Estimating Inflation-at-Risk (IaR) using Extreme Value Theory (EVT)
AbstractThe Bangko Sentral ng Pilipinas (BSP) has the primary responsibility of maintaining stable prices conducive to a balanced and sustainable economic growth. The year 2008 posed a challenge to the BSP’s monetary policy making as inflation hit an official 17-year high of 12.5 percent in August after 10 months of continuous acceleration. The alarming double-digit inflation rate was attributed to rising fuel and food prices, particularly the price of rice. A high inflation rate has impact on poverty since inflation affects the poor more than the rich. From a macroeconomic perspective, high level of inflation is not conducive to economic growth. This paper proposes a method of estimating Inflation-at-Risk (IaR) similar to the Value-at-Risk (VaR) used to estimate risk in the financial market. The IaR represents the maximum inflation over a target horizon for a given low pre-specified probability. It can serve as an early warning system that can be used by the BSP to identify whether the level of inflation is extreme enough to be considered an imminent threat to its inflation objective. The extreme value theory (EVT), which deals with the frequency and magnitude of very low probability events, is used as the basis for building a model in estimating the IaR. The estimates of the IaR using the peaks-over-threshold (POT) model suggest that the while the inflation rate experienced in 2008 can not be considered as an extreme value, it was very near the estimated 90 percent IaR.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 28266.
Date of creation: Jan 2011
Date of revision:
Inflation-at-Risk (IaR); Extreme Value Theory (EVT); Peaks-over-Threshold (POT);
Other versions of this item:
- Edward P. Santos & Dennis S. Mapa & Eloisa T. Glindro, 2010. "Estimating inflation-at-risk (IaR) using extreme value theory (EVT)," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 47(2), pages 21-40, December.
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-01-30 (All new papers)
- NEP-CBA-2011-01-30 (Central Banking)
- NEP-MAC-2011-01-30 (Macroeconomics)
- NEP-MON-2011-01-30 (Monetary Economics)
- NEP-RMG-2011-01-30 (Risk Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Stephen G. Cecchetti, 1996.
"Measuring Short-Run Inflation for Central Bankers,"
NBER Working Papers
5786, National Bureau of Economic Research, Inc.
- Jonathan Kearns, 1998. "The Distribution and Measurement of Inflation," RBA Research Discussion Papers rdp9810, Reserve Bank of Australia.
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