Capital reallocation

  • 详情 Soft Information Imbalance Is Bad for Fair Credit Allocation
    Using bank-county-year level mortgage application data, we document that minority borrowers are systematically evaluated with less soft information compared to White borrowers within the same bank-county branch. Using variation in local sunshine as an instrument and conducting a series of robustness checks, we show that the soft information imbalance significantly increases the denial gap between minority and White applicants. However, this imbalance does not appear to affect pricing disparities. Further analysis shows that internal capital reallocation to under-resourced bank branches can serve as an effective strategy to reduce soft information imbalances and, thus, promote more equitable credit allocation. Our results highlight that soft information imbalance is an overlooked but significant factor driving disparities against minority borrowers.
  • 详情 The real effect of shadow banking: evidence from China
    We provide firm-level evidence on the real effects of shadow banking in terms of technological innovation. Firm-to-firm entrusted loans, the largest part of the shadow banking sector in China, enhance the borrowers’ innovation output. The effects are more prominent when the borrowers are subject to severer financial constraints, information asymmetry, and takeover exposures. A plausible underlying channel is capital reallocations from less productive but easy-financed lender firms to more innovative but financially less-privileged borrower firms. Our paper suggests that shadow banking helps correct bank credit misallocations and thus serves as a second-best market design in financing the real economy.
  • 详情 The real effects of shadow banking: evidence from China
    We provide firm-level evidence on the real effects of shadow banking in terms of technological innovation. Firm-to-firm entrusted loans, the largest part of the shadow banking sector in China, enhance the borrowers’ innovation output. The effects are more prominent when the borrowers are subject to severer financial constraints, information asymmetry, and takeover exposures. A plausible underlying channel is capital reallocations from less productive but easy-financed lender firms to more innovative but financially less-privileged borrower firms. Our paper suggests shadow banking helps correct bank credit misallocations and thus serves as a second-best market design in financing the real economy
  • 详情 Credit Allocation under Economic Stimulus: Evidence from China
    We study credit allocation across  rms and its real e ects during China's economic stimulus plan of 2009-2010. We match con dential loan-level data from the 19 largest Chinese banks with  rm-level data on manufacturing  rms. We document that the stimulus-driven credit expansion disproportionately favored state-owned rms and  rms with lower average product of capital, reversing the process of capital reallocation towards private  rms that characterized China's high growth before 2008. We argue that implicit government guarantees for state-connected  rms become more prominent during recessions and can explain this reversal.
  • 详情 Household Wealth, Borrowing Capacity and Stock Market: a DSGE-VAR Approach
    Based on a DSGE model embedded with a stock market, we inspect interconnection between China's financial markets and macroeconomic cycles. We find consumption, investment and capacity utilization display significant and positive responses to stock market booms triggered by financial and confidence shocks, however, inflation responds insignificantly. We perceive a counteractive and significant reaction of China's monetary policy rule to credit-to-GDP gap at business cycle frequency. We decompose stock price into fundamental value influenced by the financial shock and speculative bubble driven by the confidence shock, and the confidence shock's contribution to stock price fluctuations is estimated to be about 14.8%. Model validation based on the DSGE-VAR framework indicates no serious structural model misspecification.