Republic of Croatia: Selected Issues and Statistical Appendix
Author:
International Monetary Fund
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Publication Date:
12 Aug 2004
eISBN:
9781451817294
Language:
English
Keywords:
ISCR; CR; rate; lending rate; interest rate; lending; monetary policy; labor market performance; performance in Croatia; unit labor; labor market performance in Croatia; employment protection in Croatia; Labor markets; Labor costs
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This Selected Issues and Statistical Appendix paper analyzes monetary transmission in Croatia. The evidence analyzed in this paper supports the view that monetary policy in Croatia is not an effective tool for aggregate demand management. One of the main conclusions is that financial conditions in the economy are only weakly correlated with the monetary policy stance. Monetary policy can exercise some control over money-market interest rates, but its influence on lending rates is uncertain and comes with long lags. The paper also examines determinants of lending rates and domestic spreads in Croatia.

Abstract

This Selected Issues and Statistical Appendix paper analyzes monetary transmission in Croatia. The evidence analyzed in this paper supports the view that monetary policy in Croatia is not an effective tool for aggregate demand management. One of the main conclusions is that financial conditions in the economy are only weakly correlated with the monetary policy stance. Monetary policy can exercise some control over money-market interest rates, but its influence on lending rates is uncertain and comes with long lags. The paper also examines determinants of lending rates and domestic spreads in Croatia.

III. Employment Protection in Croatia18

A. Introduction and Summary of Conclusions

35. This chapter discusses the economic implications of employment protection in Croatia. Labor market performance in Croatia has been relatively poor, even compared with other Central and Eastern European countries (CEECs). Recent studies, such as Rutkowski (2003), attribute this poor performance, among other factors, to the strict employment protection in Croatia. Schneider and Dominik (2000) point out that stringent employment protection could also provide an incentive for firms to move to or remain in the informal sector in order to lower labor costs. A large informal sector could have a number of unwanted implications. Tax collections could be lower (indeed the Croatian Ministry of Finance has repeatedly blamed the size of the grey economy for unsatisfactory tax collections). Moreover, it could lower the productivity of the overall economy, as a recent study by Farell (2004) suggests: firms in the unofficial sector tend to be small, and their small scale limits their ability to fully utilize new technology and business practices, which drags down the productivity of the overall economy. This chapter presents the main stylized facts about employment protection and labor market performance in Croatia and examines the link between employment protection and the shadow economy.

36. The main conclusion is that the strict employment protection in Croatia is likely to have negative economic implications. Circumstantial evidence suggests that employment protection may have played an important role in explaining Croatia’s poor labor market performance. Also, empirical tests indicate that employment protection is correlated with the size of the shadow economy. The policy implications of these findings are that Croatia could enhance employment in the official sector, expand the tax base, and boost productivity by relaxing employment protection. Labor law amendments implemented at the beginning of this year, which lowered Croatia’s employment protection legislation (EPL) index by 23 percent,19 are an important step in this direction.

B. Employment Protection and Labor Market Performance in Croatia: Stylized Facts

37. Stringent employment protection may be significant in explaining the poor labor market performance in Croatia. There is no consensus in the literature on the overall effect of employment protection on the aggregate level of employment and unemployment over the economic cycle. However, it is widely agreed that stringent employment protection increases the incidence of long-term unemployment (Blanchard 2000), as it makes labor turnover difficult in the course of economic cycles. This issue becomes relevant in particular when the economy is hit by a severe negative shock, such as the transition from a planned to a market economy or a war, both of which Croatia experienced in the 1990s.

38. The labor market in Croatia has not performed well. In the early 1990s, economic restructuring and privatization significantly increased redundancies. The war between 1991 and 1995 worsened the situation. While labor shedding by many firms led to improved productivity, it also contributed to massive inflows to unemployment. Although economic growth has been brisk since the mid-1990s, outflows from unemployment, including outflows to jobs, have not accelerated, and have been falling short of inflows until 2000.20 The labor force survey-based unemployment rate has been hovering around 15 percent for the past five years, which is relatively high even among CEECs (Figure 1). In addition, the share of long-term unemployment in total unemployment has been significantly higher in recent years (hovering around 55 percent) than in major CEECs, such as the Czech Republic, Hungary, and Poland (averaging around 45 percent). Finally, the labor force participation rate has remained low at around 50 percent. In particular, unemployment is high and participation is low among the young. The overall low participation may reflect poor availability of job opportunities and mismatch problems.

