Republic of Croatia: Selected Issues

International Monetary Fund

doi:10.5089/9781451817478.002.A001

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Republic of Croatia

Selected Issues

Author: International Monetary Fund

Publication Date:: 16 May 2008

eISBN:: 9781451817478

Language:: English

Keywords:: ISCR; CR; Croatia; GDP; spending; balance; debt; growth assumption; rate of return; creating flow; debt service; macroeconomic balance approach; Current account; Current account deficits; Foreign direct investment

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The first analysis focuses on external stability, an important issue in view of Croatia’s external imbalances and the requirements of the IMF’s 2007 Decision on Bilateral Surveillance. The paper shows that the real exchange rate is broadly in line with economic fundamentals and that external debt dynamics are sustainable as long as macroeconomic policies remain strong. The second analysis finds significant inefficiencies in Croatia’s social spending. It also discusses several reform measures to reduce inefficiencies in public spending and generate budgetary savings to reduce the general government deficit.

Abstract

I. Assessing Croatia’s External Stability¹

A. Introduction

1. The deteriorating global economy and ongoing re-pricing of credit risks warrant a closer look at countries with high current account deficits and large external financing requirements.² In view of the magnitude of Croatia’s external imbalances, as well as the requirements of the IMF’s 2007 Decision on Bilateral Surveillance,³ external stability is a key focus of this Article IV consultation.

2. External stability is defined as “a balance of payments position that does not, and is not likely to, give rise to disruptive adjustments in exchange rates.”⁴ This requires that: (i) the underlying current account (i.e., the current account stripped of temporary factors, such as cyclical fluctuations, temporary shocks, and adjustment lags) is broadly in equilibrium—a situation in which the country’s net external asset position is evolving consistently with the economy’s structure and fundamentals; and (ii) the capital and financial account does not create risks of abrupt shifts in capital flows.

3. This Chapter asks three main questions:

What are the key drivers of Croatia’s current account dynamics?
Is Croatia’s current account position sustainable?
Do financial account and external debt positions pose any risks to external stability?

4. The main conclusion is that external stability risks relate largely to financial account vulnerabilities rather than exchange rate misalignment. There is no compelling evidence that the widening current account deficit reflects competitiveness problems stemming from real exchange appreciation; rather the lackluster merchandise export performance seems to be largely due to structural factors. Under the baseline medium-term scenario, which assumes a limited impact of global slowdown on Croatia and a continuation of strong macroeconomic policies, the underlying current account balance is broadly in line with Croatia’s economic fundamentals, and external debt dynamics are sustainable. However, the sustainability of Croatia’s external debt and financial account position may be at risk from possible increase in the cost of foreign borrowing and/or a significant slowdown in capital inflows. These event risks are non-trivial in the environment of lower global growth, heightened concerns about inflation, on-going repricing of credit risks, and lingering uncertainties about the full ramifications of the subprime crisis.

5. The chapter is structured as follows. Section B examines the key drivers of the current account dynamics and competitiveness indicators for Croatia and its regional peers. It also assesses whether Croatia’s real exchange rate and current account dynamics might be considered “normal”, given the country’s structural and macroeconomic characteristics. Section C examines the composition of external financing and assesses the sustainability of Croatia’s international investment position and external debt dynamics, reviews Croatia’s external liquidity indicators and discusses associated risks. Section D concludes.

B. Current Account Sustainability

What are the key drivers of the current account dynamics?

6. Large current account deficits in Eastern Europe were (mostly and until recently) seen as part of a “normal” convergence process, and not so much as a cause for concern. Indeed, theory suggests that an increase in goods and financial market integration implies that countries with lower per capita income levels and higher expected rates of return should experience faster investment and consumption growth, financed (in many cases), by foreign capital inflows and accompanied (in some cases) by a decline in domestic saving. All of these factors should contribute to a deterioration in current account balances.

7. In terms of the speed of convergence and the magnitude of the current account deterioration, Croatia seems to hold the middle-ground among transition economies. Croatia started with a higher level of relative income than several other EU accession countries (e.g., Bulgaria, Romania and the Baltic states, Figure I.1) and its average annual GDP growth (Figure I.2) and speed of income convergence have been slower. In comparison with other transition economies, the deterioration in Croatia’s current account deficit throughout 2000-07 was fairly modest, with the deficit remaining within the range of 3–9 percent of GDP. Also, in the case of Croatia, the deterioration in the saving-investment balance reflected a rising investment-to-GDP ratio, while the ratio of national savings-to-GDP remained stable. Croatia’s domestic stock of credit-to-GDP, which was already fairly high in 2000 by regional standards, rose by over 30 percentage points by end-2006, faster than in Poland, Czech Republic and Hungary, but less rapidly than in the Baltic states (Figure I.2).

Do the current account dynamics reflect deteriorating competitiveness?

8. Real exchange rate appreciation is often part of the convergence story. In theory, growing economic and financial integration of lower-income countries should lead to faster productivity growth in the tradable sector compared to the non-tradable sector, pushing up wages in both sectors and raising the relative prices of non-tradables as well as the overall price level (the Balassa-Samuelson effect). Thus, for transition countries with stable nominal exchange rates (as in the case of Croatia), the observed inflation differentials with the euro area should be attributable, at least in part, to productivity growth differentials. While most standard real effective exchange rate measures for Croatia (i.e., the CPI-, PPI- and ULCM-based⁵ REER) indicate appreciation on the order of 1–2 percent per year during 2000-07 (Figure I.3), the empirical evidence on the magnitude and significance of the Balassa-Samuelson effect for Croatia is mixed.⁶

9. The worsening of Croatia’s current account position does not seem to be due to an exchange-rate induced erosion of competitiveness. The current account deteriorated during 2000-07, notwithstanding a temporary improvement in 2003-04. The deterioration was driven mainly by higher goods imports; the goods export-to-GDP ratio remained broadly stable and the non-financial services balance improved, supported by strong tourism revenues (Figure I.6). Apart from a rising share of energy imports, the structure of goods imports has been remarkably stable (Figure I.6), with the share of intermediate and capital goods at 60–64 percent. While the broad structure of exports has been stable as well (Figure I.6), there are some indications of changing patterns of specialization.⁷ In sum, there does not seem to be compelling evidence that the trend real exchange rate appreciation has been fueling consumer goods imports, nor that it has been the key factor behind lackluster goods exports.

10. Weak merchandise export performance could be explained by structural factors. The average annual growth rates of Croatia’s merchandise exports to both the EU and non-EU markets have been positive, but below the peer group average throughout 2000-07 (Figure I.5). As a result, Croatia’s market share, especially in the EU market, expanded at a much slower pace than that of other Eastern European countries. Comparing price and cost competitiveness measures across the region does not reveal a strong link between the extent of REER appreciation (depreciation) and merchandise export under (over) performance vis-à-vis the regional average. For example, Croatia has consistently underperformed, while Slovakia and the Czech Republic have outperformed despite much stronger REER appreciation than in Croatia on both the CPI and the ULCM basis (Figures I.5 and I.6). Wage developments (in industry) across these countries do not fully explain the differences in export performance either, which suggests that other factors may be at work, including patterns of specialization, lack of FDI in the tradable sector, or other structural features of the economy.

