsidiary listings for companies included in both the 1998 and the 2001 versions of the Amadeus database. 6 The ownership information pertains mostly to year 2000 and in some cases to 1999. If a firm has more than one subsidiary in a given country, we focus our attention on the one with the highest value of the parent company's equity participation. The sample also includes non-investors that is, firms without any subsidiaries in foreign countries. 7 After deleting firms with missing information and removing outliers, 8 the data set contains 7,150 parent firms with 6,391 subsidiaries in 19 destination countries, including the home country, of which 3,053 are foreign subsidiaries. The potential number of observations is thus equal to 7,150 x 19 = 135,850 investment decisions at the firm level. The Amadeus database provides a good reflection of FDI inflows into the host countries considered. The correlation between the FDI inflows reported by UNCTAD for 1999-2000 and the total value of foreign assets in the subsidiaries listed in Amadeus and created in the same group of host countries during the same period is .61. 9

Variable Definitions
The dependent variable in Equation (1) is equal to one if the database indicates the existence of firm i's subsidiary in country c. In Equation (2), we construct FDI volume by multiplying the percentage of the equity owned by firm i in its subsidiary located in country c by the total assets of the subsidiary. If firm i has more than one subsidiary in country c we use the largest investment. If no subsidiary exists, the variable takes on the value of zero. All information from the Amadeus database presented in national currencies is converted to U.S. dollars using the average market exchange rate for the given year from the IMF's International Financial Statistics.
In addition to taking into account conditions in the host country, our data set provides us with an opportunity to control for characteristics of parent companies. We do so only in Equation (2) as Equation (1) includes parent fixed effects. As larger firms and firms with greater international experience may be more likely to expand into foreign countries (see Javorcik 2004 for empirical evidence), we control for the firm size using the value of total assets and for the international experience by including the total number of foreign subsidiaries. In order to avoid simultaneity we use the values of these variables pertaining to 1998, which is the first year considered in our sample. 10 We expect to find a positive coefficient on both variables. We also take into account the population size, the average wage and GDP per capita of the source country, expecting that more FDI is likely to come from larger and richer countries and from economies with higher labor costs. The average wage is calculated as the average of wages paid by the top 10,000 firms in each country. 11 The population and GDP per capita figures come from the World Bank's World Development Indicators.
Since the purpose of our paper is to test for the effect of labor market flexibility on the multinational firm's decision to invest in various countries, it is crucial to have plausible measures of labor market regulations. The first measure used in our analysis is the Index of Flexibility of Hiring and Firing Practices from the Global Competitiveness Report 2001-2002 published jointly by the Geneva-based World Economic Forum and the Center for International Development at Harvard University. It is a country specific index that quantifies the average response to the survey question: "Is hiring and firing of workers impeded 8 Firms with negative or unusually large values for sales, total assets or employment were dropped from the sample. 9 Total FDI inflows were calculated by subtracting the total FDI stock as of end-1998 from the corresponding figure for end-2000, as reported in the UNCTAD online database (www.unctad.org). To calculate total FDI inflows based on the Amadeus data we considered only subsidiaries with more than 10% foreign ownership. 10 Note that the number of subsidiaries pertains to investments located all over the world, not just in the 19 countries considered in our sample. 11 Top 10,000 firms in decreasing order of total assets and with more than 5 employees in 1999. by regulations or flexibly determined by employers?" It takes on the value of 7 for a very flexible labor market and 1 in the case of the most rigid ones. Since it is based on the views of "business practitioners" in each country, it captures not only laws on the books but also their enforcement.
We also include four additional measures, compiled by Djankov et al. (2001), reflecting the strength of employment protection legislation, which relates to employers' liberty to lay off workers. These are: the Index of the Flexibility of Individual Dismissal Procedures, the Index of the Flexibility of Collective Dismissal Procedures, the Index of Notice and Severance Payment and the Overall Index of Rules of Dismissal. 12 These indices rely on information collected in 2001 and thus match well the time period of our sample. The value for the Overall Index of Rules of Dismissal ranges from 0 to 12, with 0 representing very strict rules of dismissal and 12 the most ample ones. Thus, the higher the index value, the less costly it is for the employer to dismiss workers. The indices are country specific but, since firing costs are usually comparable across industries as they are set by the national legislation, the use of country level data is appropriate.
