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Public procurement and foreign direct investment across France, Germany, Italy and the UK.

Introduction

During the last two decades foreign direct investment (FDI) has become an important factor of economic development in host economies by bolstering the quality of local workforce and entrepreneurship, by contributing to the diffusion of technology, by creating positive externalities, and by alleviating capital shortage. Attracting and sustaining FDI inflows has become a policy objective in its own right while policies in other fields have been reshaped to accommodate the new objective. This paper examines the way public procurement policies in the host state interfere with FDI inflows. In other words, it analyzes public procurement as a determinant of FDI.

Recent research on FDI and its determinants has mainly focused on market size (Barrell and Pain 1999a; Bengoa and Sanchez-Robles 2003; Bevan and Estrin 2004; Trevino and Mixon 2004), relative unit labor cost (Barrell and Pain 1999b; Bevan and Estrin 2004; Farrell et al. 2004) and political and economic risk, especially in developing host countries (Bengoa and Sanchez-Robles 2003; Trevino and Mixon 2004). Furthermore, a number of studies suggest that wherever non-tariff barriers such as antidumping replaced tariffs, FDI regained its "tariff-jumping" role (Belderbos 1997; Blonigen and Feenstra 1997; Barrell and Pain 1999b; Bloningen 2002; Farrell et al. 2004).

It has furthermore been established that location, being a strategic variable of corporate policy, is also a major determinant of FDI (Barrell and Pain 1999a). External economies to location may be either due to local comparative advantage or to a targeted industrial policy, an important element of which is public procurement. In fact, public procurement may be used as a tool of discrimination in favor of local firms and "buy national" policies may operate as a non-tariff barrier for foreign suppliers of final goods. On the other hand, government contracts constitute an essential and privileged instrument towards supporting domestic suppliers, promoting production innovation and assisting cost reducing efforts (Laffont and Tirole 1986, 1990); their effectiveness however may be questioned (Miyagiwa 1991). Through their public procurement policies, governments may also pursue a wider set of objectives such as sectoral, regional, and social development (Laffont and Tirole 1991; Vagstad 1995; Geroski 1990).

In this paper a cross-country and cross-industry sample is analyzed in order to assess whether public procurement policies and agglomeration economies are statistically significant determinants of FDI. The sample consists of industry data spanning 30 sectors within France, Germany, Italy, and the UK for 1991, that is 2 years prior to the enactment of the Single European Market (1993). After accounting for labor productivity and trade openness, we find that FDI is significantly affected by both public procurement policies and agglomeration economies. These findings have important policy implications both on the corporate and the national level. Governments could attract foreign investment in specific industries either by adopting a "buy national" policy or by creating agglomeration economies.

The rest of the paper is organized as follows. In the first section we present the stylized facts of public procurement in the EU. In the second section we set forth the theoretical underpinnings and the hypotheses under investigation, whereas data and estimations are presented in the third section. We discuss policy implications in the fourth section and epitomize our analysis in a final section.

Public Procurement Regulation in the European Union

Early European Community (EC) Directives for the opening up of public procurement date back to the 1970s (first Works Directive 1971/305 and first Supplies Directive 1977/62). It must be noted that import penetration to public procurement markets at that time was unimportant (1.5% on average), although public procurement on supplies, works and services represented a 15% to 18% of EC GDP (Atkins 1988). The "Single European Act" of 1987 stipulated that EC (and later EU) member-states had to remove all non-tariff barriers (NTBs), such as public procurement, on their intra-community trade flows by 1993. More specifically, as per the Directives on Supplies (93/36), Works (93/37), Services (92/50) and Utilities (93/38), EU public procurement national markets had to be opened to intra-EU competition before January 1st, 1993.

Foreign bidders and Multinational enterprises (MNEs) realized in the early 1990s that permeability of the public procurement market was unlikely at least in the medium run, a view held by several European public procurement experts as well (Cox and Furlong 1997). This meant that domestic suppliers would retain their advantage, while MNEs could counter host country "buy national" provisions and succeed in public auctions only by establishing a local subsidiary. (Commission of the EU 2004). This strategy was followed throughout the decade and is expected to pay out in the 2000s as well.

