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Published on November 23, 2007

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Slide1:  International Workshop “Bridging the gap: the role of trade and FDI in the Mediterranean” Napoli, Castel dell’Ovo 8-9 Giugno, 2006 FDI Potential and Shortfalls in South Mediterranean Countries: Determinants and Diversion Effects A. Ferragina (aferragina@unisa.it) F. Pastore (fpastore@unina.it) Outline :  Outline FDI in the MED-10 vis-a-vis Central and Eastern Europe: overview of performance and potential. Determinants of FDI with the help of the gravity model: the role of institutional and policy variables. Simulation analysis of the magnitude of “normal” value of FDI expected on the basis of the explanatory variables. Diversion of FDI from MED to CEECs? Introduction:  Introduction A worrying stylised fact: Southern Mediterranean countries (MED so far) receive little FDI from most other regions in the world. FDI flows into some of them have tended to grow slowly over the 90s and to decline after 2000, while they have been booming in Central and Eastern Europe (CEECs). World FDI outflows to CEEC10 and MED10 :  World FDI outflows to CEEC10 and MED10 EU investment are crucial:  EU investment are crucial EU is the main provider of FDI to the South Mediterranean. In 2004 the EU provided on average more than 70% of the FDI to MED10. The European presence is not equally distributed in all the MED but for some countries it is really striking: Turkey received more than 75% , Morocco 73% (more than 95% in 2001), Tunisia 65%. According to the MIPO database from ANIMA, 59% of the investment projects are coming from European investors, essentially France, Spain, the United Kingdom, and Germany. Things are not going well:  Things are not going well EU FDI: a slow trend of growth up to 1997 an upsurge between 1997 and 1999 and a good performance up to 2002: overall from 5 to 15 billions $ and from less than 1% to almost 14% of total EU FDI. However, from 2002 to 2004 a strong decline has eroded previous results: a fall from almost 14 to 4 per cent, corresponding to a decrease of more than 10 billions USD (from 15 to 5 billions $). EU FDI outflows to CEECs and MED10:  EU FDI outflows to CEECs and MED10 actual dollar values of EU FDI outflows to CEEC10 and MED10 from 1994 to 2004 as percentage of total EU FDI outflows (Eurostat, Economics and Finance Statistics) : this cursory evidence might suggest investment diversion from MED to CEECs Slide8:  Source: Eurostat, Economics and Finance Statistics. Perfomance and Potential Index:  Perfomance and Potential Index two indicators for ranking countries with respect to FDI (UNCTAD, 2004): 1) a “performance index” which relates the share of the FDI flows to a country to its share in the world GDP. An index above (below) one indicates that the couuntry attract more (less) FDI as a percentage of its economic dimension 2) a “potential index”, which is calculated as simple average of 12 structural variables which corresponds to the main FDI determinants identified by theoretical and empirical models (market size, degree of openness, infrastructures, technologies, qualified labour force at low cost, natural resources endowment, regulatory framework, busineess climate and country risk which influence the degree of confidence of investors). Performance of MED in 2004: ranking over 140 countries (Unctad, 2005):  Performance of MED in 2004: ranking over 140 countries (Unctad, 2005) UNCTAD ranking of countries according to the inward FDI performance index: MED lag behind at the international level: Lybia is at the bottom of the list (116), followed by Turkey (111), Egypt (108), Algeria (95), Lebanon (90), Israel (83). Better Tunisia (67), Morocco (65), Jordan (48) and Syria (39). CEECs position is far better for most countries: Bulgaria 12, Estonia 16, Slovak R. 25, Czech R. 28, Croatia 33, Romania 35, Poland and Albania 42, Hungary 46, Latvia 47, Lithuania 59, Slovenia 60, Macedonia 72. Potential of MED in 2003: ranking over 140 countries (Unctad, 2005):  Potential of MED in 2003: ranking over 140 countries (Unctad, 2005) UNCTAD ranking of countries according to the inward FDI potential index in 2003: USA (1), China (12), Slovenia (28), while Egypt 75 Morocco 87, Syria 95! The MED (excluding Israel) all from 60 downward. Evolution of Performance :  Evolution of Performance Only in few MED changes occurred over the last decade through economic reforms and the adoption of more friendly policy towards investors have translated into significant improvement. This is suggested by the evolution of the performance index over the period 1993-95 and 2000-2002. Jordan, Algeria and Lebanon have realised an important increase in the index of development of FDI. But Tunisia, Egypt, Morocco, Syria, Turkey show a negative evolution. Evolution