Exploration of GDP and Life Expectancy

Data Science Notebook using World Bank and World Health Organization data.
Author: E. J. Kluge, 2020, ekluge@ikp.uni-koeln.de

Intro

It is to be expected, that with a nations development and progress, the living standard should raise, and with it, the average life expectancy. The gross domestic product or GDP, is the monetary market value of all final goods and services produced in a specific time period (mostly annual) [1], [2]. It can aid as a statistical indicator of national development and progress. The GDP can thus be used as a metric for economic progress on an international scale as well [3].

The purpose of this project is to investigate the development of GDP and the life expectancy over the last decades for multiple countries. The GDP and life expectancy correlation assumption is being put to the test.

Methodology

To show the existence and specify the type of connection between the GDP of a country and the life expectancy of its citizens, on an international basis, GDP data from

• A comprehensible but broad data set is used. Therefore, the GDP and life expectancy data, from an excerpt of five countries from different continents, stages of development and social-economic order was chosen.
• Their median GDP's and median life expectancies are investigated and compared via boxplots.
• The development of the countries GDP's and their citizen life expectancies over the years is visualized and compared.
• Correlation types are visualized and their "strength" numerically investigated.

Summary & Conclusions

The development of GDP and life expectancy over the years is mainly similar for the investigated countries. The high GDP to life expectancy correlation factors strongly suggest a simple linear correlation between the two metrics. Despite the political and socio-economic complexity, and under consideration, that GDP is no measure for medical progress, it can be concluded, that GDP and life expectancy are correlated in the described way.

Suggested Proceeding

Note that growth imperative critics further argue that GDP leaves out factors, such as unpaid work, resource extraction and environmental impacts. Further more, it does not reflect inflation rates and differences in the cost of living. Using the GDP per capita at purchasing power parity (GDP-PPP), is arguably more useful, when comparing living standards between nations. Therefore, at next, an investigation with GDP-PPP data should be carried out. Further more, one should explore the causes of China's drastic GDP and life expectancy growth. After all, China is the highest deviator from a simple linear GDP to life expectancy correlation.

Setup

Library imports

Data processing

Data info

Categories: COUNTRY, YEAR, LIFE_EXPECT, GDP

Table 1: Data Types

	data type
country	object
year	int64
life_expect	float64
gdp	float64

Table 2: Content Excerpt

	country	year	life_expect	gdp
0	Chile	2000	77.3	7.786093e+10
1	Chile	2001	77.3	7.097992e+10
2	Chile	2002	77.8	6.973681e+10
3	Chile	2003	77.9	7.564346e+10
4	Chile	2004	78.0	9.921039e+10
...	...	...	...	...
91	Zimbabwe	2011	54.9	1.209845e+10
92	Zimbabwe	2012	56.6	1.424249e+10
93	Zimbabwe	2013	58.0	1.545177e+10
94	Zimbabwe	2014	59.2	1.589105e+10
95	Zimbabwe	2015	60.7	1.630467e+10

96 rows × 4 columns

Table 3: Content Statistics

	country	life_expect	gdp
0	Chile	78.94375	1.697888e+11
1	China	74.26250	4.957714e+12
2	Germany	79.65625	3.094776e+12
3	Mexico	75.71875	9.766506e+11
4	USA	78.06250	1.407500e+13
5	Zimbabwe	50.09375	9.062580e+09

Data Analysis

Category correlation exploration

Investigated countries: Chile, China, Germany, Mexico, USA, Zimbabwe

Investigated years: 2000 - 2015

Figure 1: Country Facets

Figure 2:

Figure 3: GDP Facets

GDP

The above figures clearly show, that the USA has the greatest GDP in comparision. While China, Germany and Mexico are relatively close in figures, Chile and especially Zimbabwe lag behind. From Fig.3 follows, that the USA and China have experienced substantial gains in the investigated time period. The other countries had no increases of this magnitude. Hence Fig.2 shows for the USA's and China's GDP relatively wide ranges, while Germany, Mexico, Chile and Zimbabwe are short ranged.

Life Expectancy

In the life expectancy department, the majority of the countries reach about 78 years with a relative narrow range of about +/- 2 years. With about 47 years on median and a range of about 10 years, Zimbabwe falls exceptionally behind (see Fig.1 and Fig.2).

Possible correlations

Almost all countries show a possible linear connection between GDP and Life Expectancy at first sight (Fig.3b). However, with a gradient to the power of about 2, China falls out of line. Hence, a more thorough correlation investigation is required.

Correlation investigation

Visual investigation

Figure 4:

Chile:

Life Exp. to GDP linear corr. strength:
covariance: 0.12
pearson corr.: 0.95

China:

Life Exp. to GDP linear corr. strength:
covariance: 0.1
pearson corr.: 0.91

Germany:

Life Exp. to GDP linear corr. strength:
covariance: 0.1
pearson corr.: 0.93

Mexico:

Life Exp. to GDP linear corr. strength:
covariance: 0.1
pearson corr.: 0.93

USA:

Life Exp. to GDP linear corr. strength:
covariance: 0.1
pearson corr.: 0.98

Zimbabwe:

Life Exp. to GDP linear corr. strength:
covariance: 0.13
pearson corr.: 0.97

Figure Analysis

The right side of Figure 4 shows, that GDP and life expectancy development have similar slopes. A "minor exception" is China. In general GDP and life expectancy seem synchronous. The synchronicity is further underlined by the high linear correlations shown on the left. A numeric investigation follows:

Numeric investigation:

Table 4: Correlation Strengths:

	country	gdp_year	lifeExp_year	lifeExp_gdp
0	Chile	0.96	0.98	0.95
1	China	0.97	0.98	0.91
2	Germany	0.89	0.99	0.93
3	Mexico	0.94	0.95	0.93
4	USA	0.99	0.99	0.98
5	Zimbabwe	0.84	0.92	0.97

Table 5: Correlation Strength Statistics:

	gdp_year	lifeExp_year	lifeExp_gdp
count	6.00	6.00	6.00
mean	0.93	0.97	0.95
std	0.06	0.03	0.03
min	0.84	0.92	0.91
50%	0.95	0.98	0.94
max	0.99	0.99	0.98

Table Analysis

The listed correlation factors life in the [ 0 : 1 ] = [no linear correlation, definite linear correlation] interval. Life expectancy of a country shows a strong linear correlation to the country's GDP.

References

1. Finance & Development, "Finance & Development", 2019, [ Website ]
2. Philipp Lepenies, "The Power of a Single Number: A Political History of GDP, Columbia University", 2016, [ Website ]
3. Mary Hall, "What Is Purchasing Power Parity (PPP)?", Investopedia, 2019, [ Website ]

Data Sources

• Gross Domestic Product: World Bank and OECD national accounts data.
• Life Expectancy: World Health Organization