Figure 1.
Figure 1.

Unemployment Rates, 1993-2002

(In percent)

Citation: IMF Staff Country Reports 2004, 251; 10.5089/9781451817294.002.A003

39. Firm-level data reveal that the job reallocation in Croatia is sluggish. Croatian firms yearly terminate about 5 percent of all jobs, compared with the job destruction rate of 10–11 percent in other CEECs.21 At the same time, the job creation rate in Croatia is only 3½ percent, compared with 7-11 percent in other CEECs. These figures point to the stagnant nature of Croatian labor market and indicate that the Croatian economy does not seem to undergo the same intensive enterprise restructuring as the leading reformers among CEECs.

40. Labor costs cannot explain the stagnant job creation in Croatia. A gross wage comparison in manufacturing sector among CEECs by the World Bank (2003) suggests that gross wages in Croatia are higher than in most of other CEECs. However, economy-wide unit labor cost comparisons show that Croatia has held a relatively strong position in recent years among CEECs (Figure 2). Furthermore, the gross wage in relation to GDP per employee indicates that Croatian workers are not overpaid compared with those in other CEECs (Figure 3).

Figure 2.
Figure 2.

Unit Labor Costs, 1998-2003

(In Euros; 1998Q1=100)

Citation: IMF Staff Country Reports 2004, 251; 10.5089/9781451817294.002.A003

Figure 3.
Figure 3.

Gross Monthly Wages and GDP per Employee, 2003

Citation: IMF Staff Country Reports 2004, 251; 10.5089/9781451817294.002.A003

41. Moreover, the unemployment benefit system in Croatia is not particularly generous. The unemployment benefit in Croatia is a flat rate benefit and the fixed maximum amount is only about one-fourth of the average wage. Figure 4 compares the replacement ratios of unemployment benefits in CEECs for the past 10 years, measured as the stipulated unemployment benefits in percent of previous year’s earnings. The comparison reveals that the replacement ratio in Croatia is relatively low. Also, relatively few unemployed receive the unemployment benefit in Croatia and the duration of the benefit payment is capped at 312 days, which is not out of line compared with other CEECs (Figure 5). The benefit coverage rate has been below 20 percent since the mid-1990s, reflecting two factors: (i) the unemployment rate is highest among new entrants to the labor market, who do not qualify for the unemployment benefit; and (ii) a large proportion of the unemployed are long-term unemployed, who are no longer eligible for the benefit. All these characteristics—low replacement rate, moderate duration of the benefit payment, and limited coverage—suggest that the labor supply disincentives related to the unemployment benefit system are likely to be modest in Croatia.

Figure 4.
Figure 4.

Stipulated Replacement Ratio of Unemployment Benefits to Previous Earnings, 1993-2002

(In percent)

Citation: IMF Staff Country Reports 2004, 251; 10.5089/9781451817294.002.A003

Figure 5.
Figure 5.

Duration of Unemployment Benefits, 1993-2002

(In number of months)

Citation: IMF Staff Country Reports 2004, 251; 10.5089/9781451817294.002.A003

42. However, employment protection in Croatia is among the strictest in CEECs. According to the estimated value of the EPL index, employment protection in Croatia is even stricter than in most of the EU-15 and other CEECs (Table 1). Individual dismissals are costly due to the long advanced notice period and high severance pay. Collective dismissals are even more difficult mostly because of the overly inclusive definition of collective redundancy. Although fixed-term employment is a way of circumventing the high costs of terminating regular employment contracts, the labor law until recently restricted its use by requiring that fixed-term contracts were signed only on an exceptional basis.

