Factor Movements and International Business < F -International Economics, H25 -Business Taxes and Subsidies

Introduction

Foreign Direct Investment (FDI) is carried out by Multinational Enterprises (MNEs) in order to earn profits. The profitability of FDI is expected to decrease with increases in energy, taxes, labour costs etc.. Concerning taxation, the negative relationship between tax burden and FDI inflows is basically confirmed by the empirical evidence for OECD countries. (e.g. DeMooij andEderveen 2003 and2005) However, the empirical evidence concerning FDI and taxation in the Central-and East European Countries (CEECs) has consistently not found evidence that taxes matter for location decisions (see below).

We suggest that one possible reason for this somewhat unexpected evidence for the CEECs in the empirical FDI-taxation literature is due to the use of a flawed indicator of tax burden.

These flaws, we argue, can be remedied.

The present paper differs from previous studies by including a theoretically well founded measure of the tax burden, namely forward-looking effective tax rates derived by Devereux and Griffith (1999), rather than the statutory tax rate, which has various shortcomings in explaining FDI.

In this paper we examine first of all whether there is any substance in the belief that corporate tax rates are an important location factor for FDI from 7 home countries to 8

CEECs. 1 Secondly, we investigate whether, and to what extent, the choice of measure of the tax burden affects the tax elasticity of FDI. This is mainly motivated by the fact that there has been a gap between the conceptually ideal measure of the tax burden and its operational counterpart in empirical models in earlier studies. Thirdly, we compare the role of the corporate tax burden to that of other location determinants. Our empirical results show that the semi-elasticity of FDI with respect to taxation ranges between -3.3 and -4.6. This is above those of earlier studies in absolute terms and can partly be attributed to using a superior measure of the corporate tax burden than the statutory tax rate. The results indicate that tax-lowering strategies of CEEC governments seem to have an important impact on foreign firms' location decisions.

The remainder of the paper is structured as follows. Section 2 provides some conceptual background and a review of previous studies. Section 3 describes our data set and the variables used. Section 4 describes the empirical specification and methodology used in the estimation. Section 5 presents the estimation results and discusses their significance in relation to earlier studies. Section 6 provides a summary of our main findings.

Some Conceptual Considerations and a Review of Previous Studies

The question why a particular country succeeds in competing for inward FDI can be answered by reference to the eclectic paradigm (Dunning 1988;Markusen 1995). Based on various theories (e.g. Trade Theory, Theory of the Firm and Theory of Industrial Organisation) the eclectic paradigm avers that FDI emerges if a firm has an Ownershipadvantage (e.g. a patent) combined with a Location-advantage (e.g. low production costs; large market size) and an Internalisation-advantage (e.g. economies of interdependent activities).

The particular location factors considered by the firm in choosing between different foreign markets have to be valid proxies for host-country Location-advantages. The eclectic paradigm incorporates all possible location factors which attract FDI conditional on a firm's decision to undertake FDI. This poses a problem as it neither attributes weights to single location factors like taxation, nor does it assess their relative weights. Hence empirical applications based upon the eclectic paradigm have to rely on more or less ad hoc specifications. Recently, gravity-models have been successful in explaining bilateral tradeflows and, more recently, bilateral FDI-flows as well (e.g. [START_REF] Frenkel | A panel analysis of bilateral FDI flows to emerging economies[END_REF], Brainard 1997). As these models can easily be combined with the eclectic paradigm, empirical models explaining bilateral FDI-flows should be based on a Panel-gravity setting. It is then possible to classify Location-advantages in terms of factors which are efficiency-or market-related, supply and demand based (e.g. Mold 2003) or transition specific (Carstensen and Toubal 2004). Our variable of main interest, the corporate income tax burden, clearly falls into the efficiency and supply related categories.

As the tax burden is a factor which reduces profitability in the host-country, it should be negatively related to the inflow of FDI. In general, few studies have dealt with taxes as drivers of FDI to the CEECs. Recently, anonymous (2006) surveyed eight papers, which dealt explicitly with FDI to the CEECs, in order to ascertain their tax-rate elasticities. The outcome suggests a median tax-rate elasticity of around -1.45 (semi-elasticity). This result implies that a 1 percentage point increase in the tax rate will reduce FDI inflows by 1.45 percent. As almost all of the studies surveyed used statutory tax rates as a measure of the corporate tax burden, the result is in line with the tax-rate elasticities found by DeMooij andEderveen (2003 and2005), i.e. -1.2 and -2.05, respectively. However, we question this low tax-rate elasticity. The statutory tax rate is not an appropriate indicator of the tax burden, especially in the case of FDI, because it does not include all relevant tax codes. From a conceptual and empirical point of view, bilateral forward-looking effective average tax rates (beatrs) should be used (Devereux andGriffith 1999 and2002).

Hence the estimated tax-rate elasticities from statutory tax-rates are probably flawed and suffer from some measurement error bias. In our study, we follow Devereux and Griffith (1999) and use beatrs. We expect a higher tax-rate elasticity than the one based on statutory tax rates as the meta-analyses by DeMooij andEderveen (2003 and2005) show tax-rate elasticities of -9.3 and -5.9 respectively, when effective average tax-rates are used.. In addition, the low semi-elasticities derived by anonymous (2006) may also be explained by the following facts, which are partly transition-specific. First, since relatively little FDI is efficiency-oriented but most is horizontal FDI,, other location factors are believed to be important, too. In the case of the CEECs, location factors specific to the transition process such as hyper-inflation, privatisation, recession, exchange-rate fluctuations etc. may play an important role. Second, the more varied the mix of location factors in competing host countries, the smaller should be the influence of a single factor such as taxation. It follows that the tax burden should be more important the more similar potential host countries are with respect to other location factors, ceteris paribus. Third, MNEs may avoid taxes via profit shifting. Fourth, insofar as FDI-flows contribute to expansionary investment in the existing capital stock, it may react less than in the case of new investment and Greenfield investment in particular.

Data and Variables

Dependent Variable

The bilateral net-FDI-outflow in millions of euro from home country (i) to host country (j) for the years 1995 to 2003 (t), is used as the dependent variable (fdi). Data are mainly taken from the 'OECD International Direct Investment Statistics Yearbook' and the 'OECD Foreign Direct Investment' database. Missing values are substituted by information from Eurostat's 'New Cronos' database and from National Statistical Offices.

The fact that we use net-FDI-outflows in our study requires some explanation, as criticism has frequently been directed at this measure. In particular, some authors argue that FDIflows reflect financial flows only and not necessarily real-capital formation in the host country (see Devereux and Griffith 2002, p. 84f.). These authors conclude that there is a superior measure, namely plant, property and equipment (PPE), which reflects real capital (fixed assets).

In our view net-FDI-outflows indeed represent the annual decisions of MNEs, either to invest Greenfield or to acquire a foreign firm directly or to expand an existing affiliate or to divest in the CEECs. Net-FDI-outflows include (i) equity of the parent company in the subsidiary, (ii) net-loans between parent and affiliate, as well as (iii) reinvested earnings. In addition, local financing in the form of raising new capital, or taking loans, contributes to the affiliate's capital (vi). Empirically, using FDI-flows as the dependent variable may thus overestimate or underestimate "real investment". Overestimation may result from the fact that financial flows, which are unrelated to the activities of the affiliate, may enter the components (i), (ii) or (iii). For example, transfer pricing (i.e. overvaluing services or goods by the parent) could have this effect as it inflates debt or overvalues services or goods by the affiliate, which in turn, inflates reinvested earnings. Another source of overestimation is the capital provided by the parent company to cover losses of the affiliate abroad.

Underestimation of real capital formation results from the fact that the local financing (component iv) is excluded from FDI-flow figures.

In the case of the CEECs, over-and under-estimation effects of real capital by FDI-flows tend to exist but should be rather small. Profit shifting might play a certain role, as the CEECs are low-tax countries in general, but underestimation due to local new equity financing is probably of minor importance. 2 Thus, we are left with 'local loans' as the most serious remaining source of under-estimating real capital. Falcetti et al. (2003) reported that the ratio of total domestic credit to annual GDP was only 43.2 per cent in Central and Eastern Europe and the Baltic States, while it was 108.8 per cent in the Euro Area on average. Still in 2005, the EBRD's Transition Report concludes on "financial sector vulnerabilities in Hungary", one of the most advanced countries of the CEEC-8.

In summary, we are convinced that, due to the minor importance of local financing, net-FDIoutflows to the CEECs are a reasonable proxy for the annual real capital formation of affiliates abroad. The independent variables have to be valid proxies for host-country related Locationadvantages. We base our choice of independent variables on the findings of some recent and widely cited studies which, however, use a somewhat different operationalisation. We group the location advantages as follows: market-related variables: host market size, distance, common border, efficiency-oriented location factors: unit labour costs, effective tax rate, transition-specific location factors: inflation, privatisation, political risk.

