Gianmarco Ruzzier

Many borrowers do not refinance even when doing so would lower their payments. We show that this is partly driven by a lender-side friction: the difficulty of valuing a house, or collateral uncertainty, restricts refinancing. Using loan performance and property records, we find that borrowers refinance less where homes are harder to value, even when refinancing would yield net savings. Mortgage application data show that greater uncertainty about local home values predicts a higher likelihood that lenders turn down a refinance application. In these markets, refinance appraisals rely on fewer and more distant comparable sales, making valuations less precise. Foreclosed homes also sell at larger discounts, pointing to weaker recovery in default. When mortgage rates fall, borrowers are less likely to refinance where homes are harder to value, leaving substantial savings unrealized.

Shadow banks’ share of U.S. mortgage lending has risen substantially, while their expansion has varied widely across local markets. We study whether uncertainty about property values shapes this geographic pattern by making mortgages costlier to sell. Using mortgage and property data, we find that shadow banks have lower local market shares and expand more slowly in higher-uncertainty areas, even among conventional loans below the conforming loan limit. Application data link this pattern to lenders’ decisions: denial rates rise more with uncertainty for shadow banks than for banks, with the difference concentrated in refinancing. Consistent with a role for balance-sheet capacity, denial responses are stronger among more sale-dependent shadow banks. We also find evidence consistent with higher distribution costs in higher-uncertainty markets: less use of appraisal alternatives, greater repurchase risk and longer times to sale. Collateral uncertainty constrains shadow-bank expansion and preserves a local role for balance-sheet lending.

We develop a model with firm dynamics, imperfect competition, and investment options. Firms borrow using credit lines offered by competitive lenders that can optimally provide “zombie” lending, with an interest rate below the risk free rate. We solve and calibrate the model and show that zombie lending is used in equilibrium to subsidise two very different types of firms: “Stagnant zombies” previously borrowed to fund projects that are no longer feasible. They are offered zombie lending so that they can gradually reduce their debt and avoid default. “High-potential zombies” have options to invest in projects that can increase their profitability, and borrow to pursue them. Zombie lending “buys them more time”, in the hope they will become more profitable in the future and will thus be able to repay the debt. The main insight of the model is that while both types of zombie firms are consistent with the way such firms are usually identified in the empirical literature, they have opposite implications for misallocation and aggregate productivity and welfare. We use the model to propose novel criteria to identify the different zombie types and new testable predictions of their allocative effects: an increase in markup dispersion within industries should increase the share of zombie firms and the share of zombies that in the future recover and reach top quartile performance; sectors where zombies behave like high-potential ones should exhibit positive TFP responses to zombie prevalence, while those dominated by stagnant zombies should show declining productivity. Using firm-level data from Italian firms between 2007–2016, we provide robust empirical evidence confirming these predictions.

Using granular bank-firm data from the Spanish credit register and U.S. syndicated loans, I examine the impact of banks' sectoral specialization on credit supply decisions in response to monetary policy shocks. Following an expansionary monetary policy, banks significantly increase lending to firms in sectors where they specialize. A 25 basis point rate reduction leads specialized banks to increase credit by 1.2–1.4 percentage points more to firms in their sectors of expertise, with effects peaking after one year. This result holds across both the Spanish lending market and the U.S. syndicated one. The mechanism operates through information advantages: the specialization effect is stronger for opaque borrowers, and specialized banks experience lower default rates following monetary easing. These supply decisions have real effects, as firms with greater exposure to specialized lenders exhibit larger increases in investment and profitability during expansionary periods. The findings show that monetary policy transmission varies systematically across sectors depending on the distribution of bank specialization.