Table 1.

Employment Protection Legislation Index (EPL) of Selected CEECs

article image
Sources: World Bank (2002) and OECD Employment Outlook 1999.

Does not include Greece and Luxemburg.

43. Strict employment protection is also likely to have discouraged entry or expansion of new businesses in Croatia, which have been the engine of job creation in other CEECs.22 According to World Economic Forum’s “Quality of the National Business Environment Rank”, which ranks almost 100 countries based on survey scores of various factors affecting the business environment, Croatia ranks significantly behind the major CEECs, such as the Czech Republic, Hungary, and Poland. Croatia ranks worst in “cooperation in labor-employer relations”, which could be explained by the strict employment protection. The share of employment by small and medium-sized enterprises (SMEs), a proxy for new businesses, is 46 percent in Croatia, compared to well over 50 percent in major CEECs.

44. With a view to making the labor market more flexible, the labor law was amended in July 2003. The amended labor law, which entered into effect at the beginning of 2004, has lowered Croatia’s EPL index by 23 percent. The main changes include: (i) relaxing restrictions on the use of fixed-term contracts; (ii) easing the pre-conditions for valid dismissals; (iii) shortening the advanced notice period from 6 to 3 months; (iv) reducing the amount of severance pay from half to one-third of the monthly pay; and (v) relaxing the definition of mass lay-offs.

C. Employment Protection and the Shadow Economy

45. This section analyzes in more detail the role of employment protection in explaining the size of the shadow economy using cross-country data on selected OECD countries and CEECs. Although there is disagreement about the definition of shadow economy and estimation procedures of its size,23 many studies in this field find a growing trend in the share of the shadow economy relative to the official economy among the majority of OECD countries during the past 10 to 20 years.

46. Stringent employment protection leads to increased labor costs in the official economy. It provides an incentive for firms to move or remain in the informal sector in order to lower labor costs. Since labor costs can be shifted onto employees, it could also provide workers with an incentive to work in the shadow economy. Schneider and Pöll (1999) present some empirical evidence of this using firm-level data in Germany.

47. Cross-country comparisons indicate that strict employment protection is correlated with a large shadow economy. Figure 6 plots the size of the shadow economy in percent of GDP and the EPL index of 20 OECD countries and 7 CEECs and shows a clear positive correlation. As mentioned above, different methodologies give rise to different estimates of the size of a country’s shadow economy.24 This study uses the estimations provided by Schneider (2002) because the study covers a large variety of countries and reports the most recent estimates (average of 2000/01 on 22 transition economies and average of 2001/02 on 21 OECD countries). As the EPL index only exists for a smaller number of countries, the sample size is limited to 27 countries.

Figure 6.
Figure 6.

Strictness of Employment Protection and Size of Shadow Economy

Citation: IMF Staff Country Reports 2004, 251; 10.5089/9781451817294.002.A003

48. However, other factors also affect the size of the shadow economy and have to be controlled for to assess the impact of employment protection.25 Almost all studies point out that the tax and social security burden is one of the most important factors in explaining the size of the shadow economy. The bigger the tax wedge in the official economy, the greater the incentives to work in the shadow economy. Business regulations also affect the size of the shadow economy. Finally, it is widely recognized that the quality of infrastructure and effectiveness of public services improve as a country becomes richer. This indicates that the incentives to work in the unofficial sector become weaker as a country develops and per capita income grows.

49. Even after controlling for the tax wedge, business regulations, and per capita income, employment protection is still significant in explaining the size of the shadow economy. Table 2 reports the results of OLS regression of the size of the shadow economy on the log of per capita GDP, the EPL index, the tax wedge on labor income, and a business regulation index.26 As expected, the coefficient of per capita income is significantly negative, while the EPL coefficient is positive and highly significant: evidence that less employment protection is correlated with a lower share of the shadow economy even after controlling for other factors. This is consistent with a strand of literature (including Tokman 1990 and Loayza 1996) suggesting that labor regulation is a major factor behind the dynamics of the unofficial economy. However, it is in contrast with the findings of Johnson, et al (1998), who did not find significant evidence of a positive relation between labor regulation and the size of the shadow economy. Finally, contrary to a lot of existing studies, neither the tax wedge on labor income or business regulation index is significant. These results suggest that the strictness of employment protection plays a more important role in explaining the cross-country difference in the size of the shadow economy than the tax burden on labor income or business regulations.