11. Structural indicators paint a relatively unfavorable picture of Croatia’s competitiveness (Figure I.7). In particular, poor protection of property rights, inefficient public administration and judicial system, corruption, and heavy state regulation are often listed as Croatia’s main competitive disadvantages, which could, in part, explain why it has been less successful in attracting FDI than other countries in the region. Most FDI in Croatia went into the non-tradable sector (Figure I.7), with some exceptions (e.g., chemicals was one of the sectors that attracted significant foreign investment, accounting for around 15 percent of the total FDI stock at end-2006). Hence, any marked improvements in export performance are unlikely to materialize without structural reforms.⁸ The question remains as to whether current account deficits of the magnitude recently experienced by Croatia are sustainable over the medium-term under the baseline assumptions about policies and fundamentals (discussed in the accompanying staff report).

Is the current account deficit sustainable?

12. Current account sustainability is typically assessed on the basis that a country’s current account balance should evolve in a manner consistent with the external and internal balance of the economy. The sustainability of the current account balance can be gauged from the estimated degree of real exchange rate “misalignment,” i.e., a deviation of the prevailing exchange rate from its “equilibrium” level, defined as the level consistent with an underlying current account being in equilibrium. The equilibrium current account balance (also referred to as the current account norm) is a country’s savings-investment balance determined by its medium-term economic fundamentals. The underlying current account is the prevailing current account stripped of temporary factors, such as cyclical fluctuations, temporary shocks, and adjustment lags. This section presents the application of the macroeconomic balance and external sustainability approaches, and also discusses some alternative assessments.⁹

The macroeconomic balance approach

13. The macroeconomic balance approach estimates the degree of real exchange rate misalignment in three steps: (i) the current account norm (CA norm) is computed as a function of the country’s medium-term economic fundamentals; (ii) the underlying current account balance is estimated assuming that the country’s and its trading partners’ output gaps are closed and all temporary factors, including lagged effects of exchange rate changes, are taken into account; and (iii) the exchange rate adjustment required to close the gap between the underlying current account balance and the current account norm is obtained using elasticities of the current account with respect to the real exchange rate. Each step is discussed in more detail below.

14. The CA norms are typically obtained using panel regression estimation. For the purpose of this analysis, we use the CGER panel regression coefficients that were obtained using a sufficiently large sample of countries to achieve a reasonable degree of accuracy in the estimation of the equilibrium relationship between current account balances and economic fundamentals. The explanatory variables used by the CGER are the ones that were found to be fairly robust current account determinants in a number of empirical studies¹⁰:

Fiscal balance: a higher government budget balance contributes to higher national savings, thereby raising the current account balance (in the absence of full Ricardian equivalence).

Demographics: a higher share of economically inactive population reduces national savings, thereby decreasing the current account balance.

Commodity terms of trade: an improvement in the terms of trade leads to a higher current account balance (e.g., higher oil prices increase the current account balance of oil exporters and reduce the current account balance of oil importers).

The stage of economic development: a country that has a lower income level or stronger economic growth relative to its trading partners tends to have a lower current account balance.

Initial external position: either an initial Net Foreign Assets (NFA) position¹¹ or a lagged current account balance is included in some regression specifications as well. The presumption is that if a country has been borrowing steadily in the past (i.e., had negative NFA), it must have some characteristics that are attractive to foreign investors and, hence, is likely to continue attracting capital inflows.¹² On the other hand, if a country has had a high (positive) NFA, it should benefit from higher net foreign income flow. Hence, one would expect a positive association between the initial NFA and current account balance.

15. The application of the macroeconomic balance approach suggests that the real exchange rate is broadly in line with Croatia’s economic fundamentals projected over the medium-term under baseline policies. Table I.1 presents several estimates of the CA norm, using the CGER panel regression coefficients and the values of the medium-term current account determinants for Croatia and its trading partners. Based on the estimates in Table I.1 the average CA norm for Croatia is around -4 percent of GDP. The biggest negative contributions come from the initial NFA position or the lagged current account balance, Croatia’s relative income vis-à-vis its trading partners, and its status as net oil importer. In comparison, the average CA norm for the CEE countries is estimated at -4.4 percent of GDP.¹³ Given the estimated underlying current account balance of -4.9 percent of GDP, the implied degree of real exchange rate overvaluation in Croatia is 2–4 percent (which cannot be considered significantly different from zero at conventional confidence levels, given the forecast standard errors in the CA norm regressions).

Table I.1.

Real Exchange Rate Assessment Using Macroeconomic Balance Approach

Sources: World Economic Outlook, Croatian National Bank; and Fund staff calculations.

^{^1/}The CA norm corresponds to a current account level that is consistent with a specific set of economic fundamentals; “Norm_CA” and “Norm_NFA” are computed using the panel regression estimates for two model specifications, with lagged current account balance and initial NFA position, respectively (see Appendix I for details); “Norm_NFA1” is based on the official IIP data that reflects adjustments in market values, “Norm_NFA2” is based on the official IIP data with the exception of the inward FDI position, which is estimated as cumulative FDI flows from 1998 onward (this will be discussed in more details in Section C); All data (historical and medium-term projections) used in the computations come from the April 2008 WEO.

^{^2/}Underlying current account balance assumes that both domestic and foreign output gaps are closed and is adjusted for the projected REER movement during 2008–13.

^{^3/}The current account elasticity to REER is computed using the standard long-run exchange rate elasticities for imports (0.92) and exports (-0.71), as well as exports and imports of goods and services (in percent of GDP) over a period of 2003-07.

Table I.1.

Real Exchange Rate Assessment Using Macroeconomic Balance Approach

		Norm_CA	Norm_NFA1	Norm_NFA2
Current account norm (in percent of GDP) ^1/		-3.8	-4.2	-3.4
Underlying current account balance (in percent of GDP) ^2/		-4.9	-4.9	-4.9
Current account elasticity to REER ^3/		-0.39	-0.39	-0.39
Implied REER adjustment (in percent, “+” appreciation)		-2.8	-1.8	-4.0
Contributions of the current account determinants to the estimated current account norms:
	Fiscal balance	0.2	0.2	0.2
	Old-age dependency	0.0	0.0	0.0
	Population growth	0.4	0.5	0.5
	Lagged current account	-2.5	…	…
	Initial NFA	…	-2.7	-1.9
	Oil balance	-0.3	-0.4	-0.4
	Output growth	-0.3	-0.3	-0.3
	Relative income	-1.2	-1.5	-1.5
	Constant	-0.3	0.0	0.0
	Total	-3.8	-4.2	-3.4

Sources: World Economic Outlook, Croatian National Bank; and Fund staff calculations.

^{^2/}Underlying current account balance assumes that both domestic and foreign output gaps are closed and is adjusted for the projected REER movement during 2008–13.

Table I.1.

Real Exchange Rate Assessment Using Macroeconomic Balance Approach

		Norm_CA	Norm_NFA1	Norm_NFA2
Current account norm (in percent of GDP) ^1/		-3.8	-4.2	-3.4
Underlying current account balance (in percent of GDP) ^2/		-4.9	-4.9	-4.9
Current account elasticity to REER ^3/		-0.39	-0.39	-0.39
Implied REER adjustment (in percent, “+” appreciation)		-2.8	-1.8	-4.0
Contributions of the current account determinants to the estimated current account norms:
	Fiscal balance	0.2	0.2	0.2
	Old-age dependency	0.0	0.0	0.0
	Population growth	0.4	0.5	0.5
	Lagged current account	-2.5	…	…
	Initial NFA	…	-2.7	-1.9
	Oil balance	-0.3	-0.4	-0.4
	Output growth	-0.3	-0.3	-0.3
	Relative income	-1.2	-1.5	-1.5
	Constant	-0.3	0.0	0.0
	Total	-3.8	-4.2	-3.4

Sources: World Economic Outlook, Croatian National Bank; and Fund staff calculations.

