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on Forecasting |
| By: | Helge Berger; Michael Ehrmann; Marcel Fratzscher |
| Abstract: | Monetary policy in the euro area is conducted within a multicountry, multicultural, and multilingual context involving multiple central banking traditions. How does this heterogeneity affect the ability of economic agents to understand and to anticipate monetary policy by the European Central Bank (ECB)? Using a database of surveys of professional ECB policy forecasters in 24 countries, we find remarkable differences in forecast accuracy, and show that they are partly related to geography and clustering around informational hubs, as well as to country-specific economic conditions and traditions of independent central banking in the past. In large part, this heterogeneity can be traced to differences in forecasting models. While some systematic differences between analysts have been transitional and are indicative of learning, others are more persistent. |
| Keywords: | Monetary policy , Europe , European Central Bank , Economic forecasting , Data collection , Data analysis , |
| Date: | 2006–02–17 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:06/41&r=for |
| By: | Christensen, Bent Jesper (Department of Finance, Copenhagen Business School); Raahauge, Peter (Department of Finance, Copenhagen Business School) |
| Abstract: | We consider a random utility extension of the fundamental Lucas (1978) equilibrium asset pricing model. The resulting structural model leads naturally to a likelihood function. We estimate the model using U.S. asset market data from 1871 to 2000, using both dividends and earnings as state variables. We find that current dividends do not forecast future utility shocks, whereas current utility shocks do forecast future dividends. The estimated structural model produces a sequence of predicted utility shocks which provide better forecasts of future long-horizon stock market returns than the classical dividend-price ratio. |
| Keywords: | Randomutility; asset pricing; maximumlikelihood; structuralmodel; return predictability |
| JEL: | G00 |
| Date: | 2004–12–14 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:cbsfin:2004_007&r=for |
| By: | Gagik G. Aghajanyan |
| Abstract: | Several non-monetary (mainly supply) factors affect prices in the short-run. It is widely acknowledged that in countries (especially countries in transition), where the price level is highly volatile and seasonal, it is not expedient for central banks to use official inflation index while formulating monetary policy. For this reason, it is crucial for central banks to work out, study and follow the behavior of core inflation that enables to reflect long-run price movements. This paper presents the application of various methods of calculating core inflation to Armenian data (for 1996:1-2002:12). Each measure is calculated at monthly frequencies and evaluated by different criteria. The analysis shows that core inflation indices, calculated by trimming the distribution of prices at 10 or 15%, are the best and most effective indicators for monetary policy-makers in Armenia, since they capture inflation trends and are closely tied to monetary aggregates. However, the median seems to be the best predictor for forecasting inflation of all core inflation measures discussed in this paper |
| JEL: | P2 R5 E31 P3 |
| Date: | 2005–06–01 |
| URL: | http://d.repec.org/n?u=RePEc:liu:liucej:16&r=for |