Pre‐recession pattern of six economic indicators in the USA

This paper applies a tightly parameterized pattern recognition algorithm, previously applied to earthquake prediction, to the problem of predicting recessions. Monthly data from 1962 to 1996 on six leading and coincident economic indicators for the USA are used. In the full sample, the model performs better than benchmark linear and non‐linear models with the same number of parameters. Subsample and recursive analysis indicates that the algorithm is stable and produces reasonably accurate forecasts even when estimated using a small number of recessions. Copyright © 2000 John Wiley & Sons, Ltd.     

Professional forecasters' expectations,consistency, and international spillovers

This paper focuses on the expectation formation process of professional forecasters by relying on survey data on forecasts regarding gross domestic product growth, consumer price index inflation and 3-month interest rates for a broad set of countries. We examine the interrelation between macroeconomic forecasts and also the impact of uncertainty on forecasts by allowing for cross-country interdependencies and time variation in the coefficients. We find that professional forecasts are often in line with the Taylor rule and identify significant expectation spillovers from monetary policy in the USA.     

Forecasting trend output in the Euro area

This paper is an applied study about forecasting trend output and the output gap in the Euro area. The need for trend output forecasts is justified by an analysis of the monetary strategy of the European Central Bank. Trend output serves as a direct inflation indicator and helps to determine the reference value for money. For both purposes, trend output has to be forecasted. A permanent–transitory decomposition based on cointegration restrictions gives an estimate of trend output in the Euro area. Ex‐ante point forecasts of trend output are computed and bootstrap simulation is employed to construct prediction intervals that take estimation uncertainty into consideration. The uncertainty of trend output and the output gap is quite large and raises questions about their usefulness as indicators for monetary policy. Copyright © 2002 John Wiley & Sons, Ltd.     

Do Media Data Help to Predict German Industrial Production?

In an uncertain world, decisions by market participants are based on expectations. Therefore, sentiment indicators reflecting expectations have a proven track record at predicting economic variables. However, survey respondents largely perceive the world through media reports. Here, we want to make use of that. We employ a rich dataset provided by Media Tenor International, based on sentiment analysis of opinion‐leading media in Germany from 2001 to 2014, transformed into several monthly indices. German industrial production is predicted in a real‐time out‐of‐sample forecasting experiment and media indices are compared to a huge set of alternative indicators. Media data turn out to be valuable for 10‐ to 12‐month horizon forecasts, which is in line with the lag between monetary policy announcements and their effect on industrial production. This holds in the period during and after the Great Recession when many models fail. Copyright © 2016 John Wiley & Sons, Ltd.     

Quarterly forecasts of the italian business cycle by means of monthly economic indicators

Recent years have witnessed a growing availability of high-frequency indicators which can be used to forecast future economic activity. This paper shows how some of the widely known monthly economic indicators at present available in Italy can be used in a systematic and coordinated manner to forecast the main variables of the National Accounts. In order to reduce as much as possible the amount of judgment in the analysis of the business cycle, a model-based approach is adopted. Thus, a pseudo macro-econometric model of the Italian economy is built, which can be used to produce forecasts one semester ahead of the last National Accounts data release. The model can be used autonomously as well as in combination with the Bank of Italy's quarterly econometric model.     

Forecasts of inflation from var models

Why are forecasts of inflation from VAR models so much worse than their forecasts of real variables? This paper documents that relatively poor performance, and finds that the price equation of a VAR model fitted to US post-war data is poorly specified. Statistical work by other authors has found that coefficients in such price equations may not be constant. Based on specific monetary actions, two changes in monetary policy regimes are proposed. Accounting for those two shifts yields significantly more accurate forecasts and lessens the evidence of misspecification.     

Tentative business confidence indicators for the Italian economy

This paper concerns the cyclical evolution of the Italian economy and, in particular, the role of confidence indicators. In the first part of the paper various confidence indicators, computed according to the European Commission (EC) methodology, are investigated. In particular, the analysis concentrates on the dynamics of some business climate indicators referred to the supply side of the economy (i.e. manufacturing, retail and construction industries). In the second part of the analysis, new confidence indicators exploring the wide informative set characterizing the ISAE business surveys are computed. The ability of these indicators in predicting the short‐term evolution of GDP, here considered as a reference series, is compared with that of the previous EC confidence indicators. Finally, in the third part, some estimates of the relationship between the chosen business confidence indicator and some driving variables are presented. Copyright © 2003 John Wiley & Sons, Ltd.     

Vector smooth transition regression models for US GDP and the composite index of leading indicators

In this paper, I extend to a multiple‐equation context the linearity, model selection and model adequacy tests recently proposed for univariate smooth transition regression models. Using this result, I examine the nonlinear forecasting power of the Conference Board composite index of leading indicators to predict both output growth and the business‐cycle phases of the US economy in real time. Copyright © 2004 John Wiley & Sons, Ltd.     

