1. Sticky-information vs. Backward-looking index.: Inflation inertia in the U.S. by Julio A. Carrillo Maastricht University Econometric Society 2008 North American Summer Meeting Pittsburgh, June 2008

2. Outline I. Introduction II. Indexation mechanisms and lagged expectations III. Minimum Distance Estimator IV. Results V. Conclusions

3. Introduction I Problem Empirical high persistence of inflation and output to changes in monetary policy Standard sticky-price models unable to generate such inertia Solutions State-of-the-art (Christiano et al. 2005) For price/wage setting, add lagged inflation indexation For output, add habit formation Challenging (Mankiw and Reis 2007) Sticky-information on households, firms and workers

4. IntroductionII Problem Critics for state-of-the-art assumptions: Lagged inflation indexation: rule-of-thumb No optimizing behavior from firms/workers Very specific rule-of-thumb Too much price rigidity not verified by micro-data studies Information equally distribuited

5. IntroductionIII Motivation Arguments in favor challenging assumptions: Prices react to old information (Klenow and Willis 2007) Prices change every 5.5 months at least (Bils and Klenow 2004) People update information once per year (Carroll 2003) Is information the same for everybody ? Sticky- information

6. IntroductionIV Motivation Implementation of sticky information Should we replace sticky-prices with sticky-information? No. Evidence suggest prices are indeed sticky. Besides, new literature points out both rigidities are needed (Dupor et al. 2008) Compare 2 ways of adding inertia to a sticky-price model

7. IntroductionV Aim Confront these two set of assumptions with data Backward-looking inflation indexation vs. Sticky-information A multivariate system (DSGE) may bring useful extra info Asses implications to aggregate dynamics Which is the best approximation to macroeconomic inertia?

8. Introduction VI Methodology

9. New Keynesian model in the spirit of Christiano et al. 2005 Nominal rigidities: Price/Wage stickiness with lagged inflation indexation rule Real rigidities: Habit formation on consumption Money in the utility function Taylor rule with policy inertia and persistent shocks ModelI Backward-looking inflation index.

10. ModelII Backward-looking inflation index.

11. Hybrid sticky-information and sticky-price model Nominal rigidities: Price/Wage stickiness Real rigidities: Information disseminates slowly among consumers, firms and workers Money in the utility function Taylor rule with policy inertia and persistent shocks ModelIII Sticky-information

12. ModelIV Sticky-information model

13. ModelV Sticky-information model

14. Sample period: 1960Q1-2002Q4 federal funds rate, per capita GDP, linearly detrended, inflation from GDP’s implicit deflator, wage inflation from nominal hourly compensation, money growth, inflation of commodities Findings echo results by Christiano et al 1996, 2005 MethodologyI SVAR with US data

15. MethodologyII SVAR with US data

16. Use actual economy’s responses from SVAR-IRFs  T Let  parameters to be estimated. Model IRFs are h(  ). Then the objective is J T = argmin (h(  ) −  T )V T (h(  ) −  T )′ where V T is a weighting matrix Variables of interest: Output, Inflation, Wage Inflation and interest Rate. MethodologyIII SVAR with US data

17. All parameters other than  are calibrated Fully control our experiment! Model IRFs depend on how inertia is added Standard values for calibration (Christiano et al. 2005; Rotemberg and Woodford 1997); Sensitivity analysis is also performed MethodologyIV Calibration

18. Three set of estimations are considered 1)Degree of information stickiness vs Degree of backward-looking indexation and habit formation 2)1) + price stickiness in both models 3)2) + interest rate inertia in both models MethodologyV Set of estimations

19. ResultsI MDE estimations

20. ResultsII … in words Sticky-information model: Rejected when assuming prices are too rigid Requires less price/wage rigidities Equally succesful than backward-looking model Slightly better for inflation and wages (in estim. 3) Backward-looking model very stable

21. ResultsIII Best fit

22. ResultsIV Average duration of price adjust. Backward-looking model: price adjust once per year BUT Bils and Klenow (2004): for the U.S., prices change every 5.5 months Sticky-information model: prices change at least 2 times per year firms update information every 2.5 years overall, prices adjust every 2.25 years

23. ResultsV Sensitivity analysis Estimation robust to different calibrations (preferences, technology, policy rule) Sticky-info outperforms Backward-looking model for inflation and wages Substitution effect between information and price stickiness

24. ResultsVI Sensitivity analysis

25. Conclusions Sticky-information and backward-looking indexation equally successful Price rigidities differs Backward-looking model very stable, but not verified by micro-data Sticky-info natural replacement of lagged inflation indexation... But the way is still long