Determinants of Non Performing Loans

The link between the Non Performing Loans (NPLs henceforth) and loss of banks, is regarded a fact in literature of banking. Increase in NPLs rate is referred often as the failure of credit policy too.

By viewing other side of the picture, it is also evident that financial crisis is also the effect of high NPLs rate in the banking sector. Financial crisis of late 2000s, which started from US and spread into whole world having trading relationships with US, is also labeled as cause of default in mortgages/loans.

Increases in NPLs’ rate are the main reason of reduction in earnings of banks. The reason behind the bad debts is low repaying capacity of borrowers, which in turn is the result of uneconomic use of loans, low per capita, and high interest rate.

Extra flexible credit rationing policy could also be the reason of high NPLs rate. Hence, it is clear why NPLs rate is most crucial for banks. The aim of this study is to analyze the sensitivity of non-performing loans to macroeconomic indicators in United States of America.

In particular, it employs regression analysis and a time series dataset covering 25 years (1984 to 2010) to examine the relationship between nonperforming loans rate and several key macroeconomic variables along with the amount of Total Loans.

Literature Review

Lot of researches has been conducted on the widespread issues of banking activities. NPLs also have a lot of literature due to its importance for the survival of banks. While talking about the determinants of NPLs specifically, different categories are involved.

At first step there are bank specific determinants, then macroeconomic variables, and at last the regulatory framework. In bank specific factors, total loans, and credit policy are important. In the class of macroeconomic determinants, real GDP per capita, Interest rate are well known. Below paragraphs include literature on the relationships of these factors with NPLs rate.

There is no global standard to define non-performing loans at the practical level. A non-performing loan (NPL) is defined as a sum of borrowed money upon which the debtor has not made his or her scheduled payments for at least 90 days.

A nonperforming loan is either in default or close to being in default. Once a loan is nonperforming, the odds that it will be repaid in full are considered to be substantially lower. If the debtor starts making payments again on a nonperforming loan, it becomes a re-performing loan, even if the debtor has not caught up on all the missed payments.

One of the early and important studies on the subject of loan losses includes Keeton & Morris (1987). It used NPLs net of charge offs rate as the proxy for loan losses. The study regarded the macroeconomic conditions as the reason of low payback.

It also concluded that too much loaning in a sector is the major cause of high bad debts, upon the bad performance in that sector. Study also highlighted that risk taking behavior of banks also lead to the greater loan losses ratios.

Many other similar studies proposed that a balanced issue of credit should be made for all sectors of economy, and conservatism prickle should be adhered while issuing loans. Another research which focused the loan loss ratio of commercial banks in US is Sinkey & Greewalt (1991).

They used the loan loss ratio by the proxy constituting charge offs plus NPLs divided by total loans. Study resulted in both external and internal determinants of the NPLs. Excessive financing and interest rate (high) is regarded main reason for high rate of NPLs in US banking sector.

Study of Salas & Saurina (2002) conducted the analysis for NPLs by combining the macroeconomic and firm specific factors by employing the Spanish commercial banks’ data. It covered the period of 1985 to 1997.

It concluded that there is the problem of management inefficiency that leads to greater NPLs rate. The study found that bank size in not related to the NPLs rate, rather these are firm specific factors that generate more loan losses and raise the NPLs rate.

Study of Rajan & Dhal (2003) employed the regression analysis for Indian banks. It claimed that macroeconomic factors and financial factors both have significant impact over the NPLs rate.

Reported macroeconomic factors include the GDP growth, among financial factors; maturity, bank size, credit orientation, and credit terms were included. Some studies also considered the impact of ownership structure on the NPLs rate.

One of those is Hu et al (2006) which studied Taiwan’s banking sector. It covered the study period of 1996 to 1999. It claimed that government owned banks have fewer NPLs rate. It also found negative relationship between the bank size and NPLs rate.

The impact of diversification is not proven significant. The literature suggests a strapping association between NPLs and several macroeconomic factors.

These are annual growth in GDP, credit growth, real interest rates, the annual inflation rate, real effective exchange rate annual unemployment rate, broad money supply (M2) and GDP per capital etc. This study only considers the real GDP per capita, Interest Rates and Total Outstanding Loans including Leases and NPLs Rate.

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