Forecasting the Effects of a Canada–US Currency Union on Output and Prices: A Counterfactual Analysis

This paper is a counterfactual analysis investigating the consequences of the formation of a currency union for Canada and the USA: whether outputs increase and prices decrease if these countries form a currency union. We use a two‐country cointegrated model to conduct the counterfactual analysis, where the conditional forecasts are generated based on the Gaussian assumption. To deal with structural breaks and model uncertainty, conditional forecasts are generated from different models/estimation windows and the model‐averaging technique is used to combine the forecasts. We also examine the robustness of our results to parameter uncertainty using the wild bootstrap method. The results show that forming the currency union would probably boost the Canadian economy, whereas it would not have significant effects on US output or Canadian and US price levels. Copyright © 2013 John Wiley & Sons, Ltd.     

The Effect of Nonlinearity between Credit Conditions and Economic Activity on Density Forecasts

This paper examines the effect of nonlinearities on density forecasting. It focuses on the relationship between credit markets and the rest of the economy. The possible nonlinearity of this relationship is captured by a threshold vector autoregressive model estimated on US data using Bayesian methods. Density forecasts thus account for the uncertainty in all model parameters and possible future regime changes. It is shown that considering nonlinearity can improve the probabilistic assessment of the economic outlook. Moreover, three illustrative examples are discussed to shed some light on the possible practical applicability of density forecasts derived from non‐linear models. Copyright © 2015 John Wiley & Sons, Ltd.     

Medium‐term forecasts of potential GDP and inflation using age structure information

Economic behaviour as well as economic resources of individuals vary with age. Swedish time series show that the age structure contains information correlated to medium‐term trends in growth and inflation. GDP gaps estimated by age structure regressions are closely related to conventional measures. Monetary policy is believed to affect inflation with a lag of 1 or 2 years. Projections of the population's age structure are comparatively reliable several years ahead and provide additional information to improve on 3–5 years‐ahead forecasts of potential GDP and inflation. Thus there is a potential scope for using age structure based forecasts as an aid to monetary policy formation. Copyright © 2004 John Wiley & Sons, Ltd.     

Forecasting US GNP growth: The role of uncertainty

A large number of models have been developed in the literature to analyze and forecast changes in output dynamics. The objective of this paper was to compare the predictive ability of univariate and bivariate models, in terms of forecasting US gross national product (GNP) growth at different forecasting horizons, with the bivariate models containing information on a measure of economic uncertainty. Based on point and density forecast accuracy measures, as well as on equal predictive ability (EPA) and superior predictive ability (SPA) tests, we evaluate the relative forecasting performance of different model specifications over the quarterly period of 1919:Q2 until 2014:Q4. We find that the economic policy uncertainty (EPU) index should improve the accuracy of US GNP growth forecasts in bivariate models. We also find that the EPU exhibits similar forecasting ability to the term spread and outperforms other uncertainty measures such as the volatility index and geopolitical risk in predicting US recessions. While the Markov switching time‐varying parameter vector autoregressive model yields the lowest values for the root mean squared error in most cases, we observe relatively low values for the log predictive density score, when using the Bayesian vector regression model with stochastic volatility. More importantly, our results highlight the importance of uncertainty in forecasting US GNP growth rates.     

Composite leading indicators of underlying inflation for seven EU countries

This paper presents short‐ and long‐term composite leading indicators (CLIs) of underlying inflation for seven EU countries, namely Belgium, Germany, France, Italy, the Netherlands, Sweden and the UK. CLI and CPI reference series are calculated in terms of both growth rates and in deviations from its trend. The composite leading indicators are based on leading basic series, such as sources of inflation, series containing information on inflation expectations and prices of intermediate goods and services. Neftci's decision rule approach has been applied to transfer movements in the CLIs into a measure of the probability of a cyclical turning point, which enables the screening out of false turning point predictions. Finally, CLIs have been used to analyse the international coherence of price cycles. The forecast performance of CLIs of inflation over the past raises hope that this forecast instrument can be useful in predicting future price movements. Copyright © 1999 John Wiley & Sons, Ltd.     

Simulating the European economies under alternative monetary policy assumptions

This paper examines the implications of alternative monetary policy rules for economic stabilization within Europe, using the OECD world model, INTERLINK. The results suggest that policy linkage through the Exchange Rate Mechanism will have differing effects on the effectiveness of stabilization policies depending on the nature of economic shocks. For demand shocks, the choice of monetary rule in the country of the ‘anchor’ currency is of more consequence than the flexibility of exchange rates. For supply shocks, exchange rate rigidity is likely to have more problematic effects on economic adjustment. Spillover effects are also important when the shock is felt primarily by the ‘anchor’ economy.     