As illustrated in Figures 1 and 2, there is a large variation in the 19 countries considered in our sample in terms of labor market flexibility. In both Western and Eastern Europe we can find economies with inflexible labor markets (France and Poland) as well as countries giving employers relative freedom in hiring and firing decisions (Denmark and Hungary). While there are some differences in individual rankings between the GCR and the Overall Index of Rules of Dismissal, the two measures appear to be highly correlated (see Figure 3). Therefore, we start our analysis by including labor market indices one by one in the regressions. As higher labor market flexibility is associated with lower costs of doing business, we expect to find a positive relationship between the probability of FDI or the investment volume and the host country's flexibility of labor markets. Recognizing that impediments to adjusting employment numbers constitute a push factor encouraging firms to transfer production out of their own country as well as a pull factor enticing firms to enter economies with flexible rules, we also focus on the difference in labor market flexibility between the host and the source country. As higher values of the variable correspond to greater flexibility in the host country relative to the source country, we expect to find a positive relationship between Flexibility ic and the likelihood or the volume of investment.
Turning to other host country characteristics, we control for factors commonly mentioned in the literature as determinants of FDI, including proxies for the market size (population size) and the labor costs in the host country (average wage). We expect that larger markets attract investors while higher labor costs act as a deterrent. As in the case of labor market flexibility variables, we also allow for the difference in labor costs between the home and host country. The higher the labor costs difference between the home and the host country, the higher the likelihood of FDI or the volume of investment. 13 We also control for various aspects of the business climate in the host country. The first control is the FDI Restrictions Index derived by Wei and Schleifer (2000) based on reading the detailed country reports produced by PricewaterhouseCoopers. The index focuses on four areas: the existence of foreign exchange controls (which may interfere with foreign firms' ability to import intermediate inputs or repatriate profits abroad), the exclusion of foreign firms from strategic sectors (e.g., defense industry, media), the exclusion of foreign firms from other sectors, and restrictions on the share of foreign ownership. Each of these four dimensions is represented by a variable taking on the value of 1 in the presence of restrictions and 0 otherwise. The overall index is defined as the sum of these variables and ranges from 0 (no restrictions) to 4 (restrictions present in all areas).
The second control is the Index of Property Rights, which comes from the Global Competitiveness Report 2001Report -2002 It is based on an extensive survey of managers who were asked to rate on the scale 1 to 7 whether the "property rights [in a given country] are clearly delineated and protected by law." Subsequently, the arithmetic mean of all responses by country was reported. A score of 7 corresponds to countries with well protected property rights and 1 to the countries with little or no protection. This variable is intended to capture the country specific risk that multinational firms may face from possible expropriation of assets, insecurity of property rights and contracts.
Another potentially important factor influencing the FDI location is the level of corporate taxation in the host country, as demonstrated by Hines (1996) and Devereux and Griffith (1998). We employ the corporate tax rates reported by PricewaterhouseCoopers. All taxes are expressed in percentages; if several rates apply, the highest one is used. We anticipate that high tax rates deter FDI. We also expect the difference in taxation rates between the home and the host country to be positively correlated with the probability of investing abroad as well as with the volume of investment. 14 Finally, we add a dummy variable for transition countries to control for other differences between industrialized and transition economies that may not be captured by the explanatory variables. For instance, if a large presence of foreign investors encourages subsequent inflows due to agglomeration effects and transmission of knowledge about the host country to source economies, then transition countries are at a disadvantage vis-à-vis Western Europe as they have opened to FDI relatively recently.
All variables definitions and data sources are summarized in Table 1.
