Republic of Slovenia: Selected Issues

International Monetary Fund. European Dept.

doi:10.5089/9781484300749.002.A001

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Republic of Slovenia: Selected Issues

Author: International Monetary Fund. European Dept.

Publication Date:: 15 May 2017

eISBN:: 9781484300749

ISBN:: 9781484300749

Language:: English

Keywords:: ISCR; CR; export; Slovenia; GDP; bank credit expansion; bank credit extension; bank capital; dummy recession; bank credit growth in Slovenia; Global financial crisis of 2008-2009; Credit; Credit booms; Gross fixed investment; Global

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Selected Issues

Abstract

Selected Issues

Credit Growth and Economic Recovery in Europe: The Case of Slovenia¹

Economic activity in Europe has yet to fully recover nearly eight years after the global financial crisis (GFC). Bank credit expansion also remains tepid despite historically low lending interest rates. Trying to identify the key factors underpinning such developments, this study uncovers that: (i) Emerging Europe’s post-GFC recovery is slower than what one can expect after a crisis; (ii) Slovenia’s post-GFC recovery path, on the other hand, is generally explained by the global nature of the 2008 financial crisis and Slovenia’s 2012–13 banking crisis; (iii) loan quality, customer deposits, and bank capital, as well as the macroeconomic environment are key factors influencing bank credit developments in Europe and Slovenia; and (iii) bank credit to the private sector has a positive, but modest impact on economic activity in European countries, working mainly through the investment channel.

A. Introduction

1. The 2008 global financial crisis (GFC) had a seemly large and permanent effect on output and bank credit growth in European countries, including Slovenia (see panel). Prior to the crisis, European countries experienced significant GDP and credit growth. Amid buoyant global financial market conditions, both GDP and bank credit accelerated sharply in the three years preceding the crisis, pushing both measures well above their trend levels. The 2008 economic and financial crisis led to a significant tightening in global financial conditions. European countries were not immune. In the immediate period following the onset of the GFC, output and bank credit contracted severely. GDP growth took three years to return to Europe as a whole, while European bank credit extension stabilized but has yet to decidedly turn the corner toward sustained growth, despite aggressive monetary policy easing by European central banks. Slovenia’s GDP and bank credit dynamics followed a similar pattern but were more volatile.

2. Slovenia experienced a double-dip recession following the 2008 global financial crisis (see Box 1 in accompanying staff report). Output contracted nearly 8 percent in 2009 as the external demand shock, co-incident with the end of the domestic investment cycle, and sudden stop of capital inflows caused by the global financial crisis triggered an adverse feedback loop between the over-leveraged corporate and banking sectors and the sovereign. Despite a feeble recovery in 2010-11, the highly leveraged corporate sector was unable to service its debts, driving the mostly state-owned banking system towards insolvency. These dynamics precipitated a two-year recession in 2012-13 with a cumulative output loss of nearly 4 percent.

3. The “double dip” recession forced over-leveraged corporates to retrench dampening demand for investment and domestic bank lending. In addition to the enterprise sector’s excessive leverage, the crisis revealed that its true equity base was much weaker than previously thought. In the wake of the sudden stop in external financing, large segments of the enterprise sector turned out to be insolvent or close to insolvency. This led to widespread bankruptcies, an inability to service debt, and mounting NPLs which consumed bank capital. The balance sheet nature of Slovenia’s “double dip” recession required both Slovenian banks and their primary clients, non-financial corporations (NFCs), to focus on repairing weak balance sheets. NFCs eschewed bank borrowing and investment in favor of strengthening their balance sheets, which has relied primary on using available cash to deleverage rather equity infusions. At the same time, large NFCs began to rely more heavily on foreign financing.

4. Considering this background, this paper draws on a cross-country and bank-level analysis to help inform policy discussions in Slovenia: ² (i) Are Slovenia’s post-GFC economic developments in line with expectations given the scale and severity of the GFC and the credit boom that preceded it? (ii) What are the main determinants of credit dynamics in Slovenia? (iii) How strong is the link between credit and economic activity? Has it changed post-GFC? The paper tackles these issues through a cross-country European and Slovenia-specific data analysis.

5. The findings of the analysis can be summarized as follows. The post-GFC recovery in Slovenia significantly lags typical post-recession recoveries for both normal and financial-crisis-driven recessions. Credit dynamics have also been much more subdued. However, controlling for Slovenia’s “double dip” recession and the slowdown in global growth after the GFC, reveals that Slovenia’s recovery is not atypical. The cross-country study finds that bank-specific factors—loan quality, customer deposits, capital—are the key determinants of bank lending. Also, bank credit to the private sector has a positive, but modest impact on economic activity, working mainly through the investment channel. Thus, the need to strengthen bank and corporate balance sheets in Slovenia after the GFC likely contributed significantly to weaker investment and GDP growth during Slovenia’s post-GFC recovery.

