Credit is actively used by only about 8 percent of people in developing countries and about 14 percent in developed countries (World Bank Findex). The observed gaps in financial inclusion thus suggest that greater access to credit is warranted.
However, finance can be a double-edged sword. Rapid financial development and deepening can cause accumulation of systemic risk and lead to costly financial crises (Reinhart and Rogoff 2009). Banking crises in Thailand (1997), Colombia (1982), and Ukraine (2008), for example, were preceded by excessive credit growth of 25 percent, 40 percent, and 70 percent per year, respectively. Providing the right amount of credit—not too much and not too little—is thus a major concern for countries and their policy makers.
When credit provision becomes excessive or insufficient is judged against an unobserved benchmark known as equilibrium credit. Estimating equilibrium credit is one of the most challenging tasks of determining excessive or insufficient credit provision.
The Basel III regulatory framework instructs macroprudential supervisors to estimate equilibrium credit by applying the Hodrick-Prescott (HP) filter to the ratio of nominal credit to nominal GDP (the credit-to-GDP ratio). Any “significant” deviation of the ratio from its HP filtered trend then triggers accumulation (or release) of the countercyclical capital buffer. However, because the HP filter is a purely univariate statistical tool, it fails to account for the possibility that the financing needs of the real economy could be growing with the development and changing structure of the economy. In fact, any univariate statistical tool would ignore the impact of economic and financial development on equilibrium credit. This ignorance could lead to costly mistakes in financial policy.
The existing literature has studied equilibrium credit provision by estimating long-run credit demand functions. The studies focus on modeling the ratio of nominal credit to the GDP deflator (real credit; Cottarelli et al. 2005) or to nominal GDP (the credit-to-GDP ratio; Eller et al. 2010). We argue that these approaches are too restrictive. They assume that as economies develop, they use credit to the same degree and with the same intensity. However, growing financial inclusion (more people and firms using credit) and more intensive use of credit products by households and firms (mortgages, credit cards, and credit lines) undermine this assumption. Indeed, we show that cross-country panel data reject these assumptions, which could result in important biases when estimating equilibrium credit.
Our recent paper (Buncic and Melecky, 2014) proposes a structural framework to estimate equilibrium credit that considers the effects of economic and financial development on credit demand and supply. The proposed framework consists of three stages. First, we estimate country-specific credit demand functions using a quarterly panel data set for high- and middle-income countries from 1980 to 2010. Second, we model the cross-country variation in the first-stage estimates of the income and price elasticities of credit by regressing the country-specific elasticities on “relevant” economic and financial indicators. The main indicators that influence country-specific income and credit elasticities are: financial depth, access to financial services, use of capital markets, efficiency and funding of domestic banks, central bank independence, the degree of supervisory integration, and the experience of banking crises. Third, we use the predicted income and price elasticities from the second stage, together with estimates of equilibrium GDP and prices, to compute a structural estimate of equilibrium credit for each country.
Figure 1 illustrates how a structural estimate of equilibrium credit can differ from the estimate that uses the Basel III approach in countries that have been undergoing economic and financial development. In general, we observe that credit gaps (actual credit minus equilibrium credit) based on our structural estimates could provide a more timely and accurate indication of excessive credit supply (as for the Slovak Republic before its 1998 banking crisis) or insufficient credit provision (as for Latvia after its 2008 banking crisis) than credit gaps computed based on the Basel III approach. The structural credit gaps are also less volatile and thus less likely to produce false alarms.
Figure 1: Comparison of credit gap estimates
Source: Buncic and Melecky (2014).
Note: (+) excessive; (-) lacking credit provision.
Our empirical findings have important policy implications. Our results show that Basel III fails to account adequately for systematic changes in equilibrium credit caused by changes in the financial, economic, and institutional development of a country. Hence, the Basel III approach, which uses the HP-filtered credit-to-GDP ratio to compute equilibrium credit, may be too simplistic for developing economies. We also show that, in some cases, the Basel III approach can lead to a pro-cyclical estimate of equilibrium credit, thereby potentially amplifying economic booms and intensifying recessions.
Developing countries have much to lose if they fail to properly balance financial stability oversight with financial development. Overly restrictive credit provision can hinder economic growth and low access to finance can inhibit equal access to opportunities and adequate sharing of prosperity.
Buncic, D., and M. Melecky. 2014. “Equilibrium Credit: The Reference Point for Macroprudential Supervisors.” Journal of Banking and Finance.
Cottarelli, C., G. Dell’Ariccia,and I. Vladkova-Hollar. 2005. “Early Birds, Late Risers, and Sleeping Beauties: Bank Credit Growth to the Private Sector in Central and Eastern Europe and in the Balkans.” Journal of Banking and Finance 29(1): 83–104.
Eller, M., M. Frommel, and N. Srzentic. 2010. “Private Sector Credit in CESEE: Long-run Relationships and Short-run Dynamics.” Focus on European Economic Integration 2010(2): 50–78.
Reinhart, C.M., and K.S. Rogoff. 2009. This Time Is Different: Eight Centuries of Financial Folly. Princeton, NJ: Princeton University Press.
Source : blogs.worldbank.org