Republic of Poland
Selected Issues
Author: International Monetary Fund
Publication Date:
18 Apr 2008
eISBN:
9781451832044
Language:
English
Keywords:
ISCR; CR; EU fund; nominal exchange rate; fund; exchange rate; government wage bill; recipient country; monetary policy; EU inflow; EU fund shock; EU fund impetus; Real exchange rates; Income; Consumption
Download PDF (2 MB)

This paper provides three policy lessons to take full advantage of the opportunity afforded by EU funds. The main features of the global integrated monetary and fiscal (GIMF) model and how it was modified to account for income convergence are discussed. The impact of EU funds as exhibited in the model and highlights potential risks related to the authorities’ policy choices, in particular in the fiscal area, are also discussed. The macroeconomic literature on the impact of EU funds can be divided into broad groups: model simulations and econometric studies.

Abstract

This paper provides three policy lessons to take full advantage of the opportunity afforded by EU funds. The main features of the global integrated monetary and fiscal (GIMF) model and how it was modified to account for income convergence are discussed. The impact of EU funds as exhibited in the model and highlights potential risks related to the authorities’ policy choices, in particular in the fiscal area, are also discussed. The macroeconomic literature on the impact of EU funds can be divided into broad groups: model simulations and econometric studies.

I. Macroeconomic Effects of EU transfers in New Member States1

A. Introduction

1. Large inflows from the European Union over the next few years could significantly impact macroeconomic outcomes. The European Union’s cohesion policy provides the basis for substantial transfers to member countries and regions that lag behind in terms of income or face particularly high unemployment. For the eight member states (NMS) that joined the union in 2004,2 and for the additional two that joined in 2007,3 this implies transfers that could exceed 3-4 percent of GDP per year during 2007-12 (Rosenberg and Sierhej (2007) and Appendix I). The growth dividend of such inflows continues to be debated, with opinions divided on whether they speed up convergence, on the channels through which these funds affect the economy and on their impact on resource allocation. A clear understanding of the macroeconomic impact of EU funds is however key to assessing current and future economic outcomes, hence informing policy alternatives.

2. The discussion of the impact of EU funds resounds with issues still debated in the aid and transfers literatures. These funds are essentially a cross-country transfer of resources, just like the Franco-Prussian War indemnity payments of the 19th century, the German reparation payments following World War I, or the official development assistance flowing annually into low-income countries. The growth dividend of aid continues to be disputed, but there seems to be a growing consensus in favor of the argument that aid boosts growth by increasing total savings (Bulir and Lane, 2004; Easterly, 2003; Tressel, 2007). In this respect, the real exchange rate behavior is critical, reflecting opposing forces exerted by a transfer’s income effects in the donor and recipient countries (Brock, 1996; Devereux and Smith, 2005). The impact of EU funds on incomes and savings should similarly be key in assessing their overall macroeconomic effect on NMS.

3. In addition, a full account of the macroeconomic effects of EU funds requires accounting for the NMS convergence process. The large income gap between these countries and the EU average is essentially a reflection of the NMS’s lower productivity and capital stock. Gains in both fronts currently underpin the rapid catch-up process; and, EU funds should further support convergence to the extent that they encourage investment, for example. But EU funds could also slow convergence if the associated wealth effect increases demand for leisure and decreases labor supply. In this paper, we modify the IMF’s Global Integrated Monetary and Fiscal (GIMF) model to reflect the convergence process underpinning the NMS’s economies, and use it to analyze the impact of EU inflows on the latter. We show the conditions under which the inflows would help speed up convergence, and the consequences on resource reallocation, intertemporal saving and investment decisions, and the real exchange rate. Our results also help assess the impact of EU funds inflows on inflation and government budget outcomes, impacts that should be brought to bear in identifying policy choices.

4. The rest of this paper is organized as follows. Section B offers a focused review of the vast aid and transfer literature that the paper builds on. Section C describes the main features of the GIMF model and how it was modified to account for income convergence. Section D spells out the impact of EU funds as exhibited in the model and highlights potential risks related to the authorities’ policy choices, in particular in the fiscal area. Section E concludes.

B. Review of the Literature

5. The EU’s cohesion policy is predicated on the theoretical argument that low-income countries need support to bridge their gap with the rich members of the union. Available growth models have different implications for the possibility of income catch-up (De la Fuente, 2002; Martin and Sunley, 1998; Rassekh, 1998; Temple, 1999). The standard Solow-Swan neoclassical model implies convergence of per capita output, while endogenous growth theories, by incorporating increasing returns and technological change, suggest that convergence in (per capital) levels does not take place but convergence in growth rates could. However, in either model, adverse sociopolitical conditions can delay or disrupt convergence; these conditions would thus require policy intervention, therefore validating EU’s cohesion policy to bring initial conditions to more comparable levels between regions, as noted by Boldrin and Canova (2001).4

6. Evidence on whether EU funds have been successful in the past in helping bridge the income gap is mixed.5 The macroeconomic literature on the impact of EU funds can be divided into two broad groups: model simulations and econometric studies (Everdeen et al, 2003; Bradley, 2005). Simulations could be interpreted as the ex-ante impact of EU funds—that is the effect they would be expected to have if they finance projects that are devised and implemented optimally and efficiently. Econometric studies, on the other hand, come closer to an assessment of the ex-post impact of EU funds:

  • Econometric studies offer meager support for the growth impact of EU funds. These studies generally base their conclusions on cross-country growth regressions. While some find evidence of a positive growth impact of EU funds (Fayolle and Lecuyer, 2000; Garcia-Solanes and Maria-Dolores, 2001), others present inconclusive results (Gaspar and Leite, 1994 and Cappelen and others, 2001), or only for open economies. Boldrin and Canova (2001) find no evidence of income catch-up in the EU after the mid-70s, even in the case of EU funds disbursements. Nor do they find evidence that supports the growth divergence theory, the platform on which the EU’s cohesion policy rests, in line with Tondl (1998), Fagerberg and Verspagen (1996), and Corrado et al (2005).

  • Conversely, model-based simulations tend to support the growth impact:

    • article image
      The first models to be used were macro-econometric models with conventional Keynesian demand-side features and backward-looking expectations, like the European Commission’s HERMES model and its successor, the HERMIN model (Bradley 2002, Bradley et al Chp 10 in 1; Bradley, 2002,). For Greece, Portugal, Ireland and Spain, which received some 1½ to 3 percent of GDP per year during the second half of the 90s, HERMIN simulations find that real GDP growth was boosted by between 1 and 4½ percent, but that income convergence would only increase by ½ to 2 percent by 2010.6

    • article image
      The European Commission has also drawn on dynamic general equilibrium (DGE) models with micro-foundations and forward-looking optimizing agents, like QUEST II, to evaluate the impact of EU funds.7 For EU fund programs over 1989–96, Roger (1996) finds that demand effects dominate in the short run, as the investments financed by EU funds take time to generate a growth impact, and points to a risk of real exchange rate appreciation and rising interest rates overshadowing the positive growth impact in the medium term. Nevertheless, the model predicts a permanent and positive supply-side impact on GDP in the long run.