B. The Post GFC-Recovery in Slovenia: Is It Different?

6. Projection paths derived from pre-GFC recession and recoveries are used to assess Emerging Europe and Slovenia’s post GFC-recoveries. Drawing from Jordà, Schularick, and Taylor (2013), the local projection (LP) method is used to develop projections of ‘typical’ recession and recovery paths. It follows the standard specification below:

Δ_{h} y_{i (r) + h}^{k} = \propto_{i}^{k} + \emptyset_{h} N_{i t (r)} + γ_{h} F_{i t (r)} + φ_{h} N_{i t (r)} * (x_{i t (r)} - \bar{x_{N}}) + θ_{h} F_{i t (r)} * (x_{i t (r)} - \bar{x_{F}}) + Σ_{j = 0}^{j = 1} β_{j}^{k} Y_{i t (r) - j} + e_{i t (r)}^{k}

The dependent variable (y) is the cumulative change in key macroeconomic variables (real GDP per capita, real private-sector consumption per capita, real investment (GFCF) per capita, and real bank credit to the private sector per capita) from the beginning of each recession and recovery period included in the analysis. N and F are dummy variables indicating whether the recession and recovery episode was preceded by a financial (banking) crisis (F = financial) or not (N = non-financial). The control variables include: measures of excess credit accumulated during the expansion period $(x_{i t (r)} - \bar{x_{F o r N}})$ preceding the recession; and a vector Y of the standardized percentage change in the dependent variables two-years and the year before the start of each recession. Finally, ∝ represents the fixed effect for ith country; and e is the error term.

7. The coefficients ø and γ on the non-financial and financial dummies are of interest. Intuitively, ø and γ are similar to the average cumulative response of the dependent variable at each horizon (projection) period and are used to construct the projection paths for ‘typical’ non-financial and financial recession and recovery paths plotted in the first column of the panel below. The coefficients are derived from observations on a sample of 79 recession and recovery episodes across 35 advance and large emerging-market countries (hereinafter referred to as the control group) that occurred from the beginning of the post-Bretton Woods era up to the eve of the GFC (1971–2006). With a projection horizon of 7 years, consistent with the post-GFC period from 2009–2015, 28 separate regressions were run (7 regressions for each dependent variable). The sample episodes include 20 recession and recovery periods in European countries. Out of the total episodes, 64 were classified as non-financial and 15 as financial recessions based on the definition of systemic banking crisis in Laeven and Valencia (2012).³ The Bry and Boschan (1971) algorithm was used to date business cycles across countries.⁴

8. We then generated counterfactual dependent variable paths to account for the extremely weak global demand environment that followed the GFC. The counterfactual paths were generated as follows: (i) a contemporaneous external demand variable based on actual data was included as a regressor in the standard regressions described above to estimate its influence on the ‘typical’ projection path; (ii) this external demand variable was then rescaled to reflect, on average, the external demand faced by European countries after the GFC and (iii) new counterfactual dependent variables were generated using the coefficients and values of the regressors from step (i), and the counterfactual external demand values from step (ii). These steps yielded counterfactual dependent variables, which represented “what-if”’ estimates of the dependent variables had the control group countries faced the same subdued external demand that European countries faced post-GFC. The standard regressions were then re-run with the new counterfactual dependent variables generate the coefficients used to construct the projection paths for non-financial and financial recession and recovery episodes plotted in column two of the panel below.

9. Before introducing controls, Slovenia’s economy appears to have underperformed relative to past recession and recoveries if the starting date for the assessment is 2009. ⁵ Slovenia’s performance, measured as the cumulative change in real GDP per capita (real GDP) for each horizon year from 2008 to 2015 is significantly below the projection path for typical recessions and recoveries following a financial crisis (Figure 1, first column). It is also below the average cumulative change for Emerging European countries that experienced a financial crisis in 2007 or 2008. Conversely, Slovenia’s real private consumption per capita (real consumption), real gross fixed capital formation (real investment), and real bank credit to the private sector per capita (real bank credit) outperform these comparator groups until at least horizon year three. In addition, Slovenia’s performance over the projection horizon for real investment and real bank credit is within the 95 percent confidence interval of the projected path.

10. Slovenia’s 2012–13 recession and the unusually weak external environment appear to explain much of Slovenia’s underperformance since the GFC. Indeed, Slovenia’s performance is more typical when the starting point for the analysis is 2012 (Figure 1, second column) and the severe worldwide effects of the GFC faced by Slovenia and other European countries are considered. Specifically, on the latter point, the dependent variables used to develop the projection paths in the second column were adjusted as described above. This had the effect of dampening the cumulative growth of these paths relative to the standard projection paths in the first column, particularly for the typical financial crisis path. With these adjustments to the analytical framework, Slovenia’s real investment performance since the start of the 2012 recession outperforms the projected path for real investment following a financial crisis. Real GDP also outperforms in the outer projection horizon years and real consumption remains broadly within the confidence interval of a typical recession and recovery period for countries that experienced a financial crisis. The only outlier remains real bank credit in the early projection years, but this can largely be explained by the transfer of EUR 4.9 billion in commercial bank loans to a government-sponsored bad bank (BAMC) in 2013–14. Nonetheless, as the chart shows, by end-2015 bank credit had not begun to pick up as the projection path suggests it should. To shed some light on this, the analysis now turns to determinants of bank credit extension.

