The behaviour of households is similarly affected by financial market imperfections. Due to imperfections, including an inability to borrow against one’s life time income, households can be subject to borrowing constraints and therefore undertake more precautionary saving. This can make household consumption highly sensitive to fluctuations in transitory income. A number of empirical studies suggest that changes in aggregate consumption are significantly correlated with lagged or predictable changes in income or credit growth (Flavin (1981), Campbell and Mankiw (1989, 1990) and Deaton (1992); see Jappelli and Pistaferri (2010) for a review). Ludvigson (1999) shows a statistically significant correlation between consumption growth and predictable credit growth.

Changes in house prices affect household borrowing and spending substantially through their impact on household net worth and cost of credit. Home equity is often a large part of household net worth. A variety of micro-based empirical studies document that household consumption is affected more by changes in house prices than what simple life-time consumption models would predict (Claessens and Kose (2017)). Lamont and Stein (1999) report that US households with weak balance sheets adjust their housing demand more strongly in the face of income shocks, consistent with a role for borrowing constraints. Other studies also show that households face an external finance premium, which is lower when their financial position is stronger (Almeida et al (2006)).

Financial imperfections associated with housing markets are shown to have implications beyond their impact on individual households. Using regional-level data for the United States, Mian and Sufi (2010) show that the local variation in house price appreciation in the 2000s, and related subprime expansion and securitisation, led to a disassociation of local mortgage credit from income as borrowing constraints became (excessively) relaxed. Credit extension was driven by expectations of house price appreciation but this was followed by a wave of mortgage defaults when prices started to decline (Figures 2 and 3). In the regions affected, this triggered subsequent large adjustments in durables consumption (proxied by auto sales) and a rapid increase in unemployment (Mian and Sufi (2014b) and Loutskina and Strahan (2015); see also Benmelech et al (2017) on the important role of credit supply shocks in the auto loan market during the GFC).

However, some question the potential role of imperfections in explaining the behaviour of households and firms. They argue that the close association between income and consumption may not be entirely due to imperfections. Others point out the general difficulty in separating real effects from balance sheet effects. Factors, such as the expected rate of return, while difficult to measure, also affect firm and household access to finance. Some consequently argue that changes in cash flows represent a set of factors that is different from the strength of balance sheets (Eberly et al (2008)). Carroll (1997), for example, suggests that the excess sensitivity of consumption growth to forecastable income growth is explained by nonlinearities of the marginal utility function rather than by borrowing constraints.

The quantitative importance of financial frictions for small firms has been under scrutiny as well. Chari et al (2008) challenge the findings of Gertler and Gilchrist (1994) and report that the behaviour of small and large firms is not significantly different during US recessions than it is during other times. Kudlyak and Sánchez (2017) consider how the debt, sales and inventories of small and large firms evolved during the third quarter of 2008, a period of elevated financial stress. They report that large firms experienced bigger declines in sales and short-term debt than small ones (Table 1). They also document similar patterns for earlier recessions. Others argue that even if smaller firms tend to face significant external finance premia, the role of such firms in explaining business cycles may be small (Cummins et al (2006)). Srinivasan (1986) shows that small- and medium-size manufacturing firms depend 10