    • article image
      Outside the European Commission, Pereira and Gaspar (1999) find, in a 2-sector endogenous growth model calibrated to Portugal, that annual EU fund inflows of 3½ percent of GDP during 1989–93 increased growth by about ½ percentage point a year (both in the short and long run), with a maximum impact when EU funds were spent on infrastructure rather than on human capital accumulation. Similarly, Gaspar and Pereira (1995), and Pereira (1997) find a positive growth impact of EU funds disbursed to Greece, Ireland and Portugal. In their survey paper, Goybet and conclude that overall the EU funds impact on annual growth reaches only 0.4 percentage point, a result comparable to what Lolos et al (1995) and Lolos and Theodoulides (2001) find for Greece over 198999 using a computable general equilibrium model.

7. The divergence between these two strains of evaluation can partially be explained by differences in methodology. Everdeen et al (2003) have noted that it is not surprising to find less favorable assessments from econometric (ex post) studies, as several factors can hinder the optimal use of EU funds (as assessed in ex ante model simulations)—such as crowding out, rent seeking, and capacity constraints. The findings of econometric studies may also be constrained by limitations in their approaches, from data availability and reliability to vulnerability to the Lucas critique or the ad-hoc specification linking EU funds to income growth rather than its level. On the other hand, model-based simulations require strong assumptions on structural parameters that may be hard to link to available data.

8. The literature on the impact of EU funds in NMS is less abundant. Lolos (2001), in discussing the possible impact of EU funds in NMS, interprets the past experience as suggesting a boost of ½ percentage point to GDP growth for each 1 percent of GDP additional funds. In its most recent cohesion report, the Commission evaluates, based on simulations of ECOMOD, HERMIN and QUEST, that by 2020, GDP would be increased by 3 percent on average across the NMS thanks to EU fund inflows. Bradley and others (2006) and the Magyar Nemzeti Bank (2006) exhibit similar results respectively for Poland and Hungary, while Kaczor (2006) finds a much smaller effect on GDP but improvement in employment, labor productivity, and prices in the near term. Bradley and others (2006) also note that the external current account would deteriorate over the period of EU funds inflows but turn into a small surplus thereafter.

9. This paper is closest to the work undertaken by the Commission with its QUEST model, but it enriches the analysis with new features. The model used here is also an intertemporal DGE model. However, rather than studying each specific EU member country, the analysis focuses in this paper on a representative NMS receiving EU funds inflows consistent with the newly released 2007–13 Financial Perspectives. Moreover, unlike QUEST, the model used here specifically models the ongoing convergence process of the NMS and traces the impact of the funds through various aspects of the NMS’s economies, not just GDP.

C. Modeling the Effects of EU Transfers to Converging NMS Economies

10. In this study, the macroeconomic effect of EU transfers is assessed using the Fund’s open macro model calibrated separately for the Central European and Baltics economies. The Global Integrated Monetary and Fiscal model (GIMF) is a large scale version of new open-economy macroeconomic models, with microeconomic foundations based on optimizing forward-looking consumers and producers under sticky prices, real and nominal rigidities, monopolistic competition as well as explicit cross-country linkages (Kumhof and others, 2007a; Kumhof and others, 2007b). The GIMF has a number of advantages over traditional large scale models.8 For our purposes, key features are non-Ricardian consumers—barriers to full intertemporal consumption smoothing are still pervasive in NMS—a richly defined production structure that includes public capital and allows intra-industry (in addition to final goods) trade across economies, the inclusion of a monetary sector with either a fixed exchange rate or an inflation targeting regime and of an explicit fiscal reaction function. We consider two types of recipient countries: moderately-sized, relatively open inflation targeters (CEEs, IT) and very small, very open fixed-exchange rate economies (Baltics, FE).

11. This study also tailors the GIMF model to capture the catch-up process currently experienced by these countries as well as the transfers of financial resources from the EU. We use a two-country version of the model, whereby the “home” country is an EU fund recipient and the “rest of the world” is represented by the EU15. Adjustments to standard model are the following:9

  • Convergence baseline: In contrast with the standard GIMF setting where both countries are already at the same level of development, we design a baseline scenario where the EU fund recipient country converges towards the EU15 level. More specifically, our baseline scenario has the NMS’s GDP per capita gradually rising from 60 percent of the EU15 level in 2003 to close to 75 percent twenty years later, through a catch-up in total factor productivity in the tradable sector (Figure 1).10 As a consequence, throughout the convergence path, both the labor productivity gap and the capital to labor ratio gradually close, capturing a trend of capital accumulation that would happen even in the absence of EU fund inflows. Part of the production shifts to the tradable sector as it becomes more productive. Still, the rise in demand also leads to a deterioration of the trade balance. Productivity gains in the tradable sector lead to wage increases that firms in the nontradable sector pass on to consumers, triggering an increase in nontradable prices related to tradable prices and generating a trend appreciation of the real exchange rate.

  • Impact of EU funds throughout the economy: We introduce cross-country transfers from the EU15 to the NMS in the model in the form of a flow of (financial) resources transiting through the current account. These transfers have to be spent in the year they are received. Furthermore, we distinguish between transfers to the private sector, which go directly to support households’ income, and transfers to the public sector, which finance public investment. In practice, some EU funds are also directed to private sector firms. These funds are not captured in this exercise but their impact is likely to be similar to those funding public investment in so far as they boost the capital stock.

  • Impact of public investment on total factor productivity (TFP): Given the nature of the EU fund infrastructure projects—a public good that will boost private firms’ profitability—we assume that they will have a positive impact on TFP, unlike in the standard model where TFP is exogenous and independent of the amount of capital stock. The elasticity of TFP to the public capital stock is calibrated based on the average estimate found in the literature (see Lightart and Suarez (2005)).11

Figure 1.
Figure 1.

Convergence scenario (baseline for shocks), 2003-40

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Source: IMF Staff estimates.

12. Other features of GIMF are maintained. The main features of GIMF relevant for this study include the following elements:

  • Households are forward-looking, and hence know that the EU transfers are only temporary. They own the firms and decide how to allocate their time between work and leisure. Except for a portion of households that do not have access to financial markets (liquidity-constrained households), all agents make their consumption decision inter-temporally. Other non-Ricardian features of the model include consumer myopia, declining lifecycle income profile that make future labor income taxes less relevant to lifetime wealth, and distortionary taxes.

