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metadata language: English

The Use of Long-Run Restrictions for the Identification of Technology Shocks

Version
v1
Resource Type
Dataset : survey data
Creator
  • Francis, Neville R. (Lehigh University)
  • Owyang, Michael T. (Federal Reserve Bank of St. Louis)
  • Theodorou, Athena T. (Federal Reserve Bank of St. Louis)
Other Title
  • Version 1 (Subtitle)
Publication Date
2004-08-12
Language
English
Description
  • Abstract

    The authors survey the recent empirical literature using long-run restrictions to identify technology shocks and provide an illustrative walk-through of the long-run restricted vector autoregression (VAR) methodology in a bivariate framework. Additionally, they offer an alternative identification of technology shocks that can be imposed by restrictions on the long-run impulse responses to evaluate the robustness of the conclusions drawn by the structural VAR literature. Their results from this methodology compare favorably with the empirical literature that uses structural VARs to identify technology shocks.
  • Table of Contents

    Datasets:

    • DS1: Dataset
Collection Mode
  • The file provided is the data and program file 0311nf.xls. These data are part of ICPSR's Publication-Related Archive and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.

Availability
Download
This study is freely available to the general public via web download.
Alternative Identifiers
  • 1286 (Type: ICPSR Study Number)
Publications
  • Francis, Neville R., Owyang, Michael T., Theodorou, Athena T.. The Use of Long-Run Restrictions for the Identification of Technology Shocks. Federal Reserve Bank of St. Louis Review.85, (6), 53-66.2003.

Update Metadata: 2015-08-05 | Issue Number: 6 | Registration Date: 2015-06-15

Francis, Neville R.; Owyang, Michael T.; Theodorou, Athena T. (2004): The Use of Long-Run Restrictions for the Identification of Technology Shocks. Version 1. Version: v1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/ICPSR01286.v1