Independent Variables

Moreover, as we use a gravity setting we also include home country size.

The larger a home country, the greater the potential for FDI outflows ceteris paribus, which suggests a positive coefficient on home country size (gdphome). With a larger market, there is a greater likelihood that MNEs will be able to recoup the costs of their FDI [START_REF] Navaretti | Multinational firms in the world economy[END_REF]. We therefore expect a positive sign of the estimated coefficient of host market size (gdphost).

While a larger distance (dist) between home and host country may encourage FDI due to an Internalisation-advantage it may also discourage FDI due to the lack of market know-how, higher communications and information costs and differences in culture and institutions (Buch and Lipponer 2004). Hence, from a theoretical point of view the sign on the distance coefficient is ambiguous a priori (see Markusen and Maskus 2002). Here, we expect a negative sign as intra-firm trade flows between parent and affiliate tend to be high in the case of vertical FDI (VFDI) where the costs of re-exporting are an important determinant of overall cost. Secondly, even with horizontal FDI (HFDI), distance matters. If affiliates are relatively new, as is often the case in the CEECs they typically depend on headquarter services and intermediate inputs supplied by the parent. Thirdly, the negative impact of Markusen and Maskus (2002), who discriminate between various theories of FDI.

As explained above the average tax rate is the relevant measure of tax burden for discrete choices like the location decision of MNEs. Moreover, for international investment decisions beatrs are the relevant location factor to reflect the tax component of the location decision of MNEs. As taxes are a cost we expect a negative sign on the estimated coefficients.

Privatisation revenues on an annual basis (privrev) are used to reflect progress in privatisation. We expect a positive sign on the estimated coefficient, as a higher degree of privatisation implies more investment opportunities for foreign investors arising from firstmover advantage, competition effects etc. In our view this variable is a better measure of privatisation progress than the index of the private-sector's share in the total economy, as published by the EBRD, which is sometimes used. This index exhibits little variation over time as it varies, if at all, only in steps of 5 percentage points, so that it may underestimate the actual progress of privatisation.

Our labour cost variable is a measure of real unit labour costs in a common currency (ulc).

According to public opinion, low labour costs are among the most important determinants of inward FDI in the CEEC-8. This reasoning is in line with evidence reported in Hunya (2004) inter alia, who suggests that after the first wave of vertical FDI in the CEECs, FDI has shifted "further East" within, and across, the CEECs due to increasing labour costs. In general, high labour costs in the host country should exert a negative impact on FDI. Should the coefficient carry a positive sign, this could be an indication of an omitted variable problem, as in this case labour costs may capture effects of an increasing level of skill in the host country.

In countries in transition, property rights may be insecure and political stability may be low.

Hence, political risk may play a role as a determinant of FDI, too. As Navaretti and Venables (2004, p. 6) argue "political risk and instability seems to be an important deterrent to inward FDI". Political instability could seriously deteriorate the investment climate of a CEE host country and thus cause losses for foreign investors. We expect a negative relationship between political risk and FDI but a positive coefficient due to the measurement of political risk ranging from 0 (highest risk) to 25 (lowest risk).

Inflation (pp) is included as a proxy for macroeconomic instability, which transition countries may be confronted with (Buch and Lipponer 2004). We expect a negative sign on the estimated coefficients.

A common-border dummy-variable is considered in addition to dist, as centre-to-centre distance may overstate the effective distance between home and host countries (Head 2003).

We expect a positive sign on the estimated coefficient.

Tariffs (tar) are defined as the ratio of tariff revenues over imports of goods and services.

From a theoretical point of view the sign of the coefficient on this variable is ambiguous a priori depending on the underlying motive for FDI. If the observed FDI is mainly HFDI, the market imperfection theory of FDI suggests a positive sign. In this case HFDI is observed due to an Internalisation-advantage ("tariff-jumping" FDI). If, on the other hand, FDI is mainly VFDI, theory suggests a negative sign (e.g. [START_REF] Frenkel | A panel analysis of bilateral FDI flows to emerging economies[END_REF][START_REF] Navaretti | Multinational firms in the world economy[END_REF]). In the case of VFDI high trade costs can be seen as a location disadvantage, which deters FDI.

Table 1 summarises the discussion of individual location factors.

[Table 1 here]

Descriptive data analysis

Our data set constitutes a balanced panel of bilateral net-FDI-outflows for seven home countries (i), eight host countries (j) and nine years (t), resulting in 504 observations. However, as bilateral net-FDI-outflows can be negative, and the log of FDI is used as the dependent variable, we are obliged to drop 45 observations (about 9 percent of our data set). The search for unsystematic outliers 3 in the dependent and independent variables via boxplots and added variable plots pinpoints four data points as potential outliers which are also dropped from the analysis. Table 2 shows the descriptive statistics for our dataset and reveals that the between variability is higher than the within variability. Our variable of interest, the beatr, has an overall mean of 34.8 percent and ranges between 16 percent (Austria -Bulgaria in 2002) and 56 percent (Italy -Czech Republic in 1995). The broad range is not only due to large differences in the statutory tax rates of the home and the host countries but also due to large differences in the withholding tax rates on dividends and interests as well as in allowances.

[Table 2 here]

Empirical Specification and Methodology

The basic panel-gravity-model includes the logarithm of home country and host market size, distance, country-pair specific effects as well as time dummies [START_REF] Cheng | Controlling for Heterogeneity in Gravity Models of Trade and Integration, The Federal Reserve Bank of St. Louis Working Paper Series[END_REF]Egger and Pfaffermayr 2003). 4 The estimated model is a generalised panel-gravity model with various location factors added. It is shown in equation (1).

ijt ij t jt ij ijt ij jt it ijt e W b Z b X b DIST b Y b Y b FDI + + + + + + + + = 6 5 4 3 2 1 ln ln ln ln (1)
where: lnFDI ijt is the log of net-FDI-outflow from home country i to host country j at time t (lnfdi); lnY it is the log of GDP in country i at time t and the same for lnY jt for country j (lngdphome and lngdphost); lnDIST ij is the log of the distance between countries i and j (lndist); X ijt are location factors which vary between country-pairs and over time (e.g. beatr); Z ij are location factors which vary over country-pairs only (i.e. combord); W jt are location factors which vary over time and over host countries (e.g. pp); J t are time dummies (TD); 3 We define unsystematic outliers as data points which do not represent heterogeneity between the host countries. For example, using box plots the ulc for Slovenia are shown to be extreme values throughout the sample period. Hence, these data represent heterogeneity between the host countries which we exploit in our analysis. 4 These variables may be called "gravity-specific". We regard the country-pair specific effects as random for two reasons. First, Hausman-tests 5 on fixed versus random effects show that the random effects assumptions cannot be rejected.

Hence, using the random effects estimator results in more efficient estimates than the fixed effects estimator, which can be inefficient as the cross-section dimension is large relative to the time dimension (Pesaran et al. 1998). Using the random effects approach is in line with several recent studies dealing with FDI, trade or capital flows to CEECs (e.g. Clausing and Dorobantu 2005;Dawson and Hubbard 2004;Bevan and Estrin 2004;Gibson and Tsakalotos 2004) and it allows estimating the impact of time fixed variables (i.e. dist and combord) on FDI-flows. Second, from a more substantive point of view, the random effects approach is relevant here as we are concerned with the decision of MNEs between various host countries. In this decision, differences between country-pairs matter, which are exploited by the random effects estimator. Concerning time effects we consider these to be fixed. They account inter alia for the business cycle, for common shocks and common trends (Egger and Pfaffermayr 2003).

Our estimation strategy is based on two pillars. We first estimate equation (1) with the gravity-specific variables only and include the beatr. Then we introduce additional location factors stepwise to this basic specification ("pillar 1" strategy). Second, we apply a general to specific strategy, starting with the most general model (1) and test down until a specification is reached with all significant 6 variables included ("pillar 2" strategy). This procedure should reduce the probability of an omitted variable bias and it provides information about the robustness of the tax-rate elasticity. An additional robustness and stability analysis (see below) is carried out via the jackknife procedure with respect to host 5 We perform two types of Hausman-tests. First, if no serial correlation and heteroskedasticity seem to be present and if the other requirements of the original Hausman-test are fulfilled (e.g. the difference between fixed effects and random effects variance matrices is invertible) we use the original Hausman-test. Second, in case of nonspherical errors or a non-positive definite difference in the fixed effects and random effects variance matrices we follow Wooldridge (2002, p. 290ff.) 2004) in the residual error term. Furthermore, we inspect standard errors from different types of robust covariance estimates (non-robust, White-robust; cluster-robust). In case statistical tests do not show the presence of non-spherical residuals but the significance of our estimates changes when more robust standard errors are used, we also present these results for comparison reasons (cf. models 2b and 4b below).

Results

Tax-rate elasticities using effective tax rates

Table 3 shows the results of our "pillar 1" strategy. The coefficients on the gravity-specific variables are always significant with the expected signs, with the exception of home-country size. The magnitude of the coefficients on distance and host-market size is reasonable as they are in line with the theoretical prediction of the gravity model and with empirical evidence for gravity models explaining international trade flows (Head 2003;Leamer and Levinsohn 1995). In some models, the relatively low and statistically insignificant coefficient on homecountry size is not unexpected as relatively small countries (Austria and The Netherlands) are among the main source countries of FDI to CEECs.

The coefficient on beatr is always statistically significant and negative, and falls in the range -3.3 and -4.6 (-5.7 excluding time dummies). Concerning other location factors considered, only privrev and ulc have a statistically significant impact on net-FDI-outflows. All other location factors carry the expected sign and the magnitude of their coefficients seems to be economically meaningful, but they are statistically insignificant. 7 The positive sign on tar does suggest the tariff jumping motive for FDI. But the insignificance of tar is plausible as 7 For example, the coefficient on combord implies that sharing a border increases net-FDI-outflows by about 67%, a typical value for gravity models explaining international trade-flows (Head 2003). The insignificant coefficient on inflation points to the fact that inflation has decreased considerably in the CEEC-8 compared to earlier periods of transition. Studies including earlier years and countries in macroeconomic turbulence (e.g. Edmiston et al. 2003) reveal significant negative effects of inflation on FDI-flows. Political stability (risk) does not seem to be a relevant location factor within the CEEC-8. This is in marked contrast to studies using data from the beginning of the transformation process till the end of the 1990ies (e.g. Carstensen and Toubal 2004;[START_REF] Frenkel | A panel analysis of bilateral FDI flows to emerging economies[END_REF]). Furthermore, statistical tests show that time dummies are mostly jointly significant and that the random effects assumption can not be rejected.

[Table 3 here] Turning to our "pillar 2" strategy, the results are reported in table 4. Model 8 is our most general model including all location factors as well as time dummies. The results are not very different from those of our "pillar 1" strategy: beatr, privrev and ulc are statistically significant with the expected signs, while all the other variables have the expected signs but are statistically insignificant. Moreover the magnitude of the estimates is in line with those of our "pillar 1" strategy.

Dropping insignificant variables step-by-step beginning with the most insignificant variable and controlling for possible multi-collinearity effects we finally end up with model 9. This includes the gravity-specific variables as well as beatr, ulc (both efficiency-related) and privrev (transition specific). Again, statistical tests show that the random effects specification is valid. Further tests suggest that model 9 has satisfactory properties from a statistical point of view. Studentised residuals do not show the presence of outliers using a cut off-level of +/-3.5 (Egger and Pfaffermayr 2003), the highest variance inflation factor of 3.95 implies 13 that multi-collinearity should not be a problem in model 9 and a Reset-test suggests that our linear specification is sufficient. Finally a regression based Hausman-test for endogeneity of our privatisation variable in model 9, using the index of the private-sector share in the total economy as well as dummies for the method of privatisation as instruments (see Carstensen and Toubal 2004 and below) does not reject the null hypothesis of exogeneity (p-value = 0.38).

[Table 4 here] The tax-rate elasticity in model 9 is -4.4 8 implying that a 1 percentage-point decrease in the effective tax rate increases net-FDI-outflows, ceteris paribus, by about 4.4 per cent, which, evaluated at the mean net-FDI-outflow of € 193.5 m., amounts to € 8.5 m. on average. Thus, in the past, tax-lowering strategies of governments in the CEECs have had an important effect on the allocation of FDI among the CEEC-8.

The derived semi-elasticity is higher than the median value concerning CEECs reported above and it is lower than those reported by DeMooij andEderveen (2003 and2005). As the study by Carstensen and Toubal (2004) partly covers the same countries as well as a similar time period, it is convenient to compare our results to those of their study. Their study is also based on bilateral FDI data. The comparable median value of their semi-elasticities is -1.6 and is thus lower than ours in absolute value. It must be kept in mind, however, that besides other differences to our study Carstensen and Toubal base their analysis on statutory tax rates.

To conclude the discussion on efficiency-related variables we take a closer look at the impact of ulc on net-FDI-outflows. Model 9 shows that a one percentage-point increase in ulc reduces net-FDI-outflows by about 3.1 percent. Comparing this estimate with those of other studies is notoriously difficult, as almost every study uses an alternative definition of 8 The mean value of all estimates is about -4.0. Lansbury et al. (1994) use unit labour costs in a host country relative to other potential hosts in Central Europe and find that is has a significant and negative impact on FDI. Inclusion of relative wage and relative productivity measures as in Holland and Pain (1998) appears to leave only the relative wage variable significant. Productivity differentials across host countries do not appear significant. According to the authors this implies "that considerations of comparative factor costs across countries influence some investment decisions" (p. 16). Clausing and Dorobantu (2005) measure labour costs by the average compensation rate in the host country and also find a negative effect throughout. Some studies (e.g., Benassy-Quere et al., 2005, p. 590) even find a positive relationship between FDI and labour costs, which is most likely attributable to an omitted variable problem. The authors themselves state, that "unit labour costs are positively related to the quality of labour." (ibidem, p. 589) Hence labour costs include the impact different skill levels may exert upon FDI-flows.

Concerning the privatisation process, our analysis shows a significant and positive impact of privrev throughout. At first sight, the coefficient on privrev, although significant and with the correct sign, seems very low; ceteris paribus, net-FDI-outflows increase by about 0.03% if privatisation revenues increase by one million euro. Yet, given that foreign MNEs have been active in the CEEC-8 for some time now and that privatisation programmes are far advanced, the share of FDI unrelated to privatisation processes per se should have increased.

This is what our result indicates.

Other studies use the EBRD's private-sector share in total economy (see Lansbury et al. 1996, Holland andPain 1998;Carstensen and Toubal 2004) and/or the method of privatisation (Holland and Pain 1998;Carstensen and Toubal 2004) to capture the effect of the privatisation process on FDI. Using the private sector share often results in insignificant coefficients, partly because the share variable does not vary much over time. In Carstensen and Toubal (2004) and Holland and Pain (1998) the "method of privatisation" (i.e. vouchers vs. other methods) turns out to have a significant effect on FDI inflows. Holland and Pain conclude that "countries with a program of direct privatisation through cash sales have

Relative importance of effective tax rates as a location factor

Table 5 shows the Beta coefficients corresponding to model 9. 9 The gravity-specific variables are the most important determinants of net-FDI-outflows. This result is in line with many other studies (e.g. Mold 2003). Taxation and privatisation are equally important location factors, while unit labour costs are slightly less important. These results imply that the role of taxes should not be over-emphasised relative to that of other location determinants.

An alternative measure of the corporate income tax burden

In order to check our argument that the appropriate tax rate is the effective tax rate we replace the beatr by the statutory tax rate in model 9. Results for model 10 (reported in table 5) show the expected substantial drop of the semi-elasticity to about -2.4, although this estimate falls short of statistical significance at the 5% level. This implies that the relatively low value of the semi-elasticity derived in our meta-analysis is partly due to the use of statutory tax rates in empirical studies. This result is also important with regard to evaluating the effectiveness of governments' tax cuts, which might have had a larger effect on inward FDI than earlier studies have revealed.

[Table 5 here] Robustness and stability analysis 9 These are calculated by applying the usual formula for standardised coefficients on the random effects estimates using the overall standard deviations for the random effects transformed variables of model 9. We check the robustness of our preferred specification in model 9 against the impact of possible cross-section outliers by dropping host countries stepwise (e.g. [START_REF] Winner | Has Tax Competition Emerged in OECD countries? Evidence from Panel Data[END_REF]. Table 6 reports the resulting minimum and maximum values of the coefficient estimates and the coefficient derived from our preferred specification (model 9) as well as the country excluded. The results are robust with respect to dropping countries as no coefficient changes sign and none becomes insignificant at the 10% level with the exception of the coefficient on ulc when Slovenia is excluded (not shown). Hence, the relatively low FDI-flows to Slovenia may be partly due to the high unit labour costs when compared to other host countries in our sample.

[Table 6 here] The stability of the coefficients on beatr, ulc and privrev is checked by combining these variables with a dummy variable for the years 2000-2003. The year 2000 has been chosen as some host countries (notably Romania and the Slovak Republic) started to reduce their beatr since 2000. Table 7 (models 11 to 13) shows that the semi-elasticities for beatr and ulc for the period 2000-2003 are not significantly different from that of previous years, but that the importance of privatisation as a driver of FDI is significantly lower from 2000 onwards. This last result seems to be plausible as the privatisation process levelled off in many CEECs around 2000 (EBRD transition report, various issues). In contrast, the sensitivity of FDI with respect to taxation and unit labour costs has not changed during this period.

