The spike in Slovenian inflation in 2007–08 has shown how structural bottlenecks may hamper Slovenian growth in the future. This Selected Issues paper investigates the role of supply factors and demand-side effects in explaining this surge. The paper concludes that the spike in Slovenian inflation in 2007–08 was a consequence of cost-push and demand-pull factors. The supply-side factors, including the spike in commodity prices and demand-pull factors related to the business cycle, explained approximately two-thirds of the surge.

Abstract

The spike in Slovenian inflation in 2007–08 has shown how structural bottlenecks may hamper Slovenian growth in the future. This Selected Issues paper investigates the role of supply factors and demand-side effects in explaining this surge. The paper concludes that the spike in Slovenian inflation in 2007–08 was a consequence of cost-push and demand-pull factors. The supply-side factors, including the spike in commodity prices and demand-pull factors related to the business cycle, explained approximately two-thirds of the surge.

I. What Can we Learn from the Spike of Inflation in Slovenia in 2007–08?1

1. The spike in Slovenian inflation in 2007 and 2008 (an increase from 3.8 percent in 2007 to 5.5 percent in 2008, well above the euro-area average) has shown how structural bottlenecks may hamper Slovenian growth in the future. This paper investigates the role of supply factors (i.e., the increase in commodity prices and the catching-up effect) and demand-side effects (i.e., business cycle) in explaining this surge. Commodity related cost-push factors account for about 30 percent of the 2007–2008 surge in inflation while demand-pull factors explain approximately 37 percent; the remaining third is explained by other factors, including possibly labor cost pressure.

A. Context

2. Inflation in Slovenia (measured as percentage change Harmonized index of consumer prices, HICP) has always been higher than that in other Euro area countries but the gap has changed over time.2 Slovenian inflation was 6.8 percent greater than Euro area inflation in 2000 but the gap decreased in the first half of the 2000s, reaching 0.3 percent in 2005, mainly due to the monetary policy framework focusing on price stability in 2001 and the introduction of Exchange Rate Management II (ERMII) in June 2004. Inflation diverged again in 2007 with the gap widening from1.6 percent in 2007 to 2.2 percent in 2008 (see Figure 1). Core inflation, which excludes food and fuel, followed the same path.

Figure 1:
Figure 1:

Slovenia Inflation

Citation: IMF Staff Country Reports 2009, 160; 10.5089/9781451835816.002.A001

Source: Eurostat

Supply-Side: The Effect of Commodity Price Increase

3. The increase in food and fuel prices contributed greatly to the sharp rise in inflation in 2007 and 2008. In 2007, international food and fuel prices increased by 15.2 and 10.4 percent, respectively. The combined commodity price increases contributed directly to Slovenia’s HICP inflation of about 2 percent.3 The effect intensified in 2008 when the surge of 23.4 and 40.1 percent in world food and fuel prices translated into 3.1 percent increase in Slovene inflation (Figure 2).

Figure 2:
Figure 2:

Food and Fuel Prices

Citation: IMF Staff Country Reports 2009, 160; 10.5089/9781451835816.002.A001

Source: Eurostat, IMF staff calculation

4. The pass-through of food and fuel prices to Slovenian prices is high for three reasons:

  • First, the share of food and fuel in Slovenia’s HICP basket (35.3 percent) is higher than that of the euro area (28.5 percent), leading mechanically to a large first round effect (Surti, 2007).

  • Second, increases in international prices translate to high increases in domestic fuel prices: a one percent increase in world fuel prices leads to a 0.29 percent increase in domestic fuel prices.4 This estimate is comparable to that of advanced economies and twice as much as the average of emerging economies. Assuming that all pass-through was completed during the first year, the first-round fuel pass-through effect accounted for 2.4 percentage points of inflation in the first nine months of 2008 (see Figure 3).