As can be seen in Table 2, a large degree of heterogeneity is found in terms of the business environment in host countries in our sample. Transition economies usually rank low with respect to property rights protection. However, the picture is mixed with regard to FDI incentives, labor market flexibility and corporate taxation, as in both Western as well as Eastern Europe we find countries with very different scores in these areas. For instance, while some transition economies, especially Hungary, the Czech Republic and Poland, have no or very few restrictions on FDI, others, such as Ukraine, have restrictions in all categories. Similarly, while Ukraine has the highest corporate tax rate, Hungary offers the lowest one in the sample. More importantly for the topic of interest, we find a large variation with respect to labor market regulations. The Overall Index of Dismissal Rules range from a score of 3 (rigid labor markets) for Portugal and Ukraine to 8 (flexible) for Austria and Hungary and 11 (highly flexible) for Belgium.

FDI Determinants
We begin by examining determinants of FDI and proceed by including one by one the five measures capturing a host country's labor market flexibility. We estimate a logit model with fixed effects for each investing company. 15 The results are presented in Table 3. We find a positive and significant coefficient on the host country's population size, suggesting that larger countries are more attractive investment destinations. Further, the data suggest that lower restrictions on FDI and stronger property rights protection are associated with a higher probability of FDI taking place. As anticipated, we find a negative and statistically significant coefficient on the corporate tax rate in the host country, which suggest that, all things being equal, more taxation deters FDI. The coefficient of the host country average wage is positive and significant, which is somewhat counterintuitive, yet not unusual in the literature on determinants of FDI as the average wage may be capturing the purchasing power of the population. Finally, the dummy for the host country being a transition economy is negative and significant indicating that transition countries have a lower probability of receiving FDI than what would be predicted given their economic and regulatory environment. The transition economies dummy is introduced in the model to capture some common unobserved characteristics of the transition countries. Excluding it, however, would not affect the conclusions of the analysis.
We now turn our attention to the labor market variables. As higher values of these variables correspond to a more flexible labor market in the host country, we expect the estimated coefficient to be positive if greater flexibility in the host economy attracts FDI. We start with the Indices of Dismissal Rules. The first measure included is the Index of Flexibility of Individual Dismissal Procedures. Its coefficient is positive and statistically significant at the one percent level, thus suggesting that indeed, ceteris paribus, the more flexible the host country's labor market, the higher the probability of FDI taking place. The same conclusion is reached when the Index of Flexibility of Collective Dismissal Procedures, the Index of Notice and Severance Payment as well as the Overall Index of Rules for Dismissal are used. In all cases, the indices have positive and highly significant coefficients. We also use the GCR Index of Flexibility of Hiring and Firing Practices and again find evidence of a positive relationship between the labor market flexibility and the location choice of multinational investors. In addition, we estimate a model including all three components of the Overall Index of Dismissal Rules. We find that two of them (Severance Payment Rules and Collective Dismissal Rules) remain positive and statistically significant. Finally, we include the GCR index in addition to the three components of the Overall Index of Dismissal Rules. The Severance Payment Rules Index and the GCR index bear positive and significant coefficients. The lack of significance of the other two indices is most likely due to high correlation between various measures of labor market flexibility.
Next, we focus on explaining the determinants of FDI volume rather than the mere fact of investment taking place. We employ the Tobit specification and follow the same procedure of consecutively adding labor market variables to the regression, keeping the same controls as before. In addition, we include some source country characteristics, such as the logarithm of the 15 Note that in the fixed effect logit, firms without any investment projects drop out of the estimation. GDP per capita and the population size. We also account for the characteristics of the investing firm, in particular its size and its international experience. 16 The results, presented in Table 4, confirm our previous findings that the labor market flexibility in the host country is an important factor affecting the location decision of multinational firms. When entered one at a time, all five indices of the host country labor market flexibility have the expected positive signs and are statistically significant at the one percent level. When we include all labor market flexibility measures in the same regression, all measures with the exception of the Individual Dismissal Rules Index remain positive and statistically significant. The other controls for host country characteristics have the same signs as in the fixed effects logit regressions and are highly significant. The only exception is the host country average wage, which now bears a negative and statistically significant sign in five out of seven specifications. As for investor characteristics, we find that larger firms as well as firms with greater international experience are more likely to undertake FDI. The same is true of firms headquartered in richer countries.