Public procurement remains only partially exposed to intra-EC competition and European governments find their way in preserving their "buy national" policies. According to the Commission of the EU (2004), only 16% of total public procurement (or 2.6% of EU GDP) in member-states is subjected to the appropriate publication procedures in 2002, and is thus open to foreign bidders. The remaining part remains a "chasse privee" for local suppliers.

Direct cross-border procurement (i.e., when foreign firms win contracts in local tenders) has remained low, while indirect cross-border procurement (i.e., when foreign firms win contracts in local tenders through their subsidiaries) has increased. As a result, 11 years after the enactment of the Single European Market, not only do MNEs prefer to bid in local procurement auctions through their local subsidiaries, but they also tend to slightly outperform their local competitors.

Theoretical Considerations

According to the UNCTAD (1993), FDI has become an essential factor of economic development, especially for developing countries, for several reasons. First, MNEs are an important capital source for developing economies particularly in times when foreign aid from industrial countries falls short. Second, direct investment, as opposed to its financial counterpart, is far less sensitive to monetary and capital market downturns, a property which has become substantially valuable after the financial crisis in Far East Asia in 1997, in Russia and Brazil in 1998, and in Argentina in 2000. Moreover, MNEs can positively affect the host economy, either directly or indirectly through their local subcontractors by transferring their advanced technological, organizational, and management practices. Finally, it is worth noting that export oriented FDI improves the macroeconomics of recipient countries by lessening balance of payments constraints and exchange market pressures.

Given the importance of FDI on the host economy, the question is raised as to the appropriate policy a recipient country should pursue in order to attract MNEs and foster FDI inflows. As a matter of fact, the question boils down to determining those parameters in the MNE's decision to go abroad that may be more or less set by host policies, although it is widely accepted that MNEs go abroad for more than one strategic reason (Dunning 1993). Foreign trade policies, such as tariffs and NTB, and policies affecting foreign trade, such as "buy national" procurement, are at the center of the host country's policy options.

The impact of NTBs on the MNE's decision is equivalent to that of a unit tariff. Typical NTBs such as technical regulations, public procurement, and antidumping may be assimilated to a tariff as long as they impose an extra cost to foreign suppliers and may induce a "tariff-jumping" FDI (Cantwell and Randaccio 1992). Although "tariff-jumping" FDI received significant theoretical treatment, the corresponding empirical evidence is relatively sparse. Belderbos (1997) reports an important "tariff-jumping" effect at firm and product level in inward USA FDI. Blonigen and Feenstra (1997) suggest that actual measures of anti-dumping and the threat there of are correlated with industrial FDI. Barrell and Pain (1999b) find that the initiation of anti-dumping cases has had a significant effect on the pattern of Japanese manufacturing investment, whereas Bloningen (2002) maintain that "tariff-jumping" is limited only to MNEs from industrialized countries. Finally, Farrell et al. (2004) argue that even though anti-dumping measures against Japanese firms affected only a small proportion of trade, Japanese FDI has been mainly a response to rising foreign trade barriers, especially in machinery and metal products industries.

As stated earlier, a "buy national" public procurement policy is equivalent to a NTB and although as such it may affect the MNE's decision to invest abroad, it received relatively little attention, as opposed to anti-dumping policy. Mardas and Varsakelis (1996) found a positive impact of "buy national" public procurements policies on Greek inward FDI. In Greece, with preferential public procurement policies and longstanding interaction between government agencies and incumbent, usually local, firms have seemed to end up to discriminatory practices against foreign suppliers, e.g. narrow product specifications, which produced "tariff-jumping" FDI.