[Table 7 here] 6. Summary The aim of this paper was to test the hypothesis that a high corporate tax burden acts as a deterrent to FDI-flows, since it exerts a negative effect on the profitability of investments.

We suggest that using the statutory tax rate in previous studies might blur the effects of the tax burden on FDI and lead to questionable results. Therefore, we use the bilateral effective average tax rates to explaining net-FDI-outflows from the 7 most important home countries to the CEEC-8. Referring to the eclectic paradigm as a conceptual basis, we find in a panelgravity setting that FDI is positively related to both source country and host-market size as well as to progress in privatisation. Also, FDI is inversely related to the distance separating home and host countries, to the corporate tax burden and to unit labour costs. Concerning the role of taxes three points are worth noting:

First, the derived tax-elasticity is robust across various specifications and is greater in absolute value than those reported in earlier studies on the CEECs, pointing to a greater importance of tax policy for company location decisions than previously acknowledged.

Second, the differences in the absolute value of the semi-elasticities when compared to earlier studies are clearly partly due to the use of beatrs. The derived semi-elasticity after replacing the beatr by statrate in our study is, indeed, substantially lower.

Third, the relative importance of the corporate tax rate as a determinant of FDI must not be over-emphasised as our results (Beta-coefficients) reveal that at least during the period 1995-2003 the tax burden had no exceptional influence on net-FDI-outflows to the CEEC-8 when compared to other determinants.

While this study is a step towards a greater understanding of FDI-flows to the CEECs, there are several limitations to our analysis; in particular, we are conscious of the exclusion of location factors such as the size and quality of public infrastructure. This omission is due to the lack of meaningful data. Moreover, special investment incentives (e.g. regional, R&D) are not included, as many different incentives have been granted by CEEC governments throughout the sample period of nine years. The choice of incentives to be included in the beatr would be arbitrary. Finally, many CEECs have reduced their special investment We suggest that one possible reason for this somewhat unexpected evidence for the CEECs in the empirical FDI-taxation literature is due to the use of a flawed indicator of tax burden.

These flaws, we argue, can be remedied.

The present paper differs from previous studies by including a theoretically well founded measure of the tax burden, namely forward-looking effective tax rates derived by Devereux and Griffith (1999), rather than the statutory tax rate, which has various shortcomings in explaining FDI.

In this paper we examine first of all whether there is any substance in the belief that corporate tax rates are an important location factor for FDI from 7 home countries to 8

CEECs. 1 Secondly, we investigate whether, and to what extent, the choice of measure of the tax burden affects the tax elasticity of FDI. This is mainly motivated by the fact that there has been a gap between the conceptually ideal measure of the tax burden and its operational counterpart in empirical models in earlier studies. Thirdly, we compare the role of the corporate tax burden to that of other location determinants. Our empirical results show that the semi-elasticity of FDI with respect to taxation is about -4.3. This is above those of earlier studies in absolute terms and can partly be attributed to using a superior measure of the corporate tax burden than the statutory tax rate. The results indicate that tax-lowering strategies of CEEC governments seem to have an important impact on foreign firms' location decisions.

The remainder of the paper is structured as follows. Section 2 provides some conceptual background and a review of previous studies. Section 3 describes our data set and the variables used. Section 4 describes the empirical specification and methodology used in the estimation. Section 5 presents the estimation results and discusses their significance in relation to earlier studies. Section 6 provides a summary of our main findings.

Some Conceptual Considerations and a Review of Previous Studies

The question why a particular country succeeds in competing for inward FDI can be answered by reference to the eclectic paradigm (Dunning 1988;Markusen 1995). With Recently gravity-models have been used to explain not only bilateral trade-flows but also bilateral FDI-flows (e.g. Brainard 1997). These models can easily be combined with the eclectic paradigm. Empirical models explaining bilateral FDI-flows should be based on a Panel-gravity setting.

Location-advantages can be classified in terms of factors which are efficiency--or marketrelated, supply and demand based (e.g. Mold 2003) or transition specific (Carstensen and Toubal 2004). Our variable of main interest, the corporate income tax burden, clearly falls into the efficiency and supply related categories.

As the tax burden is a factor which reduces profitability in the host-country, it should be negatively related to the inflow of FDI. 2 In general, few studies have dealt with taxes as drivers of FDI to the CEECs. Recently, anonymous (2006a) surveyed eight papers, which dealt explicitly with FDI to the CEECs, in order to ascertain their tax-rate elasticities. The outcome suggests a median tax-rate elasticity of around -1.45 (semi-elasticity). This result implies that a 1 percentage point decrease in the tax rate will increase FDI inflows by 1.45 percent. As almost all of the studies surveyed used statutory tax rates as a measure of the corporate tax burden, the result is in line with the tax-rate elasticities found by DeMooij andEderveen (2003 and2005), i.e. -1.2 and -2.05, respectively. However, we question this low tax-rate elasticity. The statutory tax rate is not an appropriate indicator of the tax burden, especially in the case of FDI, because it does not include all relevant tax codes. From a conceptual and empirical point of view, bilateral forward-looking effective average tax rates (beatrs) should be used (Devereux andGriffith 1999 and2002).

2 Having described the general relationship between FDI and lower taxes, the story could, however, be different on a more disaggregated level. We are grateful to the referee for raising this problem. First, footloose manufacturing sectors may react differently to service sectors. Second, different tax incentives etc. may apply on the sectoral level. Recently this issue was analysed empirically by [START_REF] Stöwhase | Tax-Rate Differentials and Sector-Specific Foreign Direct Investment: Empirical Evidence from the EU[END_REF]. He shows that the tax sensitivity of FDI depends crucially on the sector receiving the capital flow. This raises the possibility of an over-or underestimation of sectoral tax elasticities on the aggregate level. Given the difficulties of obtaining appropriate data at a reasonable scale at Hence the estimated tax-rate elasticities from statutory tax-rates are probably flawed. In our study, we follow Devereux and Griffith (1999) and use beatrs. We expect a higher tax-rate elasticity than the one based on statutory tax rates as the meta-analyses by DeMooij andEderveen (2003 and2005) show tax-rate elasticities of -9.3 and -5.9 respectively, when effective average tax-rates are used.

In addition, the negative but low median semi-elasticity derived by anonymous (2006a) may also be explained inter alia by the following facts, which are partly transition-specific. First, since relatively little FDI is efficiency-oriented but most is horizontal FDI other location factors are believed to be important, too. In the case of the CEECs, location factors specific to the transition process such as hyper-inflation, privatisation, recession, etc. may play an important role. Second, the more varied the mix of location factors in competing host countries, the smaller should be the influence of a single factor such as taxation. It follows that the tax burden should be more important the more similar potential host countries are with respect to other location factors, ceteris paribus. Third, MNEs may avoid taxes via profit shifting. Fourth, insofar as FDI-flows contribute to expansionary investment in the existing capital stock, it may react less than in the case of new investment and Greenfield investment in particular.

Data and Variables

Dependent Variable

The bilateral net-FDI-outflow in millions of euro from home country (i) to host country (j) for the years 1995 to 2003 (t), is used as the dependent variable (fdi). Data are mainly taken from the 'OECD International Direct Investment Statistics Yearbook' and the 'OECD Foreign Direct Investment' database. Missing values are substituted by information from Eurostat's 'New Cronos' database and from National Statistical Offices. present, we have not followed this strategy. As more data will become available in the future, sectoral analyses will show the size of the bias incurred. The fact that we use net-FDI-outflows in our study requires some explanation, as criticism has frequently been directed at this measure. In particular, some authors argue that FDIflows reflect financial flows only and not necessarily real-capital formation in the host country (see Devereux and Griffith 2002, p. 84f.). These authors conclude that there is a superior measure, namely plant, property and equipment (PPE), which reflects real capital (fixed assets).

In our view net-FDI-outflows indeed represent the annual decisions of MNEs, either to invest Greenfield or to acquire a foreign firm directly or to expand an existing affiliate or to divest in the CEECs. Net-FDI-outflows include (i) equity of the parent company in the subsidiary, (ii) net-loans between parent and affiliate, as well as (iii) reinvested earnings. In addition, local financing in the form of raising new capital, or taking loans, contributes to the affiliate's capital (iv). Empirically, using FDI-flows as the dependent variable may thus overestimate or underestimate "real investment". Overestimation may result from the fact that financial flows, which are unrelated to investment activities of the affiliate, may enter the components (i), (ii) or (iii). For example, transfer pricing via overvaluing services or goods by the affiliate inflates reinvested earnings. Another source of overestimation is the capital provided by the parent company to cover losses of the affiliate abroad.

Underestimation of real capital formation results from the fact that the local financing (component iv) is excluded from FDI-flow figures.