  • Third, the second-round pass-through effect from domestic food and fuel prices to core inflation in Slovenia is elevated.5 The food price pass-through is 0.66 percent for a one percent increase in domestic food prices, which is approximately three times as much as that of advanced countries and 0.11 percent greater than that of emerging economies.6

Figure 3:
Figure 3:

Commodity Price Pass-through

Citation: IMF Staff Country Reports 2009, 160; 10.5089/9781451835816.002.A001

Source: IMF Staff calculation

B. The Euro Adoption

5. The surge in Slovene inflation is only partly due to the introduction of the Euro. The Euro adoption could have resulted in both a short-term currency changeover effect and the catching-up effect as observed also in other non-core countries joining the euro area. Figure 4 presents the difference between each country’s and the average euro-area inflations in the years immediately before and after the Euro adoption. In all cases, the inflation differential increased after the introduction of the Euro; in the cases of Greece, Ireland, and Slovenia one year after the adoption of the Euro; in the case of Portugal, after two years.

Figure 4:
Figure 4:

Inflation Response to the Euro Adoption

Citation: IMF Staff Country Reports 2009, 160; 10.5089/9781451835816.002.A001

Source: Eurostat

6. The Euro changeover effect was rather small. During the transition period, inflation perceptions could have been blurred by expectations of price increases and the complexity of the conversion rate from national currency to the Euro. Some retailers may have used the changeover to increase short-term profits by increasing prices. For Slovenia, nonetheless, the Euro changeover contributed only 0.13 and 0.10 percent to inflation in December 2006 and January 2007 respectively, and it mostly affected prices of services (IMAD, 2007). The limited effect of currency changeover may be due to price control policies enacted during the first half of 2007.

7. The catching-up effect is plausible, but its magnitude is negligible.7 A Balassa-Samuelson effect is plausible because productivity growth in tradable sector has been leading the increase in prices of nontradables after the ERMII. Table 1 presents the estimates of catching-up effect for Slovenia in 2000–2008 and the two sub-periods before and after the ERMII. A one percent difference of the productivity growth between tradable and non-tradable sectors results in a 0.04–0.11 percent increase in the relative price of nontradables.

Table 1:

The Estimates of Catching-up Effect

article image
Note: The above table shows the estimates of the catching-up effect for Slovenia following the empirical specification, Log(PtNTPtT)=α+βLog(Pt1NTPt1T)+φ.Log(δγLPtTLPtNT)+εt, where (PNT/PT) is the relative price of non-tradable goods and (LPT/LPNT) denote the ratio of labor productivity of tradable to non-tradable sector. The quarterly data range from 2000:Q1 to 2008:Q2. The labor productivity of tradable sector considers the ratio of output to employment in agriculture, fishing, mining and manufacturing, while that of non-tradable sector is the ratio of output to employment of the rest in national account. The above equation is estimated by GMM estimation using lagged dependent and independent variables up to 4 lags as instrument variables. Robust standard errors are shown in parenthesis. ***, ** and * imply significance level at 1 percent, 5 percent and 10 percent respectively.

8. Nonetheless, the contribution of the catching-up effect to Slovene HICP inflation appears to be small and relatively stable in the past four years. Figure 5 shows the catching-up effect in 2005–2007, using the estimates from equation 4 after the ERMII and assuming that factor intensities are the same in both tradables and nontradables. The estimated catching-up effect was about 0.3 percent in 2005–2007, explaining only 10 percent of Slovenia’s inflation. Consequently, the catching-up effect does not account for a recent surge in inflation (Figure 5).

Figure 5:
Figure 5:

The Catching-up Effect

Citation: IMF Staff Country Reports 2009, 160; 10.5089/9781451835816.002.A001

Source: Staff calculation

C. Demand-Side: Business Cycle

9. This study applies the traditional Phillips curve framework to analyze the demand-pull effect on inflation. The augmented Phillips curve is estimated to address the relationship between output and inflation, i.e., regresses the inflation on its lag level (to measure persistence), the output gap, and other controls. The sample includes Euro-12 countries and Slovenia. The data are annual from 1997 to 2007. The results are shown in Table 2.