To test the robustness of these results and to make sure that they are not driven by the presence of transition countries, we restrict the sample to Western European economies. As before, all four labor market variables are statistically significant and bear the expected positive sign (see panels A and B of Table 5). As a further robustness check, we express the FDI volume relative to the host country GDP. As illustrated in Panel C of Table 5, the results confirm our previous findings that labor market flexibility is an important factor explaining the volume of foreign direct investment in host countries.
One may argue that FDI decisions are not driven by the labor market regulation in the host country but rather by the difference in the flexibility of firing and hiring between the source and the host country. For instance, a French company may have a greater incentive to engage in FDI than its British counterpart simply because French labor market regulations are more stringent than those prevailing in the U.K. Therefore, next we examine how the differences in labor market regulations between the home and the host countries influence the FDI location choice. For the purpose of consistency other variables, where the differential in the business environment between the source and the host country (rather than the absolute level) is likely to matter, enter in the relative form. These are: corporate tax rates and wage rates. We do not enter the population size in the relative form since we do believe that it should matter for FDI decisions. Similarly, we do not include relative GDP per capita as it is highly correlated with relative wage rates.
The results are presented in Table 6. As a higher value of the labor market flexibility term corresponds to more flexible host country's labor market relative to the source country (recall that Flexibility ic = Flexibility host -Flexibility source ), we expect to obtain a positive coefficient. And indeed we find evidence that a more flexible labor market in the host country relative to the home country is associated with a higher likelihood of investment. The magnitude of the effects is economically meaningful. As the labor market flexibility in the host country (keeping the source country and other things constant) increases from the level of France (inflexible) to the level of the United Kingdom (flexible) the volume of investment goes up by between 12 and 26 percent depending on the measure employed.
As expected, we find that a differential in corporate tax rates is positively associated with the likelihood and the volume of investment. Note that to facilitate the interpretation of the results, we define the differences in tax rates and wages as those prevailing in the source country relative to those in the host (i.e., Tax rate ic = Tax rate source -Tax rate host ). On the other hand, the difference in the average wages appears to be negatively correlated with the probability of investing abroad and the investment size. However, this may not be surprising since most of the FDI originates from and is destined for rich countries that differ little in terms of wage level. All other variables have the expected signs.
The regressions presented so far constrain the effects of labor market flexibility on FDI to be equal across countries. This may be a strong assumption since the sample of host countries in our data set includes both industrial and transition economies. To relax this assumption we introduce an interaction between the labor market flexibility measures and the dummy variable for transition host countries and repeat the exercise. As illustrated in Table 7, the coefficients of the labor market differentials remain positive and highly significant in all regressions. The interaction terms with the transition dummy are negative and significant in six cases, which suggests that the relationship between the value of investment and the labor market flexibility appears to be weaker for transition countries than for the sample as a whole. In all regressions, however, the link between labor market flexibility and the value of FDI in the sample as a whole remains robust. Thus we conclude that the presence of transition economies in our sample does not drive the results.

Robustness Checks
As an additional robustness check we also control for the quality of governance in the host country using the measure derived by Kaufmann, Kraay and Zoido-Lobaton (KKZ) and described in detail in their 1999 and 2002 publications. When constructing their measure based on data from 17 different sources, the authors assume that the available individual country ratings reflect both some true but unobserved level of governance as well as sampling variations and perception errors. The unobserved "true" level of governance can be backed out statistically (assuming a linear unobserved component specification). The resulting estimates range from -2.5 to 2.5, with a mean of zero and standard deviation of one. The higher the estimate, the less corrupt and better governed the country. The results, not reported here to conserve space, are robust to including the KKZ index-all labor market flexibility proxies have the expected sign and remain statistically significant. 17 As yet another robustness check (not presented here), we apply the same approach to all existing rather than only new subsidiaries of the top 10,000 European companies. In the case of multiple subsidiaries being held by the same parent company in a given host country, we include only the largest investment in the sample, regardless of when the subsidiary was created. The rationale for this exercise is that multinational companies tend to respond quickly to a change in the business environment by relocating their activities to other places. As expected, we obtain results consistent with our previous findings. Labor market flexibility variables are again consistently positive and statistically significant, reinforcing our earlier results that labor market conditions are key determinants of both the location and the volume of FDI.

