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Measuring Economic Policy Uncertainty Scott R. Baker (Northwestern) Nick Bloom (Stanford & NBER) Steve Davis (Chicago & NBER) AEA, January 2015.

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Presentation on theme: "Measuring Economic Policy Uncertainty Scott R. Baker (Northwestern) Nick Bloom (Stanford & NBER) Steve Davis (Chicago & NBER) AEA, January 2015."— Presentation transcript:

1 Measuring Economic Policy Uncertainty Scott R. Baker (Northwestern) Nick Bloom (Stanford & NBER) Steve Davis (Chicago & NBER) AEA, January 2015

2 This paper tries to investigate two questions Uncertainty: Does policy uncertainty matter? News: Can text search create data (back to 1880s)? 2

3 We approach policy uncertainty methodically 1) Measuring policy uncertainty 2) Evaluating our measure 3) Estimating the impact of policy uncertainty

4 Our policy uncertainty index is based on computer search of Newspapers For 10 major US papers get monthly counts of articles with: {economic or economy}, and {uncertain or uncertainty}, and {regulation or deficit or federal reserve or congress or legislation or white house} Divide the count for each month by the count of all articles Normalize each to SD=1, then sum all 10 papers to get the U.S monthly index

5 Newspapers: Boston Globe Chicago Tribune Dallas Morning News Los Angeles Times Miami Herald New York Times SF Chronicle USA Today Wall Street Journal Washington Post 5 Note: We use Access World News Newsbank Service when constructing a daily EPU Index, because the daily index requires a higher density of news sources. Constructing our US News-Based EPU Index

6 US News-based policy uncertainty index: Jan 1985-Aug 2014 Source: “Measuring Economic Policy Uncertainty” by Scott R. Baker, Nicholas Bloom and Steven J. Davis, all data at Data normalized to 100 prior to Gulf War I 9/11 Clinton- Election Gulf War II Bush Election Stimulus Debate Lehman and TARP Euro Crisis and 2010 Midterms Russian Crisis/LTCM Debt Ceiling; Euro Debt Black Monday Fiscal Cliff Shutdown

7 Note: Analysis uses Newsbank coverage of around 1000 US national and local newspapers See Table 1 in the Baker, Bloom and Davis (2013) for a more detailed analysis. Category EPU analysis – look for category terms alongside our economic policy uncertainty terms

8 Notes: Index of Policy-Related Economic Uncertainty composed of quarterly news articles containing uncertain or uncertainty, economic or economy, and policy relevant terms (scaled by the total number of articles) in 6 newspapers (WP, BG, LAT, NYT, WSJ and CHT). Data normalized to 100 from Can run the index back to 1900 using 6 newspapers (Jan 1900 – Dec 2012) Policy Uncertainty Index Versailles conference 9/11 and Gulf War II Debt Ceiling OPEC II Lehman and TARP Great Depression, New Deal and FDR Truman- Dewey election Great Depression Relapse Gulf War I Black Monday Start of WW I OPEC I Asian Fin. Crisis Watergate Assassination of McKinley Gold Standard Act Berlin Conference McNary Haughen farm bill

9 India Economic Policy Uncertainty Index India Based Policy Uncertainty Index Exchange Rate Fluctuations and Worry Lokpal Bill Source: Data from 7 Indian newspapers (Economic Times, Times of India, Hindustan Times, Hindu, Statesman, Indian Express, and Financial Express)www.policyuncertainty.com Congress Party wins National Election Bear Sterns Lehman Bros India-US Nuclear Deal Price Hikes

10 China Economic Policy Uncertainty Index China Based Policy Uncertainty Index 9/11 Political Transition and new National Congress Rising Interest Rates Inflation and Export Pressure Eurozone Fears and Protectionism China Stimulus China Deflation and Deficit Source: Data until August Based on newspaper articles from the South China Morning Post.www.policyuncertainty.com

11 North Korean Economic Policy Uncertainty Index Policy Uncertainty Index Source: Data from 0 North Korean newspaperswww.policyuncertainty.com

