Aggregate Effects of Collateral Constraints ∗ VERY PRELIMINARY VERSION – DO NOT CIRCULATE

This paper provides a quantitative exploration of the aggregate effects of an important source of financing friction, collateral constraints. We develop a general equilibrium model of firm dynamics with collateral constraints and adjustment costs, which we structurally estimate using administrative data on French firms. The model is estimated using the joint firm-level dynamics of capital and labor observed following exogenous shocks to the value of collateral. We find that welfare increases by 5.4% when collateral constraints are removed. 25% of these welfare gains come from an improved allocation of inputs across heterogenous firms; 75% are derived from an aggregate increase in capital. Interestingly, removing collateral constraints has little effect on aggregate employment, as financially constrained firms tend to substitute labor for capital. ∗We are grateful to conference and seminar participants in Berkeley, Capri, HBS, NYU-Stern, Stanford, the LSE, the Chicago Fed, the FED Board for their insightful comments. We warmly thank Toni Whited for sharing her fortran code with us. All errors are our own. †Toulouse School of Economics and CEPR (e-mail: thomas.chaney@gmail.com) ‡Princeton (e-mail: congerhuang@gmail.com) §Berkeley, NBER and CEPR (e-mail: sraer@berkeley.edu) ¶HEC and CEPR (e-mail: thesmar@hec.fr) 1 There is an accumulating body of evidence showing the causal effect of financing frictions on firms’ investment and employment decisions at the micro-level.1 In this paper, we use a quantitative model to investigate the aggregate effects of a pervasive source of financing friction – collateral constraints. Our approach expands on the existing literature by combining several features: (1) we provide clean firm-level evidence that collateral constraints causally affect investment and employment decisions, (2) we use this well-identified relationship to estimate a dynamic model that includes both adjustment costs and collateral constraints, and (3) we nest this model in a general equilibrium framework with heterogenous firms to study aggregate effect of collateral constraints. Our estimated model shows that even in a developed country like France, collateral constraints significantly reduce aggregate welfare. In a counterfactual economy where collateral constraints are removed, we find that aggregate welfare increases by 5.4% relative to its actual level. Of these welfare gains, about a quarter come from the better allocation of inputs among heterogenous firms 2. The remaining welfare gains can be attributed to the fact that the aggregate capital stock increases when firms become unconstrained. Importantly, we find that the removal of collateral constraints has little effect on aggregate employment: collateral constrained firms typically substitute labor for capital since labor requires less up-front financing; when the financing constraint is removed, these previously constrained firms grow by expanding their capital to labor ratio, which leaves the aggregate stock of labor used in equilibrium almost unchanged. The paper starts by documenting how, at the firm-level, capital and labor respond to shocks to collateral values. Since real estate is a sizeable asset on firms’ balance sheet, our empirical strategy uses variations in local real estate prices as shocks to the collateral value available to land-holding firms. Precisely, we measure how firms’ investment and hiring decisions respond to each additional dollar of real estate that the firm actually owns. Because variations in local house prices may simply reflect changing investment opportunities or demand shocks, we benchmark 1See, among many others, Lamont (1997), Rauh (2006), Chaney et al. (2012a), Blanchard et al. (1994) for the effect of financial frictions on investment and Benmelech et al. (2010) or Chodorow-Reich (2013) for the effect of financial frictions on employment 2These gains from the reallocation of input in the economy are the focus of Hsieh and Klenow (2009), Moll (2014), Midrigan and Xu (2014)