Journal Issue

Republic of Poland: Selected Issues

International Monetary Fund
Published Date:
August 2005
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I. What is Driving Investment in Poland?1

A. Introduction

1. Investment as a share of GDP rose sharply in Poland in the late 1990s, followed by a rapid decline during 2000–03. The decline remains somewhat of a puzzle, despite a number of competing hypotheses that have been offered. The objective of this paper to answer the following questions: (i) What factors were driving the broad movements of investment over the past decade? (ii) Did investment in the late 1990s exceed the amount suggested by fundamentals so that an investment overhang subsequently had to be worked out? and (iii) What are the prospects for investment recovery in the medium term—that is, can investment relative to GDP be expected to return to peak levels of the late 1990s? The structure of the paper is as follows. Section B provides a historical perspective on the evolution of economywide and sectoral investment in Poland and briefly summarizes possible determinants of investment. Section C analyzes the determinants of investment more systematically, using panel regressions based on sectoral data, and reports the results of in-sample and out-of-sample simulations. Section D offers concluding remarks and policy recommendations.

B. Historical Perspective

2. The early transition period saw a dramatic shakeup of the economy, followed by a rapid rise in investment during the second half of the 1990s (Figures 1 and 2). Prior to 1990, growth in Poland—a planned economy—had primarily taken place through fixed capital investment in heavy industry (Doyle, Kuijs and Jiang, 2001). By the eve of the transition, the stock of capital was fundamentally misallocated. In the early phase of the transition, as the liberalization of prices and international trade exposed inefficiencies, a sizable part of the capital stock became obsolete overnight. The ratio of investment to GDP fell throughout 1993–94, before staging a strong revival in the second half of the 1990s. Between 1995 and 1999, investment increased substantially in most of the RAM8 countries, but was especially rapid in those with a low initial investment-to-GDP ratio, including Poland.2 Despite this relatively rapid increase, Poland’s investment-to-GDP ratio remained substantially lower than in the other RAM8 countries throughout this period—except in 1999 and 2000, when investment in the Baltics declined sharply in response to the Russia crisis.

Figure 1.RAM-8: Gross Capital Formation, 1995-2004 1/

(in current prices, in percent of GDP)

Sources: Eurostat; and IMF staff calculations.

1/ RAM-8 comprises the Czech Rep., Estonia, Hungary, Latvia, Lithuania, Poland, the Slovak Rep. and Slovenia.

Figure 2.RAM-8: Change in the Investment-to-GDP Ratio, 1995-99 1/

Sources: Polish authorities; and IMF staff calculations.

1/ RAM-8 comprises the Czech Rep., Estonia, Hungary, Latvia, Lithuania, Poland, the Slovak Rep., and Slovenia.

3. After booming for half a decade, Poland’s investment plummeted during 2001–03 and has recovered only marginally since (Figures 1 and 3). This pattern has diverged considerably from those observed in the other RAM-8 countries, and has resembled more closely developments in investment in the EU-15 (Pelgrin, Schich, and de Serres, 2002).3 The remainder of the paper focuses solely on investment in Poland.

Figure 3.EU-15 and Poland: Investment, 1995-2004

(in percent of GDP)

Sources: Eurostat; and IMF staff calculations.

4. Developments in Poland’s total investment over the past decade were largely driven by changes in private sector investment (Figures 4 and 5). The sharp increase in the latter in the second half of the 1990s was to some extent accentuated by the privatization process, which led to the reclassification in the official statistics of a large number of public enterprises as private sector firms. This is consistent with the increasing share of the private sector in total output. Yet it is also likely that, once privatized, enterprises truly increased their investment activity.

Figure 4.Poland: Public and Private Investment Outlays, 1995-2003

(in percent of GDP)

Sources: Polish authorities; GFS; and IMF staff calculations.

Figure 5.Poland: Private Sector Output as a Share of Total, 1995-2003

(in percent)

Sources: Polish authorities; and IMF staff calculations.

5. Privatization significantly changed the sectoral composition of public sector investment (Figure 6). Public investment continued to be concentrated heavily in sectors providing public goods, such as public administration, education, health, utilities, and mining, the latter two reflecting delays in the privatization process. In other sectors with historically large public involvement, such as transportation and manufacturing, public investment fell to low levels.

Figure 6.Poland: Public Investment by Sector, 1995 and 2003

(in percent of total investment)

Sources: Polish authorities; and IMF staff calculations.

