This chapter extends the workhorse model of Berg, Karam, and Laxton (2006b) to better capture Philippine-specific factors:
First, the large and persistent fiscal deficit in the Philippines could be an important source of shocks to the economy. Therefore, we include the fiscal gap in the output gap equation and a fiscal rule to simultaneously capture the possibility of countercyclical fiscal policy and ensure a stable public debt, as in Honjo and Hunt (2006). The specification is:
where FB is the fiscal balance gap, and Dgap the deviation from the government’s debt target. The foreign sector does not have an endogenous fiscal policy reaction function. Debt is defined as the cumulative fiscal balance, and the debt target is set equal to zero, which implies the equilibrium fiscal balance is zero and there is no debt accumulation over time. This can be thought of as normalization around a nonzero, but constant, ratio of public debt to GDP.
Second, this chapter extends the model to include macro-financial linkages as in Carabenciov and others (2008). The global financial crisis and great recession have highlighted how financial developments can affect the real economy, particularly through “financial accelerator” effects (Bernanke et al., 1999). Given the dominance of banks in the Philippines, the analysis focuses on bank lending conditions, as in Carabenciov and others 2008). Bank lending (BL) is a function of BL* (defined as the equilibrium level of BL), the real interest rate gap, and banks’ expectation of the economy four quarters ahead. The output gap is explained by the same variables as in equation (1) above as well as by a distributed lag of
The values of the coefficients imposed on the distributed lag of are intended to react to a pattern in which an increase of loosening of credit conditions) is expected to positively affect spending by firms and households in a hump-shaped fashion, with an initial buildup and then a gradual rundown of the effects as in Carabenciov and others (2008). The specification in this case is:
where η is the distributed lag of
Third, the chapter introduces a pass-through coefficient pt to capture the pass through of international oil price to local fuel prices.
Berg, A., P. Karam, and D. Laxton, 2006a, “A Practical Model-Based Approach to Monetary Policy Analysis: Overview,” IMF Working Paper 06/080 (April). Available at www.imf.org
Berg, A., P. Karam, and D. Laxton, 2006b, Practical Model-Based Monetary Policy Analysis: A How-to Guide”, IMF Working Paper 06/081 (April). Available at www.imf.org
Bernanke, B. S. Mark Gertler, and Simon Gilchrist, 1999, “The Financial Accelerator in a Quantitative Business Cycle Framework,” in Handbook of Macroeconomics, Volume 1C, Handbooks in Economics, vol. 15. Amsterdam: Elsevier, pp. 1341–93.
Carabenciov, I., I. Ermolaev, C. Freedman, M. Juillard, O. Kamenik, D.. Korsunmov, and D. Laxton, 2008, “A Small Multi-Country Global Projection Model with Financial-Real Linkages and Oil Prices,” IMF Working Paper No. 08/280 (Washington: International Monetary Fund).
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)| false Carabenciov, I., I. Ermolaev, C. Freedman, M. Juillard, O. Kamenik, D.. Korsunmov, and D. Laxton, 2008, “A Small Multi-Country Global Projection Model with Financial-Real Linkages and Oil Prices,”IMF Working Paper No. 08/280 ( Washington: International Monetary Fund).
Guinigundo, Diwa C., 2010 “Measurement of Inflation and the Philippine Monetary Policy Framework” in Monetary Policy and the Measurement of Inflation: Prices, Wages and Expectations, BIS Papers No 49. (January 2010).
International Monetary Fund, 2005, “Does Inflation Targeting Work in Emerging Markets?” in World Economic Outlook (September 2005) (Washington).
Keiko, H., and H. Benjamin, 2006, “Stabilizing Inflation in Iceland”, IMF Working Paper 06/262, (Washington: International Monetary Fund).
Kongsamut, Piyabha, 1999, “Philippines: Preparation for Inflation Targeting” IMF Working Paper 01/99 (Washington: International Monetary Fund).
Laxton, Douglas, David Rose and Alasdair M. Scott, 2009, “Developing a Structured Forecasting and Policy Analysis System to Support Inflation-Forecast Targeting (IFT)” (March 2009), IMF Working Papers 09/65 (Washington: International Monetary Fund).
McNelis, Paul D. and Cristeta B. Bagsic., 2007, “Output Gap Estimation for Inflation Forecasting: The Case of the Philippines” BSP Working Paper Series No. 2007-01.
Stone, M. S. Roger, S. Shimizu, A. Nordstrom, J. Restrepo, 2009, “The Role of the Exchange Rate in Inflation-targeting Emerging Economies” (Washington: International Monetary Fund).
Prepared by Shanaka J. Peiris (APD).
The BSP’s monetary policy framework provides for exemption clauses to recognize the fact that there are limits to the effectiveness of monetary policy and that there may be occasional breaches owing to factors beyond the control of the central bank (see Guinigundo, 2010).
In conveying to the public the views of the BSP, an assessment of the output gap is presented along with the inflation forecast. The BSP also assesses inflation expectations, evidence of second-round effects, and the yield curve among a host of critical factors (see Guinigundo, 2010).
See McNelis and Bagsic, (2007) for details on the BSP inflation forecasting models and performance.
This contrast with the financial programming approach, which emphasizes the role of monetary aggregates in analyzing the monetary sector (see Berg, Karam, and Laxton, 2006, for a discussion of the different approaches).
The model-based forecast provides a relatively good out-of-sample forecast (compared to a bayesian VAR beyond two lags).