12 Orange Revolution in Ukraine Duma elections and protests against election fraud Kizlyar hostage crisis; PM Chubais resigns Constitutional Crisis Russian financial crisis First Chechen War Second Chechen War Acting PM Gaidar resigns Russian military exits Chechnya Timoshenko resigns; Terror attack in Nalchik Parliament dismissed In Ukraine Terror attacks in Nalchik & Stavropol Medveded election Putin becomes PM Lehman Brothers Failure Ukraine Conflict Taper Tantrum Putin election Kiev Euromaidan; Crimea annexation 12 Russian Economic Policy Uncertainty Index (beta) Source: Data from Kommersant daily newspaper ( )

13 We approach policy uncertainty methodically 1) Measuring policy uncertainty 2) Evaluating our measure 3) Estimating the impact of policy uncertainty 4) Why policy uncertainty changes over time

14 A) Market Use Market suggests informational value in the data I) We have also tracked numerous institutions using the data like Goldmans, Citibank, JP Morgan, Blackrock, Wells Fargo, IMF, Fed, ECB etc (see II) This has led Bloomberg, FRED, Reuters and Haver to stream the data for their financial and policy users

15 VIX (red) Economic Policy Uncertainty Index (Blue) /11 WorldCom & Enron Gulf War II Credit Crunch Asian crisis Gulf War I Obama Election, Banking Crisis Debt Ceiling LTCM default B) Comparison: stock market implied volatility (the VIX) Correlation 1-month VIX and EPU index = 0.55 Correlation 10-year VIX synthetic and EPU index = 0.73 Large interest rate cuts Clinton election Source: Data until October 2012www.policyuncertainty.com

16 C) Running Detailed Human Audits 10 undergraduates read ≈ 9,098 newspaper articles to date using a 63-page audit guide to code articles if they discuss “economic uncertainty” and “economic policy uncertainty” 16

17 Human index based on audit of 3727 articles (ave=34 per year) in the LA Times and New York Times (the two papers we could audit from 1900 to 2012) versus the historical index for these two papers. Find humans and computers give similar results in large samples: yearly from 1900 Computer Human Correlation=0.837

18 Human index based on audit of 3891 articles (34.7 per month) in the LA Times, New York Times, Miami Herald and SF Chronicle (the five papers we could audit from 1985 to 2012). Computer Human Correlation=0.721 Find humans and computers give similar results in large samples: quarterly from 1985

19 The human-computer differences are uncorrelated with real outcomes: e.g. GDP growth Yearly economic policy uncertainty index based on human audit of 3727 articles in the LA Times and New York Times (the two papers we could audit from 1900 to 2012) in a 3-year moving average to yield an average of 121 articles per year. Correlation=0.071

20 Papers sorted into 5 most ‘Republican’ or ‘Democratic’ groups using the media slant measure from Gentzkow & Shapiro (2010). D Bias test: compare 5 most Republican and 5 most Democrat papers – they looks similar Reagan, Bush IBush IIClintonObama

21 We approach policy uncertainty methodically 1) Measuring policy uncertainty 2) Evaluating our measure 3) Estimating the impact of policy uncertainty - Firm-level regressions - Macro VARs

22 Microdata: Firm-level estimates exploit differences in industry exposure to government Use the Federal Registry of Contracts and match this to Compustat firms (using Compustat parent & D&B subsid names) Generate average industry contracts/revenue (1999 to 2012)

23 Y it = F i + P t + α*Exp j *Gov t + β*Exp j *EPU t + ε i,t Microdata: Run firm level panel regressions Firm stock price volatility Firm fixed effects Period fixed effects Firm government exposure × government expenditure (1 st moment effect) Firm government exposure × policy uncertainty (2 nd moment effect) i=firm, j=industry, t=quarter Estimated firm by quarter , standard-errors clustered by j

24 Microdata: Firms with greater government exposure have higher stock vol uncertainty when EPU is high Notes: Firm-clustered standard errors. Firm by quarter panel data from , using individual firm implied volatility from individual firm equity options.

