Online Appendix for “The Macroeconomics of Shadow Banking”

This document contains additional results for the paper “The Macroeconomics of Shadow Banking.” These results include robustness to alternative parameter values, evidence on the composition of the liquidity supply over the 2003–2015 cycle, and extensions for analyzing liquidity requirements and equity issuance costs. ∗Yale University School of Management, [email protected]. †New York University Stern School of Business and NBER, [email protected]. 1 Robustness to alternative parameter values To provide further support for our results, we explore robustness to alternative parameter values. The benchmark parameters are listed in Table 1 in the paper. We focus on the parameters that are unique to our setting, those governing crash exposure, the information sensitivity constraint, and liquidity events. Whenever we change a given parameter, we adjust the subjective discounting parameter ρ to keep the overall discount rate in the case where wealth is fully liquid constant at 1.6%. Doing so allows us to compare across economies without changing the rate at which investors discount the future in the absence of frictions. The results of the model under alternative parameters are presented in Figure A.1. We keep the capital mix χ at 0.95, which is close to its unconditional steady state. The first column of panels shows shadow money issuance and the second and third column show the prices of the two assets. In the first row of panels we vary the crash exposure of the risky asset κa k , which controls the exogenous component of the supply of collateral in the economy. A higher κa k (less collateral) leads to more shadow money issuance at low uncertainty. This occurs because shadow money is ideally suited to producing liquidity with limited collateral and because investors are only willing to hold shadow money at low uncertainty. Less collateral means less overall liquidity, however, which brings down asset prices, in particular the price of the risky asset a. The price of the safe asset b actually rises as the collateral it carries becomes more scarce. Higher κa k also increases the uncertainty exposure of asset prices. Overall, κa k illustrates the important role of collateral scarcity in the model. The second row of panels in Figure A.1 varies the tightness of the information sensitivity constraint on fragile-liquid securities, which is set by the crash exposure bound κ. This parameter affects the collateral advantage of shadow money. When κ is high, shadow money can produce a lot of liquidity with only a little collateral. This means that at low uncertainty a small amount of shadow money can cover the crash exposure of the balance sheet, leaving more collateral for money. It also means that as uncertainty rises shadow banking takes longer to shut down. Both effects expand liquidity provision, which leads to a higher price for the risky asset a and a lower price for the safe asset b. Next, we change ψ, the marginal utility of investors in a liquidity event. Since ψ enters all expressions in tandem with the intensity of liquidity events h as the term h (ψ− 1), this experiment is also equivalent to changing h. When ψ is high, liquidity is very valuable at the margin, and so discount rates become more sensitive to changes in liquidity. This is why even though shadow money issuance is relatively unaffected, asset prices show large