In the case of the CEECs, over-and under-estimation effects of real capital by FDI-flows tend to exist but should be rather small. Profit shifting via transfer pricing might play a certain role, as the CEECs are low-tax countries in general, but underestimation due to local new equity financing is probably of minor importance. 3Thus, we are left with 'local loans' as the most serious remaining source of under-estimating real capital. Falcetti et al. (2003) reported that the ratio of total domestic credit to annual GDP was only 43.2 per cent in Central and Eastern Europe and the Baltic States, while it was In summary, we are convinced that, due to the minor importance of local financing, net-FDIoutflow to the CEECs is a reasonable proxy for the annual real capital formation of affiliates abroad.

Independent Variables

The independent variables have to be valid proxies for host-country related Locationadvantages. We base our choice of independent variables on the findings of some recent and widely cited studies which, however, use a somewhat different operationalisation. We group the Location-advantages as follows: market-related location factor: host market size efficiency-related location factors: unit labour costs, effective tax rate, distance, common border transition-specific location factors: inflation, privatisation, political risk.

Moreover, as we use a gravity setting we also include home country size as another marketrelated variable.

The larger a home country, the greater the potential for FDI outflows ceteris paribus, which suggests a positive coefficient on home country size (gdphome). With a larger market, there is a greater likelihood that MNEs will be able to recoup the costs of their FDI (Barba [START_REF] Navaretti | Multinational firms in the world economy[END_REF]. We therefore expect a positive sign of the estimated coefficient of host market size (gdphost).

While a larger distance (dist) between home and host country may encourage FDI due to an

Internalisation-advantage it may also discourage FDI due to the lack of market know-how, F o r P e e r R e v i e w 7 higher communication and information costs and differences in culture and institutions (Buch and Lipponer 2004). Hence, from a theoretical point of view the sign on the distance coefficient is ambiguous a priori (see Markusen and Maskus 2002). Here, we expect a negative sign as intra-firm trade flows between parent and affiliate tend to be high in the case of vertical FDI (VFDI) where the costs of re-exporting are an important determinant of overall cost. Secondly, large distance will impact negatively even on horizontal FDI (HFDI).

. If affiliates are relatively new, as is often the case in the CEECs they typically depend on headquarter services and intermediate inputs supplied by the parent. Thirdly, the negative impact of distance on FDI has been shown by many empirical studies, notably by Markusen and Maskus (2002), who discriminate between various theories of FDI.

As outlined above the average tax rate is the relevant measure of tax burden for discrete choices like the location decision of MNEs. Moreover, for international investment decisions beatrs are the relevant location factors. As taxes are a cost we expect a negative sign on the estimated coefficients.

Privatisation revenues on an annual basis (privrev) are used to reflect progress in privatisation. We expect a positive sign on the estimated coefficient, as a higher degree of privatisation implies more investment opportunities for foreign investors arising from firstmover advantages, competition effects etc. In our view this variable is a better measure of privatisation progress than the index of the private-sector's share in the total economy, as published by the EBRD, which is sometimes used. This index exhibits little variation over time as it varies, if at all, only in steps of 5 percentage points, so that it may underestimate the actual progress of privatisation.

Following anonymous (2006b) our labour cost variable is a measure of real unit labour costs in a common currency (ulc). According to public opinion, low labour costs are among the most important determinants of inward FDI in the CEEC-8. This reasoning is in line with evidence reported in Hunya (2004), who suggests that after the first wave of VFDI in the CEECs, FDI has shifted "further East" within and across the CEECs due to increasing labour In countries in transition, property rights may be insecure and political stability may be low.

Hence, political risk may play a role as a determinant of FDI. As Barba Navaretti and Venables (2004, p. 6) argue "political risk and instability seems to be an important deterrent to inward FDI". Political instability could seriously deteriorate the investment climate of a CEEC and thus cause losses for foreign investors. We expect a negative relationship between political risk and FDI but a positive coefficient due to the measurement of political risk ranging from 0 (highest risk) to 25 (lowest risk).

Inflation (pp) is included as a proxy for macroeconomic instability, which may occur especially in transition countries (Buch and Lipponer 2004). We expect a negative sign on the estimated coefficients.

A common-border dummy-variable is considered in addition to dist, as centre-to-centre distance may overstate the effective distance between home and host countries (Head 2003).

We expect a positive sign on the estimated coefficient.

Tariffs (tar) are defined as the ratio of tariff revenues over imports of goods and services.

From a theoretical point of view the sign of the coefficient on this variable is ambiguous a priori depending on the underlying motive for FDI. If the observed FDI is mainly HFDI, the market imperfection theory of FDI suggests a positive sign. In this case HFDI is observed due to an Internalisation-advantage ("tariff-jumping" FDI). If, on the other hand, FDI is mainly VFDI, theory suggests a negative sign (e.g. [START_REF] Barba Navaretti | Multinational firms in the world economy[END_REF]). In the case of VFDI high trade costs can be seen as a Location-disadvantage, which deters FDI.

Descriptive data analysis

Our data set constitutes a balanced panel of bilateral net-FDI-outflows for seven home countries (i), eight host countries (CEEC-8) (j) and nine years (t), resulting in 504 observations. However, as bilateral net-FDI-outflows can be negative, and the log of FDI is used as the dependent variable, we are obliged to drop 45 observations (about 9 percent of our data set). The search for unsystematic outliers 5 in the dependent and independent variables via box-plots and added variable plots pinpoints four data points as potential outliers which are also dropped from the analysis. Table 2 shows the descriptive statistics for our dataset and reveals that the between variability is higher than the within variability. Our variable of interest, the beatr, has an overall mean of 34.8 percent and ranges between 16 percent (Austria -Bulgaria in 2002) and 56 percent (Italy -Czech Republic in 1995). The broad range is not only due to large differences in the statutory tax rates of the home and the host countries but also due to large differences in the withholding tax rates on dividends and interests as well as in allowances. This again is a strong hint of the importance to exploit the considerable heterogeneity across host countries and in bilateral relationships to their home countries.

[Table 2 here] Table 3 shows the correlation matrix of the various location factors used in the empirical study. No correlation coefficient is above 0.8 in absolute value, which is often used as a threshold value. As low pairwise correlation coefficients are not sufficient for concluding that the variables are not highly multicollinear we provide further evidence using variance inflation factors in the empirical analysis (e.g. [START_REF] Kennedy | A Guide to Econometrics[END_REF]). 5 We define unsystematic outliers as data points which do not represent heterogeneity between the host countries. For example, using box plots the ulc for Slovenia are shown to be extreme values throughout the sample period. Hence, these data represent heterogeneity between the host countries which we exploit in our analysis. 3 here]

Empirical Specification and Methodology

The basic panel-gravity-model includes the logarithm of home country and host market size, distance, country-pair specific effects as well as time dummies (Egger and Pfaffermayr 2003). 6 The model applied is a generalised panel-gravity model with various location factors added. It is shown in equation ( 1).

ijt ij t jt ij ijt ij jt it ijt e W b Z b X b DIST b Y b Y b FDI + + + + + + + + = 6 5 4 3 2 1 ln ln ln ln (1)
where: lnFDI ijt is the log of net-FDI-outflow from home country i to host country j at time t (lnfdi); lnY it is the log of GDP in country i at time t and the same for lnY jt for country j (lngdphome and lngdphost); lnDIST ij is the log of the distance between countries i and j (lndist); X ijt are location factors which vary between country-pairs and over time (e.g. beatr); Z ij are location factors which vary over country-pairs only (i.e. combord); W jt are location factors which vary over time and over host countries (e.g. pp); t are time dummies (TD); ij are country-pair-specific effects; e ijt is the remainder error term.

We regard the country-pair specific effects as random for two reasons. First, Hausman-tests 7 on fixed versus random effects show that the random effects assumptions cannot be rejected.

Hence, using the random effects estimator results in more efficient estimates than the fixed effects estimator, which can be highly inefficient if the cross-section dimension is large relative to the time dimension (Pesaran et al. 1998). Using the random effects approach is in line with several recent studies dealing with FDI, trade or capital flows to CEECs (e.g. Clausing and Dorobantu 2005; Dawson and Hubbard 2004; Bevan and Estrin 2004; Gibson 6 These variables may be called "gravity-specific". 7 We perform two types of Hausman-tests. First, if no serial correlation and heteroskedasticity seem to be present and if the other requirements of the original Hausman-test are fulfilled (e.g. the difference between fixed effects and random effects variance matrices is invertible) we use the original Hausman-test. Second, in case of nonspherical errors or a non-positive definite difference in the fixed effects and random effects variance matrices we perform a regression based Hausman-test with cluster robust standard errors (see Wooldridge, 2002). ) and it allows estimating the impact of time fixed variables (i.e. dist and combord) on FDI-flows. Second, from a more substantive point of view, the random effects approach is relevant here as we are concerned with the decision of MNEs between various host countries. In this decision, differences between country-pairs matter, which are exploited by the random effects estimator. Concerning time effects we consider these to be fixed as they are likely to be correlated with gdphome and gdphost as time dummies account inter alia for the business cycle and for common shocks (Egger and Pfaffermayr 2003).