Manufacturing versus Services Sectors
If labor market flexibility indeed matters for the location choice of multinational companies, we would expect it to be of greater importance to multinationals in more laborintensive sectors. Since services are usually more labor-intensive than manufacturing, and since our rich database includes information about the industry in which the investing company operates, we examine whether the two types of sectors respond differently to labor market regulations. To do so, we introduce an interaction between a dummy variable equal to one for services sectors and the proxies for labor market flexibility and follow the same empirical strategy as before. The results, presented in Tables 8, confirm our hypothesis. We find that the interaction terms are statistically significant and positive in all cases. That is, labor market flexibility matters more for investors in services sectors than those in manufacturing industries.

Conclusions
Labor market rigidities are often cited as one of the factors multinationals take into account when deciding on a prospective host country, yet hardly any attention has been paid to this issue in the empirical literature. This paper is an attempt to further our knowledge in this area. Using firm level data on new foreign investments undertaken by European companies during the period 1998-2001 and a comprehensive set of labor market indicators, we examine the impact of labor market flexibility on FDI inflows into 19 European countries.
Our empirical findings are as follows. The FDI location choice as well as the volume of FDI are positively related to labor market flexibility in the host country and to the difference between labor market regulations in the host and the source country. That is, a more flexible labor market in the host economy (relative to the investor's home country) is associated with a higher likelihood of investment. As expected, this effect matters more for firms operating in services sectors than for manufacturing companies.
Europe: The Role of Agglomeration Benefits. In Geography and Direct Investment: The Activities of Multinational Enterprises in Europe, PhD Thesis, Graduate Institute of International Studies, Geneva. Wei, S.J., and A. Schleifer. (2000). Local corruption and Global Capital Flows. Brookings Papers on Economic Activity 2: 303-354. Wheeler, D., and A. Mody. (1992). International Investment Location Decisions: The Case of US Firms. Journal of International Economics. 33(1-2):57-76.  Ranges from 0 for very strict to 2 for very flexible rules. Is based on equally weighted answers to the following questions: -"Does the employer need to notify a third party before dismissing one redundant employee?" -"Does an employer need the approval of a third party to dismiss one redundant employee?" Djankov et al. (2001) Index of Flexibility of Collective Dismissal Procedures Ranges from 0 for very strict to 5 for very flexible rules. Is based on equally weighted answers to the following questions: -"Does the employer need to notify a third party prior to collective dismissal?" -"Does the employer need the approval of a third party prior to a collective dismissal?" -"Are there laws mandating retraining or replacement prior to dismissal?" -"Are there priority rules applying to dismissal or lay-offs?" -"Are there priority rules applying to re-employment?" Djankov et al. (2001) Index of Notice Period and Severance Payment Ranges from 0 for very strict to 2 for very flexible rules. Based on the sum of two scores: -the legally mandated notice period (in weeks) is above the sample median for 73 countries; -the severance pay as a number of months for which full wages are payable after covered employment of three years is above the sample median for 73 countries Djankov et al. (2001) Transition Country Dummy Equal to 1 for transition countries (Bulgaria, Czech Republic, Hungary, Poland, Ukraine), and 0 otherwise.   Standard errors in brackets. * significant at 10%; ** significant at 5%; *** significant at 1%.  36,196 36,196 36,196 36,196 36,196 Prob>Chi 2 0.00 0.00 0.00 0.00 0.00 The explanatory variables (not reported here) include: investing firm's size and international experience, source country's population and GDP per capita, and host country's population, average wage, corporate tax rate, index of property rights and index of restrictions to FDI. 0.00 0.00 0.00 0.00 0.00 The explanatory variables (not reported here) include: investing firm's size and international experience, source country's population and GDP per capita, and host country's population, average wage, corporate tax rate, index of property rights and index of restrictions to FDI.