of Performance:  Evolution of Performance Evolution of Potential:  Evolution of Potential Most of the countries with upsetting FDI performance (Turkey, Tunisia, Morocco, Egypt, Syria) have had a negative or static dynamic also as far as the potential index is concerned Only Israel shows a big increase in potential from 0,20 to almost 0,40 Evolution of Potential :  Evolution of Potential Perfomance and Potential:  Perfomance and Potential Comparing the Potential Index value with the Performance Index value gives an indication of how each country performs against its potential. Countries in the world can be divided into the following four categories: front-runners (countries with high FDI potential and performance); above potential (countries with low FDI potential but strong FDI performance); below potential (countries with high FDI potential but low FDI performance); under-performers (countries with both low FDI potential and performance Perfomance and Potential:  Perfomance and Potential In the figure below, it is shown the position of the 10 Mediterranean partners with respect to both these two indicators in the period 2000-2002. On the horizontal axis, it is portrayed the Performance index and on the vertical axis the Potential index. For comparison, to measure the distance of Mediterranean economies from international partners, there are also countries with high and average potentials, such as USA, China, Poland, Venezuela. Striking the potential value of China and Poland, quite close competitors for MED. Perfomance and Potential Index:  Perfomance and Potential Index Four partitions of the figure: MED with high (low) performance those which on the horizontal axis intercept value of the inward FDI performance index above (below) one countries with high (low) potential those with a potential index above (below) the average for the Mediterranean area (South and North) as a whole Perfomance and Potential Index:  Perfomance and Potential Index 1) MED with high performance combined with high potential (frontrunners): only Israel, close to Spain, France, Slovenia, Portugal and Cyprus. 2) MED with high performance but low potential (countries “above their potential”): Morocco, Tunisia, close to Albania, Croazia, Macedonia. 3) MED with worrying position both as performance and as potential (“underperformers”), above all Egypt, Turkey, Syria, but also Jordan, Algeria, Lebanon. Why so little FDI?:  Why so little FDI? Does the current situation with both low performance and low potential and with some countries even showing performance “above their potential” suggests that MED have reached an equilibrium although of low level? What role is played by distortions of an institutional and policy type that economic agents are submitted to in MED? Determinants of FDI :  Determinants of FDI pick up the determinants of FDI flows to a large sample of host economies: a gravity model is estimated to this purpose with panel data techniques based on aggregate country-level data on bilateral FDI flows of fourteen European countries and two non EU countries (USA and Japan) into a large sample of developed and developing partners (84), using among the relevant explanatory variables also institutional and policy factors for the years 1994-2004 Simulation analysis:  Simulation analysis Use these estimates to perform forecasts for FDI flows to both the single CEECs and Southern Mediterranean countries, subsequently comparing these estimated flows to actual flows For CEECs, the stock adjustment might have already taken place. Hence, actual and expected flows should not be strongly misaligned. On the contrary, we would expect that actual capital flows to MED are much below the expected flows because the stock adjustment process still has to take place. However, the current situation although not corresponding to an optimum allocation of resources, might also correspond to an equilibrium taking into account the distortions of various types that economic agents are submitted to in MED (actual flows not below expected). Diversion of FDI from MED to CEECs?:  Diversion of FDI from MED to CEECs? Here we use the gravity model to assess whether changes in FDI flows to CEECs which are economically integrating appear to be associated with negative changes in FDI flows to MED. Our methodological approach is based upon that of Sapir (1997) who sought to identify whether a “domino effect” had characterised the impact of European integration upon bilateral trade flows. We experiment by including interaction of regional dummies with dummy variables for particular sub-periods: 1994-1998 (transition period), 1998-2004 (pre-accession period) and for years, checking how regional dummies change. Choice of the model: underlying theoretical reasons:  Choice of the model: underlying theoretical reasons Why firms produce abroad and