Santos, Edward P. and Mapa, Dennis S. and Glindro, Eloisa T. (2011): Estimating Inflation-at-Risk (IaR) using Extreme Value Theory (EVT).
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Abstract
The 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.
Item Type: | MPRA Paper |
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Original Title: | Estimating Inflation-at-Risk (IaR) using Extreme Value Theory (EVT) |
Language: | English |
Keywords: | Inflation-at-Risk (IaR), Extreme Value Theory (EVT), Peaks-over-Threshold (POT) |
Subjects: | E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E31 - Price Level ; Inflation ; Deflation C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics |
Item ID: | 28266 |
Depositing User: | Dennis S. Mapa |
Date Deposited: | 22 Jan 2011 20:20 |
Last Modified: | 12 Oct 2019 03:59 |
References: | Bangko Sentral ng Pilipinas (2008). Third Quarter Inflation Report. Cecchetti, S. (1996). Measuring Short-Run Inflation for Central Bankers. Working Paper No. 5786. National Bureau of Economic Research, Cambridge. Gali, J. and Gertler, M. (2003). Inflation Dynamics: Combining Measurement with Theory. NBER Reporter: Research Summary Summer 2003. Guinigundo, D.C. (2009). Measurement of Inflation and its Implications on the Philippine Monetary Policy Framework. Bank for International Settlements (BIS Papers No. 49). Kearns, J. (1998). The Distribution and Measurement of Inflation. Research Discussion Paper 9810. Reserve Bank of Australia. LeBaron, B. and Samanta, R. (2004). Extreme Value Theory and Fat Tails in Equity Markets McNeil AJ, Frey R, Embrechts P (2005). Quantitative Risk Management: Concepts, Techniques and Tools. Princeton University Press. Tsay, R.S. (2002). Analysis of Financial Time Series. University of Chicago. John Wiley and Sons, Inc. Woodford, M. (2003). Interest and Prices: Foundations of a Theory of Monetary Policy. Princeton University Press. Kuester, K., Mittnik, S., and Paolella, M. (2006). Value-at-Risk Prediction: A Comparison of Alternative Strategies. Journal of Financial Econometrics, 2006, Vol. 4, No. 1, 53–89 |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/28266 |