Forecasting Manufacturing Output Growth Using Firm-Level Survey Data

Traditionally forecasts of macroeconomic aggregates are extracted from prospective qualitative survey data by relating official data on the aggregate to both the proportion of survey respondents who are "optimists" and the proportion who are "pessimists". But there is no reason to focus on these proportions to the exclusion of other possible means of aggregating and quantifying the underlying panel of respondent or firm-level survey responses. Accordingly in this paper we show how the panel of firm-level responses underlying these proportions can be exploited to derive forecasts of (aggregate) manufacturing output growth that do not lose information that may be contained in the pattern of individual responses. An application using firm-level prospective survey data from the Confederation of British Industry shows that the forecasts of manufacturing output growth derived using these "disaggregate" methods mark an improvement over the so-called "aggregate" methods based on use of the proportions data alone.

[1]  James Mitchell,et al.  Quantification of Qualitative Firm-Level Survey Data , 2002 .

[2]  Richard J. Smith,et al.  Aggregate versus Disaggregate Survey-Based Indicators of Economic Activity , 2002 .

[3]  W. Newey,et al.  Large sample estimation and hypothesis testing , 1986 .

[4]  Cheng Hsiao,et al.  Analysis of Panel Data , 1987 .

[5]  F. Schiantarelli,et al.  A Qualitative Response Analysis of UK Firms' Employment and Output Decisions , 1989 .

[6]  Giovanni Urga,et al.  Transforming Qualitative Survey Data: Performance Comparisons for the UK , 2004 .

[7]  Roy Batchelor,et al.  Expectations, output and inflation: The European experience , 1982 .

[8]  M. Hashem Pesaran,et al.  The Limits to Rational Expectations , 1988 .

[9]  S. Gregoir,et al.  Measuring the Probability of a Business Cycle Turning Point by Using a Multivariate Qualitative Hidden Markov Model , 2000 .

[10]  Richard J. Smith,et al.  Applied Economics and Public Policy: Measurement errors and data estimation: the quantification of survey data , 1998 .

[11]  R. Batchelor Aggregate expectations under the stable laws , 1981 .

[12]  Maurizio Bovi Consumers Sentiment and Cognitive Macroeconometrics Paradoxes and Explanations , 2006 .

[13]  Richard A. Ashley,et al.  Statistically significant forecasting improvements: how much out-of-sample data is likely necessary? ☆ , 2003 .

[14]  Whitney K. Newey,et al.  Efficient estimation of limited dependent variable models with endogenous explanatory variables , 1987 .

[15]  David C. Ribar,et al.  Analysis of panel data: Second Edition, Cheng Hsiao, Cambridge University Press, Cambridge, United Kingdom, 2003, ISBN 0-521-81855-9, 382 pages, [UK pound]21.95 , 2004 .

[16]  S. Wren‐Lewis The Quantification of Survey Data on Expectations∗ , 1985, National Institute Economic Review.

[17]  S. Chib,et al.  Bayesian analysis of binary and polychotomous response data , 1993 .

[18]  Richard Blundell,et al.  An Exogeneity Test for a Simultaneous Equation Tobit Model with an Application to Labor Supply , 1986 .

[19]  Marc Nerlove,et al.  Expectations, Plans, and Realizations in Theory and Practice , 1983 .

[20]  Michael McAleer,et al.  Alternative Procedures for Converting Qualitative Response Data to Quantitative Expectations: An Application to Australian Manufacturing , 1995 .

[21]  Horst Entorf,et al.  Constructing leading indicators from non-balanced sectoral business survey series , 1993 .

[22]  Serena Ng,et al.  Tests for Skewness, Kurtosis, and Normality for Time Series Data , 2005 .

[23]  James B. Mitchell,et al.  The Use of Non-Normal Distributions in Quantifying Qualitative Survey Data , 2002 .

[24]  J. Madsen The predictive value of production expectations in manufacturing industry , 1993 .

[25]  Nicholas S. Souleles Expectations, Heterogeneous Forecast Errors, and Consumption: Micro Evidence from the Michigan Consumer Sentiment Surveys , 2004 .

[26]  H. Erkel-Rousse,et al.  Conjonctures sectorielles et prévision à court terme de l'activité : l'apport de l'enquête de conjoncture dans les services , 2002 .

[27]  G. Parigi,et al.  Quarterly forecasts of the italian business cycle by means of monthly economic indicators , 1995 .

[28]  M. Pesaran,et al.  Survey Expectations , 2005, SSRN Electronic Journal.

[29]  W. Branch The Theory of Rationally Heterogeneous Expectations: Evidence from Survey Data on Inflation Expectations , 2004 .

[30]  F. Hild Une lecture enrichie des réponses aux enquêtes de conjoncture , 2002 .