Measurement Errors and Tests for Rationality

Jeong, Jinook; Maddala, G. S.

doi:10.1080/07350015.1991.10509870

Cited by 20 publications

(9 citation statements)

References 23 publications

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“…Similar problems with measurement errors in the survey data on market expectations has been highlighted in the macroeconomic literature, where it is argued that the error-invariables problem results in biased parameter estimates (e.g., Dietrich and Joines 1983;Figlewski and Wachtel 1983) and a rejection of the rationality hypothesis (e.g., Jeong and Maddala 1991). Measurement errors violate the assumption of independence between the regression error term and regressors in an OLS framework, and thereby result in a smaller R-squared value as well as coefficient estimates biased toward zero.…”

Section: Measurement Errors and Their Econometric Consequencesmentioning

confidence: 59%

Supply Fundamentals and Grain Futures Price Movements

Karali¹,

Irwin²,

Isengildina‐Massa³

2019

American J Agri Economics

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A long‐standing puzzle in commodity markets is the low explanatory power of supply and demand fundamentals for explaining the variability of prices in these markets. We apply an instrumental variable correction for measurement errors to investigate how noise in the surprise component of USDA Crop Production reports affects estimated price responses in corn, soybeans, and wheat futures markets from 1970 to 2016. Our findings demonstrate that after correcting for measurement error in market surprises, the explanatory power of our models increases about threefold and often exceeds 70%. This is compelling evidence that fundamental supply news play an important role in explaining grain futures price movements.

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Section: Measurement Errors and Their Econometric Consequencesmentioning

confidence: 59%

Supply Fundamentals and Grain Futures Price Movements

Karali¹,

Irwin²,

Isengildina‐Massa³

2019

American J Agri Economics

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“…See e.g. Pesaran (1985Pesaran ( , 1987 or Jeong and Maddala (1991). are weakly stationary, the estimate for I' will be inconsistent. The estimated residuals of this equation can show autocorrelation of order higher than k. This holds even if the predictions are strongly rational as defined by Sargent (1973).…”

Section: Predictions With An Unknown Structurementioning

confidence: 95%

“…For the application of cointegration tests for testing the rational expectations hypothesis see e.g. Jeong and Maddala (1991). However, Sephton and Larsen (1991) show that it is at least questionable whether these cointegration tests provide reliable evidence in this context.…”

Section: ( 5 )mentioning

confidence: 97%

Testing weak rationality of forecasts with different time horizons

Kirchgäßner

1993

Journal of Forecasting

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Starting with conventional tests for weak rationality, we show how additional tests can be performed if predictions with different time horizons are commonly used in them. Next, we show that most of these tests can still be applied if the structure of the economic system changes but only some of them if the true system is unknown. Finally, these tests are applied to the semi-annual one-and two-step predictions of the group of five leading economic research institutes in the FederaI Republic of Germany. For the two-step predictions we find more evidence against the rational expectations hypothesis than for the one-step predictions.

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“…However, most people do not understand Bayes' rule or use it in making decisions (Salop, 1987), and they usually make systematic mistakes in estimating or revising probabilities (Machina, 1987). Moreover, Lovell (1986), Jeong and Maddala (1991), and Zarnowitz (1992, Ch. 16) present a wide range of direct evidence that observed expectations of many agents do not conform to the RE hypothesis.…”

Section: Rational Expectationsmentioning

confidence: 99%

Testing the Permanent-Income/Life-Cycle Hypothesis With Aggregate Data

Seater

1998

Macroecon. Dynam.

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The aggregate implications of the permanent-income/life-cycle hypothesis (PILCH) are derived rigorously. Virtually all empirical rejections of PILCH based on aggregated data are shown to result from misspecifications or from characteristics of aggregate data that have been overlooked. Valid aggregate tests are proposed. Those based on a properly formulated aggregate consumption function may be superior to those based on Euler-equation methods.

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Measurement Errors and Tests for Rationality

Cited by 20 publications

References 23 publications

Supply Fundamentals and Grain Futures Price Movements

Supply Fundamentals and Grain Futures Price Movements

Testing weak rationality of forecasts with different time horizons

Testing the Permanent-Income/Life-Cycle Hypothesis With Aggregate Data

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