Our estimation strategy is based on a general to specific approach. We start with the most general model (1) and test down until a specification is reached with only (at conventional levels) significant variables included. This procedure should reduce the probability of an omitted variable bias and it provides information about the robustness of the tax-rate elasticity. 8 An additional robustness and stability analysis (see below) is carried out via the jackknife procedure with respect to host countries included. Furthermore we explore the stability of the coefficient on beatr, ulc and privrev over time. We always test for the presence of serial correlation in linear panel data models ("Wooldridge-test", Wooldridge 2002) and heteroskedasticity (LM-test, Verbeek 2004) in the remainder error term. In all cases the Wooldridge-test does not reject the null hypothesis. In cases heteroscedasticity is implied by the LM-test heteroscedasticity-robust standard-errors are used.

Results

Table 3 shows the results of our estimation strategy. Model 1 is our most general model including all location factors as well as time dummies. All coefficients carry the expected sign. The core gravity variables as well as beatr, privrev and ulc are highly statistically significant. Combord and pp are marginally insignificant at the 10 percent significance level (p-values of 0.102 and 0.11, respectively) using two-sided t-tests. Applying one-sided tests with the alternative hypothesis specified according to the expected sign of the coefficient (cf. ) these two variables are significant at the 10 percent level. Risk and tar are highly insignificant even in the case of a one-sided test.

Dropping these two highly insignificant variables step-by-step beginning with the most insignificant variable (tar) we finally end up with model 2. This includes the gravity-specific variables as well as beatr, ulc, combord (efficiency-related), privrev and pp (transition specific). Pp is again marginally insignificant at the 10 percent significance level, but due to its p-value of 0.102, which implies statistical significance in case of a one-sided test, we decide to keep this variable in our preferred specification. 9

The Hausman-Wooldridge-test implies that the random effects specification cannot be rejected. Further tests suggest that model 2 has satisfactory properties from a statistical point of view. Studentised residuals do not show the presence of outliers using a cut-off level of +/-3.5 (Egger and Pfaffermayr 2003), the highest variance inflation factor (VIF) of 5.40 implies that multicollinearity should not be a problem in model 2 and a Reset-test suggests that our linear specification is sufficient. Finally, a regression based Hausman-test for endogeneity of privrev in model 2, using the EBRD's index of the private-sector share in the total economy as well as dummies for the method of privatisation as instruments (see Carstensen and Toubal 2004 and below) does not reject the null hypothesis of exogeneity.

The magnitudes of the coefficients on distance and host-market size are reasonable as they are in line with the theoretical prediction of the gravity model and with empirical evidence for gravity models explaining international trade flows (Head 2003;Leamer and Levinsohn 1995). The comparably low coefficient on home-country size is not unexpected as relatively small countries (Austria and The Netherlands) are among the main source countries of FDI to CEECs. Moreover, the coefficient on combord of about 0.68 implies that sharing a border increases net-FDI-outflows by about 97%, a value in line with those usually found for gravity models explaining international trade-flows (see Head 2003). 8 We also used a specific to general approach to asses the robustness of the tax-rate elasticity with respect to single location factors additionally included in the empirical model. The results show the robustness of our estimate in this respect but are not reported here. For details see anonymous (2005). 9 Dropping pp does not change the results of our analysis. Details can be found in anonymous (2005). The coefficient on beatr is statistically significant and negative. The estimate of -4.30 signals a substantially larger impact of corporate income taxes on FDI than earlier studies imply. For example, a median semi-elasticity of about -1.6 can be deduced from the study by Carstensen and Toubal (2004), which partly covers the same countries as well as a similar time period. This estimate is thus substantially lower than ours in absolute value. However, it must be kept in mind, that besides other differences to our study Carstensen and Toubal base their analysis on statutory tax rates.

The tax-rate elasticity of -4.30 implies that a 1 percentage-point decrease in the effective tax rate increases net-FDI-outflows ceteris paribus by about 4.30 per cent. Evaluated at the mean net-FDI-outflow of € 193.5 m. this amounts to € 8.3 m. on average. Thus, in the past, tax-lowering strategies of governments in the CEECs had an important effect on the allocation of FDI among the CEEC-8.

Model 2 shows that a one percentage-point increase in ulc reduces net-FDI-outflows by about 3.30 percent. Comparing this estimate with other studies is notoriously difficult, as almost every study uses an alternative definition of labour costs. Lansbury et al. (1994) use unit labour costs in a host country relative to other potential hosts in Central Europe and find that labour costs have a significant and negative impact on FDI. Inclusion of relative wage and relative productivity measures as in Holland and Pain (1998) appears to leave only the relative wage variable significant, while productivity differentials across host countries are not significant. According to the authors this implies "that considerations of comparative factor costs across countries influence some investment decisions" (p. 16). Clausing and Dorobantu (2005) measure labour costs by the average compensation rate in the host country and also find a negative effect throughout. Some studies (e.g. Bénassy-Quéré et al. 2005, p. 590) even find a positive relationship between FDI and labour costs, which is most likely attributable to an omitted variable problem. The authors themselves state, that "unit labour costs are positively related to the quality of labour." (ibidem, p. 589) Hence, labour costs may account for the impact of skill differentials across host countries. Concerning the privatisation process, our analysis shows a significant and positive impact of privrev. At first sight, the coefficient on privrev, although significant and with the correct sign seems very low: ceteris paribus, net-FDI-outflows increase by about 0.03% if privatisation revenues increase by one million euro. Yet, given that foreign MNEs have been active in the CEEC-8 for some time now and that privatisation programmes are far advanced, the share of FDI unrelated to privatisation processes per se should have increased.

Other studies including the privatisation process as a determinant of FDI use the EBRD's private-sector share in total economy (see Lansbury et al. 1996, Holland andPain 1998;Carstensen and Toubal 2004) and/or the method of privatisation (Holland and Pain 1998;Carstensen and Toubal 2004). Using the private sector share often results in insignificant coefficients, partly because the share variable does not vary much over time. In Carstensen and Toubal (2004) and Holland and Pain (1998) the "method of privatisation" (i.e. vouchers vs. other methods) turns out to have a significant effect on FDI inflows. Holland and Pain conclude that "countries with a program of direct privatisation through cash sales have attracted relatively higher inward investment than those countries using voucher privatisation" (p. 16). Clearly, the studies quoted here cover earlier time periods.

The marginally insignificant coefficient on inflation points to the fact that inflation has decreased considerably in the CEEC-8 compared to earlier periods of transition. Studies including earlier years and countries in macroeconomic turbulence (e.g. Edmiston et al. 2003) reveal significant negative effects of inflation on FDI-flows.

Finally, the analysis implies that political instability (risk) does not seem to be a relevant location factor within the CEEC-8. This is in marked contrast to studies using data from the beginning of the transformation process till the end of the 1990ies (e.g. Carstensen and Toubal 2004). Finally, the insignificance of tar is plausible as tariffs were brought down considerably during the 1990s and, hence, are of minor importance throughout our sample period. 4 here]

Relative importance of effective tax rates as a location factor

Table 5 shows the Beta coefficients corresponding to model 2. Host-market size and distance are the most important determinants of net-FDI-outflows. This result is in line with many other studies (e.g. Mold 2003). Taxation, privatisation and unit labour costs are almost equally important as location factors. Inter alia these results imply that the role of taxes should not be overemphasized relative to that of other location determinants.

An alternative measure of the corporate income tax burden

In order to show that using statutory tax rates instead of the conceptually superior effective tax rates may lead to an underestimation of the tax-rate sensitivity of FDI we replace the beatr by the statutory tax rate (statrate) in model 2. Results for model 3 (reported in table 5)

show the expected substantial drop of the semi-elasticity to about -1.9. This estimate also falls marginally short of statistical significance at the 10 percent significance level (twosided test). This should be considered as an indication that the relatively low value of the median semi-elasticity derived by anonymous ( 2006a) is partly due to the use of statutory tax rates. This result is also important with regard to evaluating the effectiveness of governments' tax cuts, which might have had a larger effect on inward FDI than earlier studies have revealed.

[Table 5 here]

Robustness and stability analysis

We check the robustness of our preferred specification in model 2 against the impact of possible cross-section outliers by dropping host countries stepwise (e.g. [START_REF] Winner | Has Tax Competition Emerged in OECD countries? Evidence from Panel Data[END_REF]. Thereby we focus on those variables which are relevant from a policy perspective (beatr, ulc, privrev). Table 6 reports the resulting minimum and maximum values of the coefficient estimates and the coefficient derived from model 2 as well as the country excluded. The results are robust with respect to dropping countries as no coefficient changes sign and all but one remain highly significant. The coefficient on ulc gets insignificant when Slovenia is excluded. This is plausible as Slovenia received low FDI and has comparably high unit labour costs when compared to other host countries in our sample.