An Empirical Model of the FDI-Public Procurement Relationship

On the basis of the aforementioned theoretical considerations, the empirical model is expressed in the following terms:

[FDIQ.sub.ij] = f([QPO.sub.ij], [VIV.sub.ij], [PSI.sub.ij], [QL.sub.ij], [XQ.sub.ij])

where: subscripts i and j denote sector and country, FDIQ is the share of foreign firms in domestic production, QPQ is the share of the domestic sectoral production purchased by the government, VIV is the share of sectoral public procurement over total government purchases, and PSI is the production specialization index (Balassa 1965). Furthermore, we introduce two control variables, labor productivity and trade openness, denoted QL and XQ respectively. Finally, we include a country dummy variable to control for country specific fixed effects such as investment subsidies, and tax credits or culture and language (Dunning 1993).

Domestic production of sector i purchased by the state over total domestic production for country j, [QPQ.sub.ij], is an indicator of market structure which mirrors the importance of public contracts in domestic production and is defined as:

[QPQ.sub.ij] = [QP.sub.ij]/[Q.sub.ij]

where:

[QP.sub.ij] =government purchases by sector i in country j

[Q.sub.ij] =total domestic production of sector i in country j

A large share of public purchases in a given sector indicates that local suppliers have an edge over foreign suppliers. MNEs aiming at obtaining a share from government dominated markets are expected to establish or expand local subsidiaries. FDI in those industries is of the "tariff- jumping" type and therefore the coefficient of QPQ is expected to be positive.

Governments consider some sectors to be of strategic importance and government purchases in those sectors form an important part of total public procurement. To define the share of sectoral procurement in total procurement, we posit:

[VIV.sub.ij] = [V.sub.ij]/[V.sub.j]

where:

[V.sub.ij] = public procurement from sector i in country j

[V.sub.j] = total public procurement in country j

As Mardas (1997) argued, a large share of sectoral government purchases in total public procurement indicates that "buy national" policy barriers protect local producers. Since MNEs are more likely to establish or expand a local subsidiary in order to gain a market share, the coefficient of VIV is expected to be positive.

External economies to proximity can reduce cost, and location may become a strategic factor in the MNE's decision to invest abroad (Barrell and Pain 1999a). Foreign firms may decide to invest in a region with both vertical and horizontal sectoral agglomeration economies, in order either to exploit a local build-up of knowledge or subcontract parts of their activity. We introduce, PSI, the Production Specialization Index as an indicator of agglomeration effects, defined as:

[PSI.sub.ij] = [Q.sub.ij]/[Q.sub.j]/[Q.sub.ic]/[Q.sub.c]

where:

[Q.sub.ij] = production of sector i in country j

[Q.sub.j] = total production of country j

[Q.sub.ic] = production of sector i in the EU

[Q.sub..c] = total production of the EU

A PSI value greater than unity indicates the existence of agglomeration economies, which is likely to attract MNEs (Barrell and Pain 1999a), and thus the coefficient of PSI is expected to be positive.

Cross-border investment is also significantly related to unit labour cost (Bevan and Estrin 2004; Farrell et al. 2004). Given that the four countries in our sample are among the larger and more developed economies in the EU and assuming that the average wage rate does not vary significantly across sectors in the same country, we may reasonably attribute differences in unit labor costs to differences in labor productivity. The average sectoral labor productivity, denoted by QL, is therefore used as a proxy for unit labor cost and its coefficient is expected to be positive.

Lastly, in the existing literature, FDI is positively associated with the host economy's openness. Trade openness, and export openness in particular, plays a positive role in the decision of an export-oriented MNE to invest in a country, whereas export barriers create market imperfections and penalize exporting firms (Asiedu 2001). The export openness of sector i in country j is measured by the share of exports in domestic production and is defined as:

[XQ.sub.ij] = [X.sub.ij]/[Q.sub.ij]

where:

[X.sub.ij] = total export of sector i in country j and

[Q.sub.ij] = total production of sector i in country j

An industry with significant export openness indicates the existence of a comparative advantage at the sectoral level and is likely to generate FDI. Export openness is, therefore, expected to affect FDI positively.