6. Changes in the sectoral composition of investment outlays coincided with the ongoing structural changes in the economy (Figures 7, 8, 9, and 10). Investment in manufacturing was by far the largest among all sectors, as the rapid structural changes in production led to a greater orientation toward western markets and increased the share of manufacturing in total production. Investment in real estate and the trade sector was relatively high, reflecting the underdeveloped nature of these sectors in the early stages of the transition. Substantial investment in the power and telecommunications sectors was the outcome of the modernization of these sectors. Investment growth was most rapid in the financial intermediation sector because of restructuring, privatization, and modernization. On the whole, those sectors whose real investment grew most rapidly in the late 1990s also experienced the most rapid decline of investment after 2000. This might be due to higher procyclicality in such sectors, but could also reflect overinvestment and related excess capacities. The effects of investment on output (as represented by the incremental capital-output ratio—ICOR) varied across the sectors, ranging from very low in some of the sectors with large shares of public investment (electricity, construction, and other community services) to very high in some of the most underdeveloped sectors (transportation, trade, and hotels).

Figure 7.Poland: Investment by Sector, 1991-2003

(in millions of constant 2001 zloty)

Sources: Polish authorities; and IMF staff calculations.

Figure 8.Poland: Index of Real Investment Outlays by Sector, 1991-2003

(1991 = 100)

Sources: Polish authorities; and IMF staff calculations.

Figure 9.Poland: Change in Investment by Sector

(in percent)

Sources: Polish authorities; and IMF staff calculations.

Figure 10.Poland: Incremental Capital-Output Ratio by Sector, 1995-2003 1/

Sources: Polish authorities; and IMF staff calculations.

1/ ICORs are the sum of real investment over the change in real output between 1995 and 2003.

7. A number of hypotheses have been put forward to explain the rapid growth of investment in the late 1990s and the subsequent sharp drop (Figures 11 and 12). The rapid investment growth until 1998 has been viewed by some as fueled by strong economic growth not only in Poland, but also in the EU—Poland’s main trading partner—possibly creating overly optimistic expectations about future demand growth for Poland. Other factors that could be behind the strength of investment in the 1990s include falling economywide unit labor costs relative to those in the EU, and FDI inflows, which played a crucial role in restructuring previously state-owned enterprises, creating competitive pressures, and upgrading managerial and technical expertise. FDI inflows also had important second-round effects on overall investment activity by promoting development of domestic suppliers’ networks. User cost of capital, which rose through 1997 while inflation was dropping, may have been a mitigating factor. The subsequent reversal in investment growth could have been related to the slowdown in the EU and the sharp tightening of monetary policy, which resulted in a substantial real appreciation of the zloty during 1999–2002. Additional factors that could have contributed to weaker investment in the early 2000s include institutional factors, such as elimination of tax breaks on investment from 2001, a more uncertain business environment as the number of economic areas requiring administrative permission to pursue economic activity increased and the number of legislative acts related to business activity (of which less than one-fourth can be attributed to requirements related to EU accession) rose (Paczocha and Rogowski, 2005). These institutional factors are difficult to quantify and thus are not included in the quantitative analysis of investment determinants below.

Figure 11.Poland: Factors Affecting Investment Growth, 1995-2003

Sources: Polish authorities; Eurostat; Datastream; and IMF staff calculations.

1/ Product of the real interest rate and the relative price of capital (the ratio of the investment deflator to the GDP deflator).

2/ Unit labor costs in Poland relative to the EU.

Figure 12.Poland: Factors Affecting Investment Growth, 1995-2005

Sources: Polish authorities; Eurostat; Datastream; and IMF staff calculations.

C. Panel Data Econometric Analysis of the Potential Determinants of Investment

8. In order to address the questions outlined in the introduction, it is necessary to estimate a relationship between investment and a number of its potential determinants. In the case of Poland, long-run time series are not available. Therefore, this study relies on panel estimation, drawing on a relatively underexplored data set on sectoral investment, output, and unit labor costs, as well as a variety of additional controls. This approach allows us to analyze investment in individual sectors, as well as the whole economy, and to build a simple model that can be used to simulate a future investment path. As investment in Poland is an underresearched area, the objective of this paper is to explore general hypotheses about the factors that determine investment.

Theoretical considerations

9. Theory suggests a number of possible determinants of investment:

  • Lagged real investment (sectoral). Investment is autocorrelated (investment inertia) because investment projects often span a number of years.

  • Lead real production (sectoral). A proxy for expectations of economic activity in the sector is used under the assumption of perfect foresight—higher expected domestic production would require additional investment.

  • Relative unit labor costs (sectoral). A proxy is used for cost effectiveness, defined as the unit labor cost (ULC) in Poland relative to those in the EU, and captures effects of exchange rate changes on competitiveness. Higher relative unit labor costs reduce competitiveness and thus investment.

  • Economic activity in the EU (aggregate data for the economy). This variable represents broader prospects for developments in the global environment not captured by the expectations of future production of each individual sector. A higher domestic demand in the EU leads to higher investment in Poland, which in turn will increase the country’s export potential in the tradable sectors. In the non-tradable sectors higher EU effect likely promoted investment via a positive confidence effect.

  • Real greenfield FDI (aggregate data for the economy). FDI inflows not only directly finance investment but also have important spillover effects for domestic investment, possibly with a lag.

  • User cost of capital (aggregate data for the economy). This represents the opportunity cost of investment. The user cost of capital is defined as the product of the real interest rate and the relative price of capital (the ratio of the investment deflator to the GDP deflator); lower user cost of capital tends to increase investment.

  • Profitability of the enterprise sector (aggregate data for the economy). It is measured in real zloty. To the extent investment is financed out of firms’ own resources, higher profitability leads to higher investment. In addition, large profits may attract new investment.

  • Exchange rate and interest rate volatilities (aggregate data for the economy). They serve as proxies for uncertainty. High volatility lowers the risk-adjusted rate of return and thus may hamper investment activity.

  • Dummy variable for the change in monetary policy regime (D). This is set equal to 1 for 1999–2003, when inflation targeting was in place. This dummy variable is used interactively with the user cost of capital, policy interest rates, and the relative investment-to-GDP deflator to test the hypothesis that the switch to inflation targeting instilled greater confidence.


10. The estimations are based on a panel of 11 sectors of the economy for 1995–2003. Data sources and the construction of variables are explained in greater detail in Appendix I. The list of sectors included in the analysis is presented in Appendix II. Sectors with a majority share of public investment were excluded from the analysis because investment decisions would seem unlikely to be based on market incentives. The series are in logarithms of constant prices, with the exception of dummy variables, and exchange rate and interest rate volatilities.

Panel estimation—fixed effects

11. The estimation results using the fixed-effects method are presented in Table 1. The endogenous variable is the log of real investment. In equation (i) all right-hand side (RHS) variables have the expected signs, although not all are significant. Equation (iii) indicates that the individual components of the user costs of capital—the real interest rate and the relative cost of capital—were not significant determinants of investment either. Equations (ii) and (iv) suggest that the change in the monetary policy regime (represented by a dummy variable) did not have an impact on investment through the confidence effect. Exchange rate volatility did not have an important effect either.4 Equations (v)-(ix), which test for the significance of a subset of explanatory variables, suggest that lagged investment, future production, financial results, and current and lagged greenfield FDI were, in various specifications, all significantly related to investment developments. EU demand was significant at about 20 percent in equations (viii) and (ix), relative ULCs at about 25 to 30 percent in equations (vi) and (vii). While in theory relative ULCs should be more important for tradable sectors, including a multiplicative dummy variable with the ULCs distinguishing tradable and nontradable sectors did not improve the significance. Because production technologies could differ across sectors, formal tests were conducted to see whether the statistical relationship between investment and production across sectors differs. The null hypothesis, that the coefficient on production is the same across sectors, was not rejected at conventional significance levels, thereby supporting the appropriateness of pooling data. The fixed-effect estimation method allows hypotheses to be explored from the general to the more specific, and the results presented in Table 1 are easily understood due to the intuitive specification of the equations. However, the estimated coefficients need to be interpreted with caution, owing to a bias in the coefficients that rely on panel regressions that include the lagged dependent variable. Therefore, equations with a good fit and significant coefficients were subsequently reestimated using the Arellano-Bond method.

