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Credit market developments: dynamics and stability of the system

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Presentation on theme: "Credit market developments: dynamics and stability of the system"— Presentation transcript:

1 Credit market developments: dynamics and stability of the system
Selami Xhepa

2 Motivation: high volatility of credit behavior and risks involved
Quality of loan’s portfolio Threatening recession/economic growth

3 Monetary policy responses:
A series of policy rate cuts Other policy measures related to: Execution of Collateral

4 What drives credit growth?
Surges in capital inflows (usually associated with capital account liberalization, exchange rate regimes, etc); Total factor productivity gains; Financial reforms Periods of strong economic growth are associated with credit booms Mendoza and Terrones – 2008; Dell’Ariccia

5 What drives credit growth/behavior?
financial deepening (shown to support growth, Levine, 2005), normal cyclical upswings (the demand and availability of credit tends to increase during recoveries), excessive cyclical fluctuations (“credit booms”). Excessive credit growth (credit boom) often end leading to a financial crisis, as it was the case of Asian crisis in 1997 (Selim Elekdag and Yiqun Wu, 2011).

6 Credit behavior: within the “normal” trends – part of financial deepening deviates from such pattern – financial accelerator theory; Qualifications for developing/transition economies: stronger credit growth does not indicate or qualify as “excessive” growth

7 Good and bad credit – and the ugly
Bezmer , 2014

8 ‘Healthy and unhealthy’ loans in Albania

9 Main hypothesis of the paper:
Credit supports growth, but when credit dynamics are excessive, they pose risks to growth. Has credit in Albania been “excessive” too much/too little credit supplied if compared to the credit supported by macro fundamentals Gauge into the dynamics of credit to private/public, trying to understand if: economic growth and recovery of Albania can claim support from the financial sector or we have to go for creditless recovery scenario?

10 Methodology Not an easy job
At some degree, excessive credit relates to transition adjustment path of the financial sector Two steps are followed: Identify the deviation of the credit to GDP from its long term trend (Hedrick Prescott filtered) Estimate the deviation of Credit to GDP from the its level defined by macroeconomic variables (VECM estimation of credit equation)

11 Private and Public Credit Deviation from long term trend

12 Episodes of credit dynamics being excessive are found (2004/2005; 2007-2009)
Credit to public entities “excessive”, two episode of positive excessive in a short time frame. From “over” heated credit, over reaction of crediting, with prolonged excessive negative credit growth are observed

13 Is this excessiveness a transition feature of the credit (the hypothesis of financial deepening) or; a system failure and lack of mechanisms to ensure smooth transition of credit cycles What is the effect of this volatile credit for the sustainability of growth?

14 Credit as defined by Macro fundamentals
Estimated the following credit equation using VEC A specification randomly found in similar literature, especially in studies dealing with transition economies. Most of the variables were found non-stationary and VEC gives the best results when dealing with non stationary variable. The model was then used to forecast credit and evaluate the deviation of credit from the credit as per macro fundamentals

15 Data and variables – Descriptive and expected impact
Hypothesis  Mean  Std. Dev. No.  Data frequency, source Deposits to GDP Supply side factors (+)      198 BoA, monthly Equity to GDP     Public Credit to GDP Crowding Out effect (-)     BoA, Author calculations Real GDP per Capita Demand Side factor     INSTAT, extrapolated to monthly GDP per Capita (in Logs)     Annual Inflation +     INSTAT, monthly Base Interest Rate Measure cost of credit (-) demand side (+) supply side     Spread (lending -depositing rate)     Private Credit to GDP Dependend variables     Total Credit to GDP    

16 VEC identification procedures
All variables were tested for Unit root test – 4 variables have unit root Number of lags to be included in the model were defined – 1 lag Performing Cointegration test – Rank 1 (one cointegration equation)

17 Long term cointegration equation
Credit to GDP Total Credit to GDP GDP per Capita (in log, -1) [ ] *** [ ] Deposits to GDP (-1) [ ] ** [ ] Base Interest Rate (-1) [ ] [ ] C Error Correction Term [ ] [ ] Δ[Credit to GDP (-1)] [ ] [ ] Δ[GDP per Capita (-1)] [ ] [ ] Δ[Deposits to GDP (-1)] [ ] [ ] Δ[Interest Rate (-1)] [ ] [ ] [ ] [ ] Equity to GDP [ ] [ ] Spread [ ] [ ] Public Credit to GDP [ ] [ ] Inflation Rate (annual) ( ) ( ) [ ] [ ] R-squared Adj. R-squared F-statistic Log likelihood Observations 196

18 Main findings Long term credit is strongly influenced by economic performance and deposits Interest rate, plays more on the demand side, hurting credit growth Positive and significant error correction term, more financial deepening will be needed for Albania to move toward its long term macro founded equilibrium

19 Main findings Short term adjustment/fluctuations of credit to GDP, weak and sometime “going wrong direction” Banking sector equity, not significantly related to credit dynamics, may be because of deposit driven credit supply Crowding out negative effect on private credit observed Spreads, along side base interest rate were posing negative influence on credit short term dynamics.

20 Comparing credit with forecasted

21 Some concluding remarks
Reverse dynamics of private and public credit Credit to private has to take ground, as it is currently under its long path equilibrium Credit to private entities excessive episodes are more related to financial deepening Smooth transition of credit cycles are needed in order not to hurt growth 2008 made private entities react and adjust (over adjustment and contract) It seems now is the government turn to take care of public credit.


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