Table 2:

Augmented Phillips Curve

article image
Note: The above table reports the estimates of the augmented Phillips curve of Euro-12 and Slovenia. The regression takes form: πi.t = α + β.πi, t − 1 + γ.(yy*)i,t + φ.Xi,t + εi,t where π is HICP inflation, (y − y*) is output gap as percentage deviation from potential output, and X is the set of control variables, e.g., change in oil price and a dummy for Euro adoption equal to 1 after Euro adoption and 0 otherwise. The annual data range from 1997–2007. The regression is estimated by Arellano-Bond dynamic panel technique. Robust standard errors are shown in parenthesis. ***, ** and * imply significance level at 1 percent, 5 percent and 10 percent respectively.

10. Large part of Slovene inflation is explained by business cycle. A traditional Phillips curve analysis confirms that lagged inflation and output gap are important determinants of current inflation, in addition to international food and fuel prices. The estimated degree of inflation persistence is about 0.8, whereas the result shows a one percent increase in output gap pushes up the inflation by 0.28 percent. The lagged inflation and the output gap together explain approximately 60 percent of Slovene inflation.

11. In particular, the demand-pull impacts on Slovene inflation are more evident than those of the Euro-area’s inflation. By interacting the lagged inflation and the output gap with a Slovene dummy, the result shows that their country-specific impacts on Slovenia’s inflation are significantly larger than those of the Euro-area’s inflation. Specifically, the greater degree of inflation persistence and the stronger effect of the deviation from the economy’s potential could result from the more rigid labor markets (see Figure 6).

Figure 6:
Figure 6:

Explaining Slovenia's Inflation in 2007-2008

Citation: IMF Staff Country Reports 2009, 160; 10.5089/9781451835816.002.A001

Source: Staff Calculation. Left figure presents the deviation of Slovenia's contribution from the euro area average's in 2007 and 2008 combined. Middle figure shows the difference of Slovenia's contribution from 2006 to 2008. Labor market rigidity indicator in right figure is the first principal component of 9 competition variables from Fraser Institute and World Bank Doing Business, i.e., difficulty of hiring, difficulty of firing, hiring cost, firing cost, rigidity of employment, rigidity of hours, effectivie minimum wage, coverage of collective bargaining, hiring and firing pratices. Higher indicator means more rigid labor market.

12. The overheating of the economy and the high persistence of inflation contributed to the rise in inflation in 2007–2008 (Figure 6). Slovenia’s output gap increased from about 1 percent in 2006 to 4.4 percent in 2008, while the increase was much smaller in the rest of the euro-area. In 2007–2008, the demand-pull factors, therefore, explained approximately 37 percent of the increase in inflation. At the same time, the effect of cost-push factors accounted for about 30 percent.

D. Conclusions

13. The spike in Slovenian inflation in 2007–08 was a consequence of cost-push and demand-pull factors. The supply-side factors including the spike in commodity prices and demand-pull factors related to the business cycle explained approximately two-third of the surge. Currently, the global recession is alleviating the inflationary pressures; however, inflation differentials with other countries in the Euro area persist. The structural bottlenecks, i.e. the more-rigid labor market, would continue putting labor cost pressures, thus potentially hindering Slovenian growth in the future. Consequently, greater wage flexibility, and further liberalization of employment protection legislation would be the key requirements for Slovenia to achieve faster price adjustments and successful competition in the Euro area.

Appendix

This study estimates the catching-up effect of Slovenia, comparing the periods before and after the ERM II. The empirical specification of Balassa-Samuelson catching-up model (Mihaljek and Klau, 2003) is as follows:

Log(PtNTPtT)=α+β.Log(Pt1NTPt1T)+φ.Log(δγLPtTLPtNT)+εt

where PNT and PT denote indices of non-tradable and tradable prices. LPT and LPNT denote labor productivity of tradable and non-tradable sector respectively. δ and γ are factor intensities in non-tradable and tradable in tandem. For simplicity, δ and γ are assumed to be equal.