What does the tail of the distribution of current stock prices tell us about future economic activity?

This paper proposes three leading indicators of economic conditions estimated using current stock returns. The assumption underlying our approach is that current asset prices reflect all the available information about future states of economy. Each of the proposed indicators is related to the tail of the cross‐sectional distribution of stock returns. The results show that the leading indicators have strong correlation with future economic conditions and usually make better out‐of‐sample predictions than two traditional competitors (random walk and the average of previous observations). Furthermore, quantile regressions reveal that the leading indicators have strong connections with low future economic activity.     

Long‐memory forecasting of US monetary indices

Several studies have tested for long‐range dependence in macroeconomic and financial time series but very few have assessed the usefulness of long‐memory models as forecast‐generating mechanisms. This study tests for fractional differencing in the US monetary indices (simple sum and divisia) and compares the out‐of‐sample fractional forecasts to benchmark forecasts. The long‐memory parameter is estimated using Robinson's Gaussian semi‐parametric and multivariate log‐periodogram methods. The evidence amply suggests that the monetary series possess a fractional order between one and two. Fractional out‐of‐sample forecasts are consistently more accurate (with the exception of the M3 series) than benchmark autoregressive forecasts but the forecasting gains are not generally statistically significant. In terms of forecast encompassing, the fractional model encompasses the autoregressive model for the divisia series but neither model encompasses the other for the simple sum series. Copyright © 2006 John Wiley & Sons, Ltd.     

Model uncertainty and policy choice: A plea for integrated subjectivism

A question at the intersection of scientific modeling and public choice is how to deal with uncertainty about model predictions. This “high-level” uncertainty is necessarily value-laden, and thus must be treated as irreducibly subjective. Nevertheless, formal methods of uncertainty analysis should still be employed for the purpose of clarifying policy debates. I argue that such debates are best informed by models which integrate objective features (which model the world) with subjective ones (modeling the policy-maker). This integrated subjectivism is illustrated with a case study from the literature on monetary policy. The paper concludes with some morals for the use of models in determining climate policy.     

Do monetary policy transparency and central bank communication reduce interest rate disagreement?

Yes. This study produces evidence that monetary policy transparency and communication policy of the Bank of England have information content in reducing disagreement about interest rate forecasts. Different from most extant studies employing the transparency index derived from official documents of the central banks, this study extends the literature by using a recently developed market-based monetary transparency index. Moreover, this study analyzes forecast disagreement in a multivariate perspective based on survey data of short- and long-term rates over short and long horizons. This study characterizes several patterns on forecast disagreement related to maturities of interest rates, forecast horizons, recessions, forward guidance, credibility, transparency, and communication policy. Interestingly, disagreement among the Monetary Policy Committee in policy rate decisions is associated with lower disagreement among professional forecasters on interest rate outlook, whereas neither announcement of changes in policy rates nor publication of inflation reports affects forecast disagreement. These results have important implications for monetary policymakers in managing market expectations of interest rates.     

Forecasting the price evolution of new electronic products

This study tests the hypothesis that prices in new markets change in a pattern similar to and related to the product life cycle. Three stages of price decline have been identified in electronic product markets and can be associated with the introduction, take-off and growth, and maturity stages of the product life cycle. The study integrates the methodologies of the product life cycle concept and experience curve theory and analyses price and product behaviour for radios, monochrome (black and white) televisions, colour televisions and video cassette recorders. The empirical evidence supports the hypothesis and suggests, as a general rule, that a better understanding of a product's life cycle and the factors that affect it can aid in the development of price forecasts. In fact, the marriage of experience curve theory and the product life cycle concept provides a methodology for quantifying the impact of influential factors and gives the analyst the ability to bound the uncertainty around price forecasts, ultimately leading to better strategic decisions, today, for tomorrow's markets.     

Predicting Recessions with Factor Linear Dynamic Harmonic Regressions

We propose a new framework for building composite leading indicators for the Spanish economy using monthly targeted predictors and small‐scale dynamic factor models. Our leading indicator index, based on the low‐frequency components of four monthly economic variables, is able to predict the onset of the Spanish recessions as well as the gross domestic product (GDP) growth cycles and classical industrial production cycles, both historically and in real time. Also, our leading indicator provides substantial aid in forecasting annual and quarterly GDP growth rates. Using only real data available at the beginning of each forecast period, our indicator one‐step‐ahead forecasts shows substantial improvements over other alternatives. Copyright © 2013 John Wiley & Sons, Ltd.