Combining Proxies and Narrative Sign Restrictions
Revisiting the Effects of Technology Shocks
Bibliographic Data
| ID | 21653500 |
|---|---|
| Authors | Yang Yang (0000-0002-3705-7612, School of Finance Zhongnan University of Economics and Law Wuhan China), Ren Zhang (0000-0002-1620-5620, McCoy College of Business Texas State University San Marcos Texas United States, corresponding author) |
| Year | 2025 |
| Volume | 40 |
| Issue | 5 |
| Pages | 554-568 |
| Publication date | 2025-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Applied Econometrics (JOURNAL) |
| Journal identifiers | ISSN: 1099-1255 • E-ISSN: 0883-7252 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/jae.3129 |
| OpenAlex | W4410247171 |
| Language | EN |
| References cited | 37 |
This paper proposes a novel integration of the proxy structural vector autoregression approach with narrative sign restrictions to identify multiple shocks with multiple instrumental variables. We show that this combination leads to informative inferences on shock effects through both analytical demonstrations and Monte Carlo simulations. Applying this method to identify anticipated and unanticipated technology shocks, we find that anticipated shocks account for over 45% of stock price variation but only about 13% of total factor productivity (TFP) fluctuations. The majority of TFP variations are driven by unanticipated technology shocks and measurement errors
Econometrics · Economics · Macroeconomics · Monte Carlo method · Productivity · Statistics · Total factor productivity · Vector autoregression · Financial Markets and Investment Strategies · Market Dynamics and Volatility · Mathematics · Monetary Policy and Economic Impact
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| Citation velocity | historical |
|---|---|
| Highly cited | No |