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on Forecasting |
| By: | Nikita Perevalov; Philipp Maier |
| Abstract: | The good forecasting performance of factor models has been well documented in the literature. While many studies focus on a very limited set of variables (typically GDP and inflation), this study evaluates forecasting performance at disaggregated levels to examine the source of the improved forecasting accuracy, relative to a simple autoregressive model. We use the latest revision of over 100 U.S. time series over the period 1974-2009 (monthly and quarterly data). We employ restrictions derived from national accounting identities to derive jointly consistent forecasts for the different components of U.S. GDP. In line with previous studies, we find that our factor model yields vastly improved forecasts for U.S. GDP, relative to simple autoregressive benchmark models, but we also conclude that the gains in terms of forecasting accuracy differ substantially between GDP components. As a rule of thumb, the largest improvements in terms of forecasting accuracy are found for relatively more volatile series, with the greatest gains coming from improvements of the forecasts for investment and trade. Consumption forecasts, in contrast, perform only marginally better than a simple AR benchmark model. In addition, we show that for most GDP components, an unrestricted, direct forecast outperforms forecasts subject to national accounting identity restrictions. In contrast, GDP itself is best forecasted as the sum of individual forecasts for GDP components, but the improvement over a direct, unconstrained factor forecast is small. |
| Keywords: | Econometric and statistical methods; International topics |
| JEL: | C50 C53 E37 E47 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:bca:bocawp:10-10&r=for |
| By: | Francesco D’Amuri (Economic Research Department); Juri Marcucci (Bank of Italy) |
| Abstract: | We suggest the use of an Internet job-search indicator (the Google Index, GI) as the best leading indicator to predict the US unemployment rate. We perform a deep out-of-sample forecasting comparison analyzing many models that adopt both our preferred leading indicator (GI), the more standard initial claims or combinations of both. We find that models augmented with the GI outperform the traditional ones in predicting the monthly unemployment rate, even in most state-level forecasts and in comparison with the Survey of Professional Forecasters. |
| Keywords: | Google Econometrics, Forecast Comparison, Keyword search, US Unemployment, Time Series Models |
| JEL: | C22 C53 E27 E37 J60 J64 |
| Date: | 2010–03 |
| URL: | http://d.repec.org/n?u=RePEc:fem:femwpa:2010.31&r=for |
| By: | Carstensen, Kai; Wohlrabe, Klaus; Ziegler, Christina |
| Abstract: | In this paper we assess the information content of seven widely cited early indicators for the euro area with respect to forecasting area-wide industrial production. To this end, we use various tests that are designed to compare competing forecast models. In addition to the standard Diebold-Mariano test, we employ tests that account for specific problems typically encountered in forecast exercises. Specifically, we pay attention to nested model structures, we alleviate the problem of data snooping arising from multiple pairwise testing, and we analyze the structural stability in the relative forecast performance of one indicator compared to a benchmark model. Moreover, we consider loss functions that overweight forecast errors in booms and recessions to check whether a specific indicator that appears to be a good choice on average is also preferable in times of economic stress. We find that on average three indicators have superior forecast ability, namely the EuroCoin indicator, the OECD composite leading indicator, and the FAZ-Euro indicator published by the Frankfurter Allgemeine Zeitung. If one is interested in one-month forecasts only, the business climate indicator of the European Commission yields the smallest errors. However, the results are not completely invariant against the choice of the loss function. Moreover, rolling local tests reveal that the indicators are particularly useful in times of unusual changes in industrial production while the simple autoregressive benchmark is difficult to beat during time of average production growth. |
| Keywords: | weighted loss; leading indicators; euro area; forecasting |
| JEL: | C32 C53 E32 |
| Date: | 2010–03 |
| URL: | http://d.repec.org/n?u=RePEc:lmu:muenec:11442&r=for |
| By: | Peter B. Dixon; Maureen T. Rimmer |
| Abstract: | Computable general equilibrium models can be used to generate detailed forecasts of output growth for commodities/industries. The main objective is to provide realistic baselines from which to calculate the effects of policy changes. In this paper, we assess a CGE forecasting method that has been applied in policy analyses in the U.S. and Australia. Using data available up to 1998, we apply the method with the USAGE model to generate "genuine forecasts" for 500 U.S. commodities/industries for the period 1998 to 2005. We then compare these forecasts with actual outcomes and with alternate forecasts derived as extrapolated trends from 1992 to 1998. |
| Keywords: | CGE validation Forecasting U S CGE |
| JEL: | C68 E37 F14 |
| Date: | 2009–05 |
| URL: | http://d.repec.org/n?u=RePEc:cop:wpaper:g-197&r=for |
| By: | Philip Hans Franses (Erasmus School of Economics, Erasmus University Rotterdam); Michael McAleer (Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute); Rianne Legerstee (Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute) |