face additional costs instead of simply servicing the markets via exports? Dunning (1977, 1981), the “OLI framework”, considers FDI as determined by Ownership, Location and Internalisation advantages which the MNC holds over the foreign producer. The so-called “New Theory of FDI” takes inspiration from the OLI approach and refers mainly to the Ownership and Location advantage to introduce MNCs in general equilibrium models, where they arise endogenously. The early literature (Helpman 1984, Helpman and Krugman 1985) was mainly able to explain ‘vertical FDI’, i.e. investment that takes place in order to take advantage of differences in relative factor endowments (hence in factor prices) across countries. Other theoretical explanations:  Other theoretical explanations There are also ‘horizontal’ FDI: similar types of production activities, owned by MNCs, taking place in different countries. This phenomenon is better clarified if multinational activity is not driven by factor endowments differences, but rather by the trade-off between proximity and concentration (Brainard 1993; Markusen and Venables , 1995). The proximity advantage stems from ‘firm-level’ economies of scale, whereby R&D activity (or any other type of ‘knowledge capital’) is transferable to affiliates and allows MNCs to be closer to the foreign market. The concentration advantage derives from traditional ‘plant-level’ economies of scale, which make it more profitable to concentrate production in one location and then export. Whenever the former outweigh the latter, foreign investment will take place, and this will be more likely the higher are intangible assets relative to fixed costs of opening up an affiliate and the higher are transport costs, which are assumed to be positive and an increasing function of geographical distance in this model. Gravity model:  Gravity model When we get to the empirical analysis, to compare ‘attractiveness’ across countries and explain the geographic distribution of FDI we need a model that can pick up all these common determinants. To synthesise the two approaches discussed above, i.e. Helpman and Krugman’s treatment of vertical FDI and Brainard’s of horizontal one, we will include in the model the following main variables: a measure of the ‘economic space’ between the two countries, given by the sum of the two GDPs and by the two country’s populations to catch the ‘market-seeking’ aspect of FDI the relative factor endowments, an index of countries’ similarity in size measured by their relative GDP. additional variables, such as distance, a common language, a common border, or preferential trade agreements, that may reduce the costs (transaction and transportation costs) of locating abroad and which can be introduced via dummy variables. This type of gravity model approach has been already applied to studies of FDI as a means of picking up the common determinants of FDI flows across countries (Eaton and Tamura, 1996; Brenton and Di Mauro, 1999). Enlarged gravity model:  Enlarged gravity model We apply this type of model but we propose a “broad” version: factors traditionally considered in gravity models such as proximity and market size should make countries attractive locations for FDI and should play a decisive role, but … moving from the consideration that the success of FDI attractiveness of CEECs was mainly due to the prospects of EU membership and to the fact that most CEECs have succeeded in attaining both institutional and political stability ….we attempt to explain FDI shortfalls of MED with a gravity model enlarged to include policy and institutional factors Specification:  Specification ln (Bilat FDIijt) = traditional gravity: β0 + β1 ln SUMGDPijt + β2 ln POPit + β3 ln POPjt +β4 lnDiffGDPPCijt +β5 ln Distij + β6ln Areasij + β7 LLij+ β8 Borderij + β9 Langij + β10 Colonialij + policy and instit.: + β11 Regionalijt + β12 ln (IMP/GDP)jt + β 13 ln (M2/GDP)jt + β 14 ERVijt + β 15 CUijt + β16 Govijt + β17 FTAijt +β18 Humcapjt +β19 Current + β20 Capital + regional and time dummies: + β21 EUij + β22 MED+ β23 CEECs + β24 YEARDummies where: i and j denotes donor and host country respectively, t denotes time FDIij is the value of the FDI flow from country i (home country) to country j (host country) and the variables are defined as follows: Traditional gravity variables:  Traditional gravity variables SUMGDPijt is the sum of nominal value of the gross domestic product in i and j POPi and POPj, is the population of i and j DiffGDPPCijt is the absolute difference in per capita income between i and j (a proxy for relative factor endowment) Distij is the Great Circle Distance between i and j in miles Areas is the sum of the areas of i and j in square kilometres (hence a proxy for distance within the country to the border), LLij is a dummy variable, which is 0 if no countries are landlocked, 1 if