The Inverted Leading Indicator Property and Redistribution Effect of the Interest Rate

44 Pages Posted: 9 Dec 2016 Last revised: 5 Jan 2019

See all articles by Patrick Pintus

Patrick Pintus

Aix-Marseille University and CNRS

Yi Wen

Federal Reserve Bank of St. Louis - Research Department; Tsinghua University

Xiaochuan Xing

Tsinghua University

Multiple version iconThere are 2 versions of this paper

Date Written: 2016-11-30

Abstract

The interest rate at which US firms borrow funds has two features: (i) it moves in a countercyclical fashion and (ii) it is an inverted leading indicator of real economic activity: low interest rates today forecast future booms in GDP, consumption, investment, and employment. We show that a Kiyotaki-Moore model accounts for both properties when interest-rate movements are driven, in a significant way, by self-fulfilling shocks that redistribute income away from lenders and to borrowers during booms. The credit-based nature of such self-fulfilling equilibria is shown to be essential: the dynamic correlation between current loanable funds rate and future aggregate economic activity depends critically on the property that the interest rate is state-contingent. Bayesian estimation of our benchmark DSGE model on US data shows that the model driven by redistribution shocks results in a better fit to the data than both standard RBC models and Kiyotaki-Moore type models with unique equilibrium.

Keywords: Endogenous Collateral Constraints, State-Contingent Loan Repayment, Redistribution Shocks, Multiple Equilibria.

JEL Classification: E21, E22, E32, E44, E63

Suggested Citation

Pintus, Patrick and Wen, Yi and Xing, Xiaochuan, The Inverted Leading Indicator Property and Redistribution Effect of the Interest Rate (2016-11-30). FRB St. Louis Working Paper No. 2016-27, Available at SSRN: https://ssrn.com/abstract=2882439 or http://dx.doi.org/10.20955/wp.2016.027

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Yi Wen

Federal Reserve Bank of St. Louis - Research Department ( email )

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Tsinghua University ( email )

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China

Xiaochuan Xing

Tsinghua University

Beijing, 100084
China

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