C. Determinants of Credit Growth⁶

11. Bank-level cross country panel and Slovenia-specific analyses point to both bank fundamentals as well as macro factors as influencing bank credit dynamics.⁷ Despite historically low lending interest rates, bank credit extension to the private sector in Europe remains weak, and in the case of Slovenia, negative. A bank-level panel analysis, covering 37 European countries (including Slovenia) and nearly 8,000 banks, point to both bank specific and demand factors driving bank credit extension. ⁸ The bank specific factors include bank capital, customer deposits, bank equity prices, and loan quality. The demand factors are GDP growth and inflation. The key results of the bank-level panel analysis are summarized in the bar chart below, where the bar height represents the effect of a one-standard-deviation change in the respective determinant on credit growth.⁹ The regression results indicate that the quality of a bank assets, proxied by the NPL ratio, has the largest relative impact on credit growth in both the pre- and post-GFC periods.

12. Slovenia’s bank credit dynamics are broadly track the model but are more volatile. The average annual growth in bank credit in Slovenia broadly co-moves with the fitted values from the panel regression. The rapid expansion of Slovenian bank credit in the pre-GFC period likely reflects nominal convergence before joining the euro area and mergers-and-acquisition activity, while the sharp drop in 2013 is primarily due to transfers of bad bank assets to the BAMC. A closer look at the regression results and the outturn of the key bank-specific factors, appears to offer a partial explanation for credit developments in Slovenia, in the post-GFC period.¹⁰

Bank capital

13. Bank regulatory capital as percent of total assets is found significant in the cross country analysis with a negative sign, especially during recessions. This indicates that raising regulatory capital is associated with less credit expansion.¹¹ Raising regulatory capital, owing to changes in regulatory standards or market requirements, either leads to less loanable funds or triggers deleveraging.¹² As can be seen in Figure 2, the average regulatory capital of Slovenian banks has trended consistently upward since 2012, with a big jump at the end of 2013 attributable to the recapitalization of three state-owned banks as the bank crisis unfolded. Nonetheless, after the capital injection, regulatory bank capital continued to increase. Overall, the steady rise in bank capital, notwithstanding the large capital injection, likely had a dampening effect on bank credit growth in Slovenia throughout the post-GFC period.

Customer Deposits

14. The coefficient on customer deposits is significant with an overall positive sign in the bank-level cross country analysis, though it turns negative during recessionary periods. This suggests that strong saving mobilization facilitates credit expansion. However, during a recession and uncertain recovery, growth in deposits may also reflect a desire on the part of potential consumers and investors to save rather than consume and invest. In Slovenia, deposit growth rates slid in advance of the 2012 recession and 2013 banking crisis, turning negative on the eve of the government’s bank bailout, and then accelerated sharply in the aftermath of the crisis. Domestic bank credit growth was positively correlated with deposit growth rates prior to the recession/banking crisis, i.e., growth slowed as deposits slowed – consistent with the positive coefficient on customer deposits. After the crisis, credit growth continued to contract as the customer deposits grew, which is in line with the negative coefficient on customer deposits during recessions.

Non-Performing Loans

15. The coefficient on NPL ratio is significant with a negative sign in the cross-country analysis. An increasing NPL ratio indicates trouble in the economy or in the bank’s loan selection process and hence triggers a more conservative approach to credit expansion. Even if the NPLs are fully provisioned, they still have costs in terms of credit expansion since the resources used for provisioning could have been used to extend further credits. In Slovenia, the NPL ratio rose from 2008 until the banking crisis broke in late-2013. Bank credit growth in Slovenia began decelerating in early 2010, turning negative in mid-2011 and continuing to contract thereafter. This pattern of changes in the NPL ratio and bank credit is broadly consistent with the negative correlation between the NPL ratio and bank credit growth indicated by the regression results, However, the positive correlation between the NPL ratio and bank credit extension following the banking crisis is not. This divergence can be explained by two factors. First, the aggregate NPL ratio of Slovenian remains relatively elevated at 5.1 percent despite the significant reduction over the last two years. Second, Slovenian corporates have been deleveraging since the crisis, as noted above, Thus, even though bank balance sheets have gradually improved (NPL ratio has fallen) demand for domestic bank loans from corporations has been held back by their efforts to reduce their debt burdens.

