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Name File Type Size Last Modified
  data 04/25/2020 09:47:AM
  empirics_main_text 04/25/2020 09:47:AM
  models 04/25/2020 09:47:AM
  online_appendix 04/25/2020 09:47:AM
readme-openicpsr-118082.pdf application/pdf 323.7 KB 04/25/2020 05:47:AM

Project Citation: 

Angeletos, Marios, Collard, Fabrice, and Dellas, Harris. Data and Code for: Business Cycle Anatomy. Nashville, TN: American Economic Association [publisher], 2020. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-09-24. https://doi.org/10.3886/E118082V1

Project Description

Summary:  View help for Summary We propose a new strategy for dissecting the macroeconomic time series, provide a template for the business-cycle propagation mech- anism that best describes the data, and use its properties to ap- praise models of both the parsimonious and the medium-scale va- riety. Our findings support the existence of a main business-cycle driver but rule out the following candidates for this role: technology or other shocks that map to TFP movements; news about future productivity; and inflationary demand shocks of the textbook type. Models aimed at accommodating demand-driven cycles without a strict reliance on nominal rigidity appear promising.


Scope of Project

Subject Terms:  View help for Subject Terms Business Cycle; VectorAutoregression; Shocks
JEL Classification:  View help for JEL Classification
      C32 Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
      E32 Business Fluctuations; Cycles
Geographic Coverage:  View help for Geographic Coverage United States
Time Period(s):  View help for Time Period(s) 1955 – 2017

Methodology

Data Source:  View help for Data Source Federal Reserve Economic Database

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