Financial conditions and macroeconomic behavior.

• Author: Gertler, Mark
• Position: Research Summaries

What role do financial factors play in business cycles? Many business economists and policymakers, including the chairman of the Federal Reserve Board, have cited "balance sheet conditions" as a contributing factor in both the 1990-1 recession and the extended period of stagnant growth that surrounded it. Underlying this view is the belief that unusually weak balance sheets of nonfinancial companies, depository institutions, and households were constraining spending. When Alan Greenspan spoke repeatedly of a "50-mile-an-hour headwind" that was interfering with the recovery, he had in mind these kinds of financial factors.

Much of my research has been aimed at trying to understand the links between financial conditions and macroeconomic performance. Eight years ago, Ben S. Bernanke and I developed a simple business cycle framework in which endogenous fluctuations in borrowers' financial positions served to propagate the impact of exogenous disturbances to the economy.(1) We began with the idea that, for a significant class of borrowers, information and enforcement problems may drive the cost of uncollateralized external funds above the price of internal funds. Under these circumstances, borrowers' available supplies of collateral (broadly defined) and internal funds influence their spending and production decisions. In the aggregate, swings in borrowers' balance sheets over the cycle amplify fluctuations in spending and output. We referred to this propagation mechanism as a "financial accelerator."

One by-product of having financial conditions play a key role in the model is that the output dynamics are inherently nonlinear. Because the credit frictions bind across a wider cross section of borrowers in bad times (when balance sheets are relatively weaker on average) than in good times, contractions are typically sharper than expansions. Broadly speaking, this kind of nonlinearity appears consistent with the data.

In addition to rationalizing a new kind of business cycle propagation mechanism, the model provides a formal basis for Irving Fisher's "Debt Deflation" theory of the Great Depression. To explain the severity of the Depression, Fisher cited the sharp decline in prices--largely unanticipated, in his view--that greatly reduced the net worth of the borrowing class by raising the real value of outstanding debts. In our framework, a contraction in borrower net worth curtails borrowers' access to credit, inducing a persistent downturn.

Our early paper emphasized how financial positions might influence the behavior of nonfinancial companies. In principle, these conditions might influence other important classes of borrowers similarly, including (at least subsets of both) financial intermediaries and households. In our 1987 paper, we showed how a shortage of bank capital could induce a decline in lending by restricting banks' ability to attract uninsured deposits.[2] Many observers have maintained that this kind of phenomenon was particularly relevant during the recent capital crunch in banking.

Balance sheet effects on household spending are potentially quite important, in my view. Generally speaking, households face large spreads between borrowing and lending rates (after controlling for default probabilities), particularly for unsecured loans. In addition, some major household purchases, most importantly housing, are linked directly to the condition of household balance sheets by such features as downpayment requirements, up-front transactions costs, and minimum income standards. A recent example of a formal model in which household balance sheets influence housing demand is Edward C. Prescott.[3]

Our original theoretical framework was quite stark, designed mainly to make qualitative points. In subsequent work with Bernanke, with other coauthors, and by myself, I have enriched the institutional detail, in an attempt to move the theory closer to the data.[4] Some very recent work by others that makes progress along these lines includes Nobuhiri Kiyotaki and John Moore, Owen Lamont, and Jonas Fisher.[5]

In recent years I have turned my attention to the empirical side of the issue. Attempting to identify and quantify a financial accelerator mechanism in the data is a difficult task. Because existing datasets generally were not well suited...