It is now fairly obvious that the most recent financial crisis poses major challenges to business cycle modeling, particularly to the tradition that uses dynamic stochastic general equilibrium (DSGE) models for quantitative business cycle analysis. These DSGE models have done quite well in accounting for the dynamics of the main macroeconomic variables at ’normal’ business cycle frequencies. Naturally, the meaning of normal business cycle fluctuations is open to debate, but one particular feature seems to be shared by all such fluctuations: fairly regular ups and downs in the growth rate of activity (GDP) as long as there are no major adverse or disruptive effects to or from the financial sector of the economy. ’Money’ seems to stay in the background, tracking growth paths that we tend to see as representing normal business cycle fluctuations.
Many, if not most, mainstream dynamic models for business cycle fluctuations build on the strong assumptions of well functioning financial markets, rational expectations and a representative agent maximizing her lifetime welfare subject to an inter-temporal budget constraint. Recent extensions introduce to the basic setup different types of financial frictions - eg liquidity or borrowing constraints, collateral constraints or credit spreads - with the aim of gaining a deeper understanding of the effects of such frictions on business cycle dynamics. On the quantitative side, these extensions have strengthened the hopes and desires of quantitative business cycle economists to better account for the effects of large shocks, particularly financial shocks, on business cycle fluctuations.
Important as these extensions are, most of them still do not effectively allow for banks’ balance sheets to affect business cycle fluctuations. Hence, these models imply that bank lending is unaffected by banks’ capital position. Some very recent contributions argue that abstracting from the effects of bank capital on banks’ lending capacity is a limitation of the current quantitative models of financial frictions and in fact contradicts an important part of the evidence of bank- capital effects on bank lending and economic activity.
How should one go about incorporating a role for bank capital in a DSGE model? One alternative is to first think of bank capital as emerging endogenously as a solution to an asymmetric information problem between bankers and their creditors. This implies that a bank’s capital position affects its ability to attract funds from investors for the purpose of loan origination. Consequently, bank capital influences business cycle fluctuations through what the literature has come to call a bank capital channel of transmission. Once this mechanism is incorporated into a widely used New Keynesian model for monetary policy analysis, one can provide a quantitative basis for the evaluation of the role of bank capital in the propagation of shocks in the economy. Dynamic simulations using these types of models suggest that an effective bank capital channel indeed amplifies and propagates the effects of shocks on output, investment and inflation, and that the strength of this effect depends on the nature of the shock.
 Se eg C. Meh and K. Moran (2010), ’The role of bank capital in the propagation of shocks’, Journal of Economic Dynamics and Control 34, 555-576