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Investigating the Determinants of Nonperforming Loans

Investigating the Determinants of Nonperforming Loans

The study of financial sector stability has become the cornerstone of modern macroeconomic policy. The recent global financial crisis highlighted the importance of appreciating financial institutions’ vulnerabilities in the context of managing credit risk. 

The key motivation for this paper is to improve our understanding of the credit risk determinants by focusing on the Romanian banking system while casting a vigilant eye on potential contagion effects from neighbouring countries. 

This is particularly important given that the Romanian financial system is dominated by foreignowned commercial banks. Among them, the Greek banks’ subsidiaries have a substantial presence as they hold 30.7% of aggregate foreign capital while they account for the second largest market share in the Romanian banking system [1]. 

Therefore, any attempt of exploring the deterministic factors of the Romanian banks’ credit risk should not be limited solely on endogenous variables of the respective economy. Using time series modelling techniques, this paper empirically investigates the determinants of ex post credit risk as reflected on the loss loan provisions to total loans ratio for the Romanian banking system. 

Related to a growing body of literature, the purpose of the study is to offer an insight into the factors that determine the quality of the loan portfolio of Romanian banks. In this direction, it utilizes a broad dataset that spans from December 2001 to November 2010. 

The explanatory power of macroeconomic, Romanian bank-specific, monetary, interest rates and financial markets’ variables is investigated. The key contribution of the paper lies in the introduction of proxies for the Greek debt crisis and the subsequent Greek banks’ financial distress. 

The aim is to examine a potential transmission channel or spillover effects to the Romanian banking system. As the twin Greek crises unfold, any repercussion for the neighbours is possibly the most important issue in the minds of policy makers, regulatory bodies, and bankers. 

Furthermore, the time series utilised include both the booming period as well as the downturn following the financial crisis and the ensuing manifestation of Greece’s structural weaknesses.

Overview of the Romanian Banking System

The Romanian economy has evolved from a long history of defaults on sovereign debt, periods of high inflation, and banking crises. During the Great Depression period, many local and foreign banks in Romania collapsed or experienced heavy runs [2]. 

The crisis historical database indicates that in 1933 the redemption for domestic and foreign debt was suspended. In the post-World War II period the country experiences a debt crisis during the 1980s. Barisitz [3] indicates that until 1998 the Romanian banking system was overwhelmingly state owned. 

Credit institutions granted loans to an unrestructured real sector dominated by inefficient state-owned factories, subject to “quasiautomatic” refinancing by the Central Bank of Romania, which conducted an accommodative monetary policy. 

Thus, there is no surprise in the fact that bad loans were a serious problem for all economies in the SEE region due to inherited legacies but also to continuing lending practices [4]. In Romania, the dominant state-owned banks accumulated large portfolios of defaulted loans and required massive capital injections from the government. 

Furthermore, severe macroeconomic shocks led to banking crises and economic growth resumed only after these crises were resolved. By the end of the 1990s the Romanian government carried out legal reforms through the new central bank law. 

Retrospectively, the year 1999 proved to be a sort of structural turning point for the Romanian economy as the authorities initiated the first privatizations of major Romanian banks. Given the size of the country, the Romanian financial sector offered an impressive growth potential for foreign strategic investors. 

Figures 1 and 2 depict the current situation in the Romanian banking system. The following years up to the burst of the global financial crisis were characterised by rapid credit growth. That was thought to be part of the ongoing process of financial deepening given that the credit to GDP ratio still remains at relatively low levels. 

On the other hand concerns were raised whether the economy was experiencing a credit boom, a situation where credit expands at an unsustainable pace. It has been argued that the presence of foreign banks in Romania has increased the efficiency of financial intermediation and the availability of credit to the real economy. 

Yet, there are indications that financial stress originating in Euro area-based parent banks may have been transmitted to Romania.

The lending survey of the National Bank of Romania (NBR) indicates that the risk profile of almost all industries rose with the riskiest sectors being construction and real estate, thus, reflecting the adverse impact of the global financial crisis. 

