An application of the LASSO and elastic net regression to assess poverty and economic freedom on ECOWAS countries

Author:

Sloboda Brian W.1,Pearson Dennis2,Etherton Madi2

Affiliation:

1. Department of Economics and Finance, University of Maryland, Global Campus, USA

2. Austin Peay State University, Clarksville, TN, USA

Abstract

<abstract><p>The study of poverty has been studied from several different research approaches over the years. This analysis intended to determine which variables tell us about poverty in the Economic Community of West African State (ECOWAS) countries. Many ECOWAS countries have recorded high economic growth rates in the past few decades. However, a recent trend is that this progress is reversing, and poverty rates are increasing. In this analysis, we examined the variables describing poverty in ECOWAS. We used a statistical approach coupled with economic theory to justify the inclusion of the variables used to assess poverty. Furthermore, we include the use of the Fraser Institute's Economic Freedom index for each of the West African States. As far as we know, the economic freedom and poverty of West African states have not been presented for consideration toward African growth rates and poverty rates. With few exceptions, economic freedom research suggests that economic freedom is the foundational ingredient for increasing prosperity and reducing poverty. Then, we interpreted the empirical results and assess the validity of the model as applied to the ECOWAS countries. More specifically, we use the LASSO and elastic net regression to obtain sparse solutions to regression problems. LASSO and elastic net are computational methods that rapidly inform us about the relevant variables for the model. These computational methods' performances will in the context of the number of variables exceeds the number of observations by generating a low mean squared error (MSE).</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

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