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A Smoothing Test under First-Order Autoregressive Processes and a First-Order Moving-Average Correction

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  • Ana Paula Martins

Abstract

This paper focuses on two applications of time series methods. The first proposes a simple transformation of the unit root form of stationary testing to infer about the validity of smoothing by second-order running averages of a series, or of the variables in a linear model (here opposing co-integration testing). The second one advances a simple iterative algorithm to correct for MA(1) autocorrelation of the residuals of the general linear model, not requiring the estimation of the error process parameter.

Suggested Citation

  • Ana Paula Martins, 2016. "A Smoothing Test under First-Order Autoregressive Processes and a First-Order Moving-Average Correction," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 59(2), pages 77-91.
    • Handle: RePEc:eei:journl:v:59:y:2016:i:2:p:77-91
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    Keywords

    Smoothing Tests under First Order Autoregressive Processes; Running Averages; Negative Unit Roots; Moving Average Autocorrelation Correction in Linear Models.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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