^{^2/}Underlying current account balance assumes that both domestic and foreign output gaps are closed and is adjusted for the projected REER movement during 2008–13.

The external sustainability approach

16. The external sustainability approach is based on the notion that the present value of future trade surpluses must be sufficient to service the country’s external liabilities. The extent of misalignment can then be assessed by (i) computing the difference between the underlying CA balance and the current account balance that would stabilize the net foreign asset (NFA) position of the country at some benchmark level; and (ii) translating this difference into an exchange rate adjustment that would be required to bring the CA balance in line with its NFA-stabilizing level (in a way similar to the macroeconomic balance approach). The simplified way of computing the NFA-stabilizing current account balance (which abstracts from the structure of foreign assets and liabilities, as well as differences between the rates of return on different instruments) is as follows:

NFA stabilizing $C A B / G D P = \frac{g + π}{(1 + g) (1 + π)} *$ (benchmark NFA/GDP), where g is the long run real GDP growth rate and π is the rate of inflation.

17. A range of NFA-stabilizing current account balances, computed using the external sustainability approach, does not indicate a significant misalignment. Table I.2 presents NFA estimates for different GDP growth assumptions, showing that for a given NFA benchmark, a country that grows faster in the long-term can afford to run a larger current account deficit. Or, alternatively, for a given GDP growth assumption, a country that needs to stabilize its NFA at a lower level would have to run a larger current account balance (Table I.2). For example, if Croatia chooses to stabilize its NFA position at the emerging-market countries’ average level of -34 percent of GDP, its underlying current account balance would have to narrow to -2.4 percent of GDP from an estimated -4.9 percent of GDP (which would imply a more significant REER adjustment, though still within the range that would be considered consistent with fundamentals).

Table I.2.

The NFA-Stabilizing Current Account Balances

(In percent of GDP)

Sources: Croatian National Bank; and Fund staff calculations.

^{^1/}the baseline scenario assumes a long-run real GDP growth rate of 4.8 percent and an inflation rate of 3 percent; both end-2007 and 2003-07 NFA benchmarks are based on the official IIP data with the exception of the inward FDI position, which is estimated as cumulative FDI flows from 1998 onward. All nominal variables are in euros.

Table I.2.

The NFA-Stabilizing Current Account Balances

(In percent of GDP)

			Real GDP Growth Assumptions
Baseline ^1/		5.8	4.8	3.8	2.8
NFA benchmarks
	-69 percent of GDP (end-2007)	-5.7	-5.1	-4.5	-3.9
	-60 percent of GDP (2003-07 average)	-4.8	-4.3	-3.8	-3.3
	-34 percent of GDP (EM average)	-2.7	-2.4	-2.1	-1.8

Sources: Croatian National Bank; and Fund staff calculations.

Table I.2.

The NFA-Stabilizing Current Account Balances

(In percent of GDP)

			Real GDP Growth Assumptions
Baseline ^1/		5.8	4.8	3.8	2.8
NFA benchmarks
	-69 percent of GDP (end-2007)	-5.7	-5.1	-4.5	-3.9
	-60 percent of GDP (2003-07 average)	-4.8	-4.3	-3.8	-3.3
	-34 percent of GDP (EM average)	-2.7	-2.4	-2.1	-1.8

Sources: Croatian National Bank; and Fund staff calculations.

18. Other approaches yield similar results. The reduced-form equilibrium real exchange rate (ERER) approach can be used to estimate the equilibrium real exchange rate directly as a function of the medium-term fundamentals, such as the NFA position, productivity growth in the tradable and non-tradable sectors, and the terms of trade. An application of this approach to Croatia yields broadly similar results, although the estimates cannot be considered very reliable given the short time series. Interestingly, the results do not appear to be sensitive to alternative definitions of the tradable and non-tradable sectors.¹⁴ The recent estimation of the Blanchard-Giavazzi style regional income convergence model also suggests that Croatia’s current account balance is broadly justified by fundamentals.¹⁵

C. Financial Account and External Debt Sustainability

How is the current account deficit financed?

19. Croatia’s current account deficits have so far been comfortably financed by a combination of FDI and foreign borrowing (Figure I.8). If anything, capital inflows have been fairly strong, putting upward pressure on the kuna. Inward FDI flows, excluding privatization-related inflows, ranged between 3 and 6 percent of GDP, with reinvested earnings accounting for an increasing share of total FDI inflows in recent years. Total gross external debt rose from 61 to 88 percent of GDP between 2000 and 2007, with private sector external debt gradually increasing to 70 percent of GDP, short-term debt (by original maturity) to 12 percent of GDP and variable-rate debt to 58 percent of GDP by end-2007 (Figure I.8).¹⁶

International Investment Position

20. Croatia’s net international investment position (IIP) has turned increasingly negative in recent years, reflecting the relatively faster build-up in both equity and debt foreign liabilities compared to foreign assets. The net IIP is estimated to have reached -106 percent of GDP by end-2007, with net debt (the sum of debt assets and official reserves minus debt liabilities) at -32 percent and net equity (the sum of portfolio equity and FDI assets minus portfolio equity and FDI liabilities) at -74 percent of GDP.¹⁷ A sharp increase in the value of the inward FDI stock during 2006-07 partly reflects a rapid rise of the Crobex stock market index used for valuation adjustments. Figure I. 9 also shows the evolution of the NFA position net of such adjustments, with the inward FDI stock computed as cumulative FDI flows. While, in general, there are good reasons for marking-to-market, one has to be cautious in interpreting market-based valuations in countries like Croatia, where free float is low, price volatility is high, and market values may not always accurately reflect the price that investors might reasonably expect to get for these assets.¹⁸ This suggests that the “true” value of FDI lies somewhere between its “market” and “book” values.

21. The extended external sustainability approach can be used to determine the level of non-income current account balance that would stabilize the IIP at a given level (net) and structure (See Appendix I.II for details). The non-income current account balance (NICA) includes the goods and services trade balance, compensation of employees, current transfers and capital transfers.¹⁹ Assuming that the objective is to stabilize the net IIP at its level and structure prevailing at end-2007, Croatia would have to run a NICA surplus of 0.8 percent of GDP over the medium-term, given the baseline assumptions about rates of GDP growth and returns on foreign assets and liabilities. Given the actual NICA balance of -4.1 percent of GDP in 2007, achieving such an adjustment would require a much stronger-than-baseline export performance, even if capital transfers were to increase ahead of EU accession. Table I.3 also illustrates the sensitivity of the net IIP-stabilizing NICA to two downside risks: lower global growth and a higher spread between the real rates of return on debt liabilities and debt assets. In both scenarios, a larger NICA surplus would be required to sustain the same IIP. If Croatia were to raise its potential growth, smaller surpluses would be sufficient to sustain a given IIP under baseline and downside scenarios.

Table I.3.

Stabilizing the Net IIP

I. NICA Balance (In percent of GDP)

Table I.3.

