There is now a relatively large theoretical body of literature showing that credit frictions and, more generally, financial market imperfections can amplify business cycle fluctuations. The most recent financial crisis has provided further impetus and stronger incentive for researchers to construct frameworks that incorporate such frictions and are suitable for quantitative business cycle analysis.
Although progress has been made, it is still true that the task of developing the required quantitative models is particularly challenging, since many of the relevant finance-related models display heterogeneity and frictions such as asymmetric information and costly contract enforcement. Heterogeneity is mostly needed to generate borrowing and lending, while informational and related frictions are required to give a genuine role for the capital structure. Hence, constructing models that belong to this class and can also be credibly matched to the data has proven to be more difficult than, say, calibrating a standard real business cycle model or, more generally, constructing and calibrating a DSGE model with nominal rigidities, where in the former class of models there is no heterogeneity or any kind of market failure. In the latter types of model, heterogeneity due to price rigidities is typically handled via a special (financial market) construct that effectively takes the modeller back to the representative agent framework.
Once we recognize that the market economy can fail to allocate credit most efficiently, that is to the most productive investment project, as credit transactions are subject to agency problems, it becomes evident that borrowers’ net worth, or borrowers’ balance sheet condition, as it is also known, occupies a central role in allocating credit across entrepreneurs, firms, households, industries and nations. Changes in the aggregate level of wealth as well as changes in the distribution of wealth consequently affect the equilibrium allocation of the credit, which, in turn, affects the patterns of investments.
The progress made in the microeconomics of financial markets and corporate finance over the last thirty years has, however, left in its wake a bewildering set of specific models with apparently conflicting results. Do the imperfections add persistence to the macroeconomic dynamics, or do they merely, or mainly, add volatility? If they drive fluctuations, is this because misallocation of credit creates recessions or because it creates boom-and-bust cycles? Do improvements in credit markets reduce or increase fluctuations? Does financial globalization alleviate or exacerbate credit market imperfections? These are just examples of the types of question to which researchers have been trying to provide answers.
Aggregate implications of credit market imperfections are indeed rich and diverse, so no simple answer to these questions should be expected. The underlying reason for the richness and diversity is that the aggregate implications depend on the manner in which different agents or different investments interact with each other, which consequently affects amplification and propagation mechanisms. This suggests that caution should be exercised with one’s intuition when studying only a particular family of models. The overall implication for incorporating a true role for financial factors in quantitative models of business cycle fluctuations seems, then, to be that we may need to focus on some simpler models of financial structure until there is a consensus on what aspects of financial market imperfections are model relevant. The ultimate goal seems to be, and perhaps should be, to then embed financial frictions into a DSGE structure to establish whether it all fits together in a coherent manner. This suggests that a truly interesting and challenging research agenda lies ahead of us.