  • Firms produce goods according to constant elasticity of substitution (CES) production functions using labor, capital, intermediate foreign and domestically-produced inputs. Goods and labor differentiation provides firms and unions (which buy labor from households and sell it to firms) with monopolistic market power. Because of nominal and real adjustment costs, macroeconomic variables respond only gradually to shocks.

  • Fiscal policy is countercyclical. Taxed levied on consumption, labor and capital as well as lump sum taxes provide resources for public consumption and investment. Over the long run, taxes adjust to stabilize the deficit balance at the government’s chosen target (assumed to be the average balance over the last ten years). In the short run, however, automatic stabilizers are allowed to work: temporary revenue windfalls from cyclical upturns are used to reduce debt, while the public balance is allowed to temporarily deteriorate under cyclical downturns.

  • Monetary policy in Central European countries reflects their inflation-targeting regime—with a target of 2½ percent—while in the Baltics the nominal interest rate follows the world interest rate as nominal exchange rates are fixed.12

13. The calibration is based on historical averages for the past decade (Table 1 and Appendix III). Values of the exogenous and steady state endogenous variables for the representative Central European NMS are constructed by averaging the corresponding data for the Czech Republic, Hungary, Poland, Slovakia and Slovenia over 1995–2005. Values for the representative Baltic NMS are constructed by averaging data for Estonia, Latvia and Lithuania over the same period. As for structural parameters, they were largely taken from the literature on Western Europe (Bayoumi, Laxton and Pesenti (2004), Everaert and Schule (2006)) or Chile (Kumhof and Laxton, 2007c), when these parameters were not available for NMS. In addition, we assumed lower adjustments costs to nominal variables in the Baltics than in Central European countries, as agents are expected to be willing to change prices more often when the nominal exchange rate—fixed in the former, flexible in the latter—is not available as an adjustment variable. The expected flow of EU transfers over 2004–15—as described in Appendix I—is used to calibrate the transfers in the model.

Table 1.

Selected Calibration Parameters

article image
Source: Eurostat; authors’ calculations.

14. The general equilibrium nature of GIMF precludes imbalances such as an output gap in the baseline scenario. The model is calibrated and solved for a steady state of smooth convergence vis-à-vis the EU15.13 Therefore, unlike macro econometric models, this set-up cannot reproduce exactly the past fluctuations of every variables of a specific country. In particular, it cannot capture the country’s position in the cycle but rather assumes that the starting point—that is, steady state, or baseline—is one in which the economy’s potential is consistently realized.14. For that reason, we chose to work with representative countries, instead of calibrating the model and running the shocks separately for every recipient country among the NMS. We therefore avoid giving the illusion of precision that the model does not have, and focus on identifying the core mechanisms at work.

D. Simulation Results and Lessons for Policymakers

15. To better understand the transmission mechanisms at work, we first consider the macroeconomic effects of allocating the entire amount of EU transfers either to boost households’ income or to augment public investment. The size and time profile of the EU inflows is calibrated using Rosenberg and Sierhej’s paper (2007). In the first case we examine, all transfers are grants to households; in the second case, transfers go through the government’s budget, which spends it entirely on public investment. In order to simplify the discussion, in each of these cases, all households are assumed to smooth their consumption pattern without any liquidity constraint. We later reintroduce liquidity constrains, however, when we evaluate the impact of the EU funds using the actual expected breakdown between income support and public investment.

uA01fig01

EU Funds inflows

(percent of GDP)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Case 1: All EU transfers as households’ income support:

16. Transfers are partly consumed immediately and partly saved, with only a marginal impact on real interest rates. Households use the transfers—which they know to be temporary—to smooth their consumption: they consume part of the transfers immediately, both in domestic and imported goods, lower their immediate labor supply and save the rest of the transfers. In this regard, the impact on the real interest rate is the result of opposing forces:

  • As the transfers are not entirely consumed immediately, the extra savings are invested abroad, and the net foreign asset position consequently increases. The savings also improve the current account when including the EU transfers.

  • At the same time, the extra immediate consumption puts pressures on domestic resources and hence on domestic real interest rates. Meanwhile, firms see their profitability reduced because of lower labor supply, which depresses their investment plans and consequently puts downward pressures on real interest rates: the additional consumption is initially achieved through lower resources devoted to investment.

  • The two forces on real interest rates more or less offset each other, and the real interest rate is virtually unaffected, with a very marginal increase in the short/medium term (period of EU inflows) and no change beyond that period.

uA01fig02

Consumption

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig03

Investment

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig04

Real Interest Rate

(in base point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig05

Net Foreign Asset Position

(in percentage point of GDP)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

17. The trade balance and competitiveness deteriorate. With lower labor supply and marginally higher interest rate, domestic production is not able to fulfill the surge in consumption, and the additional demand is satisfied through net imports. The current account excluding transfers deteriorates over the period of EU inflows. Lower labor supply pushes wage up. The resulting increase in production costs leads to domestic price pressures, triggering an appreciation of the real exchange rate expressed in terms of foreign versus domestic prices (external exchange rate).

uA01fig06

Exports

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig07

Imports

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig08

Current Account Excluding Transfers

(in point of GDP difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig09

Real Exchange Rate

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

18. Domestic production shifts towards nontradable goods, which is a standard Dutch disease effect. Households’ increase demand for the composite good generates more demand for both tradable and non tradable intermediary goods.15 As only tradable goods can be imported, domestic production shifts from tradable to nontradable goods; this shift is made possible through an increase in the relative price of nontradable goods; in other words, the exchange rate in terms of tradable to nontradable prices (internal exchange rate) appreciates too.

uA01fig10

Real exchange rate as the ratio of tradable to nontradable prices

(+=depreciation)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig11

Ratio of tradable to nontradable production

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

19. The boost to GDP from the EU transfers is short-lived, and convergence only marginally affected. Once the effects on prices and labor supply behaviors fade away, firms’ incentives essentially return to the pre-EU fund situation as productivity is unchanged. As a consequence, the initial demand-driven increase in GDP fully disappears as soon as the EU funds stop flowing in, and GDP per capita is virtually unchanged.

uA01fig12

GDP

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig13

Relative GDP per Capita

(in level)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Case 2: EU transfers financing public investment

20. The boost to public investment puts upward pressure on the real interest rate over the period of EU inflows, but relieves pressures in the long run, as productivity gains materialize. The transfers, as they finance public investment, affect the investment-saving balance and the immediate resources available for demand, through two channels:

  • High public capital raises private investment’s productivity and firms are willing to increase their investment program immediately, putting upward pressure on the real interest rate.