Stabilizing the Net IIP

I. NICA Balance (In percent of GDP)

								Baseline Projections
	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013
a. Goods and services	-5.8	-10.9	-7.8	-6.8	-7.0	-7.7	-8.3	-8.2	-7.6	-6.6	-5.7	-5.0	-4.4
b. Compensation of employees	0.6	0.7	0.7	0.8	0.8	1.1	1.3	1.1	1.1	1.1	1.1	1.1	1.1
c. Current transfers	5.0	4.7	4.7	4.2	3.8	3.2	2.8	2.6	2.5	2.4	2.3	2.2	2.1
d. Capital transfers	0.7	2.1	0.4	0.1	0.2	-0.4	0.1	0.3	0.3	0.3	0.3	0.2	0.2
NICA balance (a+b+c+d)	0.5	-3.4	-1.9	-1.7	-2.2	-3.8	-4.1	-4.2	-3.8	-2.9	-2.1	-1.5	-1.0

Table I.3.

Stabilizing the Net IIP

I. NICA Balance (In percent of GDP)

								Baseline Projections
	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013
a. Goods and services	-5.8	-10.9	-7.8	-6.8	-7.0	-7.7	-8.3	-8.2	-7.6	-6.6	-5.7	-5.0	-4.4
b. Compensation of employees	0.6	0.7	0.7	0.8	0.8	1.1	1.3	1.1	1.1	1.1	1.1	1.1	1.1
c. Current transfers	5.0	4.7	4.7	4.2	3.8	3.2	2.8	2.6	2.5	2.4	2.3	2.2	2.1
d. Capital transfers	0.7	2.1	0.4	0.1	0.2	-0.4	0.1	0.3	0.3	0.3	0.3	0.2	0.2
NICA balance (a+b+c+d)	0.5	-3.4	-1.9	-1.7	-2.2	-3.8	-4.1	-4.2	-3.8	-2.9	-2.1	-1.5	-1.0

II. The NICA Balances Stabilizing the End-2007 IIP (In percent of GDP)

Sources: World Economic Outlook, Croatian National Bank; and Fund staff calculations.

^{^1/}In the baseline scenario, the real rate of return on outward FDI/equity investment is equal to the world’s medium term growth rate (4.7 percent) + 100 basis points, the rate of return on Croatia’s FDI/equity liabilities is equal to its medium-term growth rate (4.8 percent) + 100 basis points; the rate of return on debt assets is equal to 2.5 percent in real terms and the spread on debt liabilities is equal to 100 basis points over the rate paid on debt assets (these assumptions are similar to Lane and Milesi-Ferretti (2006), except that the spread between the returns on debt assets and debt liabilities is assumed to be smaller, given the historical average borrowing rates of Croatian banks’ and nonfinancial firms; see Figure I.11).

^{^2/}The lower growth scenario is based on the assumption that real GDP growth rates are reduced by 1 percent compared to baseline for both the world and Croatia.

^{^3/}The higher spread scenario assumes that the interest rate spread between debt liabilities and debt assets widens by 100 basis points. All scenarios use the IIP, where the inward FDI stock is estimated as cumulative FDI flows from 1998 onward.

22. In the case of Croatia, the conclusions drawn from this type of analysis should not be taken at face value. The extended external sustainability approach implicitly assumes that the ratios among different foreign assets and liabilities remain constant at the levels prevailing in the “benchmark” IIP. This assumption may not be appropriate for transition countries. In the case of Croatia, in particular, the structure of foreign liabilities is likely to continue shifting towards a higher share of equity, as the country is likely to attract more FDI ahead of EU accession, while also possibly reducing its reliance on debt financing. Moreover, a constant IIP structure may be inconsistent with allowing FDI earnings to be automatically reinvested, which one would expect to happen in “normal times.”

23. Assuming that returns on inward FDIs are automatically reinvested, smaller NICA balances may be sufficient to stabilize a given IIP. In the case of Croatia, the average annual inflow of reinvested earnings during 2001-07 was 1.4 percent of GDP, which covers about half of the gap between the estimated net IIP-stabilizing NICA balance (+0.8 percent of GDP, under the baseline assumptions) and the average NICA balance over 2001-07 (-2.4 percent of GDP). The next section focuses on external debt dynamics, taking the projected evolution of the FDI stock as given.

External Debt

24. The debt sustainability approach (DSA) can be used to determine the level of the non-income current account balance that stabilizes the gross external debt-to-GDP ratio at a given benchmark level. Using the IMF’s standard DSA, Table I.4 presents the values of debt stabilizing NICA balances for different external debt-to-GDP benchmarks and real GDP growth rates, assuming that all net non-debt inflows are zero (i.e., the numbers in the table reflects only “automatic debt dynamics”, see Appendix I.II for details). The logic is similar to that of the NFA-stabilizing exercise, i.e., if a country wishes to stabilize its external debt-to-GDP at a lower level, it has to run a larger NICA balance; for faster growing countries, smaller NICA balances may be sufficient to stabilize external debt at a given level. For example, if the objective is to stabilize external debt at 84 percent of GDP (baseline projection for 2013), Croatia would have to run a NICA deficit of -1.2 percent of GDP in the long-run, which is close to the 2013 baseline projection.

Table I.4.

External Debt-Stabilizing NICA Balance

(In percent of GDP)

Sources: Croatian National Bank; and Fund staff calculations.

^{^1/}the baseline scenario assumes a long-run real GDP growth rate of 4.8 percent and an inflation rate of 3 percent and nominal interest rate on foreign debt equal to 6.5 percent, consistent with the assumption in Table 4; other scenarios have the same inflation and interest rate, but different growth assumptions. All nominal variables are in euros.

Table I.4.

External Debt-Stabilizing NICA Balance

(In percent of GDP)

			Real GDP Growth Assumptions
Baseline ^1/		5.8	4.8	3.8	2.8
Gross External Debt benchmarks
	88 percent of GDP (end-2007)	-2.1	-1.2	-0.4	0.5
	84 percent of GDP (baseline projection for 2013)	-2.0	-1.2	-0.3	0.5
	35 percent of GDP	-0.8	-0.5	-0.1	0.2

Sources: Croatian National Bank; and Fund staff calculations.

Table I.4.

External Debt-Stabilizing NICA Balance

(In percent of GDP)

			Real GDP Growth Assumptions
Baseline ^1/		5.8	4.8	3.8	2.8
Gross External Debt benchmarks
	88 percent of GDP (end-2007)	-2.1	-1.2	-0.4	0.5
	84 percent of GDP (baseline projection for 2013)	-2.0	-1.2	-0.3	0.5
	35 percent of GDP	-0.8	-0.5	-0.1	0.2

Sources: Croatian National Bank; and Fund staff calculations.

25. Higher FDI inflows could help to bring down Croatia’s external debt. First, for a given long-run level of NICA balance, larger non-debt creating flows (like FDI) would allow the debt-to-GDP ratio to stabilize external at a lower level. For example, if Croatia could count on an annual non-debt creating inflow of 3 percent of GDP, it could then run a NICA balance of -4.2 percent of GDP, while still being able to stabilize debt at 84 percent of GDP. Second, higher FDI inflows would lead to gradual substitution of debt for equity in Croatia’s external liability structure. Third, higher FDI in export oriented sectors would improve export performance and eventually help to narrow the trade deficit.