one partner is landlocked Borderij is a binary variable, which is 1 if i and j share a border and 0 otherwise Langij is a binary variable, which is 1 if i and j share an official language and 0 otherwise Colonialij is a binary variable, which is 1 if i colonized j Further variables:  Further variables Regionalijt is a binary variable, which is 1 if i and j belong to a Regional Trading Agreement in year t IMP/GDPj a proxy for the openness of a country to foreign trade ERVijt is the volatility of the bilateral nominal exchange rate between i and j in period t CUijt is a binary variable, which is 1 if i and j use the same currency at time t Govjt is the sum of six governance indices of j at t FTA is a dummy variable defined as 1 if only one of the countries is in a regional trading agreement (and 0 otherwise) proxi measure of trade diversion Current and Capital are variables coded 1 if host country has current and capital account restrictions respectively MED is a dummy variable which is 1 when host countries are MED10 countries, CEEC is a dummy variable for belonging to CEEC10, EU is a dummy variable for EU membership of i. Instability of FDI over time:  Instability of FDI over time Data on FDI flows at which we are looking here may be considerably biased upward or downward in a particular year For instance, a large merger and acquisition deal has taken place or a substantial portion of the domestic corporate sector has been privatized. Great instability in the coefficients over time. Year dummies are introduced to solve this problem. Empirical results:  Empirical results Here we present the results of the regression analysis of bilateral FDI flows by major investing countries over 1994-2004. The gravity model introduced is used to define a "normal pattern" of bilateral FDI flows. Dummy variables are included for three groups of countries EU, CEECs, MED10 to get a very preliminary test for a possible divergence from this pattern. If the corresponding coefficients are significant and negative, we interpret this as evidence that the group has received less FDI than other countries after controlling for all the other factors. Therefore, the group concerned can expect to benefit from further large FDI inflows as foreign investors adjust their stocks to the new opportunities created by economic transformation. If the dummies are not significant, the future growth of the FDI flows can be expected to be in line with changes in the determinants of FDI. Determinants I:  Determinants I First focus on few variables at the core of gravity models: sum of GDP (a measure of mass), Population, Distance (measure of transport and transaction costs). The “gravity variables” have all the expected sign: Increased ‘economic space’ (SUMGDP and Population) have a noticeable impact on FDI. Elasticity of bilateral FDI with respect to population larger than 1. Distance appears to harm FDI something which is more intuitive in the case of exports. However, non linear relationship: squared distance positive. Also theory suggests that firms will tend to prefer FDI to exports as trade costs, as proxied by distance, rise. More distant markets will tend to be served by overseas affiliates rather than by exporting. Differences in relative factor endowments have a negative impact on FDI; from the theoretical discussion above one can infer that, on average, EU investors are in general more prone to horizontal than to vertical FDI. Regional Dummies::  Regional Dummies: MED negative and significant at 10% CEECs positive but not significant EU positive and significant at 1% . Determinants I:  Determinants I ------------------------------------------------------------------------------ Log FDI | Coef. Std. Err. z P>|z| ----------------------------------------------------------------------------- Log sum gdp | .1151378 .0075292 -15.29 0.000 Log population host | .8594187 .0551189 15.59 0.000 Log population donor | 1.304252 .0645561 20.20 0.000 Difference of GDP p.c. | -.9031703 .048244 -18.72 0.000 Distance | -3.99e-07 6.29e-08 -6.35 0.000 Distance2 | 2.32e-14 4.06e-15 5.72 0.000 EU | .648041 .1534813 4.22 0.000 MED10 | -.5623256 .314175 -1.79 0.073 CEEC10 | .0778871 .2526697 0.31 0.758 _cons | -27.60273 1.496819 -18.44 0.000 ------------------------------------------------------------------------ Determinants II: “enlarged gravity”:  Determinants II: “enlarged gravity” As expected Border, Language, Regional agreement all have positive and significant effects on FDI levels. CU is significant and positive. FTA not significant effect, indicating that for the full sample there has been no discernible trade diversion effect of FTAs. Colonial links not significant too. The import on GDP coefficient is also not significant. Volatility of exchange rate is positive and significant: FDI more stable and less risky than portfolio and trade