  • Similarly, households integrate in their consumption pattern the expectations that growth—and hence their income—will be hiked in the future by productivity gains. As a consequence, they bring forward part of this future wealth and increase their consumption immediately, leading to a decline in their savings effort in the initial period. As opposed to the case where EU funds finance households’ income support, labor supply moderately improves as no direct transfer comes to reduce households’ incentives to work.

  • As a consequence, the real interest rate rises significantly during the period of EU flows. Initially, the surge in demand has to be fulfilled with inelastic supply, something achieved through higher real interest rates and an initial dampening of firms’ investment plans: private investment is crowded out until enough output can be produced to cover both increased consumption and investment. Once the EU transfers stop flowing, pressures from private consumption diminish, as liquidity-constrained households have exhausted their income support. In the meantime, productivity gains generated by public and private investment boost supply over time, allowing the real interest rate to stabilize at a lower level in the long run.

uA01fig14

Consumption

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig15

Investment

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

21. The current account, even including transfers, deteriorates initially but competitiveness improves substantially in the medium and long run. With households saving less and the full amount of EU inflows used immediately to boost public investment—compared to the case 1 where EU funds inflows to households were partially saved—the pressures on domestic resources materialize more decisively and net imports surge. The net foreign asset position initially deteriorates (or does not improve), before recovering over the medium-run, as the investment effort eventually leads to increased competitiveness. After an initial appreciation due to demand pressures, the external real exchange rate gradually depreciates, as domestic production capacity builds up: being more productive, firms can sell at better prices than their foreign competitors. As a consequence, once transfers taper off, the recipient country experiences a sharp improvement in its trade balance.

uA01fig16

Real Interest Rate

(in base point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig17

Net Foreign Asset Position

(in change of percentage point of GDP)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig18

Current Account Excluding Transfers

(in point of GDP difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig19

Real Exchange Rate

(in percentage point difference, +=depreciation)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig20

Exports

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig21

Imports

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

  • The initial shift to non-tradable production is only temporary. The initial crunch on domestic resources leads to a shift of production to nontradable goods, as tradable goods are imported. However, production is quickly reallocated to the tradable sector once the EU fund inflows end, as the domestic exporting capacity gets boosted by the productive gains. The internal real exchange rate follows this pattern of production: it initially appreciates before depreciating once the flows of EU funds wanes.

  • As the EU funds are spent to spur the recipient’s productivity, the real effects on GDP outlive the inflows and thus provide a lasting income convergence effect. Relative GDP per capita compared to EU15 would be boosted by close to 10 percentage points compared to a no-EU funds scenario.

uA01fig22

Real exchange rate as the ratio of tradable to nontradable prices

(in percentage difference, +=depreciation)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig23

Ratio of tradable to nontradable production

(in percentage difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig24

GDP

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig25

Relative GDP per Capita

(in level)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Putting it together: three lessons for policymakers

22. First, gains from EU transfers—potentially substantial—will depend critically on the share on productive investment.16 We evaluate the impact of EU funds using the estimated breakdown between income support and public investment provided by Rosenberg and Sierhej (2007) (Figure 2). In this scenario, activity would be gradually but substantially boosted, with significant gains in terms of consumption and ultimately welfare.17 The impact on consumption would be more front-loaded, as liquidity-constrained households spend their gains immediately. However, it also appears clearly that most of the impact would derive from the funds spent on public investment: As exemplified by the stylized cases, EU funds channeled directly to households (a temporary demand shock) would have a very limited and short-lived effect, while the financing of public investment (a relatively long-lived supply shock) would generate most of the impact, as it fosters productivity and capital accumulation over time.18 In that respect, it is important to underscore that the difference in magnitude for GDP developments between the Baltics and Central European countries stems essentially from the EU inflow assumption: EU funds financing public investment are predicted to be larger and more front-loaded in the Baltics.

Figure 2.
Figure 2.

Average EU Funds Spending

(percent of GDP) 1/

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Source: Rosenberg and Sierhej (2007); IMF WEO.1/ The aggregation is derived from a simple average.
uA01fig26

GDP

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig27

Consumption

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig28

CEEs - GDP

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig29

Baltics - GDP

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

23. The trade balance would deteriorate, but EU transfers would more than offset it, leading to an improvement in the current account balance during the period of EU inflows. Imports would immediately increase under consumption and investment demand pressures, and also because, as foreign and domestic goods are used complementarily, increased domestic production would call for higher imports of intermediary goods. Meanwhile, exports would only gradually adjust upward, as it would take time for the increased installed capacity to translate into higher competitiveness. The bulk of the trade balance deterioration would, here again, derive from EU-financed public investment, as capital goods would be imported, but also because households would bring forward some of their consumption, in expectation of future growth. However, EU funds would still more than cover the deterioration in trade balance, so that the headline current account balance would moderately improve.

uA01fig30

Headline Current Account

(in point of GDP difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig31

Current Account Excluding Transfers

(in point of GDP difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig32

CEEs - Current Account Excluding Transfers

(in point of GDP difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig33

Baltics - Current Account Excluding Transfers

(in point of GDP difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

24. On the supply side, increased productivity would translate into higher production through stronger private investment effort in both the tradable and non-tradable sectors, not through higher labor participation. With public investment raising corporate productivity, private firms would react by increasing the capital stock and their labor demand. Capital stock accumulation would initially be hindered by the increase in real interest rate, but once the latter dissipates, private investment would be stimulated in both the tradable and non tradable sector (see also Appendix Figure 4c). This would not the case for labor however: with increased labor productivity, firms would increase their labor demand, but households, feeling richer from the transfers, would not increase their labor supply. Wages would be driven up to clear the market, and overall, labor would only be marginally modified by the EU transfers. However, labor would temporarily shift away from the tradable sector to the non tradable sector, to fulfill higher demand in the non tradable sector, while imports of tradable goods would compensate for temporarily lower domestic tradable production. Of course, this result depends on the unemployment rate being close to its equilibrium level before EU fund inflows, a feature that is embedded in the model. Still, with many of the NMS economies currently nearing close to capacity limits, it is likely to be a reasonable approximation.

uA01fig34

Labor

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig35

Capital

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig36

Labor in Tradable Sector

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig37

Labor in Non Tradable Sector

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

25. Still, EU funds would not necessarily lead to appreciation and Dutch disease. Initially, and throughout the period of EU inflows, production would shift to the nontradable sector, and the internal real exchange rate (defined as the relative price of nontradable versus tradable price) would appreciate, as more of the domestic resources would need to be devoted to increase supply in nontradable goods. However, as the surge in public investment leads to an increase in competitiveness in the whole economy, fewer factors would be needed in the nontradable sector to fulfill demand, and production would shift back to the tradable sector, where the increased productivity would spur exports. In the meanwhile, the internal real exchange rate would gradually depreciate back to its value prior to the inflows. Obviously, the more EU funds would be devoted to public investment, the less likely the recipient country would be to get trapped into a Dutch disease phenomenon.

