Although a credit tightening is commonly recognized as a key determinant of the Great Recession, to date, it is unclear whether a worsening of credit conditions faced by households or by firms was most responsible for the downturn. Some studies have suggested that the household-side credit channel is quantitatively the most important one. Many others contend that the firm-side channel played a crucial role. We propose a model in which both channels are present and explicitly formalized. Our analysis indicates that the household-side credit channel is quantitatively more relevant than the firm-side credit channel. We then evaluate the relative benefits of a fixed-sized transfer to households and to firms that improves each group’s access to credit. We find that the effects of such a transfer on employment are substantially larger when the transfer targets households rather than firms. Hence, we provide theoretical and quantitative support to the view that the employment decline during the Great Recession would have been less severe if instead of focusing on easing firms’ access to credit, the government had expended an equal amount of resources to alleviate households’ credit constraints.
Recent critiques have demonstrated that existing attempts to account for the unemployment volatility puzzle of search models are inconsistent with the procylicality of the opportunity cost of employment, the cyclicality of wages, and the volatility of risk-free rates. We propose a model that is immune to these critiques and solves this puzzle by allowing for preferences that generate time-varying risk over the cycle, and so account for observed asset pricing fluctuations, and for human capital accumulation on the job, consistent with existing estimates of returns to labor market experience. Our model reproduces the observed fluctuations in unemployment because hiring a worker is a risky investment with long-duration surplus flows. Intuitively, since the price of risk in our model sharply increases in recessions as observed in the data, the benefit from creating new matches greatly drops, leading to a large decline in job vacancies and an increase in unemployment of the same magnitude as in the data.