activities? Governance is highly significant with positive sign (very robust variable). Current and capital account restrictions are both negative and highly significant. Regional Dummies::  Regional Dummies: MED no more significant : all the negative difference with respect to other countries seems to be explained by the institutional and policy variables CEECs after introducing the institutional variables becomes negative and significant: the group has received less FDI than other countries after controlling for all other factors. EU not significant: the future growth of the FDI flows can be expected to be in line with changes in the determinants of FDI. Simulation Analysis: Actual vs. Expected FDI :  Simulation Analysis: Actual vs. Expected FDI The simulation concerns the expected or “normal” FDI flows to each single MED and CEECs (that would be expected based on the empirical benchmark model described above) compared with actual FDI flows. Our expectation would be that, if the adjustment process was quite fast (slow) FDI flows are above (below) the average level of flows expected to countries with comparable attributes. For MED we would expect not to observe a strong catching-up effect in the past years in spite of the fact that these economies are underdeveloped as compared to average industrialised countries and in need to adjust and to catch up too. Germany FDI flows to MED: simulated in % of actual :  Germany FDI flows to MED: simulated in % of actual Italy FDI flows to MED: simulated in % of actual:  Italy FDI flows to MED: simulated in % of actual Simulation results by country:  The calculations for these four MED indicate that most of them attracted almost 100% of the total expected FDI inflows. A downward shift in inflows for Israel with slight increases for Egypt and Morocco. Simulation results by country Diversion of FDI from MED to CEECs?:  Diversion of FDI from MED to CEECs? Here we use the gravity model to assess whether changes in FDI flows to CEECs appear to be associated with changes in FDI flows to MED. In particular, we check whether increasing CEEC integration over the 1990s, culminating into the accession for most of them, had any noticeable negative impact upon FDI flows from EU countries going to the MED10. We experiment by including the interaction of regional dummies with time dummies for particular sub-periods: 1994-1998 (transition period), 1998-2004 (pre-accession period) and for years. Results by years::  Results by years: Interaction of regional dummies with time dummies: how they have been changing over two periods (1994-1998, 1999-2004)? and year by year? Negative and significant dummy for CEECs both in 1994-1998 and in 1999-2004 (most years show a negative and significant dummy). For MED negative and significant for the first period but not significant and positive in the second period (in each year from 1999 to 2003). Diversion of FDI from MED to CEECs?:  Diversion of FDI from MED to CEECs? We find that MED countries in the 1994-1998 were receiving substantially less FDI than could be expected on the basis of their incomes and proximity to the EU and to other variables. However, the magnitude of this ‘underpotential’ weakened in the late 1990s and in the first half of the 2000s which may suggest that the enlargement process did not adversely affected the magnitude of inward FDI from EU countries. Hence, our, albeit limited, analysis finds no evidence to suggest that the intensification of FDI in CEECs, following integration with the EU, has had a discernible dampening effect on FDI flows going to MED. Conclusions:  Conclusions The current situation of FDI in MED although does not correspond to an optimum allocation of resources corresponds to an equilibrium taking into account the distortions that economic agents are submitted to. Rejection of the hypothesis of FDI diversion away from the MED. FDI in these countries have come down but institutional and policy variables the main reason. It is from the issue of the FDIs that one can best perceive the necessity to modify the business environment and the behaviour of the enterprises but also the role of anchorage which EU can play. During the same period, Eastern Europe offered promising long term perspectives on this ground enhanced by the perspective of adhesion which also offered investors a guarantee of regulatory and institutional reforms Industries that faced difficulties (most of the time public ones), have been privatised and restructured under the impulse and with the help of Europe, a process that did not take place at a sufficient scale in the MED As a result CEECs moved towards a deeper integration not limited to a few tariff evolutions and are progressively adapting their legal framework and their practices to international standards

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