Subtopic Deep Dive
Economic Policy Uncertainty Measurement
Research Guide
What is Economic Policy Uncertainty Measurement?
Economic Policy Uncertainty Measurement quantifies ambiguity in government economic policies using text-based indices from newspapers and forecast disagreements, linking it to market volatility and investment.
Scott Baker, Nicholas Bloom, and Steven J. Davis introduced the EPU index in 2016 based on newspaper coverage frequency, validated by human readings of 12,000 articles (10987 citations). Extensions measure COVID-19 induced uncertainty via stock volatility and news (Baker et al., 2020, 1490 citations). Studies apply these indices to asset pricing and fiscal shocks (Brogaard and Detzel, 2015, 1307 citations).
Why It Matters
EPU indices reveal how policy ambiguity amplifies stock market reactions during crises like COVID-19, as shown by Baker et al. (2020) with text-based measures linking uncertainty to unprecedented volatility (1424 citations). Central banks use these to assess transmission to economic activity, per Fernández-Villaverde et al. (2015) on fiscal volatility shocks (907 citations). Investors apply them for asset pricing, with Brogaard and Detzel (2015) finding EPU predicts returns. Baker et al. (2020) quantify US uncertainty spikes guiding policy responses.
Key Research Challenges
Index Construction Noise
Newspaper-based EPU indices suffer from media bias and selection effects, as human validation of 12,000 articles shows proxy limitations (Baker et al., 2016). Time-varying volatility in fiscal processes adds estimation errors (Fernández-Villaverde et al., 2015). Refining TVP-VAR connectedness measures requires handling structural breaks (Antonakakis et al., 2020).
Causal Identification
Distinguishing policy uncertainty from general uncertainty challenges VAR structural inference (Stock and Watson, 2001). COVID-era spikes confound EPU with pandemic shocks, needing wavelet decompositions for nexus analysis (Sharif et al., 2020). Financial frictions propagate effects ambiguously (Gilchrist et al., 2014).
Dynamic Propagation Modeling
TVP-VAR models capture time-varying connectedness but demand high computational variance-covariance estimation (Antonakakis et al., 2020). Linking EPU to firm-level exposures like climate risk requires scalable text analysis (Sautner et al., 2023). Global factors complicate quantile regressions for spillovers (Mensi et al., 2014).
Essential Papers
Measuring Economic Policy Uncertainty*
Scott Baker, Nicholas Bloom, Steven J. Davis · 2016 · The Quarterly Journal of Economics · 11.0K citations
Abstract We develop a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency. Several types of evidence—including human readings of 12,000 newspaper articles—indicate ...
COVID-Induced Economic Uncertainty
Scott Baker, Nicholas Bloom, Steven J. Davis et al. · 2020 · 1.5K citations
Assessing the economic impact of the COVID-19 pandemic is essential for policymakers, but challenging because the crisis has unfolded with extreme speed.We identify three indicators -stock market v...
The Unprecedented Stock Market Reaction to COVID-19
Scott Baker, Nicholas Bloom, Steven J. Davis et al. · 2020 · The Review of Asset Pricing Studies · 1.4K citations
Abstract No previous infectious disease outbreak, including the Spanish Flu, has affected the stock market as forcefully as the COVID-19 pandemic. In fact, previous pandemics left only mild traces ...
COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach
Arshian Sharif, Chaker Aloui, Larisa Yarovaya · 2020 · International Review of Financial Analysis · 1.4K citations
The Asset-Pricing Implications of Government Economic Policy Uncertainty
Jonathan Brogaard, Andrew L. Detzel · 2015 · Management Science · 1.3K citations
Using the news-based measure of Baker et al. [Baker SR, Bloom N, Davis SJ (2013) Measuring economic policy uncertainty. Working paper, Stanford University, Stanford, CA] to capture economic policy ...
Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions
Nikolaos Antonakakis, Ioannis Chatziantoniou, David Gabauer · 2020 · Journal of risk and financial management · 1.3K citations
In this study, we enhance the dynamic connectedness measures originally introduced by Diebold and Yılmaz (2012, 2014) with a time-varying parameter vector autoregressive model (TVP-VAR) which predi...