D. GDP Growth and Credit Growth in Europe and Slovenia¹³

16. In some countries there is no clear relationship between GDP growth and domestic bank credit growth after the GFC, echoing “creditless” recoveries. This appears to be the case for Slovenia with positive GDP and private investment growth while bank credit continues to contract (See text chart on next page). It is also possible that the severity of the GFC may have altered the relationship between GDP growth and bank credit extension. With this in mind, we re-assessed the extent to which bank credit growth influences GDP growth using a dynamic system Generalized-Method-of-Moments panel estimator (Blundell and Bond, 1998), to estimate the relationship between credit growth and indicators of economic activity (GDP growth and private gross fixed capital formation, GFCF). The panel included data on 39 European countries from 1999–2015.

17. The analysis revealed that the relationship between bank credit growth and GDP growth has remained essentially unchanged during and after the GFC. A positive and significant, if moderate, relationship between economic growth and bank credit growth exists. In an “average” European country, a 10 percent increase in domestic bank credit to the private sector would raise real GDP by 0.6–0.7 percent (Table 1). The main channel seems to be gross fixed capital investment, as a credit growth of 10 percentage points raises private GFCF formation by some 1½–2 percent (Table 2). In response to an influential paper (Biggs et al., 2009), we also experiment with the change in credit growth (called the credit impulse) and find that it influences GDP growth strongly and significantly during the post-GFC recessions and recoveries, helping to resolve the puzzle of “creditless” recoveries (Table 3.) During a recession, and, for the sample of CESEE countries, during the recovery, the credit impulse coefficient is significant and larger than the coefficient of bank credit growth in Table 1.

Table 1.

Slovenia: GDP Growth and Bank Credit to the Private Sector: Recession and Recovery

Standard errors in parentheses. * p<0.10, ** p<0.5, *** p<0.001

^{^1/}Dummy takes the value of 1 during the recession period.

^{^2/}Dummy takes the value of 1 during the recovery period.

^{^3/}Volume of trading partners imports weighted by exports’ shares.

Table 1.

Slovenia: GDP Growth and Bank Credit to the Private Sector: Recession and Recovery

Dynamic panel data; two-step system GMM estimator
Sample of 39 European countries, estimation period: 1999-2015
	(1)	(2)	(3)
	Full sample	AE	CESEE
GDP growth rate (t-1)	0.219** (0.085)	0.149** (0.066)	0.0967* (0.060)
Private sector credit growth	0.0711*** (0.021)	0.0871** (0.031)	0.0558*** (0.016)
Private sector credit growth * Dummy recession^1/	0.0726 (0.096)	−0.0249 (0.093)	0.0170 (0.094)
Private sector credit growth * Dummy recovery^2/	0.0308 (0.062)	−0.0424 (0.063)	−0.0581 (0.095)
Public consumption growth rate	−0.469* (0.251)	0.206** (0.090)	0.0280 (0.051)
Private sector credit-to-GDP ratio	−0.0129* (0.008)	−0.00857 (0.011)	−0.0405*** (0.012)
External demand ^3/	0.253** (0.077)	0.216*** (0.033)	0.145** (0.063)
Log (VIX)	−0.00388 (0.005)	−0.00760* (0.004)	−0.0148* (0.009)
Dummy recession	−0.0281** (0.009)	−0.0123** (0.006)	−0.0369*** (0.006)
Dummy recovery	0.000669 (0.004)	0.00920** (0.004)	−0.000121 (0.006)
Constant	0.0349** (0.018)	0.0267 (0.021)	0.0821** (0.029)
No. Obs.	576	331	244
No. countries	39	21	18
No. instruments	20	21	20
Autocorrelation test, p-value	0.317	0.162	0.317
Hansen test, p-value	0.121	0.252	0.353

Standard errors in parentheses. * p<0.10, ** p<0.5, *** p<0.001

^{^1/}Dummy takes the value of 1 during the recession period.

^{^2/}Dummy takes the value of 1 during the recovery period.

^{^3/}Volume of trading partners imports weighted by exports’ shares.

Table 1.

Slovenia: GDP Growth and Bank Credit to the Private Sector: Recession and Recovery