uA01fig38

Ratio of tradable to nontradable production

(in percentage difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig39

Real exchange rate as the ratio of tradable to nontradable prices

(in percentage difference, +=depreciation)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

26. Income convergence would be speeded up only because of EU-fund related public investment.19 The EU fund inflows invested in public infrastructure would allow for a considerable acceleration in the catch-up process, by close to 5 percentage points of GDP in the early 2020s. Conversely, EU fund inflows supporting households’ income would have virtually no impact on per capita GDP, because, as exemplified by the stylized cases discussed above, boosted consumption would be offset by a deteriorated corporate profitability, an appreciated real exchange rate, and lost competitiveness (See also Appendix Figures 5b and 6b).

uA01fig40

Relative GDP per Capita

(in level)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

27. Second, real variables behave similarly in both exchange rate regimes, but the adjustment is achieved differently and at a different pace in each regime.

uA01fig41

Real Exchange Rate

(in percentage point difference, + = depreciation)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

  • In both the inflation targeting and the fixed exchange rate regimes, the real external exchange rate (defined as the ratio of domestic versus foreign prices) would briefly appreciate, before experiencing a sustained depreciation throughout the period of EU fund flows, as the positive productivity shock from EU- financed public investment gives these countries a competitive edge on foreign markets. The way the real exchange rate depreciation would be achieved, however, would differ substantially across regions, depending on which parameters can move more quickly. In the inflation targeting regime, the nominal exchange rate can depreciate freely, whereas in the fixed exchange rate regime, prices have to bear the full adjustment. So, in the CEEs, the currency would depreciate, while in the Baltics, inflation would be subdued during the whole period of EU transfer inflows, as a way to achieve real depreciation.

  • Similarly, the real interest rate would increase in both regions, temporarily crowding out private investment, but because of difference in speed of adjustment, the real interest rate would increase slightly more rapidly in the Baltics than in the CEEs. The mechanisms at play would also differ between regions: with nominal interest rates set at foreign levels in the Baltics, the disinflation generated by the EU fund-related productivity shock would raise real interest rates. In inflation-targeting CEEs, the nominal exchange rate depreciation would generate price pressures that monetary policy makers would counteract by hiking nominal interest rates. As a consequence, private investment would be initially depressed by higher borrowing costs. However, this effect would be short-lived, as public investment would eventually boost private capital’s marginal productivity.

uA01fig42

CEEs - Nominal Exchange Rate

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig43

Baltics - Inflation

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig44

Real Interest Rate

(in base point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig45

Investment

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig46

GDP

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

28. Inflation targeters would not benefit from modifying their monetary policy framework post EU funds inflows. In Central European countries, softening the inflation targeting regime to deal with short term pressures would end up being counterproductive: In their forward-looking behaviors, households would fully anticipate the shift in monetary policy approach, and eventually the monetary authorities would have to increase rates more sharply to counter-act a sharper rise in inflation, with no gains on the real economy.20 At the end, real interest rates would increase by as much as in the baseline scenario, and the impact of EU funds on the real economy would remain unchanged. Therefore, while the monetary authorities should use the full range of the inflation targeting bands, they should be careful not to be perceived as loosening their mandate to accommodate for the EU fund impetus. If so, they only stand to loose credibility, which would have to be regained at the cost of tighter monetary policy.

uA01fig47

Inflation

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig48

Real Interest Rate

(in base point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

29. Third, NMS countries would benefit from a counter-cyclical and conservative fiscal policy during the period of EU fund inflows for at least three reasons:

uA01fig49

Public Debt to GDP

(in percentage point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

uA01fig50

Tax rates

(in point difference)

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

  • Decreasing public debt. The full play of automatic stabilizers would allow for a decrease in public debt of at least 5 percentage points of GDP, if all additional temporary public revenue fiscal policy derived from the adjustment to the EU fund shock are saved and used to reduce public debt. Moreover, in the model, the permanent impact of the EU fund on the economy, induced by the higher productivity, enables a decline in tax rates of 2/3 percentage point over the period 2003-15, but these cuts are reverted at the end of the fund inflow period.21 If the authorities were to forgo this change in taxation—as reverting the policy by 2015 could be costly—the fiscal consolidation concomitant with EU fund inflows could even be larger. Such a strategy would be particularly welcome in some of the Central European countries whose public debt ratio is hovering around the Maastricht criteria, as a relatively seamless approach to reduce debt to less vulnerable levels.

  • Uncertainty about the efficiency of EU fund. There is still a large uncertainty surrounding the efficiency of EU funds and the exact private income support-public investment distribution of EU funds. The larger the share devoted to public investment, the more sustainable the boost to public revenue. However, if the authorities were to rely on these revenue, but EU funds to fund mostly income support, the fiscal position could end up being more deteriorated at the end of the period of EU fund inflows. The existing uncertainty should therefore warrant a cautious and conservative approach, where buoyant revenue in the upcoming ten years should be mostly saved. In countries where the public expenditure ratio to GDP is already high, one could even argue for a need to at least partially offset the increase in EU-funded public investment through cuts in other public spending.

  • Exacerbated demand pressures under pro-cyclical fiscal policy (Figure 3). If, instead of letting the automatic stabilizers play fully as in the baseline scenario, the authorities would only target a stabilization of their debt to GPD ratio, fiscal policy, by allowing sharper and more permanent declines in tax rates, would de facto be expansionary. Such a policy would act like a demand shock, next to the supply shock provided by the EU funds. As a consequence, compared to the baseline scenario, the initial real appreciation would be stronger and more prolonged, as the domestic supply side would not be ready initially to serve an even larger surge in demand. The monetary reaction would also be stronger in inflation targeting countries, and inflation less subdued in fixed exchange rate regime countries. At the end, the real interest rate tightening would be strengthened by the pro-cyclical policy. On the real front, the substantial lift in consumption compared to the counter-cyclical fiscal policy scenario would be fully (in the case of the Baltics) or even more than fully (in the case of Central Europe) offset by a stronger crowding out in private investment and the more appreciated currency. In both regions, the countries would be worse off in terms of convergence.

Figure 3.
Figure 3.

Role of a Pro-Cyclical Policy on the Impact of EU Funds, Comparison with the Baseline Scenario of Counter-Cyclical Fiscal Policy

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

E. Conclusion

30. New Member States stand to benefit greatly from EU fund inflows in the next ten years. EU fund inflows could boost GDP per capita relative to the EU by as much as 5 percentage points, therefore substantially accelerating the ongoing convergence process. Still, such benefits should not be taken for granted, and the authorities would need to set the right institutional and policy framework to avoid potential pitfalls.