Data and Estimation Results

The EU Commission undertook an extensive and analytical ad hoc study of public purchases at sectoral level for the year 1991 (Commission of the EU 1994). Although not replicated to date, this study provides a detailed data set for public procurement across industries. Our sample consists of government purchases data pertaining to 30 industrial sectors for the four larger European economies, France, Germany, Italy, and the UK, obtained from the aforementioned study. Industrial sectors were selected on the basis of their importance in total public procurement as evidenced in previous studies (Commission of the EC 1990). Data on the share of foreign firms in domestic production (FDIQ), the share of the domestic sectoral production purchased by the government (QPQ), and the share of sectoral public procurement over total government purchases (VIV), were obtained from Commission of the EU (1994). Finally, data on the Production Specialization Index (PSI), average sectoral labor productivity (QL) and trade openness (XQ) were extracted from Eurostat's VISA data bank.

Tables 1 and 2 present the descriptive statistics and the correlation matrix of our variables. In particular, Table 1 reveals that the share of local subsidiary production in total production is larger in Germany and the UK compared to France and Italy. The mean share of seetoral procurement over total government purchases in Germany and the UK is almost three times that of France and Italy. Finally, Germany exhibits the highest mean Production Specialization Index. Pair-wise correlations, depicted in Table 2, are low, implying low collinearity between explanatory variables.

A first set of estimations is presented in columns 1 through 3 of Table 3. Variables QPQ and VIV are introduced into the equation first separately (columns 1 and 2) and then combined (column 3). The overall performance of these specifications, as mirrored by their [R.sup.2] and F-statistic, is relatively good. Both variables have statistically significant coefficients with positive sign, as expected. However, when both variables are combined in the equation (column 3), VIV dominates QPQ, indicating that MNEs consider sectoral public procurement to be a stronger signal for government priorities.

PSI has also a positive and statistically significant coefficient, indicating that agglomeration economies are an important factor in the MNE's decision to invest. Control variables QL and XQ are everywhere statistically significant, except in equation 3.3, and have the correct sign, revealing that trade openness and labor productivity are affect positively FDI.

Assuming weak exogeneity for all independent variables, we next model FDI using a fixed effects Least Squares Dummy Variable (LSDV) approach (Hsiao 2002). According to Maddala (1992) LSDV tests the hypothesis that the constant intercept is common in all country equations. Results from LSDV are presented in columns 4 through 6 of Table 3, corroborating our earlier OLS estimations, with the exception of PSI. LSDV coefficients are statistically significant and retain the correct sign, while improved overall performance adds to the robustness of our empirical findings.

As noted, the Production Specialization Index loses its statistical significance after the introduction of dummy variables. In our opinion, this finding suggests that agglomeration economies are not only the outcome of comparative advantage in a given country or region, but they are also created by a targeted national industrial policy. As a result, the introduction of country dummies to control for fixed effects overlaps with the fixed effects implicitly included in the Production Specialization Index. Joint significance F-tests of country dummy variables reported in Table 3 suggest that the LSDV estimates should be retained instead of their simple OLS counterparts. Finally, country dummies appear to vary both in size and sign. Coefficients for France and Italy are negative, suggesting ceteris paribus that the former probably attract less FDI than Germany and UK. It seems after all that country effects are attributable to both national culture and public policy.

Our empirical findings suggest that FDI is both trade substituting (through "tariff-jumping") and trade supplementing given its positive association to both trade openness and labor productivity. These findings agree with Dunning's (1993) eclectic paradigm, according to which the MNE's decision to invest abroad is influenced by several factors. The positive effect of labor productivity indicates that productivity differentials affect FDI, a fact also evidenced in Bevan and Estrin (2004), Barrell and Pain (1999b), and Farrell et al. (2004). On the other hand, the positive impact of trade openness is similar to the one described by Asiedu (2001) for developing economies. At a sectoral level, our findings indicate that MNEs go abroad to avoid foreign trade restrictions, such as anti-dumping measures (Barrell and Pain 1999b; Bloningen 2002; Farrell et al. 2004) and "buy national" policies (Mardas and Varsakelis 1996).