Dynamic panel data; two-step system GMM estimator
Sample of 39 European countries, estimation period: 1999-2015
	(1)	(2)	(3)
	Full sample	AE	CESEE
GDP growth rate (t-1)	0.219** (0.085)	0.149** (0.066)	0.0967* (0.060)
Private sector credit growth	0.0711*** (0.021)	0.0871** (0.031)	0.0558*** (0.016)
Private sector credit growth * Dummy recession^1/	0.0726 (0.096)	−0.0249 (0.093)	0.0170 (0.094)
Private sector credit growth * Dummy recovery^2/	0.0308 (0.062)	−0.0424 (0.063)	−0.0581 (0.095)
Public consumption growth rate	−0.469* (0.251)	0.206** (0.090)	0.0280 (0.051)
Private sector credit-to-GDP ratio	−0.0129* (0.008)	−0.00857 (0.011)	−0.0405*** (0.012)
External demand ^3/	0.253** (0.077)	0.216*** (0.033)	0.145** (0.063)
Log (VIX)	−0.00388 (0.005)	−0.00760* (0.004)	−0.0148* (0.009)
Dummy recession	−0.0281** (0.009)	−0.0123** (0.006)	−0.0369*** (0.006)
Dummy recovery	0.000669 (0.004)	0.00920** (0.004)	−0.000121 (0.006)
Constant	0.0349** (0.018)	0.0267 (0.021)	0.0821** (0.029)
No. Obs.	576	331	244
No. countries	39	21	18
No. instruments	20	21	20
Autocorrelation test, p-value	0.317	0.162	0.317
Hansen test, p-value	0.121	0.252	0.353

Standard errors in parentheses. * p<0.10, ** p<0.5, *** p<0.001

^{^1/}Dummy takes the value of 1 during the recession period.

^{^2/}Dummy takes the value of 1 during the recovery period.

^{^3/}Volume of trading partners imports weighted by exports’ shares.

Table 2.

Slovenia: Private Gross Fixed Capital Formation (GFCF) and Bank Credit to the Private Sector

Standard errors in parentheses. * p<0.10, ** p<0.5, *** p<0.001

Table 2.

Slovenia: Private Gross Fixed Capital Formation (GFCF) and Bank Credit to the Private Sector

Dynamic panel data; two-step system GMM estimator
Sample of 39 European countries, estimation period: 1999-2015
	(1)	(2)	(3)
	Full sample	AE	CESEE
GFCF growth rate (t-1)	0.168* (0.098)	0.224** (0.083)	0.0948 (0.160)
Private sector credit growth	0.200** (0.103)	0.181** (0.069)	0.149* (0.092)
General government balance ratio (% GDP)	0.493 (0.442)	0.664* (0.370)	0.162 (0.424)
Private sector credit-to-GDP ratio	−0.126** (0.041)	−0.0743*** (0.019)	−0.324** (0.147)
Interest rate (policy rate)	−1.783*** (0.515)	−1.176** (0.507)	−1.618** (0.580)
External demand	0.725** (0.236)	0.718*** (0.154)	0.416* (0.238)
Log (VIX)	−0.0438 (0.029)	−0.00832 (0.016)	−0.131** (0.048)
Constant	0.223** (0.105)	0.0793 (0.067)	0.562*** (0.162)
No. Obs.	526	302	232
No. countries	38	21	17
No. instruments	18	18	17
Autocorrelation test, p-value	0.123	0.970	0.015
Hansen test, p-value	0.188	0.301	0.343

Standard errors in parentheses. * p<0.10, ** p<0.5, *** p<0.001

Table 2.

Slovenia: Private Gross Fixed Capital Formation (GFCF) and Bank Credit to the Private Sector

Dynamic panel data; two-step system GMM estimator
Sample of 39 European countries, estimation period: 1999-2015
	(1)	(2)	(3)
	Full sample	AE	CESEE
GFCF growth rate (t-1)	0.168* (0.098)	0.224** (0.083)	0.0948 (0.160)
Private sector credit growth	0.200** (0.103)	0.181** (0.069)	0.149* (0.092)
General government balance ratio (% GDP)	0.493 (0.442)	0.664* (0.370)	0.162 (0.424)
Private sector credit-to-GDP ratio	−0.126** (0.041)	−0.0743*** (0.019)	−0.324** (0.147)
Interest rate (policy rate)	−1.783*** (0.515)	−1.176** (0.507)	−1.618** (0.580)
External demand	0.725** (0.236)	0.718*** (0.154)	0.416* (0.238)
Log (VIX)	−0.0438 (0.029)	−0.00832 (0.016)	−0.131** (0.048)
Constant	0.223** (0.105)	0.0793 (0.067)	0.562*** (0.162)
No. Obs.	526	302	232
No. countries	38	21	17
No. instruments	18	18	17
Autocorrelation test, p-value	0.123	0.970	0.015
Hansen test, p-value	0.188	0.301	0.343

Standard errors in parentheses. * p<0.10, ** p<0.5, *** p<0.001

Table 3.

Slovenia: GDP Growth and Credit Impulse: Recession and Recovery

Standard errors in parentheses. * p<0.10, ** p<0.5, *** p<0.001

^{^1/}Dummy takes the value of 1 during the recession period.

^{^2/}Dummy takes the value of 1 during the recovery period.

^{^3/}Volume of trading partners imports weighted by exports’ shares.

Table 3.