The outlook for the Romanian banking system remains negative, driven mainly by the tough economic conditions in the country following a severe recession in 2009 [5]. The deteriorating operating environment in Romania is characterised by a contracting economy, widened fiscal deficit, and rising unemployment. 

In particular, the country’s macroeconomy appears to the main source of concern for Romanian banks given the sharp increase in the level of nonperforming loans. Furthermore, the high proportion of foreign currency lending mainly to households elevates their credit risk profile while the stressed liquidity as reflected in the system’s loan-to-deposit ratio (the loan-to-deposit ratio is at relatively high levels reflecting the Romanian banks’ reliance on wholesale-parent bank funding) may lead to a further tightening on the supply side of credit.

Empirical Literature Review

This section reviews the empirical work on the relation between macroeconomic variables and the loan portfolio quality or credit risk (the framework for studying the impact of macroeconomic variables or the business cycle on credit risk is represented by two competitive theories. 

The first one stresses that credit risk is procyclical whereas the second one defends the countercyclical view). Many studies investigate the factors that induce financial crises by examining potential links between bank-specific variables and macroeconomic factors. 

Delving into the specifics of the crises literature, Gavin and Hausmann [6] argue that excessive credit growth is a primary factor behind banking crises as usually it reflects a decline in the credit standards. 

Examining the macroeconomic factors that contributed to banking crises in Latin America during the 1990s, the authors find that interest rates, expected inflation, terms of trade, domestic income, credit growth and the monetary and exchange rate regime are important constraints on loan servicing capacity. 

Similar results can be found in Diamond and Rajan [7]. Demirguc¨¸-Kunt and Detragiache [8] theorize that banks face insolvency due to falling asset values when bank borrowers are unable to repay their debt as a result of adverse shocks to economic activity. 

Using a multivariate logistic model for a large sample of developing and developed countries during 1980–1994, the authors find that inflation and the real interest rate are positively associated with a banking crisis whereas the GDP has an inverse relationship. 

Furthermore, the study by Hardy and Pazarbasioglu [9] strongly suggests that the likelihood of banking system distress is largely in accord with declining economic growth. The authors also find that capital inflows and credit expansion to private sector, associated with rising consumption and real interest rates, typically precede banking crises. 

An increasingly popular method of assessing financial sector vulnerabilities is the macro stress-testing approach (the term refers to a range of techniques used to assess the vulnerability of a financial system to “exceptional but plausible” macroeconomic shocks). 

Relevant studies examine the link between banks’ loan losses, or Nonperforming loans, and macroeconomic factors. The most common approach in similar studies involves estimating on historical data the sensitivity of banks’ balance sheets to adverse changes in macro fundamentals.

Then the estimated coefficients can be used to simulate the impact on the financial system of possible stress scenarios in the future. The focus is on credit risk, which by large represents the most significant risk faced by banking systems worldwide. 

Two main strands of the literature can be identified in this area, building on the seminal works by Wilson [10, 11] and Merton [1]. Merton [1] models initially the response of equity prices to macro fundamentals and then maps asset price movements into default probabilities. 

On the other hand, Wilson’s [10, 11] framework allows the direct modelling of sensitivity of default probabilities in various industrial sectors to the evolution of a set of macroeconomic variables. 

Studies analysing the macroeconomic determinants of banks’ loan losses or Nonperforming loans include Pesola [12] for the Nordic countries, Kalirai and Scheicher [13] for Austria, and Delgado and Saurina [14] for Spain. 

Typically, these studies find that loan loss provisions are negatively related to GDP growth and positively related to interest rates. Kalirai and Scheicher [13] estimate a time series model of aggregate loan loss provisions in the Austrian banking system as a function of an extensive array of macroeconomic variables. 

Results indicate that a rise in short rates, a fall in business confidence, a decline in the stock market, and a decline in industrial production have an impact on the loss loan provisions. 

