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Population and Economic Growth-Case study of selected countries人口和经济增长所选国家的案例研究
Abstract摘要
This paper is about the relationship between population and economic growth. We are interested in knowing whether population has an impact on the economy. We collected data from several countries: China, Sweden, USA, Brazil, and Algeria (more detailed case study about China and Sweden) and use linear regression model to test. For the regression tests, our main data are GDP per capita, population and trade during the period of 1980 and 2010.本文是关于人口与经济增长之间的关系。我们有兴趣知道人口对经济的影响。我们收集的数据从多个国家:中国、瑞典、美国、巴西、和阿尔及利亚(更详细的案例研究对中国和瑞典),使用线性回归模型来测试。回归测试,我们的主要数据是人均国内生产总值、人口和贸易在1980年和2010年期间
Keywords: population, economic growth, linear regression line model
List of content
page
1. Introduction……………………………………………………………………… .
1.1 Problem…………………………………………………………………………..
1.2 Literature review………………………………………………………………..
1.3 Regression Line Model ……………………………………………………….
1.4 Data……………………………………………………………………………..
2. Analysis
2.1 About Population…………………………………………………..
2.2 China……………………………………………………………….
2.3 Sweden……………………………………………………………
2.4 Some Other Selected Countries………………………………….
4. Conclusion……………………………………………………………..
5. References……………………………………………………………………
6. Appendix………………………………………………………………………………
Introduction
Problem
The relationship between population and economic growth is the issue that interests us. Are they positively or negatively correlated? Or maybe there is no correlation at all? Does it work the same way in all countries?
As it is known to all that changes in population have effect on both consumption needs of an economy, namely how many people are there to feed, and the productivity of the economy, namely how many people are there to produce. As population grows, so does the output. On the other hand, as population grows bigger and bigger, with holding other factors constant, it will lead to a diminishing return effect.
Our aim is to test the relationship between these two variables and furthermore, to test if there are other more important elements other than population that affect economic growth ? We also want to compare the test results of different countries to see if there is a pattern works for all countries.
1.2 Literature Review
Ever since early time there have been many economists and researchers who tried to find out how population impacted on economic growth. Their theories however varied.
Back in 18th century Scottish Philosopher and also a pioneer in classic economics Adam Smith (1723-1790) mentioned in his ‘’An Inquiry Into Nature and Cause of Wealth of Nations’’ that growth of population is in response to growth of demand for labor and served to increase division of labor, and division of labor improves national wealth growth. However English economist Thomas Malthus (1766-1834) argued in ‘’The Power of Population’’ that the smaller the population relative to the available land, the better off people will be. The richer people are, the fast population will grow. Then in 1937 John Maynard Keynes again came up with the theory in `Some Economic Consequences of a Declining Population` that demand will shrink with a declining in population. In other words, an increase in population enhances consumption and thus benefits the economy eventually.
1.3 The Linear Regression Model
OLS (Ordinary Least Squares) is the best-known technique to estimate the regression coefficients. Suppose we have N observations of each variable. Each observation includes a vector of and a vector of X_i . A slope coefficient indicates the change in the dependent variable Y_i associated with a one-unit increase in the explanatory variable holding other variables constant.
The Multiple Regression Model we use here is:
Y_i = β_0+ β_1 X_1i+β_2 X_2i+ … +β_k X_ki + ε_i
β_0 is the intercept term: it is the value of Y when all the Xs and the error term equal zero.
In our case, the independent varible Y denotes GDP per Capita /GDP total; The β coefficients can be either positive or negative.
i = 1, 2, … N data
Dependent variables are X_1 = population; X_2= 〖(Population)〗^2; X_3= trade;
ε = stochastic error term
In order to check if the estimated model fits the data well, we need to check the R^2 value.
The higher the R^2(the goodness of the fit) is, the closer does the estimated equation fit the sample data. Usually we have 0 ≤ R^2 ≤ 1. For time series data, R^2 is usually quite high and for cross-sectional data, R^2 is often lower (0.5 is considered to be good).
In order for OLS estimators to be the best available, 6 Classical Assumptions must be met:
The regression model is linear, is correctly specified and has an additive error term.
The error term has a zero population mean
All explanatory variables are uncorrelated with the error term.
No Serial Correlation, i.e. Observations of the error term are uncorrelated with each other.
No Heteroskedasticity, i.e. the error term has a constant variance.
No perfect Multicollinearity, i.e. No explanatory variable is a perfect linear function of any other explanatory variable(s).
We use statistical software called SPSS to run the regressions. It automatically checks the conditions mentioned during each regression analysis.
1.4 Data
The best way to estimate a correct relationship between population and economy is to test as many samples as possible , ideally for all different countries. Unfortunately due to limitation it’s impossible to collect all relevant data needed for the tests. For our paper we have successfully collected statistical data for China, Sweden, Germany, USA and India. We compare the results and make estimates.
For Sweden:
Population overview (graph): measured in millions, from 1960 to 2011, cited from Trading Economics
Economy overview (graph): measured in GDP Per Capita Growth Rate, from 1800 to 1990, cited from Statistiska Centralbyrån
Regression Analysis (Tables) , collected from World Data Bank:
Population measured in units, from 1980 to 2010
GDP Per Capita, measured in constant price 2005, US Dollars
For Germany:
Table , collected from World Data Bank:
Population measured in units, from 1980 to 2010
GDP Per Capita, measured in constant price 2005, US Dollars
For china
Table ,: collected from world data bank
Population and GDP per capita, from 1949-2010
Figure 1: history population, GDP per capita(US$ and RBM)
Figure 2: growth rate of GDP and natural growth rate of population
Figure 3:data of population and population 1949-1977
Figure 4,5,6 are in appendix
For brazil
Table : collected from world data bank
Population and gdp per capita ,from1980-2010
For USA
Table collected from world data bank
Population and gdp per capita ,from1980-2010
For Algeria
Table collected from world data bank
Population and gdp per capita ,from1980-2010
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