Slovenia: GDP Growth and Credit Impulse: Recession and Recovery

Dynamic panel data; two-step system GMM estimator
Sample of 39 European countries, estimation period: 1999-2015
	(1)	(2)	(3)
	Full sample	AE	CESEE
GDP growth rate (t-1)	0.300*** (0.030)	0.198** (0.066)	0.300*** (0.040)
Change in private sector credit growth	−0.0218 (0.023)	−0.0244 (0.025)	−0.0116 (0.015)
Change in private sector credit growth * Dummy recession^1/	0.0888** (0.031)	0.109* (0.058)	0.118** (0.060)
Change in private sector credit growth * Dummy recovery^2/	0.0739** (0.029)	0.0537** (0.028)	0.0957*** (0.029)
Public consumption growth rate	0.0838* (0.050)	0.428*** (0.099)	0.0152 (0.063)
Private sector credit-to-GDP ratio	−0.0204*** (0.006)	−0.001 (0.004)	−0.0249* (0.014)
External demand ^3/	0.237*** (0.027)	0.236*** (0.057)	0.265*** (0.051)
Log (VIX)	−0.00899*** (0.003)	−0.00926** (0.004)	−0.0104 (0.009)
Dummy recession	0.00266 (0.003)	0.00817** (0.003)	−0.00125 (0.005)
Dummy recovery	−0.0222*** (0.006)	−0.0103 (0.007)	−0.0324** (0.012)
Constant	0.0491*** (0.012)	0.0209 (0.016)	0.0556* (0.029)
No. Obs.	576	325	250
No. countries	39	21	18
No. instruments	19	21	19
Autocorrelation test, p-value	0.358	0.220	0.514
Hansen test, p-value	0.651	0.294	0.355

Standard errors in parentheses. * p<0.10, ** p<0.5, *** p<0.001

^{^1/}Dummy takes the value of 1 during the recession period.

^{^2/}Dummy takes the value of 1 during the recovery period.

^{^3/}Volume of trading partners imports weighted by exports’ shares.

Table 3.

Slovenia: GDP Growth and Credit Impulse: Recession and Recovery

Dynamic panel data; two-step system GMM estimator
Sample of 39 European countries, estimation period: 1999-2015
	(1)	(2)	(3)
	Full sample	AE	CESEE
GDP growth rate (t-1)	0.300*** (0.030)	0.198** (0.066)	0.300*** (0.040)
Change in private sector credit growth	−0.0218 (0.023)	−0.0244 (0.025)	−0.0116 (0.015)
Change in private sector credit growth * Dummy recession^1/	0.0888** (0.031)	0.109* (0.058)	0.118** (0.060)
Change in private sector credit growth * Dummy recovery^2/	0.0739** (0.029)	0.0537** (0.028)	0.0957*** (0.029)
Public consumption growth rate	0.0838* (0.050)	0.428*** (0.099)	0.0152 (0.063)
Private sector credit-to-GDP ratio	−0.0204*** (0.006)	−0.001 (0.004)	−0.0249* (0.014)
External demand ^3/	0.237*** (0.027)	0.236*** (0.057)	0.265*** (0.051)
Log (VIX)	−0.00899*** (0.003)	−0.00926** (0.004)	−0.0104 (0.009)
Dummy recession	0.00266 (0.003)	0.00817** (0.003)	−0.00125 (0.005)
Dummy recovery	−0.0222*** (0.006)	−0.0103 (0.007)	−0.0324** (0.012)
Constant	0.0491*** (0.012)	0.0209 (0.016)	0.0556* (0.029)
No. Obs.	576	325	250
No. countries	39	21	18
No. instruments	19	21	19
Autocorrelation test, p-value	0.358	0.220	0.514
Hansen test, p-value	0.651	0.294	0.355

Standard errors in parentheses. * p<0.10, ** p<0.5, *** p<0.001

^{^1/}Dummy takes the value of 1 during the recession period.

^{^2/}Dummy takes the value of 1 during the recovery period.

^{^3/}Volume of trading partners imports weighted by exports’ shares.

E. Concluding Remarks

18. The analysis indicates that Slovenia’s post-GFC experience is not unusual after accounting for the severity of Slovenia’s post-GFC downturn and the banking crisis in 2012-13. It also shows that bank-specific factors such as loan quality, customer deposits, and capital likely played a role in weak credit creation following the crisis. Bank credit to the private sector influences economic activity, but the impact is modest, working mainly through the investment channel.