Table 2:

OLS Estimation on the Impact of EPL on Shadow Economy

article image
Note: *** Indicates significance at 1percent level.

References

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  • Rutkowski, Jan, 2003, “Does Strict Employment Protection Discourage Job Creation?: Evidence from Croatia,” World Bank, Mimeo.

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STATISTICAL APPENDIX

Table A1.

Croatia: GDP by Expenditure Category, 2000-05

article image
Sources: Croatian National Bank, Ministry of Finance, Central Statistics Bureau, and staff estimates

Includes public enterprises.

Due to the switch from GFS1986 to GFS2001, there is a break in series between 2002 and 2003.

Includes statistical discrepancy.

Table A2.

Croatia: Trends in Industrial Production, 1996-2004

(Industrial production by main industrial groupings, 2000=100)

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Source: Central Bureau of Statistics.
Table A3.

Croatia: Price Developments, 1996-2004

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Source: Croatian National Bank.
Table A4.

Croatia: Indices of Real Net Wages and Salaries Per Employee, 1999-2003 1/

(1997=100)

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Source: Central Bureau of Statistics.

Excludes persons employed in crafts and trades, free-lancers, police and defense, as well as private farmers.

Table A5.

Croatia: Composition of Employment, 1999-2003

(In thousands)

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Source: Central Bureau of Statistics.

Includes active insured persons - private farmers measured mid-year. For 1999 and 2000 data are measured by end-year.

Refers to persons employed in crafts and trades as well as free-lancers during mid-year. For 1999 and 2000 data are measured by end-year.

Table A6.

Croatia: Exports by Destination, 1996-2003 1/

(In millions of U.S. dollars)

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Sources: Central Bureau of Statistics and the Fund staff estimates.

Data have not been revised in line with the 1998 balance of payments compilation methodology.

Countries of the former USSR includes 14 countries. It does not include Belarus.

Developing Middle East countries refer to the OPEC countries excluding Indonesia amd Venezuela.

Table A7.

Croatia: Tourism—Overnight Stays, 1996-2004

(In thousands)

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Source: Central Bureau of Statistics.
Table A8.

Croatia: Imports by Origin, 1996-2003 1/

(In millions of U.S. dollars)

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Source: Central Bureau of Statistics.

Data have not been revised in line with the 1998 balance of payments compilation methodology.

Table A9.

Croatia: External Debt, 1996-2004 1/

(In millions of U.S. dollars, unless otherwise stated)

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Sources: Croatian National Bank; and Fund staff estimates.

Excludes nonreported principal payments. Includes short-term credits and currency and deposits.

Table A10.

Croatia: Consolidated General Government Fiscal Operations by Economic Category, 1998-2003 1/

(In percent of GDP, GFS 1986 basis)

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Sources: Ministry of Finance and staff estimates.

On a GFS 1986 basis and with subnational government consisting of the 53 largest local governments.

In 2000, includes 0.5 percent of GDP in back taxes.

Table A11.

Croatia: Consolidated General Government Financial Operations by Economic Category, 2002-03 1/

(In percent of GDP, GFS 2001 basis)

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Sources: Ministry of Finance and staff estimates.

On a GFS 2001 basis. There may be differences from historical data, which were on a GFS 1986 basis.

Table A12.

Croatia: HBOR Operations by Economic Category, 1999-2003 1/

(In percent of GDP, GFS 1986 basis)

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Sources: Ministry of Finance, HBOR, and staff estimates.

Unconsolidated before corrections for central budgetary transactions.

Table A13.

