ECONOMIC AND QUANTITATIVE ANALYSIS

Running head: ECONOMIC AND QUANTITATIVE ANALYSIS: LINEAR REGRESSION
REPORT
Economic and Quantitative Analysis: Linear Regression Report
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ECONOMIC AND QUANTITATIVE ANALYSIS: LINEAR REGRESSION REPORT1
Table of Contents
1.Purpose.........................................................................................................................................2
2. Background..................................................................................................................................2
3. Method.........................................................................................................................................2
5. Discussion....................................................................................................................................7
6. Recommendation.........................................................................................................................8
List of References............................................................................................................................9

ECONOMIC AND QUANTITATIVE ANALYSIS: LINEAR REGRESSION REPORT2
1.Purpose
The report is designed to conduct a brief analysis to establish a relation of average life
satisfaction to that of annual per capita GDP. Purpose is to build a linear relation between the
two using simple technique of linear regression.
2. Background
There is an ongoing debate among researchers, policymakers and scientists regarding the
relation of life satisfaction with aggregate income. In this regard, the study of Easterling is often
considered as the starting point of the debate (Kaiser and Vendrik 2019). Easterlin in his paper
used the time series data of USA and confirmed that for the period ranged from 1974 to 2005
income though doubled in USA however there was no appreciation of life satisfaction. As
against this some cross sectional studies showed affirmative view on the dependence of life
satisfaction on aggregate income (Altindag and Xu 2017). One literature by Proto and Rustichini
(2013) stated that life satisfaction increased undoubtedly with an upturn movement of GDP per
capita below USD 15000. After the mentioned threshold limit, the income effect on satisfaction
however becomes flat (Proto and Rustichini 2013). Because of the implication in policy
formulation researchers from different field are interested to revisit the actual relation.
3. Method
The paper deals with empirical data on two indicators such as life satisfaction and GDPs
per capita (annual). The type of data used for the analysis is cross section data which are
collected across different units at a given time. The different cross section units here are different
countries. Life satisfaction scores and per capita GDP are reported for 35 different countries
selected as sample. The sample size therefore is 35. The source from where data has been