19. Some policy recommendations can be drawn from the findings. The first relates to asset quality. The results show that non-performing loans can be a major drag on credit growth. Slovenia authorities and banks in general have made significant strides in reducing NPLs, particularly of large non-financial corporations. SMEs account for a significant portion of the remaining stock of NPLs and a concerted effort, through application of recently published guidelines on reducing SME NPLs and aggressive supervision of its implementation would be appropriate. The second relates to proper diagnosis of economic and financial developments. As the analysis shows, Slovenia’s performance when benchmarked relative to the 2012–13 recession is broadly in line with the performance of other countries that experienced financial crisis. This reflects in part the time it takes for banks and corporates to work off unsustainable debt burdens. In this context, it is important to be patient and allow balance sheet repair to take its course before encouraging banks to increase lending. Finally, the sale of state-owned enterprises could add much needed equity financing to the economy, easing the need of the corporate sector to rely on deleveraging to restore financial health.

Annex 1. Country Groups

1/ Belarus, Luxembourg, Moldova, San Morino, and Ukraine not included in sample.

^{^*}Countries with expansion peaks in 1971-2006 that are included in LP regression to derive projection paths.

Euro area - advanced		Other European - advanced		Central, Eastern, and Southeastern European		Other
1 Austria ^*	1	Denmark ^*	1	Albania	1	Argentina ^*
2 Belgium	2	Iceland ^*	2	Bosnia & Herzegovina	2	Australia ^*
3 Cyprus ^*	3	Israel ^*	3	Bulgaria	3	Brazil ^*
4 Finland ^*	4	Norway ^*	4	Croatia	4	Canada ^*
5 France ^*	5	Sweden ^*	5	Czech Republic	5	China,P.R.: Mainland
6 Germany ^*	6	Switzerland ^*	6	Estonia	6	China,P.R.: Hong Kong ^*
7 Greece ^*	7	United Kingdom ^*	7	Hungary	7	India ^*
8 Ireland ^*			8	Kosovo	8	Indonesia
9 Italy ^*			9	Latvia	9	Japan ^*
10 Malta ^*			10	Lithuania	10	Korea, Republic of ^*
11 Netherlands ^*			11	Macedonia, FYR	11	Malaysia ^*
12 Portugal ^*			12	Montenegro	12	Mexico ^*
13 Spain ^*			13	Poland	13	Philippines ^*
			14	Romania	14	Singapore ^*
			15	Russian Federation ^*	15	South Africa ^*
			16	Serbia, Republic of	16	Turkey ^*
			17	Slovak Republic	17	United States ^*
			18	Slovenia

1/ Belarus, Luxembourg, Moldova, San Morino, and Ukraine not included in sample.

^{^*}Countries with expansion peaks in 1971-2006 that are included in LP regression to derive projection paths.

Euro area - advanced		Other European - advanced		Central, Eastern, and Southeastern European		Other
1 Austria ^*	1	Denmark ^*	1	Albania	1	Argentina ^*
2 Belgium	2	Iceland ^*	2	Bosnia & Herzegovina	2	Australia ^*
3 Cyprus ^*	3	Israel ^*	3	Bulgaria	3	Brazil ^*
4 Finland ^*	4	Norway ^*	4	Croatia	4	Canada ^*
5 France ^*	5	Sweden ^*	5	Czech Republic	5	China,P.R.: Mainland
6 Germany ^*	6	Switzerland ^*	6	Estonia	6	China,P.R.: Hong Kong ^*
7 Greece ^*	7	United Kingdom ^*	7	Hungary	7	India ^*
8 Ireland ^*			8	Kosovo	8	Indonesia
9 Italy ^*			9	Latvia	9	Japan ^*
10 Malta ^*			10	Lithuania	10	Korea, Republic of ^*
11 Netherlands ^*			11	Macedonia, FYR	11	Malaysia ^*
12 Portugal ^*			12	Montenegro	12	Mexico ^*
13 Spain ^*			13	Poland	13	Philippines ^*
			14	Romania	14	Singapore ^*
			15	Russian Federation ^*	15	South Africa ^*
			16	Serbia, Republic of	16	Turkey ^*
			17	Slovak Republic	17	United States ^*
			18	Slovenia

1/ Belarus, Luxembourg, Moldova, San Morino, and Ukraine not included in sample.

^{^*}Countries with expansion peaks in 1971-2006 that are included in LP regression to derive projection paths.

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Prepared by John Ralyea with assistance from Luisa Calixto and Dustin Smith. The paper draws on an ongoing cross-country analysis of credit growth and economic recovery in Europe after the global financial crisis performed by an EUR team including Sergei Antoshin, Marco Arena, Tonny Lybek, John Ralyea, and Etienne Yehoue under the supervision of Nikolay Gueorguiev. The paper also benefitted from insightful comments and questions posed by Slovenian authorities at seminars held at the Bank of Slovenia in November 2016 and March 2017.

Credit Growth and Economic Recovery in Europe (forthcoming, European Department, International Monetary Fund).

In a few cases, the starting date of the financial crisis was adjusted to correspond with the peak of the business cycle. Laeven and Valencia (2012) broadly define a financial/banking crisis as being characterized by significant signs of financial distress and losses in wide parts of the financial system.

