World Economy

World Economy

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Matsusaka & Sbordone (1995) used quarterly data from 1953 to 1988 to empirically investigate the relationship between consumer confidence and Gross National Product in the United States. Using vector auto regressions Matsusaka ( 1995) & Afshar, Arabian, Zomorrodian (2007) examined the effect of pure confidence on GNP by implementing control variables such as the Index of leading indicators & Consumer price index respectively; finding that confidence granger caused GNP for 1, 2, 3 & 4 quarter lag models. Through forecast error variance decompositions they concluded that 12%-26% & 8-23% of the variation in GNP can be attributed to consumer confidence. The slight variations in the decompositions can b accounted for by variable orderings and differing time periods.
Similarly Utaka (2003) applied the same methodology used by Matsusaka & Sbordone(1995) to empirically investigate this relationship in the case of Japan. By using not only quarterly data, but monthly and semi annual data from 1980q1- 2000q3 they reconfirmed the consumer confidence- GDP relationship for Japan and found that it accounted for 9%-11% of variation in GNP. This showed smaller variation for Japan illustrating that confidence indicators influence on GDP movements are country dependent making it unwise to assume uniform relationship strength across countries.
Golinelli & Parigi (2004) investigated this matter by analysing the consumer confidence relationship in eight country’s from 1970-2002. They modelled the CCI-GDP relationship using a co-integrated vector auto regression using a common set of macroeconomic variables that were country specific to control for correlation being driven by other variables; therefore avoiding the limits of the single equation approach found in previous literature. They tested the forecasting power by comparing the RMSE for unrestricted and restricted models for 1, 2 & 4 steps horizons. Golinelli (2004), Mourougane & Roma (2002), Taylor & Mcnab (2007) find that RMSE was generally lower in the unrestricted model at short term horizons (1-2 steps) for EU countries, illustrating its importance in short term forecasting.
Much of previous literature has aimed at establishing whether consumer confidence indexes provide additional information in comparison to macroeconomic variables and not its forecasting power. However, these have received mixed results in most cases, yet it is acknowledged they maintained an autonomous role in forecasting, (see “Mueller 1963, Adams 1964, Suits &sparks 1965, fair 1971 a & 1971b, Adams & Klein 1972”). Opinion now acknowledges that the index can help predict economic activity (see “Garner 1991, Fuhrer 1993; Carol et al 1994, Kumar et al 1995, Bran & Ludvigson 1998, Eppright et al 1998”)

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Related literature in the case of Carroll et al (1994) found that consumer confidence did have forecasting capabilities in regard to predicting household expenditure. Consumption accounts for two thirds of US GDP & such factors that drive consumption must in essence drive GDP. This coupled with Katona’s (1972) proposal that consumer confidence indicators are merely a representation of consumer ‘willingness to buy’ and expectations of an economy it seems appropriate to investigate whether consumer confidence can predict GDP growth and how they differ across countries.

It is important to note, the majority of previous investigations have used single equation/bi-variate approaches and have paid little or no attention to the multivariate relationship between confidence and other macroeconomic variables. Insufficient attention is paid to the behaviour of the index in different periods, i.e. how well consumer confidence reacts in shock periods and the cross country variations. Katona's (1973) suggestion that consumer confidence is influenced by psychological factors appear to have more importance when these crisis events occur (at times people are more likely to alter their mind frame) peoples answer to questions on their well being seem to be dependant, not on their absolute wealth but their relative wealth compare to their neighbours and hence (keeping up with the Joneses) really does become significant.
However not all literature agrees with the view of confidence index forecasting powers. Emerson & Hendry (1994) use a Vector auto regression to find that leading indicators add no addition information in forecasting. Authors have studied leading indicators concluding limitations are numerous, due to the fact they are frequently revised and open to subjectivity. Weale (1996) finds they do not lead for long however Stock & Watson (1992) state the choice of the indicators chosen for any model is the absolute key source of uncertainty in a model specification and forecasting..

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