Sophia Chen

I study whether firms' reliance on intangible assets is an important determinant of financing constraints. I construct new measures of firm-level physical and intangible assets using accounting information on U.S. public firms. I find that firms with a higher share of intangible assets in total assets start smaller, grow faster, and have higher Tobin’s q. Asset tangibility predicts firm dynamics and Tobin’s q up to 30 years but has diminishing predicative power. I develop a model of endogenous financial constraints in which firm size and value are limited by the enforceability of financial contracts. Asset tangibility matters because physical and intangible assets differ in their residual value when the contract is repudiated. This mechanism is qualitatively important to explain stylized facts of firm dynamics and Tobin’s q.

Theory and Evidence

Financial Constraints, Intangible Assets, and Firm Dynamics

Mr. Lev Ratnovski

Yangfan Sun

Nonlocal mortgage lenders with greater exposure to high-growth housing markets accept fewer loan applications in these markets and experience greater stock return volatility. When these lenders expand to high-growth markets, they also ration credit to a significantly greater degree than when they ex-pand to other markets. Mean-variance analyses show that nonlocal lenders’ exposure to high-growth markets is associated with more risk, more efficiency, and more return on mortgage portfolios. Overall, these results imply that expansion to high-growth markets leads to a decline in screening and riskier investment by nonlocal lenders, which may reflect a risk–return tradeoff in their portfolio strategy.

Do Lenders Make Less-Informed Investments in High-Growth Housing Markets?

Mr.Lev Ratnovski

Mr.Anil Ari

This paper presents a new dataset on the dynamics of non-performing loans (NPLs) during 88 banking crises since 1990. The data show similarities across crises during NPL build-ups but less so during NPL resolutions. We find a close relationship between NPL problems—elevated and unresolved NPLs—and the severity of post-crisis recessions. A machine learning approach identifies a set of pre-crisis predictors of NPL problems related to weak macroeconomic, institutional, corporate, and banking sector conditions. Our findings suggest that reducing pre-crisis vulnerabilities and promptly addressing NPL problems during a crisis are important for post-crisis output recovery.

The Dynamics of Non-Performing Loans during Banking Crises: A New Database

Pi-Han Tsai

We jointly estimate credit and fiscal multipliers in China. We use the tenure of the provincial party secretary, interacted with the type of stimulus used in other provinces, to obtain separate instruments for provincial credit and government expenditure. We estimate a fiscal multiplier of 0.8 and a credit multiplier of 0.2 in 2001-2015. The multipliers have changed over time. The fiscal multiplier has increased from 0.75 in 2001-2008 to 1.4 in 2010-2015. The credit multiplier has declined from 0.17 to zero over the same periods. Our results suggest that reducing credit growth in China is unlikely to disrupt output growth, whereas fiscal policy may be effective in supporting macroeconomic adjustment.

Sophia Chen

Books

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