26. What could be considered a “safe” level of external debt for a country like Croatia? The now-conventional wisdom derived from the experience of other emerging market countries suggests that a “safe” level of external debt is somewhere around 35 percent of GDP.²⁰ This threshold, however, may not be meaningful for transition countries, where the run-up in external debt has been driven (at least in part) by financial deepening and financial integration associated with convergence. That said, the overall level of private credit (in percent of GDP) in Croatia is already high, by historical and by regional standards, suggesting a limited scope for viewing any further debt accumulation as an “equilibrium” phenomenon.²¹ An alternative way to determine whether an adjustment might be warranted is to test whether the projected external debt dynamics are sustainable in the face of extreme, but plausible shocks.

27. Stress tests suggest that the baseline external debt dynamics may not be sustainable under certain extreme, but plausible risk scenarios. The baseline scenario envisages a gradual decline of external debt to about 84 percent of GDP by 2013 (Figure I.10). Figure I.10 also presents several downside risk scenarios, including three macro scenarios used in stress testing of the banking system in the context of the FSAP update²². It shows that the biggest risks to the sustainability of external debt dynamics stem from (i) the global interest rate increase; and (ii) a slowdown or reversal in capital flows that results in a significant depreciation of the kuna. The latter also represents the worst case scenario from the domestic financial stability point of view.²³ In light of the on-going repricing of credit risks in global financial markets and heightened concerns about inflation, the likelihood of these event risks is not negligible.

28. While some adjustment in external borrowing rates has already taken place, reflecting the recent rise in libor/euribor rates, further increases cannot be ruled out (Figure I.11) As interest rates on variable rate obligations (accounting for 66 percent of total external debt) are reset and maturing loans are rolled over at higher rates, the projected medium-term debt service profile is likely to shift upward.²⁴ Moreover, further deterioration in credit market conditions may cause an upward revision of credit risk premia across a broad spectrum of borrowers, both banks and nonfinancial firms, while the Eurozone rates may not come down for some time due to inflation concerns.

29. Based on a number of standard indicators, Croatia’s external liquidity position does not seem overly strong. While the external liquidity ratio is estimated to have recently improved to over 120 percent at end-2007, the reserve cover remained below 80 percent and the external debt service ratio increased to around 38 percent in 2007 (Figure I.12).²⁵ Each of these indicators provides some information regarding the ability of a country to withstand the balance of payments pressures associated with significant slowdown or reversal of capital flows. While there are well known rules of thumb to determine the “comfortable” level of foreign exchange reserves (e.g., the Guidotti rule that says that reserves should fully cover total external debt by remaining maturity), the meaningful thresholds for the external liquidity indicators can only be determined within a framework that takes into account the relevant country circumstances that either provide additional buffers (e.g., in Croatia, short-term external debt includes a high proportion of bank borrowing from foreign parents, akin to “quasi-equity”) or could make the impact of negative shocks more damaging.²⁶ Moreover, what seems to matter most is a combination of liquidity indicators and other macroeconomic variables.

30. Weak external liquidity indicators tend to increase the risk of a significant slowdown or reversal in capital flows, especially against the backdrop of a deteriorating global environment. Empirical research has long tried to identify variables (and their thresholds) that would provide significant leading information regarding the likelihood of capital flow reversals. In particular, a recent empirical study that applies the Binary Classification Tree methodology for predicting the capital flow reversals suggests that a combination of (i) reserve cover of less than 81 percent, (ii) external debt higher than 24 percent of GDP; and (iii) external debt not falling by at least 3 percent of GDP per year, can significantly increase the likelihood of capital flows reversal in the following year (Figure I.13); unfavorable global cyclical conditions can contribute as well (Figure I.14).²⁷ While these thresholds should only be interpreted as suggestive, they provide useful information regarding the circumstances that could render a country more or less vulnerable to capital flow reversals.

31. Finally, capital flow reversals often have an important contagion component. This is particularly relevant for Croatia given the high share of foreign ownership of the banking sector and high reliance on relatively concentrated sources of external funding—mainly Italian and Austrian banks. These exposures render Croatia vulnerable to shocks unrelated to Croatia’s fundamentals, such as one of the parent banks’ experiencing problems due to the developments elsewhere in the region (the contagion risks are analyzed in greater detail in the accompanying FSSA report).

D. Concluding Remarks

32. In all, the analysis presented in this chapter suggests that there are reasons to be concerned about Croatia’s external position. While Croatia’s real exchange rate is broadly in line with economic fundamentals, this conclusion rests on strong macroeconomic policies. Moreover, the sustainability of Croatia’s external debt and financial account position could be at risk in the event of foreign interest rate shocks and/or a significant slowdown in capital inflows. Thus, external stability considerations suggest the following policy implications:

Macro-prudential indicators (external liquidity indicators, as well as banking sector capital adequacy and liquidity indicators) should continue to be monitored closely for any signs of emerging pressures in order to determine whether further tightening of prudential standards might be warranted.
Continued fiscal consolidation would be beneficial, including by reducing aggregate demand pressures and contributing to more favorable current account and external debt dynamics.
Structural measures to improve the business environment and thus competitiveness should be central to the reform agenda. Such measures remain critical for Croatia to become a more attractive destination for export-oriented FDI. In addition, such measures would help Croatia prepare for EU accession, raise confidence that accession will take place on a timely basis, and thereby contribute further to maintaining stability.

References

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Appendix I.I: Macroeconomic Balance Approach

Data and variable definitions:

The sample includes 54 economies (both industrial and emerging market countries, including Croatia) and the euro area, for the period from 1973–2004 (see the CGER note for a complete list of countries).

The following variables are calculated as deviations from the averages for trading partners:

Fiscal balance is measured as the ratio of the general government balance to GDP.
Old-age dependency ratio is measured as the ratio of the population above 65 to the population between 30 and 64.
Population growth is the annual population growth rate.
Output growth is growth rate of real per-capita GDP.

Other variables are as follows:

Initial NFA is measured as the ratio of NFA to GDP prevailing at the beginning of each 4-year period.
Oil balance is measured as a ratio to GDP
Relative income is measured as the ratio of per-capital PPP income to the US level, both in constant 2000 dollars.

Estimation of the current account norms:

CGER Estimates: Pooled Regression Coefficients

Note: ^*, ^**, ^***, indicate significance at the 10, 5, and 1 percent levels, based on standard errors robust to serial correlation.

CGER Estimates: Pooled Regression Coefficients

	Norm_CA	Norm_NFA
Fiscal balance	0.19 ^***	0.19 ^***
Old-age dependency	-0.12 ^**	-0.14 ^**
Population growth	-1.03 ^***	1 22 ^***
Lagged current account	0.37 ^***
Initial NFA		0.02 ^***
Oil balance	0.17 ^***	0.23 ^***
Output growth	-0.16 ^**	-0.21 ^**
Relative income	0.02 ^*	0.02 ^*
Constant	-0.003	0.000
Adjusted R-squared	0.52	0.52

Note: ^*, ^**, ^***, indicate significance at the 10, 5, and 1 percent levels, based on standard errors robust to serial correlation.

