Business Cycles Analysis and Expectational Survey Data

Zarnowitz, Victor

doi:10.3386/w1378

Cited by 5 publications

(3 citation statements)

References 32 publications

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“…This perspective has become increasingly uncommon, however. Zarnowitz (1984) and Lovell (1986) argued against the premise that assumptions should not be tested using micro data. Manski (2004) concluded that the hostility towards surveys is based on meager evidence and suggested that survey expectations provide a viable way to test models of the expectation formation process.…”

Section: Measuring Expectations: From Skepticism To Increasing Acceptmentioning

confidence: 99%

The Formation of Expectations, Inflation, and the Phillips Curve

Coibion

Gorodnichenko

Kamdar

2018

Journal of Economic Literature

302

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This paper argues for a careful (re)consideration of the expectations formation process and a more systematic inclusion of real-time expectations through survey data in macroeconomic analyses. While the rational expectations revolution has allowed for great leaps in macroeconomic modeling, the surveyed empirical microevidence appears increasingly at odds with the full-information rational expectation assumption. We explore models of expectation formation that can potentially explain why and how survey data deviate from full-information rational expectations. Using the New Keynesian Phillips curve as an extensive case study, we demonstrate how incorporating survey data on inflation expectations can address a number of otherwise puzzling shortcomings that arise under the assumption of full-information rational expectations. (JEL D04, E24, E27, E31, E37)

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Section: Measuring Expectations: From Skepticism To Increasing Acceptmentioning

confidence: 99%

The Formation of Expectations, Inflation, and the Phillips Curve

Coibion

Gorodnichenko

Kamdar

2018

Journal of Economic Literature

302

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“…But other economists have different views. For example, Zarnowitz (1984) and Lovell (1986) argued that a theory that claims to have strong microeconomic foundation should be amenable to testing with macro data. Keane and Runkle (1990) also pointed out that we would face an identification problem if only indirect joint tests could be performed.…”

Section: Brief Literature Reviewmentioning

confidence: 99%

Rational or irrational expectations? Evidence from China's stock market

Gao

Fu²,

Wang³

2008

The Journal of Risk Finance

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PurposeThe paper aims to test the rational‐expectations hypothesis using data from the Chinese stock market.Design/methodology/approachThe rational‐expectations hypothesis plays a critical role in economic and financial studies. However, it is unclear whether this hypothesis is consistent with real‐world decision making since existing empirical results are mixed. This paper tests the hypothesis directly using survey data from China's stock market by developing a technique to analyze discrete or limited independent‐variable models.FindingsThe paper shows that in China's stock market survey forecasts are overly optimistic, especially with positive information, and can be improved slightly using past information.Originality/valueThe paper develops a technique to analyze the discrete or limited independent‐variable model. Testing with Chinese stock market data provides some insights into the characteristics of emerging markets.

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“…He also found that expectations are inefficient. Finally, the most popular data has been the ASA-NBER data on professional forecasts which has been used extensively in papers that include, but are not limited to, Keane and Runkle (1990), Bonham and Cohen (1995), Zarnowjtz (1969Zarnowjtz ( , 1974Zarnowjtz ( , 1984Zarnowjtz ( , 1985, Baghestani and Nelson (2011) and Dovern and Weisser (2011). Regardless of the data set that were used, the most prevalent result that emerged from almost all the papers, with a very few exceptions, is that price forecasts are not rational.…”

Section: Literature Reviewmentioning

confidence: 95%