Paper #4: Multiple Linear Regression

Introduction

The objective of this paper is to use the Multiple Linear Regression technique to analyze possible causal relationships among several variables contained in the Democracy Cross-National Data (Norris), which is an aggregated dataset of macroeconomic and demographic variables, compiling information about 191 countries, comprising 69 variables.

The Democracy Cross-National dataset is source of non-random, secondary data that can be very useful for finding or at least get evidence of the existence of associations (causal or spurious) between variables. The possibility of establishing these kinds of relationships makes this kind of analysis very useful for policy makers.

Many authors have studied the link between social fairness and gender equality with the economic growth and prosperity of a nation, and this Democracy Cross-National dataset will serve the objective of addressing such link, due to the nature the variables it contains, and are related to economic prosperity and social fairness.

Data and Measures

The main purpose of this paper is to assess the idea that economic growth is affected by the social fairness and gender equality in a country. Also, it is expected that government effectiveness will be tightly correlated with economic growth. For this purpose, the variable GDP per capita from the Democracy Cross-National dataset will be used as the dependent variable (DV). This dependent variable is measured at the ratio level. Two predictors (IV) will be considered for this multiple linear regression analysis:

Solution:

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