Finally, the positive coefficient of the PSI variable indicates the existence of agglomeration economies, i.e. regional accumulation of industry specific production activity, which, in turn, suggests that a targeted industrial policy could boost sectoral development and, at the same time, signal unexploited profit opportunities.

Discussion and Policy Implications

It has been quite a long time since MNEs were considered detrimental and hostile to host countries' social welfare and development. In the meantime, governments have changed their attitude towards MNEs and are currently interested in attracting FDI in an attempt to promote their development goals. However, they find it difficult to attract foreign investments. Tax incentives, for instance, did not affect the decision of foreign firms to invest in transition economies (Beyer 2002).

In our opinion the policy implications of this paper are quite significant, provided that governments realize the positive role of incoming FDI. International negotiations on world trade and capital market liberalization in the frame of the Doha Round has revealed that smaller and less developed states do not fully realize the role of MNEs and, in fact, have succeeded in passing a Special and Differential Treatment clause in the July 2004 Agreement. The clause endorses the so called "policy space" which provides for the discretionary power to subsidize and protect domestic industries, and impose restrictions on foreign investment (Hoekman 2005).

In this paper we propose inter alia, an alternative approach to industrial policy for developing countries in order to stimulate FDI inflows. Policy makers in developing economies should bear in mind that foreign investment may generate positive externalities and act as a catalyst for the development of local industry which may eventually rival MNEs in that industry (Markusen and Venables 1999). For instance, Far-East Asia countries have become FDI exporters after having served for many decades as recipient countries for US and European MNEs. The sad reality for some developing areas is not that MNEs threaten local industry, but that they are, on the contrary, unwilling to invest. Sub-Saharan African countries are a typical example of this policy illusion (Asiedu 2001).

Although this and an earlier paper (Mardas and Varsakelis 1996) examines a number of major European economies and Greece, it is not unrealistic to suspect that public procurement regulation could successfully serve the same objectives in the case of developing economies. Governments should single out specific sectors and apply a "buy-national" policy attracting foreign firms to invest in the country and trigger a virtuous cycle of industrial development (Markusen and Venables 1999).

Finally, the role of agglomeration economies gives rise to interesting policy implications. Industrial policy should aim at accumulating a production base in selected sectors, both vertical and horizontal, as in the car industry example in the state of Alabama, USA. Although more countries currently compete for foreign capital, thus, increasing the global willingness to receive foreign investment, global FDI availability has increased as well, given that some of the formerly net recipient countries, e.g. South Korea and Singapore, have become net exporters of FDI.

Conclusion

This paper examines the determinants of sectoral foreign direct investment on the basis of 30 manufacturing sectors and four countries, in 1991. In particular, we investigate whether "buy national" public procurement policy generates "tariff-jumping" and find that after controlling for labor cost, trade openness, and production specialization, the larger the share of public procurements in domestic production, the higher the foreign production in the corresponding sector. It follows that a "buy national" objective in government purchases may attract foreign investment which, in turn, could act as catalyst for the local industry, create agglomeration economies and trigger a virtuous cycle of development. Moreover, we investigate the effect of agglomeration economies on FDI and find that agglomeration effects influence MNEs in their decision to invest abroad, which implies that a targeted industrial policy could foster FDI and set the country on a faster track of development.

Although our findings rely on the evidence of four major European economies, it is our belief that they equally apply to less developed economies. The same policies aiming at attracting MNEs through "buy national" government purchases and targeted industries, creating agglomeration economies, are very likely to generate a virtuous cycle of industrial development; provided, of course, that policymakers overcome their bias against the role of MNEs.