| Abstract: | Macroeconomic forecasts are frequently produced, published, discussed and used. The formal evaluation of such forecasts has a long research history. Recently, a new angle to the evaluation of forecasts has been addressed, and in this review we analyse some recent developments from that perspective. The literature on forecast evaluation predominantly assumes that macroeconomic forecasts are generated from econometric models. In practice, however, most macroeconomic forecasts, such as those from the IMF, World Bank, OECD, Federal Reserve Board, Federal Open Market Committee (FOMC) and the ECB, are based on econometric model forecasts as well as on human intuition. This seemingly inevitable combination renders most of these forecasts biased and, as such, their evaluation becomes non-standard. In this review, we consider the evaluation of two forecasts in which: (i) the two forecasts are generated from two distinct econometric models; (ii) one forecast is generated from an econometric model and the other is obtained as a combination of a model, the other forecast, and intuition; and (iii) the two forecasts are generated from two distinct combinations of different models and intuition. It is shown that alternative tools are needed to compare and evaluate the forecasts in each of these three situations. These alternative techniques are illustrated by comparing the forecasts from the Federal Reserve Board and the FOMC on inflation, unemployment and real GDP growth. |
| Date: | 2010–03 |
| URL: | http://d.repec.org/n?u=RePEc:tky:fseres:2010cf729&r=for |
| By: | James Mitchell; Bache, I.W., Ravazzolo, F., Vahey, S.P. |
| Abstract: | We argue that the next generation of macro modellers at Inflation Targeting central banks should adapt a methodology from the weather forecasting literature known as `ensemble modelling\\\'. In this approach, uncertainty about model specifications (e.g., initial conditions, parameters, and boundary conditions) is explicitly accounted for by constructing ensemble predictive densities from a large number of component models. The components allow the modeller to explore a wide range of uncertainties; and the resulting ensemble `integrates out\\\' these uncertainties using time-varying weights on the components. We provide two examples of this modelling strategy: (i) forecasting inflation with a disaggregate ensemble; and (ii) forecasting inflation with an ensemble DSGE. |
| Date: | 2009–08 |
| URL: | http://d.repec.org/n?u=RePEc:nsr:niesrd:337&r=for |
| By: | Torsten Schmidt; Helmut Hofer; Klaus Weyerstrass |
| Abstract: | Government agencies and other national and international institutions are asked to perform forecasts over the medium term. In particular, the EU Stability and Growth Pact contains the obligation to formulate stability programmes over four years, covering a general economic outlook as well as the projected development of public fi nances. However, the current practice of performing medium-term economic projections is unsatisfactory from a methodological point of view as the applied methodology has been developed for short-run forecasting and it is questionable whether these methods are useful for the medium term. In particular, currently medium-term projections are mostly based on the neoclassical Solow growth model with an aggregate production function with labour, capital, and exogenous technological progress. It might be argued, however, that for medium-run projections endogenous growth models might be better suited. In this paper we give an overview of currently used methods for medium-term macroeconomic projections. Then we analyse the performance of medium-term forecasts for Austria to illustrate the strengths and weaknesses of the typical approach. In particular, the fi ve-year projections of real GDP growth, infl ation and the unemployment rate are investigated. Finally, we describe some approaches to improve medium-run projections. |
| Keywords: | Econometric models; macroeconomic forecasts; aggregate production function; Austria |
| JEL: | C53 E32 E37 E66 |
| Date: | 2010–03 |
| URL: | http://d.repec.org/n?u=RePEc:rwi:repape:0177&r=for |
| By: | Guglielmo Maria Caporale; Davide Ciferri; Allessandro Girardi |
| Abstract: | We investigate the role of crude oil spot and futures prices in the process of price discovery by using a cost-of-carry model with an endogenous convenience yield and daily data over the period from January 1990 to December 2008. We provide evidence that futures markets play a more important role than spot markets in the case of contracts with shorter maturities, but the relative contribution of the two types of market turns out to be highly unstable, especially for the most deferred contracts. The implications of these results for hedging and forecasting crude oil spot prices are also discussed. |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:diw:diwwpp:dp988&r=for |
| By: | Kitov, Ivan; Kitov, Oleg |
| Abstract: | The predictions of the S&P 500 returns made in 2007 have been tested and the underlying models amended. The period between 2003 and 2008 should be described by the dependence of the S&P 500 stock market index on real GDP because the population pyramid was highly inaccurate. The 2008 trough and 2009 rally are well predicted by the original model, however. The rally will end in March/April 2010 and the S&P 500 level will be decreasing into 2011. This prediction should validate the model. |
| Keywords: | S&P 500; returns; prediction; population pyramid; GDP |
| JEL: | G1 J1 D4 |
| Date: | 2010–03–29 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:21733&r=for |