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Content:By Roland Döhrn and Christoph M. Schmidt, Essen: Information or Institution? On the Determinants of Forecast Accuracy JBNST - Vol. 231/1 - 2011, pp. 9-27.
+ show abstract- hide abstractThe accuracy of macroeconomic forecast depends on various factors, most importantly the mix
of analytical methods used by the individual forecasters, the way that their personal experience
is shaping their identification strategies, but also their efficiency in translating new information
into revised forecasts. In this paper we use a broad sample of forecasts of German GDP and its
components to analyze the impact of institutions and information on forecast accuracy. We
find that forecast errors are a linear function of the forecast horizon, which serves as an indicator
of the information available at the time a forecast is produced. This result is robust over
a variety of different specifications. As better information seems to be the key to achieving
better forecasts, approaches for acquiring reliable information early seem to be a good investment.
By contrast, the institutional factors tend to be small and statistically insignificant. It has
to remain open, whether this is the consequence of the efficiency-enhancing competition
among German research institutions or rather the reflection of an abundance of forecast suppliers. By Christian Schumacher, Frankfurt a.M.: Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP JBNST - Vol. 231/1 - 2011, pp. 28-49.
+ show abstract- hide abstractThis paper provides a review of the recent literature concerned with large factor models as
forecast devices.We focus on factor models that account for mixed-frequency data and missing
observations at the end of the sample. These are data irregularities applied forecasters have to
cope with in real time. To extract the factors from the irregular data, special factor estimation
techniques are necessary, expanding on the standard approaches for balanced data such as
principal components (PC). The estimation methods include variants of the Expectation-Maximisation
(EM) algorithm together with PC and factor estimation using state-space models.
Given the estimated factors, forecasts can be obtained from bridge equations, mixed-data sampling
(MIDAS) regressions and the Kalman smoother applied to fully-fledged factor models in
state-space form. Empirical applications for German GDP growth often find that forecasts
based on factor models are informative only a few months ahead compared to naive benchmarks.
Thus, these models can be regarded as short-term forecast tools only. However, the
factor models estimated on mixed-frequency data with missing observations tend to outperform
factor models based on balanced data time-aggregated from high-frequency data. By Michele Lenza and Thomas Warmedinger, Frankfurt a.M.: A Factor Model for Euro-area Short-term Inflation Analysis JBNST - Vol. 231/1 - 2011, pp. 50-62.
+ show abstract- hide abstractThis paper develops a factor model for forecasting inflation in the euro area. The model can
handle variables with different timeliness, sample size and frequency. We show that the forecasts
based on the factor model outperform na?¨ve random walk forecasts, a hard to beat
benchmark for euro area inflation forecasts in recent years, at horizons of and beyond nine
months ahead. They are also comparable, in terms of accuracy, to the judgemental forecasts
prepared in the context of the Eurosystem macroeconomic projection exercises. The factor
model is therefore a very suitable tool to extract the signal on current and future euro area
inflation from new data releases. By Fabian Krüger, Frieder Mokinski, Winfried Pohlmeier, Konstanz: Combining Survey Forecasts and Time Series Models: The Case of the Euribor JBNST - Vol. 231/1 - 2011, pp. 63-81.
+ show abstract- hide abstractThis paper reinterprets Maganelli’s (2009) idea of “Forecasting with Judgment” to obtain a
dynamic algorithm for combining survey expectations data and time series models for macroeconomic
forecasting. Existing combination approaches typically obtain combined forecasts
by linearly weighting individual forecasts. The approach presented here instead uses survey
forecasts in the estimation stage of a time series model. Thus an estimate of the model parameters
is obtained that reflects two sources of information: a history of realizations of the variables
that are involved in the time series model and survey expectations on the future course of
the variable that is to be forecast. The idea at the estimation stage is to shrink parameter estimates
towards values that are compatible (in an appropriate sense) with the survey forecasts
that have been observed. It is exemplified how this approach can be applied to different autoregressive
time series models. In an empirical application, the approach is used to forecast the
three-month Euribor at a six-month horizon. By Kai Carstensen, Klaus Wohlrabe, Munich, and Christina Ziegler, Leipzig: Predictive Ability of Business Cycle Indicators under Test. A Case Study for the Euro Area Industrial Production JBNST - Vol. 231/1 - 2011, pp. 82-106.
+ show abstract- hide abstractIn 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 checkwhether a specific indicator that appears to be a good choice on average
is also preferable in times of economic stress. We find that none of this indicators uniformly
dominates all its competitors. The optimal choice rather depends on the specific forecast
situation and the loss function of the user. For 1-month forecasts the business climate indicator
of the European Commission and the OECD composite leading indicator generally work well,
for 6-month forecasts the OECD composite leading indicator performs very good by all
criteria, and for 12-month forecasts the FAZ-Euro indicator published by the Frankfurter
Allgemeine Zeitung is the only one that can beat the benchmark AR(1) model. By Helmut Lütkepohl, Firenze: Forecasting Nonlinear Aggregates and Aggregates with Time-varying Weights JBNST - Vol. 231/1 - 2011, pp. 107-133.
+ show abstract- hide abstractDespite the fact that many aggregates are nonlinear functions and the aggregation weights of
many macroeconomic aggregates are time-varying, much of the literature on forecasting aggregates
considers the case of linear aggregates with fixed, time-invariant aggregation weights.
In this study a framework for nonlinear contemporaneous aggregation with possibly stochastic
or time-varying weights is developed and different predictors for an aggregate are compared
theoretically as well as with simulations. Two examples based on European unemployment and
inflation series are used to illustrate the virtue of the theoretical setup and the forecasting results. By Roxana Halbleib , Bruxelles, and Valeri Voev , Aarhus: Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors JBNST - Vol. 231/1 - 2011, pp. 134-152.
+ show abstract- hide abstractThis paper analyzes the forecast accuracy of the multivariate realized volatility model introduced
by Chiriac and Voev (2010), subject to different degrees of model parametrization and
economic evaluation criteria. Bymodelling the Cholesky factors of the covariancematrices, the
model generates positive definite, but biased covariance forecasts. In this paper, we provide
empirical evidence that parsimonious versions of the model generate the best covariance forecasts
in the absence of bias correction. Moreover, we show by means of stochastic dominance
tests that any risk averse investor, regardless of the type of utility function or return distribution,
would be better-off from using this model than from using some standard approaches. By Helmut Hofer, Wien, Torsten Schmidt, Essen, and Klaus Weyerstrass, Wien: Practice and Prospects of Medium-term Economic Forecasting JBNST - Vol. 231/1 - 2011, pp. 153-171.
+ show abstract- hide abstractGovernment 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 finances. 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 mediumterm
forecasts for Austria to illustrate the strengths and weaknesses of the typical approach.
In particular, the five-year projections of real GDP growth, inflation and the unemployment
rate are investigated. Finally, we describe some approaches to improve medium-run projections.
Book Reviews Skedinger, Per: Employment Protection Legislation – Evolution, Effects, Winners and Losers JBNST - Vol. 231/1 - 2011, pp. 172-172.
Vogel, Harold L.: Financial Market Bubbles and Crashes JBNST - Vol. 231/1 - 2011, pp. 173-174.
Wickstrøm, Bengt-Arne (Hrsg.): Finanzpolitik und Unternehmensentscheidung JBNST - Vol. 231/1 - 2011, pp. 175-175.
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