[Table 6 here] The stability of the coefficients on beatr, ulc and privrev is checked by combining these variables with a dummy variable for the years 2000-2003. The year 2000 has been chosen as some host countries (notably Romania and the Slovak Republic) started to reduce their beatr since 2000. Table 7 (models 4 to 6) shows that the semi-elasticities for beatr and ulc for the period 2000-2003 are not significantly different from that of previous years, but that the importance of privatisation as a driver of FDI is significantly lower from 2000 onwards. This last result seems to be plausible as the privatisation process leveled off in many CEECs around 2000 (EBRD transition report, various issues).

[Table 7 here]

Summary

The aim of this paper was to test the hypothesis that a high corporate tax burden acts as a deterrent to FDI-flows in the CEECs, since it exerts a negative effect on the profitability of investments. We suggest that using the statutory tax rate in previous studies might blur the effects of the tax burden on FDI and lead to questionable results. Therefore, we use the bilateral effective average tax rates to explaining net-FDI-outflows from the 7 most important home countries to the CEEC-8. Referring to the eclectic paradigm as a conceptual basis, we find in a panel-gravity setting that FDI is positively related to both source country and host-market size as well as to progress in privatisation. Also, FDI is inversely related to the distance between home and host countries, to the corporate tax burden and to unit labour costs. We also find weak evidence for the negative impact of macroeconomic risk on FDI.

Concerning the role of taxes three points are worth noting:

First, the derived tax-elasticity is robust across various specifications and is greater in absolute value than those reported in earlier studies on the CEECs, pointing to a greater importance of tax policy for company location decisions than previously acknowledged.

Second, the differences in the absolute value of the semi-elasticities when compared to earlier studies are clearly partly due to the use of beatrs. The derived semi-elasticity after replacing the beatr by statrate in our study is, indeed, substantially lower.

Third, the relative importance of the corporate tax rate as a determinant of FDI must not be overemphasized as our results (Beta-coefficients) reveal that at least during the period 1995-2003 the tax burden had no exceptional influence on net-FDI-outflows to the CEEC-8 when compared to other determinants.

While this study is a step towards a better understanding of the determinants of FDI-flows to the CEECs, there are several limitations to our analysis. In particular, we are conscious of the exclusion of location factors such as the quantity and quality of production related (public) infrastructure. This omission is due to the lack of meaningful data. Moreover, special investment incentives (e.g. regional, R&D) are not included, as many different incentives have been granted by CEEC governments throughout the sample period of nine years. The choice of incentives to be included in the beatr would be arbitrary. Moreover, many CEECs have reduced their special investment incentives to MNEs during our survey period in accordance with the aquis communautaire of the EU. For example, Boudier-Bensebaa (2005) reported that, in Hungary, special tax incentives for MNEs have increasingly been phased out, or that domestic and foreign firms are now treated equally.

  has been shown by many empirical studies, notably by

K

  ij are country-pair-specific effects; e ijt is the remainder error term.

  down considerably during the first part of the 1990s and, hence, are of minor importance throughout our sample period.

  inward investment than those countries using voucher privatisation." (p. 16) Clearly, the studies quoted here cover earlier time periods.

  model_4a: cluster robust standard errors change significance of time dummies but not that of other variables. Model_2b and model_4b hence exclude time dummies.

  .M. (2002) Econometric Analysis of Cross Section and Panel Data (Cambridge: MIT-Press). (FDI) is carried out by Multinational Enterprises (MNEs) in order to earn profits. The profitability of FDI is expected to decrease with increases in energy prices, taxes, labour costs etc. Concerning taxation, the negative relationship between tax burden and FDI inflows is basically confirmed by the empirical evidence for OECD countries. (e.g. DeMooij and Ederveen 2003 and 2005) However, the empirical evidence concerning FDI and taxation in the Central-and East European Countries (CEECs) has consistently not found evidence that taxes matter for location decisions (see below).

  reference to various theories (e.g. Trade Theory, Theory of the Firm and Theory of Industrial Organisation) the eclectic paradigm avers that FDI emerges if a firm has an Ownershipadvantage (e.g. a patent) combined with a Location-advantage (e.g. low production costs; large market size) and an Internalisation-advantage (e.g. economies of interdependent activities).The particular location factors considered by the firm in choosing between different foreign markets have to be valid proxies for host-country Location-advantages. The eclectic paradigm incorporates all possible location factors which attract FDI conditional on a firm's decision to undertake FDI. This poses a problem as it neither attributes weights to single location factors like taxation, nor does it assess their relative weights. Hence empirical the eclectic paradigm have to rely on more or less ad hoc specifications.

  cent in the Euro Area on average. Still in 2005, the EBRD's Transition Report concludes on "financial sector vulnerabilities in Hungary", one of the most advanced countries of the CEEC-8.

  general, high labour costs in the host country should exert a negative impact on FDI.4

  data on the sectoral level become available differences in tax-rate elasticities between sectors should provide a more detailed picture on the tax-rate sensitivity of FDI.

Table 1 :

 1 MNEs during our survey period in accordance with the aquis communautaire of the EU. For example,Boudier-Bensebaa (2005) reported that, in Hungary, special tax incentives for MNEs have increasingly been phased out, or that domestic and foreign firms are now treated equally. Further research should focus on a meaningful operationalisation of these factors.Country-level Location Factors related to Market-and Efficiency-oriented FDI

	incentives to
	F o r
	P
	e
	e r
	R e v
	i e
	w
	18

Table 3 :

 3 "Pillar 1" Results (cont') ** p < 0.05; t-values in parenthesis; Het: LM-test for heteroskedasticity in fixed effects model; TD: time dummies; BP: Breusch-Pagan-test for random individual effects; Hausman: Hausman-test or Hausman-Wooldridge-test for fixed vs. random effects; AR(1): Wooldridge-test for serial correlation in linear panel data models -values in parenthesis; stud.res: studentized residuals; VIF: variance inflation factor; Het: LM-test for heteroskedasticity in fixed effects model; TD: time dummies; BP: Breusch-Pagan-test for random individual effects; Hausman: Hausman-test or Hausman-Wooldridge-test for fixed vs. random effects; AR(1): Wooldridge-test for serial correlation in linear panel data models; Reset: Ramsey-functional-form-test

	Model_5		Model_6		Model_7
	lngdphome	0.28021		0.32341**		0.23844
		(1.70)		(2.04)		(1.40)
	lngdphost	1.24630***		1.37563***		1.25056***
		(7.66)		(8.17)		(7.80)
	lndist	-0.59275***		-0.65996***		-0.45979**
		(-3.16)		(-3.86)		(-2.01)
	beatr	-0.03254**		-0.03440***		-0.03472***
		(-2.61)		(-2.76)		(-2.84)
	pp	-0.00044 tar	0.04499 combord	0.51741
		(-0.86)		(1.43)		(1.08)
	cons	-7.48229***		-9.04955***		-7.87836***
		(-3.17)		(-3.78)		(-3.37)
	N R 2	449 within: 0.2980	N R 2	449 N within = 0.3004 R 2	449 within = 0.2964
		between: 0.5894		between = 0.5949		between = 0.5990
		overall: 0.4633		overall = 0.4671		overall = 0.4677
	AR(1): 2 1 Het.: 2 13 TD: 2 8 Hausman: 2 4 BP: 2 1	= 1.193 = 18.40 = 24.52*** = 8.92 = 227.50***	2 1 2 13 2 8 2 4 2 1	= 1.209 = 26.109** = 28.33*** = 7.36 = 228.82***	2 1 2 13 2 8 2 4 2 1	= 1.232 = 19.259 = 24.59*** = 5.55 = 213.27***
	*** p < 0.01;

Table 5 :

 5 Beta Coefficients and Statutory Tax Rate Overall standard deviations from random effects transformed variables are used to calculate beta coefficients. The values used are: 1.264 (lnfdi), 0.664 (lngdphome), 0.474 (lngdphost), 0.502 (lndist), 5.552 (beatr), 832.988 (privrev) and 4.716 (ulc).

	Beta Coeff.		Model_10
	lngdphome	0.173		0.26277
				(1.69)
	lngdphost	0.396	1.04806***
				(6.15)
	lndist	-0.261	-0.60497***
				(-3.67)
	beatr	-0.192 statrate	-0.02360
			(-1.78); p = 5.1
	privrev	0.191	0.00027***
				(3.57)
	ulc	-0.115	-0.02546**
				(-2.09)
	cons	Y	-5.057145**
				(-2.12)
	N	449	N	449
	*** p < 0.01; ** p < 0.05; t-values in parenthesis;

Table 1

 1 summarises the discussion of individual location factors.