31. This study provides three policy lessons to take full advantage of the opportunity afforded by EU funds:

  • The EU funds need to be directed predominantly to public investment rather than to income support, a prerequisite for the derived lift in overall productivity to speed up the convergence process. In addition, the focus on the supply side would guarantee that this occurs without undue pressures on monetary policy or prices and avoid the risk of a Dutch disease. In sharp contrast, the effect of funds directed to income support would be short-lived and would fail to deliver benefits in terms of additional convergence.

  • At the end of the day, real variables would be affected similarly in both exchange rate regimes. In particular, the EU fund inflows would lead to a depreciation of the real equilibrium exchange rate in the medium-run, if indeed funds are used to bolster supply, and the real interest rate would increase during the period of inflows. The only differences would be in the pace of adjustment, foreseen as slightly more rapid in the Baltics, and in the variables at play in the adjustment: In the CEEs where the currency floats freely, the equilibrium nominal exchange rate would depreciate, while in the Baltics, the real exchange rate depreciation would be achieved through lower inflation. Still, in both regimes, the larger the share of EU funds directed to income support, the greater the risks of stoking a demand boom in the region, and thereby reinforcing overheating forces and generating real appreciation pressures.

  • To best accompany the EU fund inflows the policy-mix would have to combine conservative and counter-cyclical fiscal policy with a strong commitment to the existing monetary regime. Neither a more accommodative fiscal policy nor a softening in monetary policy commitment would provide any additional boost to the real economy. On the contrary, a more pro-cyclical policy would run the risk of boosting unduly the demand side, with a build-up in either inflationary or monetary pressures that would eventually hold convergence back. In inflation-targeting countries, a more backward-looking monetary policy would eventually result in sharper interest rate hikes to counteract higher price pressures, with no effect on the real side.

References

  • Angel de la Fuente, Convergence across Countries and Regions: Theory and Empirics, Instituto de Análisis Económico (CSIC), November 2002

    • Search Google Scholar
    • Export Citation

  • Barry and others, “The Single Market, the Structural Funds and Ireland’s Recent Economic Growth,” in Journal of Common Market Studies (Sept 2001) Vol. 39 No. 3 pp. 537–52

    • Search Google Scholar
    • Export Citation

  • Bayoumi T., D. Laxton, and P. Pesenti, (2004), “Benefits and Spillovers of Greater Competition in Europe: A Macroeconomic Assessment,” ECB Working Paper 341.

    • Search Google Scholar
    • Export Citation

  • Boldrin, M. and F. Canova (2001), “Inequality and convergence in Europe’s regions: reconsidering European regional policies,” Economic Policy, Vol. 16, Isssue 32, April 2001, pp.205–53.

    • Search Google Scholar
    • Export Citation

  • Boldrin, M. and F. Canova (2003), “Regional Policies and EU enlargement”, CEPR Discussion Paper Series No. 3744.

  • Bradley J., (2002), “An Examination of the Ex-Post Macroeconomic Impacts if CSF 1994–99 on Objective 1 Countries and Regions, ESRI (Ireland), December 2002.

    • Search Google Scholar
    • Export Citation

  • Bradley J, (2005), “Promoting Cohesion in the Enlarged EU: Is There A Role For National Development Plans?,” Chapter 8 in Integration, Growth and Cohesion In An enlarged European Union, by Bradley J., Petrakos G., and Traistaru I., editors, New York: Springer, 2005, pp. 173–205.

    • Search Google Scholar
    • Export Citation

  • Bradley (2007) Evaluation for Estonia.

  • Bradley J. and others, (2005a), “HERMIN: A Macro Model Framework For the Study of Cohesion and Transition,” Chapter 9 in Integration, Growth and Cohesion In An enlarged European Union, by Bradley J., Petrakos G., and Traistaru I., editors, New York: Springer, 2005, pp. 207–241.

    • Search Google Scholar
    • Export Citation

  • Bradley J. and others, (2005b), “Macro Impact Evaluation of National Development Plans: Ireland and Estonia,” Chapter 10 in Integration, Growth and Cohesion In An enlarged European Union, by Bradley J., Petrakos G., and Traistaru I., editors, New York: Springer, 2005, pp. 243–274.

    • Search Google Scholar
    • Export Citation

  • Bradley J., Zaleski, Tomaszewski and Zembaty, (2006), “Evaluating the Combined Impact of NDP 2004-06 and NSRF 2007–13: An Analysis Based on the polish HERMIN Model,” Wroclaw Regional Development Agency, Working Paper March 2006.

    • Search Google Scholar
    • Export Citation

  • Brock, P., (1996), “International Transfers, the Relative Price of Non-Traded Goods, and the Current Account,” in The Canadian Journal of Economics, vol. 29, No. 1 (February), pp. 163–180).

    • Search Google Scholar
    • Export Citation

  • Bulir, A., and T. Lane, (2004), “Aid and Fiscal Management,” in Helping Countries Develop: The Role of Fiscal Policy, by Gupta S., Clemens B., and Inchauste G., editors, Washington DC: International Monetary Fund, pp. 422–451.

    • Search Google Scholar
    • Export Citation

  • Cappelen A and others, (2003), “The Impact of EU Regional Support on Growth and Convergence in the European Union,” Journal of Common Market Studies, Vol. 41, No 4, pp. 621–644.

    • Search Google Scholar
    • Export Citation

  • Corrado, L., R. Martin and M. Weeks (2005) Identifying and Interpreting Regional Convergence Clusters across Europe, Economic Journal 115 (March) pp. C133–C160.

    • Search Google Scholar
    • Export Citation

  • Devereux M. and G. Smith, (2005), “Transfer Problem Dynamics: Macroeconomics of the Franco-Prussian War Indemnity,” Queen’s University, Department of Economics, Working Paper No. 1025

    • Search Google Scholar
    • Export Citation

  • Easterly, W., (2003), “Can Foreign Aid Buy Growth?,” in The Journal of Economic Perspectives, Vol. 17, No. 3, pp. 23–48.

  • European Commission (2006), “Allocation of 2005 EU Expenditure by Member State,” Directorate-General Budget, available at: http://ec.europa.eu/budget/library/documents/revenue_expenditure/agenda_2000/allo crep_2005_en.pdf

    • Search Google Scholar
    • Export Citation

  • European Commission (2007), “The Impact of Cohesion Policy,” Chapter 2 of Growing Regions, Growing Europe, Fourth Report on Economic and Social Cohesion, pp 95–133 http://ec.europa.eu/regionalpolicy/sources/docoffic/official/reports/cohesion4/indexen.htm.

