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Contribution/Originality: This study is one of the few studies which have investigated the effect of the size of autocorrelation coefficient on the estimators based on the flaws of Parks-Kmenta estimator, which has mislead most researchers into becoming more inclined to use PCSE without considering others credits of Parks-kmenta estimator. 1. INTRODUCTION Statistical methods can be characterized according to the type of data to which they are applied. In survey statistics the cross-sectional data describing each of many different individuals or units at a single point in time is usually used while in economic data analysis time series data describing a single entity over several period of time is used. The econometrics literature reveals another type of data called "panel data", w hich is the pooling of observations on a cross-section of households, countries, firms etc. over several time periods. Panel data simply refers to a cross section of observations (individuals, groups, countries, regions) repeated over several time periods. The Panel data compared with purely cross-sectional data or time series are more attractive in many

In this paper, a new probability distribution is introduced following the work of Marshall and Olkin [1]. Sub models of the proposed distribution are also important models used in the literature. Expressions for some of its properties such as limiting behavior, quantile function, moments, moment generating function, order statistics, entropy, and reliability functions are derived. The method of maximum likelihood is used in the estimation of the model parameters. The graphs of the hazard rate function plotted for some values of the parameters show that the distribution can be used to model data which exhibits decreasing, increasing or bathtub hazard rate behavior. Series expression of the probability density function was also obtained which enables the expression of some properties of the new distribution in terms of the properties of the base distribution. The distribution is fitted to two real life datasets to show its flexibility and usefulness. Its goodness-of-fit indices indicate better fit to the datasets than the three other distributions compared with it. Contribution/ Originality: This study originates a new probability distribution named Marshall-Olkin Extended Weibull-Exponential distribution (MOEWED) which is a four-parameter continuous univariate probability distribution capable of modelling data sets of diverse shapes of distribution including approximately symmetric, left-skewed, right-skewed, J-shape, reversed J-shape and unimodal shapes.

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