25 Microdata: Stock vol uncertainty results are very robust to different measures, samples and controls Notes: Firm-clustered standard errors. Firm by quarter panel data from , using individual firm implied volatility from individual firm equity options.

26 Microdata: Firms in sectors with higher government exposure cut investment & hiring when EPU is high Notes: Firm-clustered standard errors. Firm by quarter panel data for investment and firm by year for employment from

27 27 Magnitude for Investment and Employment v. large in exposed sectors (health, defense & construction) Consider EPU increase from 2005/6 to 2011/12 (84%) for firm with govt. exposure of 0.25 (health, defense & constr.). Results suggest reduce investment by 9% (similar to average recessionary drop in NIPA investment of 8.5%) Results suggest reduce employment by 12% (much larger than average recessionary drop in employment of 2%)

28 We approach policy uncertainty methodically 1) Measuring policy uncertainty 2) Evaluating our measure 3) Estimating the impact of policy uncertainty - Firm-level regressions - Macro VARs

29 VAR for US industrial production and employment after a 2005/6 to 2011/12 sized EPU shock Industrial Production, (%) Months after the economics policy uncertainty shock Notes: The impulse response function for Industrial Production and Employment to a rise in the policy- related uncertainty index from the average value to the average value. The central (black) solid line is the mean estimate, the dashed (red) outer lines are the one SE bands. Estimated using a monthly Cholesky Vector Auto Regression on: the EPU index, log(S&P 500), federal funds rate, log employment, log industrial production. Monthly data from 1985M1 to 2012M12, using 3 lags. Employment Impact, (%)

30 VAR robustness Months after the policy uncertainty shock Notes: This shows the impulse response function for GDP and employment to an increase in the policy-related uncertainty index from the average to the average. Estimated using a monthly Cholesky Vector Auto Regression (VAR) of the uncertainty index, log(S&P 500 index), federal reserve funds rate, log employment and log industrial production with 3 lags unless otherwise specified. Data from 1985 to 2012, except for the pre-1985 data spec which uses EPU and IP data from 1920 to Industrial Production Impact (% deviation) BaselineBivariate (EPU and industrial production) Six months of lags historical data Adding EU (after EPU) Adding VIX (after EPU) Reverse bivariate (industrial production & EPU)

31 11 Country Panel VAR, with Country & Period FEs Industrial Production, (%) Months after the economics policy uncertainty shock Notes: Shows the impulse response function for Industrial Production and employment to an increase in the policy-related uncertainty index from the average value to the average value. The central (black) solid line is the mean estimate while the dashed (red) outer lines are the one-standard-error bands. Estimated using a monthly Cholesky Vector Auto Regression (VAR) with 3 lags on the EPU index, log(S&P 500 index), unemployment rate, and log industrial production, plus a full set of country, year and month fixed-effects. Country data weighted by the number of newspapers used to make the EPU series. Fit to monthly data from 1985M1 to 2012M12 where available. Estimated on data from Canada, China, France, Germany, India, Italy, Japan, Russia, Spain, UK and the USA. Unemployment Impact, (%)

32 11 Country Panel VAR robustness Months after the policy uncertainty shock Industrial Production Impact (% deviation) Baseline Bivariate (EPU and industrial production) Six months of lags Adding stock volatility Reverse bivariate (industrial production & EPU) Dropping stock-price Notes: XXXX This shows the impulse response function for GDP and employment to an increase in the policy-related uncertainty index from the average to the average. Estimated using a monthly Cholesky Vector Auto Regression (VAR) of the uncertainty index, log(S&P 500 index), federal reserve funds rate, log employment and log industrial production with 3 lags unless otherwise specified. Data from 1985 to 2012, except for the pre-1985 data spec which uses EPU and IP data from 1920 to No country or time FEs

33 Conclusions 1.Policy uncertainty fluctuates at a high frequency, driven by the business cycle, the political factors, & shocks (e.g. wars) 2.Policy uncertainty appears to have risen since the 1960s (maybe from political polarization & larger government) 3.Firm-level (and VAR) evidence suggests EPU can: Substantially increase stock-volatility and reduce hiring & investment, in defense, healthcare & construction Moderately reduce overall output and employment

34 Data available at: Finally, should note all the data is online

35 Back-Up

36 Future Work: working on firm-level surveys Projecting ahead over the next twelve months, please provide the approximate percentage change in your firm's SALES LEVELS for: The LOWEST CASE change in my firm’s sales levels would be: -9 % The LOW CASE change in my firm’s sales levels would be: -3 % The MEDIUM CASE change in my firm’s sales levels would be: 3 % The HIGH CASE change in my firm’s sales levels would be: 9 % The HIGHEST CASE change in my firm’s sales levels would be: 15 % Numbers in red are the average response from the pilot on 300 firms

37 Piloting results look good from testing on a monthly survey on 300 firms: change in sales

38 Please assign a percentage likelihood to these SALES LEVEL changes you selected above (values should sum to 100%) 10 % : The approximate likelihood of realizing the LOWEST CASE change 18 % : The approximate likelihood of realizing the LOW CASE change 40 % : The approximate likelihood of realizing the MEDIUM CASE change 23 % : The approximate likelihood of realizing the HIGH CASE change 9 % : The approximate likelihood of realizing the HIGHEST CASE change Numbers in red are the average response from the pilot on 300 firms Can also ask about probabilities

39 Piloting results look good from testing on a monthly survey on 300 firms: probabilities

40 Notes: Data from “The buzz: Links between policy uncertainty and equity volatility”, by Krag Gregory and Jose Rangel, Goldman Sachs, November 12, Correlation EPU and 1 month=0.578 Correlation EPU and 10 years= Month Implied Volatility (♦) 10 Year Implied Volatility (+) Economic Policy Uncertainty ( ) Stock market data: More similar to 10 year index of implied volatility on the S&P500 (correlation 0.73)

41 The key sources of policy uncertainty from 1985 Note: This quarterly chart shows the 5 most important sources of economic policy uncertainty based on frequency counts of newspaper articles. Gulf War I Clinton Election Gulf War II 9/11 Lehman and TARP Black Monday Fiscal cliff, Europe and Debt Ceiling Gingrich Shutdown

42 Why is not fully clear – but looking into this along with Jonathan Rodden and Brandice Canes-Wrone

43 Notes: Frequency of the triple of “economy/economic”, “uncertain/uncertainty” and one of a collection of financial market terms (stock price, equity price, stock market) in 10 major US papers and normalized by the total number of articles, by month and paper. Both series scaled to same mean. Each series set to mean of 100 over entire period. 43 Correlation=0.733 Also tested by fitting events we know - VIX

44 44 Note: Plots the frequency of the word “uncertain” in each quarter of the Federal Open Market Committees’ (FOMC) Beige Book. Data from 1983Q4 (when the Beige book started) to 2013Q1. The Beige Book is an overview of economic conditions of about 15,000 words in length prepared two weeks before each FOMC meeting. The count of “Policy Uncertainty” uses a human audit to attribute each mention of the word uncertain to a policy context (e.g. uncertainty about fiscal policy) or a non-policy context (e.g. uncertainty about GDP growth). See the paper for full details. Surveys: e.g. compare to the FOMC Beige Book’s mentions of uncertainty and policy uncertainty Correlation with our EPU index=0.72

45 1990 Q Q1 Gulf War I 1993 Q Q3 Clinton Tax Reforms 2001 Q Q2 9/11 Attacks 2002 Q Q2 Gulf War II 2004 Q Q4 Bush/Kerry Election 2008 Q Q4 Lehman's and recession 2010 Q Q1 Debt-ceiling crisis 1983 Q3 – 2013 Q1 Overall Average Overall Economic Uncertainty Economic Policy Uncertainty All Fiscal Matters Taxes Only Spending Only Monetary Policy Health Care National Security and War Financial Regulation Sovereign debt, currency crisis U.S. Elections and Leadership Changes Other Specified Policy Matters Politics, Unspecified Sum of Policy & Politics Categories Beige Book breakdown also points to similar factors


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