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¿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.

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

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  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

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