International interdependence of business cycles in the manufacturing industry: The use of leading indicators for forecasting and analysis

This article introduces new leading indicators for fifteen industrialized countries which enable the business cycle in manufacturing to be forecast fairly reliably between 4 and 6 months ahead. These indicators are based on an improved variant of the NBER method, yielding a composite leading indicator characterized by less erratic movements and clear turning points. The indicators are used to explore the international interdependence of business cycles and to examine the degree to which this interdependence is affected by growing economic integration, as in the EC. For each of the countries studied, the various foreign economies affecting the local business climate are identified. Since the business cycles of some countries clearly lead those of others, this international interdependence can be used to further improve the predictive power of the leading indicators in the lagging countries.     

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.     

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.     

Nowcasting quarterly GDP growth in a monthly coincident indicator model

This paper presents an extension of the Stock and Watson coincident indicator model that allows one to include variables available at different frequencies while taking care of missing observations at any time period. The proposed procedure provides estimates of the unobserved common coincident component, of the unobserved monthly series underlying any included quarterly indicator, and of any missing values in the series. An application to a coincident indicator model for the Portuguese economy is presented. We use monthly indicators from business surveys whose results are published with a very short delay. By using the available data for the monthly indicators and for quarterly real GDP, it becomes possible to produce simultaneously a monthly composite index of coincident indicators and an estimate of the latest quarter real GDP growth well ahead of the release of the first official figures. Copyright © 2005 John Wiley & Son, Ltd.     

A leading indicator approach to predicting short‐term shifts in demand for business travel by air to and from the UK

This paper uses the probit model to examine whether leading indicator information could be used for the purpose of predicting short‐term shifts in demand for business travel by air to and from the UK. Leading indicators considered include measures of business expectations, availability of funds for corporate travel and some well‐known macroeconomic indicators. The model performance is evaluated on in‐ and out‐of‐sample basis, as well as against a linear leading indicator model, which is used to mimic the current forecasting practice in the air transport industry. The estimated probit model is shown to provide timely predictions of the early 1980s and 1990s industry recessions and is shown to be more accurate than the benchmark linear model. Copyright © 2005 John Wiley & Sons, Ltd.     

In search of leading indicators of economic activity in Germany

In this paper we present two new composite leading indicators of economic activity in Germany estimated using a dynamic factor model with and without regime switching. The obtained optimal inferences of business cycle turning points indicate that the two‐state regime switching procedure leads to a successful representation of the sample data and provides an appropriate tool for forecasting business conditions. Copyright © 2003 John Wiley & Sons, Ltd.     

Traditional versus unobserved components methods to forecast quarterly national account aggregates

We aim to assess the ability of two alternative forecasting procedures to predict quarterly national account (QNA) aggregates. The application of Box–Jenkins techniques to observed data constitutes the basis of traditional ARIMA and transfer function methods (BJ methods). The alternative procedure exploits the information of unobserved high‐ and low‐frequency components of time series (UC methods). An informal examination of empirical evidence suggests that the relationships between QNA aggregates and coincident indicators are often clearly different for diverse frequencies. Under these circumstances, a Monte Carlo experiment shows that UC methods significantly improve the forecasting accuracy of BJ procedures if coincident indicators play an important role in such predictions. Otherwise (i.e., under univariate procedures), BJ methods tend to be more accurate than the UC alternative, although the differences are small. We illustrate these findings with several applications from the Spanish economy with regard to industrial production, private consumption, business investment and exports. Copyright © 2007 John Wiley & Sons, Ltd.     

Which survey indicators are useful for monitoring consumption? Evidence from European countries

This paper assesses the information content of two survey indicators for consumption developments in the near future for eight European countries in the period 1985–1998. Empirical work on this topic typically focuses on consumer confidence, the perceptions of buyers of consumption goods. This paper examines whether perceptions of sellers of consumption goods, measured by retail trade surveys, may also improve short‐term monitoring of consumption. We find that both consumer confidence and retailer confidence embody valuable information, when analysed in isolation. For France, Italy and Spain we conclude that adding retail confidence does not improve the indicator model once consumer confidence has been included. For the UK the reverse case is obtained. For the remaining four countries we show that combining consumer sentiment and retail trade confidence into a composite indicator leads to optimal results. Our results suggest that incorporating information from retail trade surveys may offer significant benefits for the analysis of short‐term prospects of consumption. Copyright © 2004 John Wiley & Sons, Ltd.     