Since the seminal work of Sims [15], the VAR approach to empirical investigation of monetary policy shocks has gained momentum. Several studies have used the VAR models (studies that employ VAR models include Blaschke et al. [16], Hoggarth et al.

[17], Delgado and Saurina [14], Gambera [18], and Baboucek and Jancar [19]) to investigate the macro fundamentals transmission mechanism in the United States and other countries (these models are used in the studies developed at the central banks of the UK, Japan, Spain, the Netherlands, and at the European Central Bank). 

These models include various macroeconomic factors, ranging from a number from two to five depending on the country. In some cases variables more directly related to the creditworthiness of firms are added, such as measures of indebtedness. 

In other cases, market-based indicators of credit risk, such as equity prices and corporate bond spreads are used (introducing market variables such as interest rates, foreign exchange rates, and equity and real estate price indices into credit risk models is a way of explicitly integrating the analysis of market and credit risks). 

Foglia’s [20] survey indicates that researchers increasingly adopt models that are more flexible and easier to use, such as VARs and other strictly statistical rather than structural models. The estimation process normally requires the selection of a set of macroeconomic and financial variables that, according to economic theory and empirical evidence, affect credit risk. 

In this regard, variables such as economic growth, unemployment, interest rates, equity prices, and corporate bond spreads contribute to default risk [20]. Several recent papers [21, 22] analyse the impact of macro fundamentals on the credit quality of banks’ debtors using the framework of Wilson [10, 11]. 

Virolainen [23] estimates a macroeconomic credit risk model for the Finnish corporate sector over the period from 1986 to 2003 (a distinguishing feature of the study is that the sample period used to estimate the model includes a severe recession and a banking crisis). 

The SUR model results suggest a significant relationship between corporate sector default rates and key macroeconomic factors including GDP, interest rates, and corporate indebtedness. As in most studies, the estimated model is employed to analyse corporate credit risks conditional on current macroeconomic conditions, that is, stress testing. 

The findings are in line with previous studies using observed bankruptcies for default rate measures. Following Virolainen [23] methodology, Trenca and Benyovszki [22] estimate a macroeconomic credit risk model for the Romanian corporate sector over the period 2002– 2008. 

Results suggest a significant relationship between industry-specific default rates and macroeconomic factors such as GDP growth rate, consumer price index, real interest rate charged on loans, the exchange rate, and industryspecific indebtedness. 

Boss [21] estimates a macroeconomic credit risk model for the aggregate corporate default rate to analyse stress scenarios for the Austrian banking sector. Findings suggest that industrial production, inflation, the stock index, the nominal short-term interest rate, and the oil price are the most important determinants of corporate default rates. 

A leading role in the development of aggregate stress tests has been performed by the IMF, in cooperation with the World Bank. In 2005 the IMF conducted for the first time in Greece a financial sector assessment program [24]. 

Similar to Boss [21], Kalfaoglou [24] emphasises that credit risk remains the most important risk in the Greek banking sector. 

Despite the satisfactory stress tests’ results, the author indicates that the cross-border expansion of banks increases their vulnerability to external shocks which, in turn, requires better and more intensive risk management practices. 

The IMF’s [5] Romanian stress tests indicate that the financial system is particularly vulnerable to the effects of further slowing or reversal of capital inflows and associated downward pressure on the exchange rate. 

The stress tests were based on data to end June 2008 (it is worth noting that the 2010 EU-wide stress test exercise did not consider the Romanian banks). Thus, the exercise takes no account of developments in macrofinancial variables and balance sheets since then. 

Furthermore, it does not explicitly assess the impact of the sharp slowing of lending, either as a result of tightening credit standards or in response to reduced funding from foreign parent banks. 

The above-mentioned studies, in general, corroborate theoretical postulates with respect to the macroeconomic influences on loan portfolio quality and, consequently, on banking sector stability. In effect, good economic conditions seem to be commensurate with good loan quality measured by either the nonperforming loans’ ratio or loan loss provisions.
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