Published online: 25 January 2008

References

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D. Mardas ([e-mail]) * G. Papachristou * N. C. Varsakelis

Department of Economics, Aristotle University of Thessaloniki, P.O. Box 188, 54124 Thessaloniki, Greece

e-mail: mardas@econ.auth.gr

G. Papachristou

e-mail: gpapahr@econ.auth.gr

N. C. Varsakelis

e-mail: barsak@econ.auth.gr
Table 1 Descriptive statistics of dependent and independent variables

Variables        FDIQ      QPQ      VIV       QL       XQ     PSI

Overall sample   2.906   10.093    0.898   34.293   22.405   1.716
  (Mean SD)      1.968   16.977    2.284   12.346   11.520   2.96
France (mean)    2.435   11.574    0.444   35.573   29.265   1.009
Germany (mean)   3.684    9.936    1.466   32.696   21.306   3.150
Italy (mean)     1.874    9.600    0.312   37.666   20.529   1.077
UK (mean)        3.619    9.269    1.317   31.236   18.519   1.627

Table 2 Correlation coefficients of dependent and independent variables

                 FDIQ      QPQ      VIV       QL       XQ     PSI

QPQ              0.281
VIV              0.534    0.453
QL               0.348    0.034    0.347
XQ               0.181   -0.074   -0.049    0.107
PSI               0.10   -0.074    0.009   -0.028   -0.018

Table 3 Least squares dummy variable estimates for foreign direct
investment

Independent               (1)          (2)          (3)
variables

Intercept          0.547        1.479 ***    1.325 **
                    (0.961)      (2.78)       (2.519)
QPQ                0.033 **                  0.009
                    (2.382)                   (0.910)
VIV                             0.438 ***    0.403 ***
                                 (10.109)     (7.989)
QL                 0.05 ***     0.023 *      0.025 *
                    (3.514)      (1.68)       (1.857)
XQ                 0.041***     0.047 ***    0.047 ***
                    (3.339)      (4.355)      (4.365)
PSI                0.011 **     0.093 ***    0.097 ***
                    (2.33)       (2.87)       (2.808)
Dummy-France

Dummy-Germany

Dummy-Italy

[R.sup.2]-Adj.     0.26         0.41         0.41
F-statistic        9.355 ***    17.417 ***   13.67 ***
                    (P=0.000)    (P=0.000)    (P=0.000)
F-statistic for
  the joint
  significance
  of the country
  dummies
Nr. Obj.           120          120          120

Independent               (4)          (5)          (6)
variables

Intercept          0.369        1.002        0.683
                    (0.673)      (1.687)      (1.231)
QPQ                0.035 ***                 0.022 ***
                    (3.562)                   (2.819)
VIV                             0.308 ***    0.216 ***
                                 (4.867)      (3.10)
QL                 0.066 ***    0.0444 ***   0.050 ***
                    (4.753)      (2.904)      (3.406)
XQ                 0.045 ***    0.042 ***    0.045 ***
                    (3.739)      (3.237)      (3.601)
PSI                0.019        0.016        0.022
                    (1.386)      (1.022)      (1.596)
Dummy-France       -2.010 ***   -1.521 ***   -1.708 ***
                    (5.033)      (3.813)      (4.204)
Dummy-Germany      -0.209       -0.16        -0.201
                    (0.549)      (0.454)      (0.562)
Dummy-Italy        -2.260 ***   -1.779 ***   -1.923 ***
                    (5.624)      (4.267)      (4.733)
[R.sup.2]-Adj.     0.45         0.46         0.48
F-statistic        14.845 ***   15.467 ***   14.922 ***
                    (P=0.000)    (P=0.000)    (P=0.000)
F-statistic for    17.354 ***   9.565 ***    11.456 ***
  the joint
  significance
  of the country
  dummies
Nr. Obj.           120          120                 120

Student t statistic

* Statistically significant at 10%

** Statistically significant at 5%

*** Statistically significant at 1%
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Author:Mardas, Dimitri; Papachristou, George; Varsakelis, Nikos C.
Publication:Atlantic Economic Journal
Article Type:Report
Geographic Code:4EUFR
Date:Jun 1, 2008
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