Monetary policy,composite leading economic indicators and predicting the 2001 recession

On 26 November 2001, the National Bureau of Economic Research announced that the US economy had officially entered into a recession in March 2001. This decision was a surprise and did not end all the conflicting opinions expressed by economists. This matter was finally settled in July 2002 after a revision to the 2001 real gross domestic product showed negative growth rates for its first three quarters. A series of political and economic events in the years 2000–01 have increased the amount of uncertainty in the state of the economy, which in turn has resulted in the production of less reliable economic indicators and forecasts. This paper evaluates the performance of two very reliable methodologies for predicting a downturn in the US economy using composite leading economic indicators (CLI) for the years 2000–01. It explores the impact of the monetary policy on CLI and on the overall economy and shows how the gradualness and uncertainty of this impact on the overall economy have affected the forecasts of these methodologies. It suggests that the overexposure of the CLI to the monetary policy tools and a strong, but less effective, expansionary money policy have been the major factors in deteriorating the predictions of these methodologies. To improve these forecasts, it has explored the inclusion of the CLI diffusion index as a prior in the Bayesian methodology. Copyright © 2004 John Wiley & Sons, Ltd.     

Modeling European industrial production with multivariate singular spectrum analysis: A cross‐industry analysis

In this paper, an optimized multivariate singular spectrum analysis (MSSA) approach is proposed to find leading indicators of cross‐industry relations between 24 monthly, seasonally unadjusted industrial production (IP) series for German, French, and UK economies. Both recurrent and vector forecasting algorithms of horizontal MSSA (HMSSA) are considered. The results from the proposed multivariate approach are compared with those obtained via the optimized univariate singular spectrum analysis (SSA) forecasting algorithm to determine the statistical significance of each outcome. The data are rigorously tested for normality, seasonal unit root hypothesis, and structural breaks. The results are presented such that users can not only identify the most appropriate model based on the aim of the analysis, but also easily identify the leading indicators for each IP variable in each country. Our findings show that, for all three countries, forecasts from the proposed MSSA algorithm outperform the optimized SSA algorithm in over 70% of cases. Accordingly, this new approach succeeds in identifying leading indicators and is a viable option for selecting the SSA choices L and r, which minimizes a loss function.     

The leading indicator approach to economic forecasting—retrospect and prospect

Our purpose in this paper is to explain briefly the theory and rationale underlying the leading, coincident and lagging indicators, describe the more important statistical procedures used, and review the evidence on how the indicators have performed in practice. The tests of performance concentrate on data not used in the selection of the indicators, in the United States and nine other countries. We conclude with some suggestions for future research and development, including the application of the approach to the analysis of inflation.     

A Novel Credit Rating Migration Modeling Approach Using Macroeconomic Indicators

Modeling credit rating migrations conditional on macroeconomic conditions allows financial institutions to assess, analyze, and manage the risk related to a credit portfolio. Existing methodologies to model credit rating migrations conditional on the business cycle suffer from poor accuracy, difficult readability, or model inconsistencies. The modeling methodology proposed in this paper extends ordinal logistic regression to estimate the complete migration matrix including default rates as a function of rating dynamics and macroeconomic indicators. The gradient and Hessian derivations show efficient optimization within the Levenberg–Marquardt algorithm. The proposed modeling methodology is applied to model corporate rating migrations using historical data from 1984 to 2011. It is shown that the resulting model captures the cyclical behavior of credit rating migrations and default rates, and is able to approximate historic migration levels with good precision. The model therefore permits analysis of the impact of economical downturn conditions on a credit portfolio. Copyright © 2013 John Wiley & Sons, Ltd.     

Forecasting UK industrial production over the business cycle

This paper examines the information available through leading indicators for modelling and forecasting the UK quarterly index of production. Both linear and non‐linear specifications are examined, with the latter being of the Markov‐switching type as used in many recent business cycle applications. The Markov‐switching models perform relatively poorly in forecasting the 1990s production recession, but a three‐indicator linear specification does well. The leading indicator variables in this latter model include a short‐term interest rate, the stock market dividend yield and the optimism balance from the quarterly CBI survey. Copyright © 2001 John Wiley & Sons, Ltd.     

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.     