Several sets of price indices from the harmonized index of consumer prices (HICP) and producer price index (PPI) are considered as proxies for the relative price of non-tradable goods (PNT/PT). The first three ratios follow Egert et al. (2003). The first ratio-HICP over PPI- assumes all items except goods in HICP are non-tradables. The ratio measures the sum of non-tradable and tradable prices divided by tradable prices. On the other hand, the second ratio-services in HICP over HICP- can be viewed as non-tradable prices divided by the sum of tradable and non-tradable prices. The third ratio defines as services in HICP over PPI. The ratio becomes closer to the definition of the relative price of non-tradables, however, it is hard to quantify the effect of an increase in service prices on overall inflation. The last ratio uses services in HICP over goods in HICP which seems to be the closet approximation for non-tradable to tradable price ratio and the two combined should capture all changes in inflation.

Labor productivity is calculated from sectoral output and employment data of national account.8 The labor productivity of tradable sector is measured by the ratio of output to employment in agriculture, fishing, mining and manufacturing. That of non-tradable sector is then the ratio of output to employment of the rest in national account. Quarterly data range from 2000:Q1 to 2008:Q2.

References

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1

Prepared by Piyaporn Sodsriwiboon.

2

Through out this paper we use inflation for HICP inflation unless specified otherwise.

3

The contribution of domestic commodity prices in the HICP inflation shown in Figure 2 is calculated as the increase in domestic food and fuel prices weighted by their shares in the HICP basket.

4

The pass-through from international to domestic prices of food and fuel is obtained from country-by-country bivariate regressions (WEO, Oct 2008):

πtfood,domestic=α+Σi=14βiπtifood,domestic+Σi=04δiπtifood,world+εtπtfuel,domestic=α+Σi=14βiπtifuel,domestic+Σi=04γiπtifuel,world+υt
Foodpricepass-through=Σi=04δi1Σi=14βiFuelpricepass-through=Σi=04γi1Σi=14βi
5

The pass-through from domestic commodity prices to core inflation is estimated using Phillips curve equations with domestic prices net of any influences. The full long-term pass-through is calculated as the sum of coefficients on the current value and four lags of the independent variable divided by one minus the sum of coefficients on the four lags of the dependent variable. (WEO, Oct 2008)

πt=α+Σi=14βiπti+Σi=04γi(ytiyti*)+Σi=04φiπtifood+Σi=04φiπtifuel+εt
Foodpricepass-through=Σi=04φi1Σi=14βiFuelpricepass-through=Σi=04φi1Σi=14βi

The reported estimates show the weighted averaged of country-by-country estimates using quarterly data from 1995 to 2008 for 25 emerging economies and 21 advanced economies, and from 2001 to 2008 for Slovenia.

6

The estimate is slightly smaller than a recent finding by Caprirolo (2008) that a one percent increase in food prices resulted in a 0.88 percent increase in core inflation in the long run.

7

The greater trade and investment opportunities after the entry in the euro area may have contributed to the improvement of Slovene productivity, particularly in the tradable sector. The Balassa-Samuelson model provides a supply-side explanation for the relative price of tradables and non-tradables in an economy. Specifically, Balassa (1964) and Samuelson (1964) argued that faster productivity growth in the tradable sector pushes up overall wages if wages are equalized across sectors, leading to a rise in the relative price of nontradable goods. This would explain why inflation is faster in economies that are catching up with richer trading partners.

8

Value added by activities and GDP at 1995 prices and employment by activities and by sectors from the statistical office of the republic of Slovenia

References

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  • International Monetary Fund, 2007, Slovenia: Selected Issues, IMF Country Report No. 07/182.

9

Prepared by Yuan Xiao.

11

See the literature surveyed in Berger, A. and others (2004).

12

The liquidity ratio is the ratio between the sum of financial assets in local and foreign currencies and the sum of liabilities in local and foreign currencies with regard to residual maturity. A bank will classify financial assets and liabilities by residual maturity in the following two categories of maturity bands: (i) category one: financial assets and liabilities with a residual maturity of up to 30 days, and (ii) category two: financial assets and liabilities with a residual maturity of up to 180 days.

13

The available data group together not only the liabilities of banks but also other domestic sectors (which accounted for 1/5 of the total amount depicted in Figure 9), but it is clear that Austria and Germany are the largest lenders.

Republic of Slovenia: Selected Issues
Author: International Monetary Fund