Vector Autoregressions
James H. Stock, Mark W. Watson · 2001 · The Journal of Economic Perspectives · 1.1K citations
This paper critically reviews the use of vector autoregressions (VARs) for four tasks: data description, forecasting, structural inference, and policy analysis. The paper begins with a review of VA...
Reading Guide
Foundational Papers
Start with Baker, Bloom, Davis (2016) for EPU index construction, then Stock and Watson (2001) for VAR methods underpinning propagation analysis, followed by Gilchrist et al. (2014) on uncertainty frictions.
Recent Advances
Study Baker et al. (2020) on COVID uncertainty, Sharif et al. (2020) wavelet nexus, and Antonakakis et al. (2020) TVP-VAR connectedness for current dynamics.
Core Methods
Text-based newspaper parsing (Baker et al., 2016), time-varying parameter VARs (Antonakakis et al., 2020), structural inference via reduced-form VARs (Stock and Watson, 2001).
How PapersFlow Helps You Research Economic Policy Uncertainty Measurement
Discover & Search
Research Agent uses searchPapers and exaSearch to find Baker et al. (2016) EPU index papers, then citationGraph reveals 10,000+ citations linking to Brogaard and Detzel (2015) asset pricing applications, while findSimilarPapers uncovers COVID extensions like Baker et al. (2020).
Analyze & Verify
Analysis Agent applies readPaperContent to extract EPU construction from Baker et al. (2016), verifies index validity via verifyResponse (CoVe) against human readings data, and runs PythonAnalysis with TVP-VAR code from Antonakakis et al. (2020) for GRADE-graded statistical replication of connectedness measures.
Synthesize & Write
Synthesis Agent detects gaps in EPU propagation models post-COVID, flags contradictions between VAR inferences (Stock and Watson, 2001), while Writing Agent uses latexEditText, latexSyncCitations for Baker et al. papers, and latexCompile to generate volatility diagrams via exportMermaid.
Use Cases
"Replicate TVP-VAR connectedness from Antonakakis et al. 2020 on EPU data"
Research Agent → searchPapers('TVP-VAR EPU') → Analysis Agent → runPythonAnalysis(NumPy/pandas TVP-VAR sandbox) → outputs replicated connectedness plot and CSV of dynamic spillovers.
"Draft LaTeX section on EPU asset pricing effects with citations"
Research Agent → citationGraph(Baker 2016) → Synthesis Agent → gap detection → Writing Agent → latexEditText + latexSyncCitations(Brogaard Detzel 2015) + latexCompile → outputs compiled PDF section with EPU-return regressions table.
"Find GitHub code for Baker EPU index replication"
Research Agent → paperExtractUrls(Baker 2016) → Code Discovery → paperFindGithubRepo → githubRepoInspect → outputs verified Python scraper for newspaper EPU index building.
Automated Workflows
Deep Research workflow conducts systematic review of 50+ EPU papers via searchPapers → citationGraph → structured report on volatility links. DeepScan applies 7-step CoVe analysis: readPaperContent(Baker 2020) → verifyResponse → runPythonAnalysis on COVID uncertainty spikes. Theorizer generates hypotheses on fiscal-EPU channels from Stock-Watson VAR critiques.
Frequently Asked Questions
What defines Economic Policy Uncertainty Measurement?
It quantifies policy ambiguity via newspaper text frequency and forecast dispersion, as in Baker, Bloom, Davis (2016) EPU index validated on 12,000 articles.
What are core methods in EPU measurement?
Newspaper keyword counts for EPU (Baker et al., 2016), TVP-VAR for dynamic connectedness (Antonakakis et al., 2020), and structural VARs for propagation (Stock and Watson, 2001).
What are key papers?
Baker et al. (2016, 10987 citations) introduces EPU index; Brogaard and Detzel (2015, 1307 citations) links to asset pricing; Baker et al. (2020, 1490 citations) covers COVID uncertainty.
What open problems exist?
Refining media bias in indices, causal separation from general uncertainty, and scaling to firm-level via machine learning keywords (Sautner et al., 2023).
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Part of the Market Dynamics and Volatility Research Guide