CGER Estimates: Pooled Regression Coefficients

	Norm_CA	Norm_NFA
Fiscal balance	0.19 ^***	0.19 ^***
Old-age dependency	-0.12 ^**	-0.14 ^**
Population growth	-1.03 ^***	1 22 ^***
Lagged current account	0.37 ^***
Initial NFA		0.02 ^***
Oil balance	0.17 ^***	0.23 ^***
Output growth	-0.16 ^**	-0.21 ^**
Relative income	0.02 ^*	0.02 ^*
Constant	-0.003	0.000
Adjusted R-squared	0.52	0.52

Note: ^*, ^**, ^***, indicate significance at the 10, 5, and 1 percent levels, based on standard errors robust to serial correlation.

Appendix I.II: Stabilizing Net IIP/GDP and External Debt/GDP

Using a simple accounting framework, the net IIP of a country can be decomposed as follows:

b_{t} - b_{t - 1} \equiv n i c a_{t} + (\frac{i_{t}^{E Q A} - n_{t}}{1 + n_{t}} a_{t - 1}^{E Q A} + \frac{i_{t}^{D A} - n_{t}}{1 + n_{t}} a_{t - 1}^{D A}) - (\frac{i_{t}^{E Q L} - n_{t}}{1 + n_{t}} l_{t - 1}^{E Q L} + \frac{i_{t}^{D L} - n_{t}}{1 + n_{t}} l_{t - 1}^{D L}) + ϵ_{t} (1)

where b_t is the net IIP of a country (expressed in percent of GDP); a_t and l_t denote gross asset and liability positions, respectively (expressed in percent of GDP); nica_t is the non-income CA balance (in percent of GDP); n_t is the growth rate of nominal GDP; $i_{t}^{E Q A}$ is the nominal rate of return on portfolio equity and FDI assets (outward FDI); $i_{t}^{D A}$ is the nominal rate of return on holdings of foreign debt instruments; $i_{t}^{E Q L}$ is the nominal rate of return on portfolio equity and FDI liabilities (inward FDI); $i_{t}^{D L}$ is the nominal rate of return on liabilities consisting of foreign debt instruments; and ε_t includes changes in the valuation of assets and liabilities, as well as errors and omissions.

Focusing on the stock of external debt, (1) can alternatively be rewritten as follows:

l_{t - 1}^{D L} - l_{t}^{D L} = n i c a_{t} - [\underset{A u t o m a t i c D e b t D y n a m i c s}{\underset{︸}{(\frac{i_{t}^{D L} - n_{t}}{1 + n_{t}} l_{t - 1}^{D L})}} - F + A] + ϵ_{t} (2)

where $A = (a_{t}^{A} - a_{t - 1}^{A}) - (\frac{i_{t}^{A} - n_{t}}{1 + n_{t}} a_{t - 1}^{A})$ is the change in gross foreign assets net of interest earned on the foreign asset holdings; $F = (l_{t}^{E Q L} - l_{t - 1}^{E Q L}) - (\frac{i_{t}^{E Q L} - n_{t}}{1 + n_{t}} l_{t - 1}^{E Q l})$ is the change in gross equity liabilities net of income paid to foreign direct/equity investors. The first term in the square brackets corresponds to the “automatic debt dynamics” from the IMF’s standard external Debt Sustainability Analysis.

Appendix I.III: Application of the Binary Classification Tree for Predicting the Capital Flow Reversals

Prepared by Anna Ilyina.

See, e.g., “Emerging Europe’s Current Account Deficits: Mind the Gap!” by FitchRatings, January 31, 2008.

In particular, the 2007 Decision on Bilateral Surveillance clarifies that the objective of the IMF’s surveillance is to foster stability of the international monetary system by encouraging national policies that do not disrupt or compromise the members’ own “external stability.”

Decision on Bilateral Surveillance, http://www.imf.org/external/np/pp/2007/eng/062107.htm

ULCM stands for “unit labor cost in manufacturing.”

The results seem to be sensitive to the choice of the time period, data frequency and the definitions of the tradable and non-tradable sectors. See Mihaljek and Klau (2003), Egert (2005), and Funda et al. (2007) for more details. For example, Funda et. Al. (2007) found no statistically significant Balassa-Samuelson effect, but using a simple accounting framework, they assess the contribution of the Balassa-Samuelson effect to annual inflation over a period of 1999–2006 to be a maximum of 0.64 percentage points.

For example, Croatia’s export share in world imports of chemicals remained stable since 2001, but the composition has been changing, with the share of “chemical elements and compounds” and “plastic materials” declining and the share of “pharmaceutical products” and “perfume materials, etc.” increasing (based on COMTRADE data), indicating possible shifts towards higher value-added goods.

See Moore and Vamvakidis (2008) for more details.

Both the macroeconomic balance and external sustainability approaches are used by the IMF’s internal Consultative Group on Exchange Rate Issues (CGER), which provides multilaterally consistent exchange rate assessments for a number of advanced and emerging market countries. While Croatia is included in the sample used in the panel regression estimation of the current account norms, it is not on the list of countries for which the CGER group provides regular assessments of real exchange rate misalignment. The results reported in this section, however, are largely based on the CGER methodology (Methodology for CGER Exchange Rate Assessments (2006)).

See Isard (2007) for an overview and discussion of the equilibrium exchange rate assessment methodologies.

NFA is the difference between a country’s total foreign assets and total foreign liabilities.

See Blanchard and Giavazzi (2002).

See Regional Economic Outlook (2008), Box 9, which presents the CEE CA norms estimated using a variant of the macroeconomic balance approach.

The ERER estimation was performed using two sets of productivity data from Funda et al. (2007), one with “hotels and restaurants” included in the tradable sector (in view of the importance of tourism revenues for Croatia’s current account position) and the other with “hotels and restaurants” included in the non-tradable sector. The results are not significantly different. For more details on the ERER approach, see Methodology for CGER Exchange Rate Assessments (2006).

See, Regional Economic Outlook (2008), Box 9, Chapter 3. This approach involves computing the difference between the actual current account balance and the predicted current account balance based on the estimated regression of the current account deficit on the level of income per capita relative to the peer group average, and a number of other control variables (see Blanchard and Giavazzi (2002) for details).

All numbers are calculated from underlying data in euro terms.

Note that the concept of “net debt” used in this Chapter is different from that used in the staff report. All ratios are calculated from underlying data in euro terms.

After having increased by 60 percent annually in 2006-07, stock prices fell by 30 percent during the first three months of 2008 (see Financial System Stability Assessment Update (2008) for more details on the stock market developments).

This concept is also referred to as “trade balance inclusive of services and transfers” (IMF (2006), page 19).

See Reinhart, Rogoff, and Savastano (2003).

Notwithstanding the improvements in methodology, possible measurement errors in both the numerator and the denominator of the external debt-to-GDP ratio are yet another reason why focusing on a particular “threshold” level may not be very practical.

See “Republic of Croatia: Financial System Stability Assessment Update,” 2008.

This is because of a high level of financial euroization and significant balance-sheet exposures of the non-financial sector to exchange rate risk. See Hilaire and Ilyina (2006) for detailed discussion of Croatia’s sectoral balance-sheet vulnerabilities.

The average interest rate paid by Croatian banks on their external liabilities may, to some extent, reflect the parent-subsidiary relationship between Croatian banks and their foreign owners (e.g., the “quasi equity” nature of certain liabilities to parent banks).