Table 1.Panel Estimation Using Fixed Effects, 1995-2003
With user cost of capital and ER volatilityWith out user cost of capital and ER volatility
lagged investment0.2820.2760.2690.2750.3540.3420.340.3070.268
lead production0.5160.5030.4560.4550.520.5250.5940.4940.514
financial results0.1880.046-0.2080.1460.0920.1650.168
lagged FDI0.2680.2380.1890.1740.2670.1890.199
relative ULC-0.139-0.149-0.156-0.149-0.16-0.135
lagged relative ULC-0.118
EU demand0.9780.4742.8272.271
lead EU demand1.4541.302
ER volatility-0.206-0.38-1.195-0.218
user cost of capital-0.521
D*user cost of capital2.038
interest rate3.353
invest/GDP deflator9.056
D*interest rate-0.051
D*invest./GDP deflator0.888
Number of sectors111111111111111111
Absolute value of t statistics in brackets* significant at 10%; ** significant at 5%; *** significant at 1%Source: IMF staff calculations.

Panel estimation—Arellano-Bond

12. The estimation results using the Arellano-Bond method (Arellano and Bond, 1991) are presented in Table 2. The change in logarithm of real investment is the endogenous variable. The magnitude of the coefficients obtained through the fixed-effects method is broadly similar when estimated using the Arellano-Bond method, which uses lags of all the variables as instruments in order to correct for the bias mentioned above. The results reported in Table 2 are based on the Arellano-Bond estimation which also takes into account that some variables, such as production, are endogenous.

Table 2.Panel Estimation Using Arellano-Bond,1995-2003
LD. investment0.1620.4860.0990.4050.6010.323
D. production0.9630.7061.0561.079
D. lead production1.4930.807
D. financial results0.0330.0110.057
D. lagged FDI0.2990.0360.254
D. FDI0.2020.305
D. EU demand0.469
D. lead EU demand6.761
D. lagged relat. ULC-0.055-0.045-0.179-0.045
Number of sectors111111111111
Absolute value of z statistics in brackets* significant at 10%; ** significant at 5%; *** significant at 1%L = lag; D = differenceSource: IMF staff calculations.

13. A number of determinants of investment can be identified from the estimation results. These include lagged investment, lead production, and financial results. Similar conclusions were reached also by Gradzewicz (2005) in a firm-level analysis of investment decisions by industrial processing enterprises in Poland. Other variables of importance included in this study include greenfield FDI inflows, EU demand, and relative unit labor costs (which were significant again at about 25–30 percent).5 The user cost of capital does not feature as a determinant of investment, probably because about half of new investments tend to be financed with firms’ own resources, and only about a third financed with credits (National Bank of Poland, 2005), suggesting possible capital market imperfections. This result is corroborated by Gradzewicz (2005) and Dobrinsky (2005) in a cross-country panel analysis of investment-to-GDP ratios in Central and Eastern European countries.6


14. In-sample dynamic simulations of the estimated equations point to some overinvestment in the second half of the 1990s and underinvestment during 2000–02 (Figures 13 and 14).7 All simulated models based on the Arellano-Bond estimation capture the broad turning points in investment since 1995. The illustrative models presented—equations AB(ii) and AB(vi)—suggest that actual investment growth somewhat exceeded predicted investment growth, in especially in 1997. Moreover, while the slowdown of investment growth in 1998–99 is consistent with developments in fundamentals, there seems to have been substantially less investment in 2000–02 compared with what the estimated models would imply. These results are reasonably robust to changes in estimation method and equation specification. Some models that include financial results (for example, equation AB(i)) predict a sharp increase in investment in 2003, due to the very high increase of real corporate profits (albeit from a very small base). In reality, investment growth did not grow in 2003 as enterprises built up deposits in the banking sector instead. The reasons for underinvestment are by definition not captured in the model; they may include lack of investor confidence—perhaps due to prevailing uncertainties about future macroeconomic policies—or institutional factors emphasized by others. Sectoral simulations suggest that overinvestment in the mid-1990s may have occurred, mainly in transportation, real estate, manufacturing and construction, whereas underinvestment may have occurred since 2000 mainly in hotels, trade, and transportation.

Figure 13.Poland: Real Investment Growth—Actual and Fitted Values, Arellano-Bond Estimation, 1993-2004,

(in percent)

Sources: Polish authorities; and IMF staff calculations.

Figure 14.Poland: Real Investment Growth—Actual and Fitted Values by Sector, 1995-2003

(in percent)
(in percent)
(in percent)

Sources: Polish authorities; and IMF staff calculations.

