The negative first-lag autocorrelation of monthly consumption changes rejects the continuous-time random walk model of consumption. This paper addresses the question of whether data distortions due to measurement errors or seasonal adjustment procedures may explain this negative autocorrelation, and thus rescue the model from failure. The paper argues that the type of measurement errors that could explain the negative autocorrelation is not plausible, whereas plausible types of errors do not explain it. The paper also shows via Monte Carlo simulations that the application of the X-11 filter may explain the negative autocorrelation or may not, depending on the statistical properties of the unknown seasonally-unadjusted monthly consumption. Overall, the paper offers further arguments against the continuous-time random walk model.
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Paper provided by University of Hawaii at Manoa, Department of Economics in its series Working Papers with number
199301.
Find related papers by JEL classification: C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics E2 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment