Subsidies should target firms with profitable opportunities and insufficient funding, but this is difficult due to information asymmetry between firms and the government. We study how credit history of firms can help design more efficient subsidies. To this end, we combine data on non-repayable firm subsidies and the credit registry from Hungary. Using subsidy winners and losers as treated and control groups and leveraging variation in access to loans, we identify the differential impact of subsidies. While subsidies lead to an incremental impact on assets of loan-deprived as compared to loan-acquiring firms, the impact is transitory and fades after a few years. The impact on profitability follows a similar pattern despite the higher expected marginal value of capital for loan-deprived firms. Thus, loan deprivation is likely caused by borrower shortcomings instead of credit rationing by banks. In such cases, subsidies need not target loan-deprived firms.

Capturing financial network linkages and contagion in stress test models are important goals for banking supervisors and central banks responsible for micro- and macroprudential policy. However, granular data on financial networks is often lacking, and instead the networks must be reconstructed from partial data. In this paper, we conduct a horse race of network reconstruction methods using network data obtained from 25 different markets spanning 13 jurisdictions. Our contribution is two-fold: first, we collate and analyze data on a wide range of financial networks. And second, we rank the methods in terms of their ability to reconstruct the structures of links and exposures in networks.