1 / 29

¿By How Much and Why Do Inflation Targeters Miss Their Targets?

¿By How Much and Why Do Inflation Targeters Miss Their Targets?. Elías Albagli Klaus Schmidt-Hebbel Central Bank of Chile Atlanta Fed Conference on “Implementing Monetary Policy in the Americas: The Role of Inflation Targeting Atlanta, 4 October 2004. Inflation convergence under IT.

nasia
Télécharger la présentation

¿By How Much and Why Do Inflation Targeters Miss Their Targets?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. ¿By How Much and Why Do Inflation Targeters Miss Their Targets? Elías Albagli Klaus Schmidt-Hebbel Central Bank of Chile Atlanta Fed Conference on “Implementing Monetary Policy in the Americas: The Role of Inflation Targeting Atlanta, 4 October 2004

  2. Inflation convergence under IT

  3. Inflation convergence under IT

  4. Inflation convergence under IT

  5. This paper’s objectives: 1. Measuring IT performance and accuracy in all inflation-targeting countries, using consistent and robust measures and high-frequency data 2. Explaining IT performance: the role of policy credibility / investment credit risk in determining IT accuracy, controlling for relevant inflation shocks.

  6. 1. Measuring Inflation Targeting Accuracy

  7. Data and methodology • Monthly inflation data (yoy), for 19 ITers, 1990-2003 • Which target? Target point or center point of target range • For robustness we use 3 target definitions: Official (OFT), interpolated (IPT), Hodrick-Prescott filter (HPT).

  8. Alternative monthly targets: Chile

  9. Alternative monthly targets: Israel

  10. Descriptive statistics of target accuracy • Mean absolute deviation • Normalized mean absolute deviation • Deviations’ persistence (half-life inflation shocks) • Large inflation deviation episodes:

  11. Large inflation deviation episodes *Target: IPT

  12. IT Accuracy: Results

  13. IT Accuracy: Results

  14. IT Accuracy: Rankings

  15. 2. ¿What explains IT Accuracy?

  16. Which role do institutional perception / credibility play in IT accuracy? • Basic hypothesis: accuracy is higher in countries with more mature institutions and lower risk that support stronger policy credibility and closer alignment of inflation expectations with inflation targets • Old idea ... backed by little empirical evidence to date.

  17. Previous findings: • Calderón and Schmidt-Hebbel (2003) use Central Bank independence dummy (CBI) and government bond spreads to measure credibility. • Both measures of credibility / institutional perception raise IT accuracy. • Problems with CBI: displays little time variation, hence hard to exploit time-series data. Makes little difference between ranges of independence (0 or 1). • Problems with government bond spreads: Available for few countries, too recent.

  18. This paper extends previous evidence in several dimensions: • Higher frequency, more recent data • Larger country sample • Panel data regressions, IV estimation • Tests for alternative measure of credibility / institutional perception: Institutional Investor’s Country Credit Rating (IICR).

  19. Institutional Investor’s Country Credit Rating • Measures “investment climate” at country level. Based on evaluation of institutions, corruption, macro policies and performance indicators. Ranges from 0 to 100. • Contains information on institutional perception and law enforcement • Series available before the 1990s, for all countries in the sample • Problem: possible endogeneity  IV estimation.

  20. Data and methodology: • Quarterly data, 1990-2003, 19 ITers. • Cross-section country averages and panel data (OLS, fixed effects, TSLS). • Dependent variable: inflation deviation from target (absolute value). • Explanatory variables: • Control variables: oil price, US GDP, exchange rates (annual changes and trend deviations, absolute value). • Credibility / Institutional Perception: Central Bank independence (CBI), sovereign spreads (SPREADS), and “Institutional Investor’s credit rating” (RISK).

  21. Cross-section averages: MAD: Mean absolute deviation TARGET: target average RANGE: Average target range DNER: Nominal exchange rate depreciation standard deviation IICR: Institutional Investor’s Credit Rating average CBI: Central Bank independence Dummy

  22. Panel data regressions AD: Absolute value of inflation deviation OILG: Oil price GAP (HP filter). NER: Nominal exchange rate depreciation (YoY) IICR: Institutional Investor’s Credit Rating • TSLS instruments: Exogenous variables (lagged), and RISK(-1).....RISK(-j).

  23. Results: Gains in IT Accuracy

  24. Conclusions • Large deviations from inflation targets are frequent, with an average duration of 7-10 months. • Exchange rate depreciation and oil price deviations from trend affect IT performance.

  25. Conclusions • Stronger credibility and/or institutional perception, reflected either by CBI, sovereign spreads, or country credit rating enhances IT accuracy, even controlling for possible endogeneity. • Results show that institutional perception / credibility gains lead to statistically and economically significant improvements in IT accuracy.

  26. ¿By How Much and Why Do Inflation Targeters Miss Their Targets? Elías Albagli Klaus Schmidt-Hebbel Central Bank of Chile Atlanta Fed Conference on “Implementing Monetary Policy in the Americas: The Role of Inflation Targeting Atlanta, 4 October 2004

More Related