Keynesian macroeconomic policy: Theoretical analysis and empirical evidence

Author:

Arestis Philip1,Filho Fernando2,Bittes Terra3

Affiliation:

1. University of Cambridge, UK + University of Basque Country, Spain

2. Federal University of Rio Grande do Sul + National Council for Scientific and Technological Development, Brazil

3. Federal University of ABC, National Council for Scientific and Technological Development, Brazil

Abstract

Investment depends on subjective factors, such as expectations, conventions, and confident animal spirits. In a context of economic instability and crises, economic policy is the main source to support entrepreneurs? expectations and investment. In this sense, macroeconomic policies are capable of affecting effective demand and building a good institutional environment, which is essential to keep the entrepreneurs? expectations confident and promote their animal spirits. Given these propositions, this contribution has two objectives. The first is to develop a Keynesian type of macroeconomic policy able to stimulate investment and effective demand, and, as a result, mitigate unemployment. The idea is to offer alternative macroeconomic policy prescriptions in relation to the New Consensus Macroeconomics one. This proposal aims to establish the role, according to the Post Keynesian view, the logic of operation of each policy, and the proper coordination among these Keynesian macroeconomic policies. The second objective is to present, briefly, relevant empirical evidence of the Post Keynesian macroeconomic policies.

Publisher

National Library of Serbia

Subject

General Economics, Econometrics and Finance

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3