    • Search Google Scholar
    • Export Citation

  • Everdeen and others, (2003), “Funds and Games,” ENEPRI Occasional Paper No. 3, October 2003.

  • Everaert L., W. Schule, (2006) “Structural Reforms in the euro Area: Economic Impact and Role of Synchronization Across Markets and Countries,” IMF Working Paper No. 06/137.

    • Search Google Scholar
    • Export Citation

  • Fagerberg, J., and B. Verspagen (1996), “Heading for divergence? Regional Growth in Europe Reconsidered,” in Journal of Common Market Studies, 34(3), pp. 431–48

    • Search Google Scholar
    • Export Citation

  • Fayolle J. and A. Lecuyer, (2000), “Croissance Régionale, Appartenance Nationale et Fonds Structurels Européens: Un Bilan d’Étape,” Revue de l’OFCE (73), pp. 165–196.

    • Search Google Scholar
    • Export Citation

  • Garcia-Solanes J. and R. Maria-Dolores, (2001), “The Impact of Structural Funds on Economic Convergence in European Countries and Regions,” Convergence Issues in the European Union, 2002, pp. 61–82, Cheltenham, U.K. and Northampton.

    • Search Google Scholar
    • Export Citation

  • Gaspar, V. and A.M. Pereira (1995), “The Impact of Financial Integration and Unilateral Public Transfers on Investment and Economic Growth,” Journal of Development Economics, 48(1), pp. 43–66.

    • Search Google Scholar
    • Export Citation

  • Gaspar V. and A. N. Leite, (1994), “Cohesion and convergence: The Economic Effects of EC Structural Transfers, Economia,” 18(0), pp 87–108.

    • Search Google Scholar
    • Export Citation

  • Genberg, H. (2005), “The Macroeconomic Effects of Adjustment Lending: A Review and Evaluation,” in The Journal of Policy Reform, Vol. 8, No. 1, pp. 1–40.

    • Search Google Scholar
    • Export Citation

  • Goybet, P. and M. Bertoldi (1994), “The Efficiency of the Structural Funds,” in Improving Economic and Social Cohesion in the European Community, J. Mortensen, editor, New York: St Martin’s Press, pp. 229–40

    • Search Google Scholar
    • Export Citation

  • Kumhof, M. and D. Laxton, 2007a, “A Party without a Hangover? On the Effects of U.S. Government Deficits,” IMF Working Paper No. 202 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Kumhof, M. and D. Laxton, 2007b, “The Global Integrated Monetary and Fiscal Model (GIMF),” mimeo (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Kumhof, M. and D. Laxton, 2007c, “Chile’s Structural Fiscal Surplus Rule: A Model-Based Evaluation,” Chile—Selected Issues Paper, Country Report No. 07/332 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Lighart J. and R. Suarez (2005), “The Productivity of Public Capital: A Meta Analysis?,”

  • Lolos (2001), “The Macroeconomic Effect of EU Structural Transfers on the Cohesion Countries and Lessons for the CEECs,” Interim Report No. IR-01–044 (October), International Institute for Applied Systems Analysis: Austria.

    • Search Google Scholar
    • Export Citation

  • Lolos, Suwa-Eisenmann, Zonzilo, Bourgignon (1995), “Evaluating the CSF With an Extended Computable General Equilibrium Model: The Case of Greece (1988–1995),” in Journal of Policy Modeling 17(2) pp. 177–197.

    • Search Google Scholar
    • Export Citation

  • Lolos and Theodoulides (2001), “The Role of EU structural Funds in the Development of Lagging Behind European Regions,” in Economic and Financial Modeling, Vol 8, No. 1 pp. 29–46

    • Search Google Scholar
    • Export Citation

  • Magyar Nemzti Bank, (2006), “The Impact of EU Funds on Potential Growth,” Chapter 2 in the Report on Convergence, pp. 49–65, December 2006.

    • Search Google Scholar
    • Export Citation

  • Martin, R. and P. Sunley, (1998) “Slow Convergence? The New Endogenous Growth Theory and Regional Development,” Economic Geography, Vol. 74, No. 3, pp. 201–227

    • Search Google Scholar
    • Export Citation

  • Pereira A.M. (1997), “Development Policies in the EU: An International Comparison,” Review of Development Economics, 1(2) pp. 219–35.

    • Search Google Scholar
    • Export Citation

  • Pereira and Gaspar (1999), “An Intertemporal Analysis of Development Policies in the EU,” in Journal of Policy Modeling 21(7) pp. 799–822

    • Search Google Scholar
    • Export Citation

  • Rassekh, F. (1998), “The Convergence Hypothesis: History, Theory, and Evidence,” in Open Economies Review Vol.9, pp. 85–105

  • Roger, (1996), “Macroeconomic Evaluation of the Effects of Community Structural Funds (CSF) With QUEST II, Paper prepared for the European Conference on Evaluation Methods for Structural Funds Intervention, Berlin,” December 2–3, 1996.

    • Search Google Scholar
    • Export Citation

  • Roger and In’t Veld, (2002), “Some Selected Simulation Experiments With the European Commission’s QUEST Model,” European Community DGEcFin No. 178, October 2002.

    • Search Google Scholar
    • Export Citation

  • Rosenberg, C., R. Sierhej (2007), “Interpreting EU Funds Data for Macroeconomic Analysis in the New Member States,” IMF Working Paper No. 07/77.

    • Search Google Scholar
    • Export Citation

  • Tondl, Gabriele (1998), The Changing Pattern of Regional Convergence in Europe. Robert Schuman Centre (EUI), RSC No. 97/53. Available at SSRN: http://ssrn.com/abstract=130688 or DOI: 10.2139/ssrn.130688

    • Search Google Scholar
    • Export Citation

  • Temple, J. (1999), “The New Growth Evidence,” Journal of Economic Literature, vol. XXXVII (March 1999) pp.112–56

  • Tressel, Thierry (2007), “Is There a Foreign Aid Paradox?,” IMF Research Bulletin, Vol. 8, No. 4, (December 2007).

Appendix I. EU Funds: What Is In The Offing?

EU funds to the NMS serve multiple purposes, ranging from income convergence to agricultural support. This is achieved by a myriad of individual programs which can be classified in three main categories (Rosenberg and Sierhej, 2007):

  • Agriculture support: these initiatives are part of the Common Agricultural policy available to the NMS. They provide price subsidies, direct payments to farmers, and support to rural development and fisheries.

  • Structural Funds: these aim at promoting catch-up in less developed regions, and at supporting areas with structural difficulties.

  • Cohesion Funds: these are available to countries with GDP below 90 percent of the EU average and directly support projects in infrastructure and environment.

Appendix Figure 1.
Appendix Figure 1.

Average EU Funds Spending

(percent of GDP) 1/

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Source: Rosenberg and Sierhej (2007); IMF WEO.1/ The aggregation is derived from a simple average. Countries in the Central Europe group are the Czech Republic, Hungary, Slovakia and Slovenia. Countries in the Baltics group are Estonia, Latvia and Lithuania.

Inflows from the EU could reach 4 percent of GDP per year in the beginning of the next decade in most of the NMS (Appendix Figures 1, 3a and 3b).22 Annual inflows have been gradually increasing since accession, to reach in 2006 on average 1½ percent of GDP in Central Europe and 3 percent of GPD in the Baltics. But with the 2004-06 plan disbursement coming to an end in 2008, inflows are expected to rise dramatically that year in Central Europe, where absorption so far has been relatively low, as the authorities will strive not to lose any amount to which they were entitled under that plan. Rosenberg and Sierhej (2007) forecast that by then EU transfers to Central Europe will average 2½ percent of GDP, and gradually rise to 3½ percent of GDP over the following five years, while they will hover around 3-3½ percent of GDP in the Baltics. The breakdown between private (largely farmers) and public recipients is close to even.

EU funds are projected to flow in to NMS more gradually than was the case for previous accessing countries, but GDP per capita relative to older members is also much lower (Appendix Figure 2). The profile of inflows is back-loaded for the current NMS, whereas new entrants in the early 90s, like Spain, Greece and Portugal -as well as Ireland - received the highest amounts in the first two years of accession, at close to 5 percent of GDP. The current slow pattern in some of the NMS is at least partly related to slow absorption rates and administrative bottlenecks, itself possibly linked to the relatively low initial relative GDP per capita: while in 1992, the large EU recipient countries’ GDP per capita reached on average 75 percent of the euro area, it was about 50 percent only in the Central European NMS and 45 percent in the Baltics in 2004.

Appendix Figure 2.
Appendix Figure 2.

EU Funds Payments and Relative GDP per Capita 1/

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Source: European Commission (2006), Eurostat, Rosenberg and Sierhej (2007), IMF WEO.1/ EU expenditures excluding administrative expenditures for Western European Members; EU payments including advances to Central European NMS.
Appendix Figure 3a.
Appendix Figure 3a.

Central Europe: EU Funds Spending, 2004-15

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Source: Rosenberg and Sierhej (2007), IMF WEO
Appendix Figure 3b.
Appendix Figure 3b.

Baltics: EU Funds Spending, 2004-15

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Source: Rosenberg and Sierhej (2007), IMF WEO

Appendix II. Modifications to GIMF

We are using here a version of the model that was available within the IMF in May 2007. It is derived from the version of the model used in Kumhof and Laxton (2007c), the “Chilean model” with contra-cyclical fiscal policy, in which the frequency was changed from quarterly to annual, and the raw commodity sector removed.

Introducing Convergence: Exogenous productivity shock

To generate the convergence baseline, the model is first calibrated in its steady state mode with the parameters described in Appendix III, and with the level of total factor productivity in the tradable sector in the home country (NMS potentially recipient of EU funds) at 45 percent of the one prevailing in the rest of the world (taken as the EU15).

The shock generating the convergence path that serves at the baseline for the EU fund shock consists of the following:

  • The long-term total factor productivity in the tradable sector of the home country (A_T_HO_SS) is risen from 45 percent to 80 percent of the level of the rest of the world.

  • Trade elasticities for both the home country (XI_D_HO and XI_T_HO) and the rest of the world(XI_D_RW and XI_T_RW) are gradually risen from 1.5 to 3.5. This change captures the increasing trade as the NMS converge towards average old EU members.

Modeling EU Funds Transfers

Home country external balance as well as households’ and government’s budgetary constraints were modified to reflect the inflows of EU funds. In addition, since the EU funds are defined in euros, namely the currency of the rest of the world, the impact of potential exchange rate evolution once the EU funds flow in was embedded, as EU funds were expressed in the national currency (value in euros multiplied by the nominal exchange rate):

  • The home country’s external balance was improved by the full amount of the EU transfers.

  • The households’ budgetary constraint was improved by the amount of EU funds devoted to the private sector. It was assumed that optimizing households and liquidity-constrained households would each receive a share of the funds proportionate to their share in overall population.

  • The government’s budgetary constraint was improved by the amount of EU funds devoted to the public sector, but with the rule that this amount is fully and immediately spent on public investment. None of the other expenditures are modified, and tax rates are only modified for the part of the fiscal improvement that is permanent (contra-cyclical fiscal rule). In addition, the overall increase in public investment also include a 15 percent co-payment paid by the government.

Given the positive externality expected from the EU-funded public investment projects, mainly in the infrastructure sector, we have added an endogenous impact of public investment on productivity: the exogenous overall TFP (A_HO) is endogenized, and made function of a long-term overall TFP (A_HO_SS) through an auto-regressive relationship. The long-term TFP is itself related to the overall stock of public capital (KG1_HO, derived from public investment) with an elasticity of 0.1:

LOG(A_HO_SS) = ALPHA_A_HO_SS * LOG(KG1_HO) + CONST_A_HO_SS, with ALPHA_A_HO_SS = 0.1.

Given that the stock of private already enters the production function as a productive factor (alfa_KG1_HO, calibrated at 0.1), it means that the overall elasticity of GDP to public capital stock amounts to 0.2. This corresponds to the upper limit in Lightart and Suarez (2005), who estimate it to range from 0.14 to 0.2.

Appendix III. List of Parameters Used for the Calibration of the model

article image
article image
article image

This corresponds to a fiscal rule that stabilizes the structural fiscal balance.

corresponds to a 75 percent probability of surviving 15 years

This parameter captures the decline in revenue at the end of the life cycle

The larger the elasticity (σ) the smaller the market power of agents, and the lower the mark-up of prices charged over marginal costs (σ/(σ-1)). An elasticity of 21 corresponds to a mark-up of 5 percent, an elasticity of 41 to a mark-up of 2.5 percent.

A 10 percent rise in public capital (resp. consumption) stock would increase GDP by 1.5 (resp. 0.1) percent.

Appendix Figure 4a.
Appendix Figure 4a.

EU Fund transfer shock, 2003-40

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Source: IMF Staff estimates1/ This corresponds to a shock where only the private flows are transferred to households
Appendix Figure 4b.
Appendix Figure 4b.

EU Fund transfer shock, 2003-40

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Source: IMF Staff estimates
Appendix Figure 4c.
Appendix Figure 4c.

EU Fund transfer shock, 2003-40

Citation: IMF Staff Country Reports 2008, 131; 10.5089/9781451832044.002.A001

Source: IMF Staff estimates
Appendix Figure 4d.