	[Table 1 here]

Table 2 :

 2 Descriptive Statistics .01; ** p < 0.05; * p < 0.10; " significant at 10 percent level in case of one-sided test; t-values in parenthesis; stud.res: studentized residuals; VIF: variance inflation factor; Het: LM-test for heteroskedasticity in fixed effects model; TD: time dummies; BP: Breusch-Pagan-test for random individual effects; Hausman: Hausman-test or Hausman-Wooldridge-test for fixed vs. random effects; AR(1): Wooldridge-test for serial correlation in linear panel data models; Reset: Ramsey-functional-form-test; Wald: model-test; groups = number of cross-sections; sigma_u = standard deviation of cross-section specific residual; sigma_e = standard deviation of remainder error term; theta = weight on cross-section specific mean in random effects model

	Variable		Mean	Std. Dev.		Min	Max	Observations
	lnfdi	overall	4.02	1.75	-0.43		7.81 N = 449
		between		1.39	1.66		7.19 n = 56
		within		1.11	0.60		7.94 T = 8.02
	lngdphome	overall	13.90	1.10	12.11		16.24 N = 449
		between		1.12	12.20		16.09 n = 56
		within		0.14	13.43		14.24 T = 8.02
	lngdphost	overall	10.40	0.76	8.96		12.24 N = 449
		between		0.75	9.38		11.94 n = 56
		within		0.21	9.93		10.88 T = 8.02
	lndist	overall	6.99	0.98	4.03		9.15 N = 449
		between		0.99	4.03		9.15 n = 56
		within		0.00	6.99		6.99 T = 8.02
	beatr	overall	34.79	7.43	16.11		55.92 N = 449
		between		5.37	24.07		48.07 n = 56
		within		5.08	17.52		47.06 T = 8.02
	ulc	overall	25.42	9.23	11.00		50.00 N = 449
		between		8.77	15.43		46.14 n = 56
		within		2.89	15.42		33.22 T = 8.02
	privrev	overall	1223.80	1157.48	58.16		4570.03 N = 449
		between		908.25	93.03		2712.47 n = 56
		within		739.74	-19.38		4375.46 T = 8.02
	pp	overall	28.08	112.81	-1.20		901.80 N = 449
		between		43.94	1.92		154.04 n = 56
		within		104.10	-122.55		803.66 T = 8.02
	risk	overall	13.88	3.32	5.32		19.82 N = 449
		between		2.90	9.59		17.48 n = 56
		within		1.64	7.73		17.39 T = 8.02
	tar	overall	4.34	3.83	0.50		18.45 N = 449
		between		3.07	0.95		11.71 n = 56
		within		2.28	-0.17		13.43 T = 8.02
	combord	overall	0.31	0.33	0.00		1.00 N = 449
		between		0.33	0.00		1.00 n = 56
		within		0.00	0.13		0.13 T = 8.02
	Table 3: Correlation Matrix
		lngdphome	lngdphost	lndist combord beatr privrev pp	risk	ulc	tar
	lngdphome	1.00
	lngdphost	0.03	1.00
	lndist	0.75	-0.02	1.00
	combord	-0.29	0.10	-0.59	1.00
	beatr	0.03	-0.01	0.01	0.04	1.00
	privrev	0.02	0.69	-0.03	0.06	-0.05	1.00
	pp	-0.02	-0.23	0.09	-0.07	0.14	-0.10	1.00
	risk	0.03	0.52	-0.18	0.27	-0.21	0.39	-0.27 1.00
	ulc	0.02	0.07	-0.10	0.18	-0.38	-0.10 -0.25 0.45 1.00
	tar	-0.05	-0.59	0.14	-0.18	0.09	-0.32	0.30 -0.67 -0.29 1.00

Table 5 :

 5 Beta Coefficients and Statutory Tax Rate < 0.01; ** p < 0.05; * p < 0.10; " significant at 10 percent level in case of one-sided test; t-values in parenthesis; Het: LM-test for heteroskedasticity in fixed effects model; TD: time dummies; BP: Breusch-Pagantest for random individual effects; Hausman: Hausman-test or Hausman-Wooldridge-test for fixed vs. random effects; AR(1): Wooldridge-test for serial correlation in linear panel data models; Wald: model-test; groups = number of cross-sections; sigma_u = standard deviation of cross-section specific effects; sigma_e = standard deviation of remainder error term; theta = weight on cross-section specific mean in random effects model; standard deviations used to calculate Beta coefficients are taken from table 2; combord is a dichotomous variable; hence calculation of a Beta-coefficient is inadmissible

	Beta Coeff.		Model 3
	lngdphome	0.16	0.19
			(1.15)
	lngdphost	0.42	0.94***
			(5.34)
	lndist	-0.26	-0.41*
			(1.84)
	beatr	-0.18 statrate	-1.90"
			(-1.59)
	privrev	0.20	0.029***
			(4.12)
	ulc	-0.17	-2.70**
			(-2.30)
	pp	-0.05	-0.094*
			(-1.84)
	combord		0.66"
			(1.41)
	cons		-4.36*
			(-1.83)
	N	449	449
	R 2 within		0.33
	R 2 between		0.61
	R 2 overall		0.49
	AR(1): 2 1		1.20
	Het.: 2 16		22.87
	TD: 2 8		36.32***
	Hausman: 2 14		16.08
	BP: 2 1		257.13***
	Wald: 2 16		267.83***
	sigma_u		0.81
	sigma_e		0.99
	*** p

Page 52 of 58 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

	Submitted Manuscript
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Table 6 : Jackknife Analysis Minimum (in absolute value) Host country excluded Estimate Maximum (in absolute value)

 6

	Host country
	excluded

Page 53 of 58 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

  Has Tax Competition Emerged in OECD countries? Evidence from Panel Data, International Tax and Public Finance, 12, pp. 667-687. Wooldridge, J.M. (2002) Econometric Analysis of Cross Section and Panel Data (Cambridge: MIT-Press).

	Table 7: Stability Analysis Winner, H. (2005) Page 57 of 58	Submitted Manuscript Submitted Manuscript Submitted Manuscript		Page 54 of 58
		Model 4	Model 5		Model 6
	lngdphome	0.26*		0.27*		0.26*
		(1.84)		(1.83)		(1.73)
	lngdphost	0.97***		0.93***		0.96***
		(6.34)		(5.96)		(6.05)
	lndist	-0.46**		-0.49**		-0.46**
		(-2.45)		(-2.49)		(-2.31)
	combord	0.68*		0.63"		0.68*
		(1.73)		(1.55)		(1.65)
	pp	-0.09*		-0.07"		-0.09*
		(-1.65)		(-1.36)		(-1.70)
	beatr	-4.50***		-3.80***		-4.40***
	dummy_beatr privrev	F o r (-3.40) 0.22 (0.13) 0.03*** (4.24) F o r F o r F o r F o r	(-3.08) 0.044*** (5.39)		(-3.44) 0.03*** (4.37)
	ulc	P e dummy_privrev -3.30*** P P P P (-3.03) e e e e	-0.03*** (-3.12) -2.80** (-2.52)		-3.40*** (-2.92)
	cons	-4.35**	e r e r e r e r e r	-4.03*	dummy_ulc	0.46 (0.38) -4.34**
	R e v (-1.90) 449 *** p < 0.01; ** p < 0.05; * p < 0.10; t-values in parenthesis; " significant at 10 percent level in case of one-sided (-2.10) (-2.01) N 449 449 test R e v R e v R e v R e v
				i e i e i e i e i e
					w w w w w
						24 27

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

The home countries are Austria, France, Germany, Italy, the Netherlands, the United Kingdom and the United States. The host countries are Bulgaria, Croatia, the Czech Republic, Hungary, Poland, Romania, Slovakia and Slovenia.

Rather, in many cases it is the other way round, i.e. a listed acquired firm is de-listed from the stock exchange after the acquisition by a foreign MNE, in order to gain 100% ownership.

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

The home countries are Austria, France, Germany, Italy, the Netherlands, the United Kingdom and the United States. The host countries are Bulgaria, Croatia, the Czech Republic, Hungary, Poland, Romania, Slovakia and Slovenia (CEEC-8).

Rather, in many cases it is the other way round, i.e. a listed acquired firm is de-listed from the stock exchange after the acquisition by a foreign MNE, in order to gain 100% ownership.

Should the coefficient carry a positive sign, this could be an indication of an omitted variable problem, as in this case labour costs may capture effects of an increasing level of skill in the host country.

Acknowledgement

We are grateful to the Austrian Science Fund for providing financial support by grant F 2008.

Acknowledgement

We are grateful to the Austrian Science Fund for providing financial support by grant F 2008.

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript