Cookies?
Library Header Image
LSE Research Online LSE Library Services

Structural reforms, animal spirits and monetary policies

De Grauwe, Paul and Ji, Yuemei (2020) Structural reforms, animal spirits and monetary policies. European Economic Review, 124. ISSN 0014-2921

[img] Text (Structural reforms, animal spirits and monetary policies) - Published Version
Available under License Creative Commons Attribution.

Download (2MB)

Identification Number: 10.1016/j.euroecorev.2020.103395

Abstract

We use a New Keynesian behavioral macroeconomic model to analyze how structural reforms affect the economy. There are two types of structural reforms. The first one increases price flexibility; the second one increases competition in the labor market and raises potential output. We find that in a rigid economy business cycle movements are dominated by movements of animal spirits. Increasing price flexibility reduces the power of animal spirits and the boom bust nature of the business cycle. We study the trade-offs between output and inflation volatility faced by the central bank. We find that flexibility improves these trade-offs making it easier for the central bank to stabilize output and inflation.

Item Type: Article
Official URL: https://www.journals.elsevier.com/european-economi...
Additional Information: © 2020 Elsevier B.V.
Divisions: European Institute
Subjects: H Social Sciences > HB Economic Theory
B Philosophy. Psychology. Religion > BF Psychology
H Social Sciences > HJ Public Finance
JEL classification: E - Macroeconomics and Monetary Economics > E1 - General Aggregative Models > E10 - General
E - Macroeconomics and Monetary Economics > E1 - General Aggregative Models > E12 - Keynes; Keynesian; Post-Keynesian
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations; Cycles
Date Deposited: 19 Feb 2020 14:18
Last Modified: 08 Nov 2024 20:33
URI: http://eprints.lse.ac.uk/id/eprint/103502

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics