Policy makers believe that uncertainty matters, 1/4

1. Really Uncertain Business CyclesNick Bloom (Stanford, CEP & NBER)Max Floetotto (Stanford)Nir Jaimovich (Stanford & NBER)Very PreliminaryKellogg, May 19th 2009

2. Policy makers believe that uncertainty matters, 1/4 FOMC (April 2008) “Several participants reported that uncertainty about the economic outlook was leading firms to defer spending projects until prospects for economic activity became clearer.”

3. Policy makers believe that uncertainty matters, 2/4 Olivier Blanchard (January 2009)"Crises feed uncertainty. And uncertainty affects behavior, which feeds the crisis. Were a magic wand to remove uncertainty, the next few quarters would still be tough, but the crisis would largely go away.”

4. Policy makers believe that uncertainty matters, 3/4 Larry Summers (March 2009) “…unresolved uncertainty can be a major inhibitor of investment. If energy prices will trend higher, you invest one way; if energy prices will be lower, you invest a different way. But if you don’t know what prices will do, often you do not invest at all.”

5. Policy makers believe that uncertainty matters, 4/4 Christina Romer (April 2009) “Volatility has been over five times as high over the past six months as it was in the first half of 2007. The resulting uncertainty has almost surely contributed to a decline in spending.”

6. We model uncertainty as a new type of shock First moment shocks in the literature • Neutral technology shocks • Investment-specific technology shocks • Oil price shocks • Labor supply shocks • Monetary policy shocks • Financial shocks • News shocks We want to consider a second moment (uncertainty) shock • For simplicity focus on technology shocks

7. The paper examines empirical evidence and a model on uncertainty and the business cycle Paper has three main parts: • Empirical evidence that uncertainty is counter-cyclical • DSGE model of the impact of time varying uncertainty: • Uncertainty shocks lead to business cycles • Uncertainty substantially reduces the impact of policy • Examine Census micro-data, to investigate further predictions we get from the model for the impact of uncertainty

8. What this paper does not (currently) do • Attempt to endogenize uncertainty • Modeled as exogenous, like first moment shocks • If uncertainty is endogenous could think of as a propagation and amplification mechanism • Include/analyze other potentially important uncertainty channels: • Consumer durables • Credit • Risk

9. Measuring UncertaintyModelTesting the model on Census micro data

10. Uncertainty over the business cycle • Uncertainty is hard to measure and the concept is vague • Build on prior literature and use different types of proxies: • Cross-industry, firm and plant evidence • Time-series aggregate data • Cross-forecaster disagreement evidence • Combine these into an aggregate uncertainty index • This reduced index rises by 48% during recessions

11. Cross industry output growth spread until 2009 Q1 Inter-quartile range of the 3-month growth rates of industrial production. Covers all 196 manufacturing NAICS sectors in the Federal Reserve Board database.

12. Cross industry output growth distribution 99th percentile, 2.2% higher in recessions 50th percentile,1.3% lower in recessions 1st percentile7.4% lower in recessions 1st, 5th, 10th, 25th, 50th, 75th, 90th, 95th and 99th percentiles of 3-month growth rates of industrial production within each quarter. All 196 manufacturing NAICS sectors in the Federal Reserve Board database.

13. Cross firm sales growth spread until 2008 Q2 Across all firms(+ symbol) Across firms in a SIC2 industry Interquartile range of sales growth (Compustat firms). Only firms with 25+ years of accounts, and quarters with 500+ observations. SIC2 only cells with 25+ obs.

14. Cross firm stock returns spread until 2008 Q4 Across all firms(+ symbol) Across firms in a SIC2 industry Interquartile range of stock returns (CRSP firms). Only firms with 25+ years of accounts, and quarters with 500+ observations. SIC2 only cells with 25+ obs.

15. Cross establishment sales & labor productivity growth spread • ASM data on 60,000 manufacturing establishments 1974-2006 • Found two stylized facts: • Cross-sectional spreads strongly counter cyclical • Increase both overall and within SIC 4-digit category

16. Industrial production growth volatility until 2009 Q1 Monthly industrial production conditional heteroskedasticity, from a GARCH(1,1) auto-regression with 12 lags.

17. Stock market volatility until 2009 Q2 S&P 100 implied volatility (the VXO, which is very similar to VIX) from 1987, and normalized realized volatility of actual S&P100 daily stock returns prior to 1986.

18. Forecaster dispersion for unemployment until 2009 Q2 Interquartile range of year ahead unemployment rates / mean unemployment rates. From Survey of Professional Forecasters. Average of 41 forecasts per quarter.

19. Forecaster dispersion for production until 2009 Q2 Interquartile range of year ahead production/mean production. From Survey of Professional Forecasters. Average of 41 forecasts per quarter.

20. Uncertainty index – average of last 7 measures until 2009 Q1 Mean of the 7 prior indicators after they have all been normalized to an average of 1 during non-recessionary quarters. Only reported when 5+ indicators present.

21. Uncertainty index and industrial production growth

22. Are recessions also conditionally associated with recessions? • So far only shown unconditional correlation between recessions and uncertainty • Use VAR analysis to investigate the conditional correlation of uncertainty with a recession, noting this does not imply causality

23. VAR analysis Use standard VAR framework from Christiano, Eichenbaum and Evans (2005) that includes the following variables (in order): • Real GDP (logs) • Real consumption (logs) • GDP deflator (logs) • Real investment (logs) • Real wage (logs) • Labor productivity (logs) • Federal Funds rate • Real profits (logs) • Growth rate of M2 Add aggregate uncertainty index, but • Check robustness to change in ordering (first, last) • TFP to control for first moment shock (Basu, Kimball & Fernald)

24. VAR analysis – uncertainty first Shock calibrated to increase uncertainty 48% during recessions Cholesky orthogonalized on quarterly data from 1968:4 to 2006:4 using 4 lags. Dotted lines are 95% confidence intervals

25. VAR analysis – different experiments Shock calibrated to increase uncertainty 48% during recessions Cholesky orthogonalized on quarterly data from 1968:4 to 2006:4 using 4 lags. Dotted lines are 95% confidence intervals

26. Results for Germany (from Frank Smets) Impact of a one SD impulse in uncertainty. Prepared by creating a German Uncertainty Index over 10 years and running the same VAR specification.

27. Results for US consumption (from Mark Doms) Source: Mark Doms (SF Federal Reserve Board), figure used for Board of Governors briefing work

28. Taking stock • Uncertainty - however measured - is strongly countercyclical • An increase in uncertainty robustly associated with a significant drop and rebound in output in a VAR framework • Well known identification problems in VAR, so results are only suggestive • Model allows us to study a possible mechanism further and provides additional micro-predictions to test in Census data

29. Measuring UncertaintyModelTesting the model on Census micro data

30. Model conforms as much as possible to the standard frictionless RBC • Main deviations are: • Second moment shocks • Non-convex adjustment costs in both capital and labor • Firm-level heterogeneity

31. Disinvest Invest Density of units Productivity / Capital Mechanism is linked to Ss investment thresholds arising from non-convex adjustment costs

32. Disinvest Invest Density of units Productivity / Capital Mechanism is linked to Ss investment thresholds arising from non-convex adjustment costs

33. Technology • Large number of heterogeneous firms • “Productivity” follows an AR process with time variation in the variance of innovations • Uncertainty (σA and σZ) follow a 2-point markov chain

34. Capital and labor adjustment costs • Capital and labor follow the laws of motion: where i: investment δk:depreciation s: hiring δn:attrition • Allow for the full range of adjustment costs • Fixed – lump sum cost for investment and/or hiring • Partial – per $ disinvestment and/or per worker hired/fired • Quadratic – to invest/disinvest and/or hire/fire more rapidly • To match micro data paid on all investment and hiring (even replacement investment and hiring)

35. Firm’s value function

36. Households • Representative agent who works, consumes and owns the firms • We assume the functional form for household utility • Separability of preferences yields a simple SDF: • The FOC for hours worked

37. General equilibrium solution overview • We have a recursive competitive equilibrium • Solve numerically as no analytical solution • Numerical solution approximates μ (the firm-level distribution over z, k and n) with moments, building on Krusell and Smith (1998) • Follow Kahn and Thomas (2008) and Bachman, Caballero and Engel (2008) in using two tricks to simplify the numerical solution

38. Simplifying the problem

39. Calibration

40. Calibration of the uncertainty process

41. Simulation of a shock to uncertainty Share of economies in high uncertainty state (in 1000 simulations)

42. Results not driven by a first moment shock Average firm times macro productivity in the simulation

43. The effect of an increase in uncertainty on employment: 3 phases Deviation from steady state (%) Overshoot Drop Rebound

44. The effect of an increase in uncertainty on investment Deviation from steady state (%)

45. The effect of an increase in uncertainty on output Deviation from steady state (%)

46. The effect of uncertainty on measured TFP Deviation from steady state (%) Measured TFP = output/(capitalαlaborν)

47. Bad fit? The effect of uncertainty on consumption Deviation from steady state (%)

48. Cross-sectional distribution of firm TFP/capital Thresholds & percentiles of firm distribution over z/k (for fixed k & l)

49. Uncertainty alters the impact of policy • Uncertainty widens firms’ Ss bands for investment and hiring, thereby reducing the impact response of any given stimulus • But, once uncertainty falls firms will start to respond again

50. Illustrate with an investment credit from Mars • Example of a 1% investment credit from Mars for 3 quarters • From Mars so not GE (much simpler to model) • Again for simplicity assume it’s a complete surprise to agents – they just find investment is 1% cheaper for 3 quarters • Evaluate during a normal period and after an uncertainty shock