scholarly journals Credit-Market Sentiment and the Business Cycle*

2017 ◽  
Vol 132 (3) ◽  
pp. 1373-1426 ◽  
Author(s):  
David López-Salido ◽  
Jeremy C. Stein ◽  
Egon Zakrajšek

Abstract Using U.S. data from 1929 to 2015, we show that elevated credit-market sentiment in year t − 2 is associated with a decline in economic activity in years t and t + 1. Underlying this result is the existence of predictable mean reversion in credit-market conditions. When credit risk is aggressively priced, spreads subsequently widen. The timing of this widening is, in turn, closely tied to the onset of a contraction in economic activity. Exploring the mechanism, we find that buoyant credit-market sentiment in year t − 2 also forecasts a change in the composition of external finance: net debt issuance falls in year t, while net equity issuance increases, consistent with the reversal in credit-market conditions leading to an inward shift in credit supply. Unlike much of the current literature on the role of financial frictions in macroeconomics, this article suggests that investor sentiment in credit markets can be an important driver of economic fluctuations.

2015 ◽  
Author(s):  
David Lopez-Salido ◽  
Jeremy C. Stein ◽  
Egon Zakrajsek

2016 ◽  
Author(s):  
David López-Salido ◽  
Jeremy Stein ◽  
Egon Zakrajšek

2014 ◽  
Vol 20 (3) ◽  
pp. 845-855 ◽  
Author(s):  
Pei Kuang

This paper introduces imperfect knowledge and learning behavior of economic agents into the Kiyotaki and Moore model and studies the interaction of agents' collateral price beliefs, collateral constraint, and aggregate economic activity over the business cycle. It establishes the E-stability condition and the convergence of the real time learning process. In addition, it shows that learning strengthens the role of collateral constraints in aggregate fluctuations.


2017 ◽  
Vol 22 (7) ◽  
pp. 1769-1789 ◽  
Author(s):  
Luca Agnello ◽  
Vitor Castro ◽  
Ricardo M. Sousa

In this paper, we assess the characteristics of the housing market and its main determinants. Using data for 20 industrial countries over the period 1970Q1–2012Q2 and a discrete-time Weibull duration model, we find that the likelihood of the end of a housing boom or a housing bust increases over time. Additionally, we show that the different phases of the housing market cycle are strongly dependent on the economic activity, but credit market conditions are particularly important in the case of housing booms. The empirical findings also indicate that although housing booms have similar lengths in European and non-European countries, housing busts are typically shorter in European countries. The use of a more flexible specification for the hazard function that is based on cubic splines suggests that it evolves in a nonlinear way. From a policy perspective, our study can be useful for predicting the timing and the length of housing boom–bust cycles. Moreover, it highlights the importance of monetary policy by influencing lending rates and affecting the likelihood of occurrence of housing booms.


2014 ◽  
Vol 69 (3) ◽  
pp. 1377-1409 ◽  
Author(s):  
R. DAVID MCLEAN ◽  
MENGXIN ZHAO

2016 ◽  
Vol 22 (2) ◽  
pp. 279-306 ◽  
Author(s):  
Manoj Atolia ◽  
John Gibson ◽  
Milton Marquis

We examine the quantitative significance of financial frictions that reduce firms' access to credit in explaining asymmetric business cycles characterized by disproportionately severe downturns. Using rate spread data to calibrate the severity of these frictions, we successfully match several key features of U.S. data. Specifically, although output and consumption are relatively symmetric (with output being slightly more asymmetric), investment and hours worked display significant asymmetry over the business cycle. We also demonstrate that our financial frictions are capable of significantly amplifying adverse shocks during severe downturns. Although the data suggest that these frictions are only active occasionally, our results indicate that they are still a significant source of macroeconomic volatility over the business cycle.


Author(s):  
David Lopez-Salido ◽  
Jeremy C. Stein ◽  
Egon Zakrajsek

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