Croatia: Debt Stock of Consolidated General Government, 1997-2003

(In percent of GDP)

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Sources: Croatian Central Bank, Ministry of Finance, and staff estimates. Note: Guarantees stock prior to 2002 based on data provided by Croatian Central Bank and stock from 2002 based on data provided by the Ministry of Finance with smaller differences in total stock and larger differences in distribution between domestic and external guarantees. Local government debt stock prior to 2002 was provided by Croatian Central Bank and from 2002 by the Ministry of Finance registering a generally higher level of local government debt.
Table A14.

Croatia: Selected Public Enterprises, 2000-03 1/

(In thousands of kuna unless otherwise specified)

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Sources: Ministry of Finance and staff calculations.
Table A15.

Croatia: Deposit Money Banks’ Accounts, 1996-2004 1/

(In millions of kuna; end-of-period)

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Source: Croatian National Bank.

From 1999 onwards, excludes assets and liabilities of banks declared bankrupt in April 1999. Changes in the statistical reporting system introduced a break in the data in July 1999.

Includes all central government agencies and funds, and the Croatian Bank for Reconstruction and Development (HBOR).

Table A16.

Croatia: Deposit Money Banks’ Credit and Deposit Rates, 1996-2004 1/

(Monthly weighted average; in percent, annualized)

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Source: Central Bureau of Statistics.
18

Prepared by Tetsuya Konuki.

19

EPL index is a weighted average of 22 indicators which represents the degree of restrictions to hire and dismiss workers. It takes values from one to six, and the higher the value the stricter the employment protection regulations.

20

See Rutkowski (2003) for detailed discussions on labor market performance in Croatia.

21

Rutkowski (2003) presents cross-country comparison of job creation and destruction among the CEECs.

23

The feature “Controversy: On the Hidden Economy” in Economic Journal (Vol. 109, No. 456, June 1999) documents the differing opinions of, e.g., Tanzi (1999), Thomas (1999), and Giles (1999).

24

See Schneider and Enste (1999) and Feige and Urban (2003) for illustrative examples.

25

Schneider and Enste (2000) provide an illustrative survey on this issue.

26

Business regulation index as of 2001, compiled by the Economic Freedom Network, is used as a measure of strictness of business regulations. It takes into account price controls, time required for new business entry, and the extent of irregular payments to business regulators. It ranges from 1 (most strict) to 10 (most liberalized).

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Cover IMF Staff Country Reports
Republic of Croatia: Selected Issues and Statistical Appendix
Author:
International Monetary Fund
Volume/Issue:
Volume 2004: Issue 251
Publisher:
International Monetary Fund
ISBN:
9781451817294
ISSN:
1934-7685
Pages:
53
DOI:
https://doi.org/10.5089/9781451817294.002
  • Figure 1.
    View in gallery
    Figure 1.

    Unemployment Rates, 1993-2002

    (In percent)

  • Figure 2.
    View in gallery
    Figure 2.

    Unit Labor Costs, 1998-2003

    (In Euros; 1998Q1=100)

  • Figure 3.
    View in gallery
    Figure 3.

    Gross Monthly Wages and GDP per Employee, 2003

  • Figure 4.
    View in gallery
    Figure 4.

    Stipulated Replacement Ratio of Unemployment Benefits to Previous Earnings, 1993-2002

    (In percent)

  • Figure 5.
    View in gallery
    Figure 5.

    Duration of Unemployment Benefits, 1993-2002

    (In number of months)

  • Figure 6.
    View in gallery
    Figure 6.

    Strictness of Employment Protection and Size of Shadow Economy

Figure 1.

Unemployment Rates, 1993-2002

(In percent)
Figure 2.

Unit Labor Costs, 1998-2003

(In Euros; 1998Q1=100)
Figure 3.

Gross Monthly Wages and GDP per Employee, 2003
Figure 4.

Stipulated Replacement Ratio of Unemployment Benefits to Previous Earnings, 1993-2002

(In percent)
Figure 5.

Duration of Unemployment Benefits, 1993-2002

(In number of months)
Figure 6.

Strictness of Employment Protection and Size of Shadow Economy