1. Presentation of study data
As part of this project of memory project, we are particularly interested in economic growth in Africa. Variables dictated by literary and empirical journals will be retrieved from the World Bank database. In this case, GDP per capita, fossil energy consumption, physical capital ... etc. Other unobservable variables will be able to be calculated. In this sense, it is the savings rate, the net capital inflow, the rates of commercial opening. Our values are in current dollars. The study period or the interval by which we analyze the theme is between 1960 and 2016. In truth, more data remains unavailable for the year 2017. We will then solicit methods of clearing and correction of the missing values before to be able to carry out studies whose prospects seem already purified in the general introduction.
2. Analysis of econometric results
Obviously, the double least squared, by its performance, it takes into account to correct the problem of endogeneity of which several model suffers. Obviously, this coincides with the stochastic least regular square hypothesis. By this means, a violation of the assumptions that depends on the reliability, the efficiency of the estimators.
To overcome this unavoidable problem, the TSLS method is created by proposing an effective solution. Notwithstanding, for the sake of comparison, we had thought of other methods to which their efficiencies seem as impressive as the double least square.
Thus, these were the methods of the triple least square, double least squared square, least squared square, triple least square repeated and weighted iteration, SUR, Instrumental variable, THEIL-OLS, POOLED-SUR, THEIL -POOLED, THEIL-ON, POOLED-OLS, LIML and FIML, MLMV, Least Generalized Residual Variance (LGRV), Indirect Least Square (ILS), K-Class Estimator, Maximum Likelihood (ML), Least Variance Ratio (LVR).
ADAN, A.-B. (2018). Croissance Economique et Développement Durable en Afrique: Analyses Statistiques et Econométriques [Kindle]. Amazon Media EU S.à r.l.
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