For example, tight credit standards were cited among the main factors constraining the US private aggregate demand in 36 Committee's statements issued between 7 August and 26 January This article uses a vector autoregressive model to estimates the impact of tightening in bank lending standards on the US economy during the great recession and recovery period until The article argues that tight lending standards had a profound negative impact on US output, reaching a peak in the second half of when restricted credit availability accounted for a 1 per cent loss in GDP in a single quarter.
Drivers Of Bank Lending: New Evidence From The Crisis
During the following two and half years, the quarterly loss averaged 0. However, by the year there was a marked turnaround, with lending standards no longer restraining aggregate demand. The easing credit conditions observed after the year —supported by the progressing economic recovery and banking sector consolidation—are estimated to contribute by average 0. Section 2 of this article explains how lending standards are measured and discusses why they matter. Section 3 then presents empirical evidence that lending standards are an important predictor for the US economy and evaluates the historical impact of changes to credit standards.
The final section then estimates the impact of changing lending standards during the recovery after the great recession. Credit is an important source of financing for both business and household sectors in the US. The index proved particularly helpful in early , before the Leman Brothers collapse, by providing an almost 5 quarter lead warning that the tightening of lending standards meant that output would likely contract by more than 4 per cent by the end of Credit has become an increasingly popular means of payment and financing source for many households and small businesses in the United States since bank deregulation and financial innovations in the late s.
Similarly, outstanding household credit card debt increased from 65 per cent of GDP in the s to 86 per cent in early The Nielson report publishes news, data and analysis of the global card and mobile payment industry. Lending and borrowing has an important role in the functioning of the economy.
Borrowing allows individuals to smooth their consumption in the face of a variable income. It allows businesses to smooth investment and production in the face of variable sales. And it improves the efficiency of capital allocation across its various possible uses in the economy. In principle, it should also shift risk to those most able to bear it. The recent financial crisis has also been a stark reminder that the stock and flow of credit matter. There are various theories attempting to explain the macroeconomic effects of credit.
Probably the most cited theory today is the theory of the financial accelerator Bernanke et al. Christiano et al.
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Employing a statistical model, Gilchrist et al. Benk et al. Why do credit standards matter Lown et al. Unlike in most other markets, price is not the only factor clearing the market. The supply of credit is also conditional on the creditworthiness on the demand side. Potential borrowers must first qualify for credit, and then they are able to negotiate the contract conditions including the price.
Therefore, some borrowers can be excluded from the market and downward price pressures may prevail despite potentially large excess demand; many profitable investment projects may get rationed out. Monetary policymakers recognise the macroeconomic importance of credit and credit standards. The Board of Governors of the Federal Reserve System conducts a regular survey of senior loan officers.
The survey results are summarised in the Tealbook report on the economic situation and the Board's Staff economic outlook and enter the Federal Open Market Committee's policy considerations. The purpose of the survey is to provide qualitative and some quantitative information on credit availability and credit demand. It is conducted four times a year.
Although the survey's history dates back to , it consolidated in its current form in the early s. The survey covers about 20 core questions about the supply and demand for various types of credit, including commercial and consumer credit. It covers an unbalanced panel of up to 60 insured, domestically chartered commercial banks, and up to 24 branches and agencies of foreign banks. The Board aim for best practice in sampling the panel to represent the structure of the banking industry, but also puts a particular stress on the representation of the largest banks in each district.
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The presence of these large banks is viewed as critical, as they are the banks leading the technological and practical innovation in the banking sector. Laxton develops the Index of Bank Lending Tightening BLT as a way of characterising the dynamic behaviour of lending standards over time Figure 2. The series used in the construction of the BLT index consists of net per cent of banks tightening standards for mortgage loans until the first quarter of , and of net per cent of banks tightening standards for primary mortgage loans from the second quarter of onwards.
The tightening of bank lending standards captured by the BLT index during the first two quarters of draw particular attention. In the third quarter of , almost 70 per cent of responding banks reported tightening in their lending standards. Figure 3 demonstrates the point. Tightening in bank lending constrains aggregate demand in the short term and causes long lasting economic contractions. This section shows that the output contraction peaks on average at 0.
They even find that credit spreads have a predictive power for the BLT index. This section presents estimates of the credit standards shocks and their historical effect on GDP. This article uses a stylised vector autoregression model to investigate the implications of bank lending tightening on the US economy. Similar models are extensively used in the monetary policy literature. Following the convention, the model captures the dependence of the variables on four lags of each variable.
The estimation runs from the second quarter of to the first quarter of The BLT index contains important macroeconomic information. Before analysing its economic predictions, the baseline model was first formally tested to ascertain whether including the BLT index improves the model fit in a statistically meaningful way. The test decisively confirms the BLT's importance. The value of the likelihood ratio test statistics was The BLT index is ordered second, after oil prices, in the baseline model. Under the recursive identification assumption such ordering implies that output, prices, interest rates and money stock contemporaneously adjust to a shock to the bank lending standards.
That means that the US consumers as well as producers and the Federal Reserve observe the prevailing current credit standards in the banking sector before making their decisions. There is no general agreement in the economic literature on the exact variable ordering. For example, in Gilchrist and Zakrajsek's article the lending conditions impact the macroeconomy with a quarter lag. Although the variables ordering matters in theory, qualitatively the baseline results presented below are to a large extent robust to the variable ordering. The recursively identified BLT shocks should be interpreted as unexpected changes of lending standards in the bank credit market.
However, the majority of the impact seems to come from the tightening of supply. Although obtained by a different method, their supply shock estimates exhibit a high level of correlation with the baseline estimates here. The tightening has a significant macroeconomic impact, in line with earlier findings by Gilchrist and Zakrajsek and Laxton An output contraction of 0. The price level initially increases but over the medium term declines by 0.
As output and prices permanently fall, monetary policy responds by lowering the policy rate by 0. Two steps are needed to answer the question of what US output would have been if credit conditions were determined only by economic fundamentals.
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To this end, the model from the previous subsection can be used. In the second step, the same model is simulated without the exogenous movements in lending standards, whilst keeping all other things the same. The result is a counterfactual path for output, prices, interest rates and lending standards that would be observed if banks had not tightened standards beyond what fundamentals warrant. The fundamental change is such that can be fully explained and predicted by the model.
Implicitly, bankers are assumed to set the fundamental level by judging where lending standards stood in the past relative to macroeconomic developments. On the other hand, the exogenous component lacks the model's explanation and cannot be predicted. Frey, Rainer, Mehigan, Caroline, Caroline Mehigan, You can help correct errors and omissions.
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