By how much and why do inflation targeters miss their targets
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¿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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¿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


Inflation convergence under IT


Inflation convergence under IT


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.


1. Measuring Inflation Targeting Accuracy


  • 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).


Alternative monthly targets: Chile


Alternative monthly targets: Israel


  • Descriptive statistics of target accuracy

    • Mean absolute deviation

    • Normalized mean absolute deviation

    • Deviations’ persistence (half-life inflation shocks)

    • Large inflation deviation episodes:


Large inflation deviation episodes

*Target: IPT


IT Accuracy: Results


IT Accuracy: Results


IT Accuracy: Rankings


2. ¿What explains IT Accuracy?


  • 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.


  • 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.


  • 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).


  • 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.


  • 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).


  • 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


  • 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).


Results: Gains in IT Accuracy


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.


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.


¿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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