Empirical analysis of systematic errors in Chilean GDP forecasts

This paper presents a statistical comparison between the actual and predicted evolution of the Chilean GDP for the period 1986 – 1998 made by several forecasters. We show that the forecasters systematically underestimate the true growth rate of the economy. The magnitude of this bias tends to be correlated with the phase of the business cycle. Copyright © 2001 John Wiley & Sons, Ltd.     

Evaluating the OECD’s main economic indicators at anticipating recessions*

Using receiver operating characteristic (ROC) techniques, we evaluate the predictive content of the monthly main economic indicators (MEI) of the Organization for Economic Co‐operation and Development (OECD) for predicting both growth cycle and business cycle recessions at different horizons. From a sample that covers 123 indicators for 32 OECD countries as well as for Brazil, China, India, Indonesia, the Russian Federation, and South Africa, our results suggest that the OECD's MEI show a high overall performance in providing early signals of economic downturns worldwide, albeit they perform a bit better at anticipating business cycles than growth cycles. Although the performance for OECD and non‐OECD members is similar in terms of timeliness, the indicators are more accurate at anticipating recessions for OECD members. Finally, we find that some single indicators, such as interest rates, spreads, and credit indicators, perform even better than the composite leading indicators.     

Forecasting Private Consumption by Consumer Surveys

Survey‐based indicators are widely seen as leading indicators for economic activity. As such, consumer confidence might be informative for the future path of private consumption. Although the indicators receive high attention in the media, their forecasting power often appears to be very limited. This paper takes a fresh look at the data that serve as a basis for the consumer confidence indicator (CCI) reported by the EU Commission for the euro area. Different pooling methods are applied to exploit the survey information. Forecasts are based on mixed data sampling (MIDAS) and bridge equations. While the CCI does not outperform the autoregressive benchmark, the new indicators are able to raise forecasting performance. The best performing indicator should be built upon pre‐selection methods. Data‐driven aggregation methods should be preferred to determine the weights of the individual ingredients. Copyright © 2011 John Wiley & Sons, Ltd.     

Predicting cyclical turning points with leading index in a markov switching model

We have evaluated the Commerce Department's Composite Index of Leading Indicators as a predictor of business cycle turning points using the two-state Markov switching model as the filter. Contrary to some recent studies, we found that the predictive performance of CLI is quite good and, with an exception of the 1973:11 peak, it made very little difference to the prediction of turning points whether real-time data are used instead of the revised series. We found, however, that imposing any degree of autoregression in the errors on the simple regime-shift model caused the filter to signal turning points inappropriately. Also, we found no evidence of duration dependence in post-war U.S. business cycles.     

Measuring downside risk and severity for global output

This paper attempts to provide a critical measure of downside risk and severity for global output by applying the Value at Risk approach to four country groups in the world as a ‘portfolio’. Global output downside risk, measured by global Growth at Risk (GaR), estimates the worst possible growth decline, relative to the baseline projection, with a specified probability over a given time horizon. This measure serves as a practical summary for predicting the risk for output downturn given a one‐year time horizon, based on the past growth distribution of individual countries and correlation among their growth rates. Our empirical estimates show that the downside risk that the world economy faced in 2002 was not as severe as the last global downturn in 1992–1993. In particular, the global GaR estimates that the worst outcome of the global economy in 2002, at 95% confidence level, was a growth rate of 0.34%. Copyright © 2007 John Wiley & Sons, Ltd.     

Evaluating early warning and coincident indicators of business cycles using smooth trends

We present a composite coincident indicator designed to capture the state of the Spanish economy. Our approach, based on smooth trends, guarantees that the resulting indicators are reasonably smooth and issue stable signals, reducing the uncertainty. The coincident indicator has been checked by comparing it with the one recently proposed by the Spanish Economic Association index. Both indexes show similar behavior and ours captures very well the beginning and end of the official recessions and expansion periods. Our coincident indicator also tracks very well alternative mass media indicators typically used in the political science literature. We also update our composite leading indicator (Bujosa et al., Journal of Forecasting, 2013, 32(6), 481–499). It systematically predicts the peaks and troughs of the new Spanish Economic Association index and provides significant aid in forecasting annual gross domestic product growth rates. Using only real data available at the beginning of each forecast period, our indicator one-step-ahead forecast shows improvements over other individual alternatives and different forecast combinations.