The number of recession and recovery episodes from 1971-2006 was 144. However, data limitations precluded use of all the episodes.

The relevant comparator countries for Slovenia are those whose recession and recovery periods were preceded by a banking crisis given that Laeven and Valencia (2012) classify Slovenia as a borderline case for experiencing a banking crisis in 2008.

In the cross-country paper, this analysis is performed by Etienne Yehoue.

The analysis uses annual data over 1999–2015 from Fitch-Connect for the bank specific data and from the World Economic Outlook (WEO) for the macroeconomic data. The credit growth variable is defined as growth of gross loans extended by individual banks to borrowers of a specific country. For some banks in the panel annual loan growth is exceptionally large, suggesting that the regression results be interpreted with some caution.

The analysis relies on system generalized method of moments (GMM) estimations, which appropriately lag the variables and instrument the right-hand variables. This has helped to correct for potential correlation between right hand variables—through lags of different orders for a set of variables and other instruments for the rest—as well as dealing with potential endogeneity issues. The J-test of over-identifying restrictions or the Sargan validity test for instruments embedded in system GMM ensures the goodness fit of the specifications.

The black fill indicates the estimated coefficient is significant.

The effect of changes in the bank equity index are not analyzed for Slovenia given the limited development (liquidity) of the local stock market.

Regulatory capital refers to the total bank capital as measured for regulatory purposes. It does not refer to the minimum capital required by the regulator.

Reduce lending due to higher regulatory capital requirements may be somewhat transitory as a stronger capital base could induce stronger credit growth over the medium term.

In the cross-country paper, this analysis is performed by Marco Arena.

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Republic of Slovenia: Selected Issues

Author: International Monetary Fund. European Dept.

Volume/Issue:: Volume 2017: Issue 126

Publisher:: International Monetary Fund

ISBN:: 9781484300749

ISSN:: 1934-7685

Pages:: 58

DOI:: https://doi.org/10.5089/9781484300749.002

Keywords
Credit Growth and Economic Recovery in Europe: The Case of Slovenia1
References

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Europe and Slovenia: GDP Growth and Bank Credit to the Private Sector¹

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Non-financial corporations balance sheets

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Proportion of non-financial corporation funding (by type) from foreign sources

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Slovenia and Emerging Europe: Performance Relative to Projection Paths ^1/

(cumulative percentage change at each horizon from start of recession percent)

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Europe: Determinants of Credit Growth

(Standardized coefficients)

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Credit Growth: Slovenia and fitted

(Annual percentage change)

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Select Banking System Indicators

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Real GDP, real private investment, and bank credit to private sector

(percent change yoy)

Foresee

Euro area - advanced		Other European - advanced		Central, Eastern, and Southeastern European		Other
1 Austria ^*	1	Denmark ^*	1	Albania	1	Argentina ^*
2 Belgium	2	Iceland ^*	2	Bosnia & Herzegovina	2	Australia ^*
3 Cyprus ^*	3	Israel ^*	3	Bulgaria	3	Brazil ^*
4 Finland ^*	4	Norway ^*	4	Croatia	4	Canada ^*
5 France ^*	5	Sweden ^*	5	Czech Republic	5	China,P.R.: Mainland
6 Germany ^*	6	Switzerland ^*	6	Estonia	6	China,P.R.: Hong Kong ^*
7 Greece ^*	7	United Kingdom ^*	7	Hungary	7	India ^*
8 Ireland ^*			8	Kosovo	8	Indonesia
9 Italy ^*			9	Latvia	9	Japan ^*
10 Malta ^*			10	Lithuania	10	Korea, Republic of ^*
11 Netherlands ^*			11	Macedonia, FYR	11	Malaysia ^*
12 Portugal ^*			12	Montenegro	12	Mexico ^*
13 Spain ^*			13	Poland	13	Philippines ^*
			14	Romania	14	Singapore ^*
			15	Russian Federation ^*	15	South Africa ^*
			16	Serbia, Republic of	16	Turkey ^*
			17	Slovak Republic	17	United States ^*
			18	Slovenia

1/ Belarus, Luxembourg, Moldova, San Morino, and Ukraine not included in sample.

^{^*}Countries with expansion peaks in 1971-2006 that are included in LP regression to derive projection paths.

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Abstract

Credit Growth and Economic Recovery in Europe: The Case of Slovenia1

A. Introduction

B. The Post GFC-Recovery in Slovenia: Is It Different?

C. Determinants of Credit Growth6

Bank capital

Customer Deposits

Non-Performing Loans

D. GDP Growth and Credit Growth in Europe and Slovenia13

E. Concluding Remarks

Annex 1. Country Groups

References

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Credit Growth and Economic Recovery in Europe: The Case of Slovenia¹

C. Determinants of Credit Growth⁶

D. GDP Growth and Credit Growth in Europe and Slovenia¹³