15. Out-of-sample simulations indicate that, under reasonable assumptions, investment relative to GDP may not reach the previous peak in the medium term (Figure 15). The speed of increase of the investment-to-GDP ratio depends on the specification of the model and the assumptions about RHS variables. Two separate illustrative scenarios of the real investment-to-GDP ratio are presented in Figure 15. Both scenarios use World Economic Outlook (WEO) projections for EU domestic demand (ranging from 1.7 percent to 2.2 percent during 2005–10) and GDP growth in Poland (averaging 3¾ percent in the medium term). The conservative scenario 1 assumes no change in corporate financial results (albeit from the high base of 2004 after two years of exceptionally strong profit growth), unchanged relative ULC, and 2.4 percent growth of real greenfield FDI (equal to the growth of FDI in 2003) each year. The more optimistic scenario 2 assumes a rise in corporate financial results in line with nominal GDP, a 5 percent growth of real greenfield FDI, and a 3 percent fall in relative ULC per year. In the medium term, real investment is projected to continue growing under all plausible assumptions. However, whether the investment-to-GDP ratio would rebound to its peak level of the late 1990s depends on the specification of the model. The forward-looking simulations are particularly sensitive to assumptions about FDI growth.

Figure 15.Poland: Real Investment-to-GDP Ratio—Out-of Sample Simulation, 1991-2010 1/

(in percent)

Sources: Polish authorities; and IMF staff calculations.

1/ Scenario 1 assumes: unchanged financial results, unchaged relative ULC and real greenfield FDI growth of 2.4 percent per year.

Scenario 2 assumes: growth of financial results in line with GDP, 5 percent growth of real greenfield FDI and 3 percent fall in relative ULC per year.

See Table 2 for specification of equations AB(ii) and AB(vi).

D. Conclusions

16. This study has sought to identify the determinants of investment in Poland and provide a gauge for assessing whether investment has displayed an overly cyclical pattern in the past. Based on a sectoral panel covering the past decade, the main determinants of investment include lagged investment, production expectations, profitability, relative unit labor costs, and greenfield FDI, and EU demand. The estimates point to some overinvestment in 1997, and sizable and more prolonged underinvestment during 2000–02 than what the model would imply. The relatively low investment in 2000–02 is thus unlikely to be related to the previously created excess capacity. Other factors, such as investor uncertainty, must have been at play.

17. Strong investment is essential for Poland to realize its potential output. Policies can play a role in promoting investment by affecting several of the determinants of investment identified in the estimates. In light of the estimates suggesting a key role for FDI inflows, structural policies aimed at maintaining Poland’s attractiveness for foreign investors will be important. The reduction of the corporate income tax (CIT) introduced in 2004 is also likely to play a role by boosting after tax profitability. In addition, relative unit labor costs can be influenced by macroeconomic policy coordination to support a competitive real exchange rate; and through structural policies seeking to improve workers’ skills and enhance labor market flexibility. Measures to reduce uncertainty regarding the macroeconomic framework and the business environment would also help; such measures could, for example, include improvements in fiscal institutions.

18. Finally, EU membership and EU transfers are likely to have a positive impact on private investment by deepening trade integration, creating opportunities for new private projects, and financing infrastructure. The investment equations were estimated for the period before the EU accession and thus do not take into account the benefits of EU membership and EU funds. Therefore, the medium-term projections based on the estimated models may prove to be lower bounds for future investment.

APPENDIX I: Data Sources and Construction of Variables

Unless noted otherwise, all variables are based on data from the various issues of the Statistical Yearbook of the Republic of Poland, Central Statistical Office (GUS).

  • Real investment is based on investment outlays by sections and divisions in constant prices (converted into 2001 constant prices series).

  • Real production is based on indices of gross output by sector in constant prices, (converted into 2001 constant price series).

  • Relative unit labor costs are defined as the ratio of the sectoral unit labor costs (ULC) in Poland to sectoral unit labor costs in the EU. ULC for Poland was calculated using data on employed persons by sector, average monthly gross wages and salaries by sector, and gross output by sector. Sectoral ULCs for the EU were obtained from DATASTREAM.

  • Domestic demand in the EU in constant prices was obtained from Eurostat.

  • Greenfield FDI in U.S. dollars for the economy as a whole is defined as total FDI inflows less privatization receipts from abroad, obtained from the NBP, converted into zlotys at period average exchange rates (from the NBP), and deflated by the investment deflator.

