Journal of Money Credit and Banking最新文献

Many studies using quantile regressions (QRs) have found that downside risk to output growth varies more than upside risk. We show that Bayesian vector autoregressions (BVARs) with stochastic volatility are able to capture tail risks in forecast distributions. Even though the one-step-ahead conditional predictive distributions from the conventional stochastic volatility specification are symmetric, forecasts of downside risks to output growth are more variable than upside risks, and the reverse applies in the case of inflation and unemployment. Overall, BVAR models perform comparably to QR for estimating and forecasting tail risks, complementing BVARs' established performance for forecasting and structural analysis.

This paper constructs a survey-based measure capturing the evolution of market's expectations of the Federal Reserve's Large-Scale Asset Purchases (LSAP) program during 2008–18, and examines the transmission mechanism of unconventional monetary policy. Estimation results suggest that both signaling and portfolio balance channels of the LSAP were important in lowering long-term interest rates; Moreover, the Federal Reserve's forward guidance policy had led to a gradual extension of market's projections of the duration of the LSAP, making its effects more persistent. Model estimation also explains the 2013 taper tantrum well, and suggests that the LSAP's effects might have declined during QE III.

We assess how financial development affects innovation. For this purpose, we employ a unique Research Quotient data set from 1980 to 2018, and observe significant inverted-U effects of financial development on innovation for equity and credit markets. Specifically, the effects of the markets are sector-specific, implying that the inverted-U effect of the equity market on innovation is mainly driven by its diminishing effect on innovation in high-technology industries, while credit markets mostly affect innovation in non-high-technology industries. Regarding the mechanism, we posit that the inverted-U shape between finance and innovation may be explained by the disproportionate funds allocation-induced market concentration.

We evaluate the forecasting ability of several popular measures of uncertainty. We construct new real-time versions of both macro-economic and financial uncertainty, and analyze them together with their ex post counterparts. We find some explanatory power in all uncertainty measures, with relatively good performance by ex post macro-economic and financial uncertainty. However, real-time versions perform only about as well as other uncertainty measures such as economic policy uncertainty (EPU), a finding we relate to data revisions in the construction of ex post uncertainty. Real-time data and estimation considerations are highly consequential, owing to look-ahead bias. Real-time uncertainty forecasts real-time outcome variables better than it forecasts ex post revised outcome variables.

This paper contributes to and extends our current understanding of information frictions in expectations. I first propose a new framework for estimating noisy information using individual forecasts. I further extend this framework to incorporate misperceptions on the part of economic agents about the persistence of the underlying process being forecasted. Applying this framework to the U.S. inflation, forecasts of professional forecasters suggest a systematic overestimation on the part of forecasters of the persistence of inflation in addition to the presence of noisy signals. Using a structural model that incorporates both noisy signals and misperceptions of persistence, I quantify the relative importance of each channel in accounting for the expectations formation process of these agents. The results indicate that, even for professional forecasters, there are multiple forces that generate economically significant deviations from full information.

What happens when banks compete with deposit and loan contracts contingent on macro-economic shocks? The private sector insures the banking system efficiently against crises through such contracts when failing banks go bankrupt. When risks are large, banks may shift part of the risk to depositors who receive state-contingent contracts. In contrast, when failing banks are rescued, new phenomena such as risk magnification emerge. Depositors receive noncontingent contracts, while loan contracts demand high repayment in good times and low repayment in bad times. Banks overinvest and generate large macro-economic risks, even if the underlying productivity risk is small or zero.

Using supervisory data on small and midsized nonfinancial enterprises (SMEs), we find that those SMEs with higher leverage faced tighter constraints in accessing bank credit after the COVID-19 outbreak in spring 2020. Specifically, SMEs with higher pre-COVID leverage obtained a smaller volume of new loans and had to pay a higher spread on them during the pandemic period. Consistent with an inward shift in loan supply, these effects were concentrated in loans originated by banks with below-median capital buffers. Highly levered SMEs that relied on low-capital large banks for funding before the pandemic were not able to substitute to other sources of debt financing and thus experienced more of a reduction in total debt as well as a decline in investment and employment. On the other hand, the unprecedented public support, especially the Paycheck Protection Program (PPP), mitigated the adverse real effect stemming from bank credit constraints.

In a business cycle model with endogenous firms' dynamics and debt renegotiation, we show that during financial crises loan forbearance does not harm the economy unless banks imperfectly monitor loans, and loan opacity worsens banks' moral hazard problem. Aggressive interest rate reductions and quantitative easing limit defaults and financial crisis-induced output contractions without hampering the entry of new firm entries. The decline in the natural interest rate, due to slower productivity growth and persistent liquidity shocks, potentially explains the observed long-term trend in nonperforming loan shares.

We estimate a New Keynesian model incorporating two notable features: bounded rationality and the zero lower bound on the nominal interest rate. Our Bayesian estimation of a nonlinear model shows that the model with bounded rationality better fits the U.S. data than its rational expectations counterpart, and that both households and firms exhibit a substantial degree of bounded rationality. Moreover, we demonstrate that bounded rationality expands a parameter region in which the model can be estimated and weakens the power of forward guidance.

We analyze the gross worker flows over the life cycle by constructing a quantitative general equilibrium model. Using U.S. data, we first document the life-cycle patterns of flows across different labor market states (employment, unemployment, and not in the labor force), as well as job-to-job transitions. We then build a model of the aggregate labor market that incorporates the life cycle of workers, consumption-saving decisions, and labor market frictions. We estimate the model and use it to examine the effects of policies on aggregate labor market outcomes. In particular, we analyze a taxes-and-transfers policy and an unemployment insurance policy.