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Forecasting and Monetary Policy Analysis in Low-Income Countries :, Food and non-Food Inflation in Kenya, Michal Andrle, Andrew Berg, R. Morales, Rafael Portillo, Jan Vlcek

We develop a semi-structural new-Keynesian open-economy model, with separate food and non-food inflation dynamics, for forecasting and monetary policy analysis in low-income countries and apply it to Kenya. We use the model to run several policy-relevant exercises. First, we filter international and Kenyan data (on output, inflation and its components, exchange rates and interest rates) to recover a model-based decomposition of most variables into trends (or potential values) and temporary movements (or gaps)—including for the international and domestic relative price of food. Second, we use the filtration exercise to recover the sequence of domestic and foreign macroeconomic shocks that account for business cycle dynamics in Kenya over the last few years, with a special emphasis on the various factors (international food prices, monetary policy) driving inflation. Third, we perform an out-of-sample forecast to identify where the economy—and therefore policy—was likely headed given the inflationary pressures at the end of our sample (2011Q2). We find that while imported food price shocks have been an important source of inflation, both in 2008 and more recently, accommodating monetary policy has also played a role, most notably through its effect on the nominal exchange rate. The model correctly predicted that a policy tightening was required, although the actual interest rate increase was larger. We discuss implications for the use of model-based policy analysis in low income countries
Table Of Contents
Cover; Contents; I. Introduction; II. Kenya: Inflation Developments and Monetary Policy 2007-2011; III. The Model; A. Price Indices and Relative Prices; B. Trends in Relative Prices; C. Output and Real Interest Rates; D. Philips Curves; E. Exchange rate (UIP); F. Monetary policy rule; G. Foreign Block; IV. Applying the model for policy analysis in Kenya; A. Calibration and Data; B. Impulse Response Analysis; C. Filtering Kenyan Data Through the Model; D. A Model-Based Interpretation of Recent History; 1. The 2007-2009 Period; 2. The 2010-2011 Period
Literary Form
non fiction
Description based upon print version of record
Physical Description
1 online resource (64 p.)
Specific Material Designation
Form Of Item

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