  • User cost of capital is defined as the product of the real interest rate (proxied by nominal policy rate from the NBP deflated by the GDP deflator) and the relative price of capital (the ratio of the investment deflator to the GDP deflator).

  • Profitability of the enterprise sector is defined as the gross financial results on economic activity deflated by the GDP deflator. Ideally, net profitability series would be used to capture the impact of taxation, but these cannot be used for technical reasons (the net profitability series have negative values during some periods of the sample and thus cannot be used in a log-linear form in the estimation). However, because of the co-movement of the gross and net profitability, the results based on gross profitability series can be assumed to apply to the net series as well (see Figure 12).

  • Exchange rate and interest rate volatility— Daily observations of the zloty/euro exchange rate from the NBP and of three-month Warsaw Interbank Offered Rate (WIBOR) from DATASTREAM; a sixth-month rolling standard deviation is averaged for each calendar year.

  • DULC--a dummy variable, used in a multiplicative form with relative ULCs, was set equal to 1 for the tradable sectors (agriculture, fishing, manufacturing (industry), mining, and electricity), and to zero otherwise.

APPENDIX II: List of Sectors Included in the Panel Data AnalysisAGR





Financial intermediation




Hotels and restaurants


Manufacturing (industry)


Mining and quarrying (industry)


Electricity, gas, and water (industry)


Real estate, renting and business activities


Trade and repair


Transport, storage, and communications


    Arellano, M., and S.Bond, 1991, “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,” Review of Economic Studies, Vol. 58, No. 2: pp. 27797.

    Caballero, R., 1999, “Aggregate Investment,” in Handbook of Economics, ed. by J.B.Taylor, and M.Woodford, (New York: NorthHolland)

    Dobrinsky, R., 2005, “Domestic Savings and the Driving Forces of Investment in the ECE Emerging Market Economies,” Occasional Paper No. 4, UN Economic Commission for Europe.

    Doyle, P., L.Kuijs, and G.Jiang, Real Convergence to EU Income Levels: Central Europe from 1990 to the Long Term,” Working Paper 01/146 (Washington: International Monetary Fund).

    Gradzewicz, M., 2005, “Analysis of Investment Behavior in Industrial Processing Enterprises”, NBP Working Paper (forthcoming).

    National Bank of Poland (Quarterly Survey), 2005, “Wstepna Informacja o Kondycji Sektora Przedsiebiorstw ze Szczegolnym Unwzglednieniem Stanu Konjuktury W 1 KW.”

    Paczocha, J., and W.Rogowski, 2005, “Regulatory Restrictions in the Polish Economy in 1989–2003”, NBP Working Paper (forthcoming).

    Pelgrin, F., S.Schich and A. deSerres, 2002, “Increases in Business Investment Rates in OECD Countries in the 1990s: How Much Can Be Explained by Fundamentals?OECD Economics Department Working Papers, No. 327.

    Tevlin, S., and K.Whelan, 2003, “Explaining Investment Boom of the 1990s,” Journal of Money, Credit and Banking, February, No. 35 Vol. 1.

Prepared by Zuzana Murgasova.

RAM8 countries include eight of the recently acceded members (RAM): the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, the Slovak Republic and Slovenia.

EU-15 is defined as the EU prior to the 2004 enlargement.

Interest rate volatility was also not a significant determinant of investment (regression results are not shown in the paper).

To determine whether the impact of the 1998 Russia crisis may have contributed to the investment slowdown, the equations were reestimated using Poland’s partner country demand (weighted by trade shares) calculated by the WEO, instead of EU demand. While the estimated coefficients on the partner country demand had the correct sign (positive), the overall fit of the model was much worse than when using EU demand. This may be due to the relatively low share of Polish exports to Russia in total exports prior to the crisis (less than 7 percent) and a high share of export to the EU (about two-thirds) throughout the sample period.

Empirical studies of investment generally have difficulties finding a significant relationship between investment and the user cost of capital. There are a number of possible reasons (other than capital market imperfections). First, firms may adjust expectations about economic activity in response to monetary policy changes, and thus revise their investment plans. Second, cost of capital may be mismeasured, particularly on the aggregate level. Third, there may be an identification problem related to reduced-form estimates which include endogenous regressors. Nevertheless, in this paper monetary policy can have an impact on investment by affecting relative unit labor costs and profitability through the exchange rate, and perhaps to a lesser extent, the interest rate channels.

The figures are based on the equations estimated using the Arellano-Bond method.

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