A Comparison of Monthly Global Indicators for Forecasting Growth
Christiane Baumeister, Pierre Guérin
Abstract
This paper evaluates the predictive content of a set of alternative monthly indicators of global economic activity for nowcasting and forecasting quarterly world GDP using mixed-frequency models. We find that a recently proposed indicator that covers multiple dimensions of the global economy consistently produces substantial improvements in forecast accuracy, while other monthly measures have more mixed success. This global economic conditions indicator contains valuable information also for assessing the current and future state of the economy for a set of individual countries and groups of countries. We use this indicator to track the evolution of the nowcasts for the US, the OECD area, and the world economy during the coronavirus pandemic and quantify the main factors driving the nowcasts.
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Regional, Individual and Political Determinants of FOMC Members' Key Macroeconomic Forecasts
Stefan Eichler, Tom Lähner
Journal of Forecasting,
No. 1,
2018
Abstract
We study Federal Open Market Committee members' individual forecasts of inflation and unemployment in the period 1992–2004. Our results imply that Governors and Bank presidents forecast differently, with Governors submitting lower inflation and higher unemployment rate forecasts than bank presidents. For Bank presidents we find a regional bias, with higher district unemployment rates being associated with lower inflation and higher unemployment rate forecasts. Bank presidents' regional bias is more pronounced during the year prior to their elections or for nonvoting bank presidents. Career backgrounds or political affiliations also affect individual forecast behavior.
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Much Ado About Nothing: Sovereign Ratings and Government Bond Yields in the OECD
Makram El-Shagi
IWH Discussion Papers,
No. 22,
2016
Abstract
In this paper, we propose a new method to assess the impact of sovereign ratings on sovereign bond yields. We estimate the impulse response of the interest rate, following a change in the rating. Since ratings are ordinal and moreover extremely persistent, it proves difficult to estimate those impulse response functions using a VAR modeling ratings, yields and other macroeconomic indicators. However, given the highly stochastic nature of the precise timing of ratings, we can treat most rating adjustments as shocks. We thus no longer rely on a VAR for shock identification, making the estimation of the corresponding IRFs well suited for so called local projections – that is estimating impulse response functions through a series of separate direct forecasts over different horizons. Yet, the rare occurrence of ratings makes impulse response functions estimated through that procedure highly sensitive to individual observations, resulting in implausibly volatile impulse responses. We propose an augmentation to restrict jointly estimated local projections in a way that produces economically plausible impulse response functions.
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Do We Need New Modelling Approaches in Macroeconomics?
Claudia M. Buch, Oliver Holtemöller
Financial Cycles and the Real Economy: Lessons for CESEE Countries,
2014
Abstract
The economic and financial crisis that emerged in 2008 also initiated an intense discussion on macroeconomic research and the role of economists in society. The debate focuses on three main issues. Firstly, it is argued that economists failed to predict the crisis and to design early warning systems. Secondly, it is claimed that economists use models of the macroeconomy which fail to integrate financial markets and which are inadequate to model large economic crises. Thirdly, the issue has been raised that economists invoke unrealistic assumptions concerning human behaviour by assuming that all agents are self-centred, rationally optimizing individuals. In this paper, we focus on the first two issues. Overall, our thrust is that the above statements are a caricature of modern economic theory and empirics. A rich field of research developed already before the crisis and picked up shortcomings of previous models.
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Forecast Dispersion, Dissenting Votes, and Monetary Policy Preferences of FOMC Members: The Role of Individual Career Characteristics and Political Aspects
Stefan Eichler, Tom Lähner
Public Choice,
No. 3,
2014
Abstract
Using data from 1992 to 2001, we study the impact of members’ economic forecasts on the probability of casting dissenting votes in the Federal Open Market Committee (FOMC). Employing standard ordered probit techniques, we find that higher individual inflation and real GDP growth forecasts (relative to the committee’s median) significantly increase the probability of dissenting in favor of tighter monetary policy, whereas higher individual unemployment rate forecasts significantly decrease it. Using interaction models, we find that FOMC members with longer careers in government, industry, academia, non-governmental organizations (NGOs), or on the staff of the Board of Governors are more focused on output stabilization, while FOMC members with longer careers in the financial sector or on the staffs of regional Federal Reserve Banks are more focused on inflation stabilization. We also find evidence that politics matters, with Republican appointees being much more focused on inflation stabilization than Democratic appointees. Moreover, during the entire Clinton administration ‘natural’ monetary policy preferences of Bank presidents and Board members for inflation and output stabilization were more pronounced than under periods covering the administrations of both George H.W. Bush and George W. Bush, respectively.
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Do We Need New Modelling Approaches in Macroeconomics?
Claudia M. Buch, Oliver Holtemöller
IWH Discussion Papers,
No. 8,
2014
Abstract
The economic and financial crisis that emerged in 2008 also initiated an intense discussion on macroeconomic research and the role of economists in society. The debate focuses on three main issues. Firstly, it is argued that economists failed to predict the crisis and to design early warning systems. Secondly, it is claimed that economists use models of the macroeconomy which fail to integrate financial markets and which are inadequate to model large economic crises. Thirdly, the issue has been raised that economists invoke unrealistic assumptions concerning human behaviour by assuming that all agents are self-centred, rationally optimizing individuals. In this paper, we focus on the first two issues. Overall, our thrust is that the above statements are a caricature of modern economic theory and empirics. A rich field of research developed already before the crisis and picked up shortcomings of previous models.
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The GVAR Handbook: Structure and Applications of a Macro Model of the Global Economy for Policy Analysis
Filippo di Mauro, M. Hashem Pesaran
Oxford University Press,
2013
Abstract
The recent crisis has shown yet again how the world economies are globally interlinked, via a complex net of transmission channels. When it comes, however, to build econometric frameworks aimed at analysing such linkages, modellers are faced with what is called the "curse of dimensionality": there far too many parameters to be estimated with respect to the available observations. The GVAR, a VAR based model of the global economy, offers a solution to this problem. The basic model is composed of a large number of country specific models, comprising domestic, foreign and purely global variables. The foreign variables, however, are treated as weakly exogenous. This assumption, which is typically held when empirically tested for virtually all economies - with the notable exception of the US which is treated differently - allows to estimate first the individual country models separately. Only in a second stage country-specific models are simultaneously solved, thus allowing global interactions.This volume presents - for a first time in a compact and rather easy to read format - principles and structure of the basic GVAR model and a number of its many applications and extensions developed in the last few years by a growing literature. Its main objective is to show how powerful the model can be as a tool for forecasting and scenario analysis. The clear modelling structure of the GVAR appeals to policy makers and practitioners as shown by its growing use among major institutions, as well as by econometricians, as shown by the main extensions and applications.
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The Financial Crisis from a Forecaster's Perspective
Katja Drechsel, Rolf Scheufele
Kredit und Kapital,
No. 1,
2012
Abstract
This paper analyses the recession in 2008/2009 in Germany. This recession is very different from previous recessions in particular regarding their causes and magnitude. We show to what extent forecasters and forecasts based on leading indicators fail to detect the timing and the magnitude of the recession. This study shows that large forecast errors for both expert forecasts and forecasts based on leading indicators resulted during this recession which implies that the recession was very difficult to forecast. However, some leading indicators (survey data, risk spreads, stock prices) have indicated an economic downturn and hence, beat univariate time series models. Although the combination of individual forecasts provides an improvement compared to the benchmark model, the combined forecasts are worse than several individual models. A comparison of expert forecasts withthe best forecasts based on leading indicators shows only minor deviations. Overall, the range for an improvement of expert forecasts in the crisis compared to indicator forecasts is small.
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Stock Market Firm-Level Information and Real Economic Activity
Filippo di Mauro, Fabio Fornari, Dario Mannucci
ECB Working Paper,
No. 1366,
2011
Abstract
We provide evidence that changes in the equity price and volatility of individual firms (measures that approximate the definition of 'granular shock' given in Gabaix, 2010) are key to improve the predictability of aggregate business cycle fluctuations in a number of countries. Specifically, adding the return and the volatility of firm-level equity prices to aggregate financial information leads to a significant improvement in forecasting business cycle developments in four economic areas, at various horizons. Importantly, not only domestic firms but also foreign firms improve business cycle predictability for a given economic area. This is not immediately visible when one takes an unconditional standpoint (i.e. an average across the sample). However, conditioning on the business cycle position of the domestic economy, the relative importance of the two sets of firms - foreign and domestic - exhibits noticeable swings across time. Analogously, the sectoral classification of the firms that in a given month retain the highest predictive power for future IP changes also varies significantly over time as a function of the business cycle position of the domestic economy. Limited to the United States, predictive ability is found to be related to selected balance sheet items, suggesting that structural features differentiate the firms that can anticipate aggregate fluctuations from those that do not help to this aim. Beyond the purely forecasting application, this finding may enhance our understanding of the underlying origins of aggregate fluctuations. We also propose to use the cross sectional stock market information to macro-prudential aims through an economic Value at Risk.
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Flow of Conjunctural Information and Forecast of Euro Area Economic Activity
Katja Drechsel, L. Maurin
Journal of Forecasting,
No. 3,
2011
Abstract
Combining forecasts, we analyse the role of information flow in computing short-term forecasts up to one quarter ahead for the euro area GDP and its main components. A dataset of 114 monthly indicators is set up and simple bridge equations are estimated. The individual forecasts are then pooled, using different weighting schemes. To take into consideration the release calendar of each indicator, six forecasts are compiled successively during the quarter. We found that the sequencing of information determines the weight allocated to each block of indicators, especially when the first month of hard data becomes available. This conclusion extends the findings of the recent literature. Moreover, when combining forecasts, two weighting schemes are found to outperform the equal weighting scheme in almost all cases. Compared to an AR forecast, these improve by more than 40% the forecast performance for GDP in the current and next quarter.
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