The external liquidity ratio is defined as liquid external assets (net official reserves plus banks’ gross external assets) divided by liquid external liabilities (short-term external debt on the remaining maturity basis). The reserve cover is the ratio of official reserve to the sum of current account deficit and short-term external debt by remaining maturity. The external debt service ratio is the ratio of debt service to current external receipts.

For example, an adjusted external liquidity ratio (which adds foreign currency deposits in domestic banks to external liabilities) is sometimes used to gauge the adequate level of external liquidity in the context of high financial dollarization/euroization (see, e.g., FitchRatings (March 2007)). This is because the adjusted external liquidity indicator also takes into account the amount of foreign exchange that banks would need to raise in an extreme event of withdrawal of all foreign currency deposits from the banking system. In the case of Croatia, this indicator stood at around 58 percent at end-2007, reflecting the historically high level of financial euroization as well as the size of Croatia’s banking system. However, this indicator should be interpreted with caution: in particular, if one were to draw policy implications taking into account the level of euroization, it would be essential to make realistic assumption with regard to the share of foreign currency deposits that might be withdrawn in an extreme scenario, taking into account historical experience.

See Chamon, Manasse and Prati (2007) for more details. The main advantage of this approach is that it considers a large number of variables and complex interactions between these variables without imposing any specific functional forms on these interactions.

References

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Appendix. Data Envelopment Analysis (DEA)²³

The DEA technique is a non-parametric method of estimating production possibility sets, which can be used to evaluate the efficiency in the use of inputs in producing outcomes for a sample of production units.²⁴ It is mostly used for estimating relative efficiency in business applications, but it has recently also been used to assess the relative efficiency of public expenditure. In the context of government expenditure efficiency, indicators of public production are typically used to measure outcomes, for example, life expectancy and infant mortality rates (in health care), youth literacy rates and test scores (in education), and the number of roads and telephone lines (in infrastructure). Inputs used to produce these outcomes are public and private expenditure on health, education, and infrastructure, as well as intermediate outputs and resources such as the number of doctors and hospital beds (in health care) and enrollment rates and student-teacher ratio (in education). The production units in this case are often countries, but could also be sub-national regions.²⁵

Figure II.A1 illustrates a stylized example of DEA based on a single input and outcome indicator across countries. The efficient frontier connects countries A to D as these units dominate countries E and G in the interior. The convexity assumption allows an inefficient country (point E) to be assessed relative to a hypothetical position on the frontier (point Z) by taking a linear combination of efficient unit pairs (points A and B). In this manner, an input-based technical efficiency score that is bounded between zero and one can be calculated as the ratio of YZ to YE. The score corresponds to the proportional reduction in inputs that is consistent with relatively efficient production of a given output, and can be interpreted as an indicator of the cost savings that could be achieved from efficiency enhancement. Similarly, an output-based technical efficiency score can be calculated as the ratio of FX to EX, which reflects the improvement in outputs for given inputs that could be achieved from efficiency enhancement. This paper focuses on output-based efficiency scores, since Croatia will need to improve outcomes without increasing expenditures.²⁶ ²⁷

DEA is a powerful tool to assess the relative efficiency of spending, but also has important caveats. For example, it does not require an assumption about unknown functional forms for the efficiency frontier or complex distributional properties for econometric analysis. However, it is also subject to the following caveats:

Results are highly sensitive to sample selection and measurement error. As a result, outliers exert large effects on the efficiency scores and the shape of the frontier. For this reason, proper sample selection is the key to ensuring that cross-country input-output combinations are comparable.
Spending attributes that are difficult to quantify are not easily incorporated in the analysis, such as the quality of spending.
The outcome indicators against which inputs are evaluated may not actually be targeted by policy makers.
Large differences across countries in private health care or education spending could bias the efficiency scores of public spending, as the outcomes targeted by policy makers are also impacted by private spending.
Factors beyond the direct control of policy makers can also affect relative efficiency scores. For instance, a high incidence of AIDS would reduce the measured efficiency of health spending in African compared to other countries.

Moreover, simple DEA estimation produces biased estimates of the efficiency scores that need to be corrected. In particular, the best-practice frontier can move outward, if efficient pairs/countries are added in the sample, but cannot move inward. This one-sided error means that estimating the best-practice frontier with a finite sample is subject to bias. Since output–oriented efficiency scores are measured in relation to the frontier, the estimated scores are subject to the same finite sample downward bias (i.e., the level of efficiency is overestimated unless a correction is made for the bias). This bias stems from the fact that since we only observe a sub-sample of the possible outcomes representing all feasible combinations of spending and outcomes, we do not know the exact position of the best-practice frontier. Where appropriate, corrections are made for the estimation bias in the best-practice frontier and efficiency scores through bootstrapping, as suggested by Simar and Wilson (2000).²⁸

DEA results can be disaggregated to assess at what stage of the spending process inefficiencies arise. This is done as by comparing spending efficiency (the overall measure of efficiency from spending to outcomes as discussed above) and system efficiency (the measure of efficiency from intermediate outputs to outcomes; Tables II.5 and II.9). Figure II.A2 illustrates how it is done in the analysis of efficiency of health care spending. First, cost efficiency is assessed using health care spending and intermediate output indicators such as hospital beds, immunizations, physicians, health care workers and pharmacists per capita. Second, efficiency scores are calculated, using the intermediate output index as an input and associated outcomes (infant, child, and maternal mortality rates, as well as HALE, standardized death rates and the incidence of tuberculosis). Third, the resulting system efficiency rankings are averaged, and expressed as a ratio of the average OECD ranking, and compared with similar ratios for spending efficiency.

Prepared by Etibar Jafarov (EUR) and Victoria Gunnarsson (FAD).

This pressure is related to the use of EU structural funds, contributions to the EU budget, and an upgrading of environmental standards. Funck (2003) suggested that implementing National Programs for the Adoption of the Acquis of the new member states was going to have entailed additional annual spending of (on average) about 3½ percent of GDP for these countries. Cucilić, Faulend, and Šošic (2004) estimated net fiscal costs (netting out transfers from the EU) of Croatia’s EU accession for 2007, the year the authors had expected accession to take place at the time of writing, at 1.1 percent of GDP.

The projection does not include spending related to the use of EU structural funds.

EU-10 countries are new EU members and comprise the Czech Republic, Estonia, Latvia, Hungary, Lithuania, Poland, Slovakia, Slovenia, Bulgaria, and Romania. EU-15 countries comprise Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden, and the United Kingdom.

Old-age pensions will not be a subject of this study, since this component of social spending does not lend itself to analysis of efficiency in the same way as the other components that are analyzed.

Results for the EU-10 are heavily influenced by the results for Bulgaria and Romania, which have significantly worse results than the other new EU members. But Croatia’s performance is still slightly better than the averages for the other EU-10 countries.

Twenty groups of people, including pensioners, unemployed, and students, are exempt from paying contributions. Only around 35 percent of the population pays contribution.

See Funding Health Care by Mossialos et al. (2002) for a description of cost sharing in Europe. Several countries, including Australia, Canada, and Switzerland, do not allow supplementary insurance to cover co-payments associated with services paid for by the health insurance fund.

These lists were introduced in 2006. For drugs on the B list, the HZZO pays a reference price for drugs on the A list and consumers pay the difference between the sale and reference prices. As a result of strong bargaining, pharmaceutical spending was reduced by about 2 percent in 2007, despite a 6 percent increase in consumption of drugs.

Over a third of total health care spending in Croatia finances hospital (in-patient) care.

Croatia ranked 26^th on the PISA science scale, ahead of some EU countries (e.g., Italy and Spain).

The sequencing of possible reforms and related political economy issues are beyond the scope of this paper.

This analysis does not provide estimates of causality. It is possible that causality goes the other way around or both ways. The small sample size precludes regression analysis in the second-stage.

Given the close relationship of spending and outcomes with income levels, correlations of efficiency scores and associated factors are conditional on GDP. GDP per capita is adversely related to efficiency since many of the factors that are associated with efficiency are also closely related to income level. In order to avoid attribution of factors whose effects on the variation in efficiency cannot be separated from the effect of GDP, only GDP per capita and factors that are correlated with efficiency independently of GDP per capita are considered in the second-stage analysis of this chapter. The association with efficiency of factors that are strongly correlated with GDP is assessed by regressing the efficiency score on both GDP and the associated factor.

The Croatian government adopted the National Health Care Development Strategy 2006–11 to enhance and secure better-quality health care for citizens. The strategy includes both system reforms and financing reforms.

The replacement rate is the ratio of benefits to (previously received) income.

About 6 percent of the labor force was on sick leave in 2005; anecdotal evidence suggests that sick leave is used to deal with excess employment at the business level.

Moreover, restricting the basic benefit package would stimulate private participation in the provision of additional insurance.

The share of obese people in Croatia is almost double the average of the EU-15. Mihaljek (2007) mentions an unhealthy lifestyle (high alcohol and tobacco consumption, and prevalence of physical inactivity) as the likely reason for the difference in mortality rates for non-communicable diseases between Croatia and EU-15 countries.

Efficiency in secondary education is estimated using both a combined set of secondary intermediary outputs and outcomes, and PISA scores only.

System efficiency was estimated only for the secondary education level, where PISA test scores were used as education outcome. The overall public sector efficiency (quartile) rankings in the primary and secondary levels presented in Table II.7 are for the first stage of the production process (spending to intermediary outputs), since no education outcomes such as test scores are available at these levels.

See Annex I for description of caveats of DEA.

This Appendix is based on Zhu (2003), Mattina and Gunnarsson (2006), and Verhoeven et al. (2007).

It was developed by Farrell (1959) and popularized by Charnes, Cooper and Rhodes (1978). See Zhu (2003) for more detailed discussion of DEA.

There is well-established literature using DEA to assess the relative efficiency of public expenditure. Gupta and Verhoeven (2001) studied the relative efficiency of education spending in a broad sample of African countries during the 1984–95 period. Afonso and St. Aubyn (2004) applied DEA and a related frontier-based approach on health and education spending in a sample of OECD countries. Herrera and Pang (2005) studied the relative efficiency of spending in 140 countries using DEA. Afonso, Schuknecht and Tanzi (2006) applied DEA in a sample of EU and emerging market countries. An important contribution of their work was to apply truncated regression models based on procedures developed by Simar and Wilson (2007) to control for exogenous factors that impact efficiency but that are not directly controlled by policy makers. Coelli, Lefebvre, and Pestieau (2007) applied DEA to study social protection performance in the EU.

An output-based efficiency score of one corresponds to a relatively efficient country operating on the frontier. Scores exceeding one imply that spending could achieve better output performance. This differs from input-based efficiency scores that range between zero and one.

The input- and output-based efficiency scores are equal assuming constant returns to scale. However, the DEA models considered in this chapter permit variable returns to scale.

A key issue is how quickly the estimated efficiency scores converge to their unbiased true values if the sample of observations is expanded. This convergence speed is n^2/(p+q+1), where p is the number of inputs and q is the number of production items. In the 1 input / 1 product examples of this Appendix, the convergence speed is n^-2/3. This is faster than the convergence speed for a standard parametric regression of n^-1/2, suggesting that reasonable estimates of efficiency scores and confidence intervals can be reached with a lower number of observations than would be needed for standard regression analysis. However, the convergence speed declines exponentially as the number of inputs and production items is increased, and already at two inputs and production items, the speed of convergence is markedly slower than for a parametric regression. This implies that an expansion in the numbers of inputs and production items comes at a significant cost in terms of the ability to draw conclusions on efficiency from a limited number of observations.

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Republic of Croatia: Selected Issues

Author: International Monetary Fund

Volume/Issue:: Volume 2008: Issue 159

Publisher:: International Monetary Fund

ISBN:: 9781451817478

ISSN:: 1934-7685

Pages:: 71

DOI:: https://doi.org/10.5089/9781451817478.002

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Income Catch-up and Current Account Deficits in Eastern Europe

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Croatia and Selected European Countries: Saving-Investment Balances, Credit and Real GDP Growth

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Croatia: Price and Cost Competitiveness Indicators, 1996–2007

REER, NEER and CPI (seasonally adjusted, 2000=100)

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Croatia: Current Account Components, 1997–2007

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Croatia and Selected European Countries: Merchandise Exports—Regional Comparisions

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Croatia and Selected European Countries: Competitiveness Indicators—Regional Comparisons

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Croatia and Selected European Countries: Structural Indicators

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Croatia: Financial Account and External Debt Developments

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International Investment Position

(In percent of GDP)

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External Debt (in percent of GDP): Baseline and Downside Risk Scenarios

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Croatia: Average Nominal Foreign Interest Rates by Domestic Sector

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External Liquidity Indicators, 2001-07 ^1/

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Binary Classification Tree Based on 1994–2005 Sample and Crisis Episodes

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Binary Classification Tree Based on 1994–2005, Including Contemporaneous Global Demand Variables

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Illustrative Example of Applying DEA

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The Efficiency Relationship Between Health Expenditures, Resources, and Outcomes

CGER Estimates: Pooled Regression Coefficients

	Norm_CA	Norm_NFA
Fiscal balance	0.19 ^***	0.19 ^***
Old-age dependency	-0.12 ^**	-0.14 ^**
Population growth	-1.03 ^***	1 22 ^***
Lagged current account	0.37 ^***
Initial NFA		0.02 ^***
Oil balance	0.17 ^***	0.23 ^***
Output growth	-0.16 ^**	-0.21 ^**
Relative income	0.02 ^*	0.02 ^*
Constant	-0.003	0.000
Adjusted R-squared	0.52	0.52

Note: ^*, ^**, ^***, indicate significance at the 10, 5, and 1 percent levels, based on standard errors robust to serial correlation.

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Abstract

I. Assessing Croatia’s External Stability1

A. Introduction

B. Current Account Sustainability

What are the key drivers of the current account dynamics?

Do the current account dynamics reflect deteriorating competitiveness?

Is the current account deficit sustainable?

The macroeconomic balance approach

The external sustainability approach

C. Financial Account and External Debt Sustainability

How is the current account deficit financed?

International Investment Position

External Debt

D. Concluding Remarks

References

Appendix I.I: Macroeconomic Balance Approach

Data and variable definitions:

Estimation of the current account norms:

Appendix I.II: Stabilizing Net IIP/GDP and External Debt/GDP

Appendix I.III: Application of the Binary Classification Tree for Predicting the Capital Flow Reversals

References

Appendix. Data Envelopment Analysis (DEA)23

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Table of Contents

Headings

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I. Assessing Croatia’s External Stability¹

Appendix. Data Envelopment Analysis (DEA)²³