Economic growth of a country id influenced by various factors such as inflation, urbanization and unemployment. These factors can also influence economic income of a country. The relationship between inflation and real GDP per capita is one of the most widely researched topics.
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According to Khan & Ssnhadji, (2001), inflation implies an increase in commodity prices which results into a decrease in purchasing power, which in turn results into decline of GDP. Furthermore, an increase in commodity prices means that the value for money has gone down, significantly reducing the rate of income per capita. Dornbusch & Fischer, (1993) argues that inflation is negatively correlated to productivity, growth and investment. This finding was also supported by Mallik & Chowdhury, (2001) who found that inflation has a significantly negative correlation with economic growth.
Similarly, unemployment rate has been cited by most researchers as the major cause of slow economic growth to a country. In a research study conducted by Andrei, Vasile & Adrian, (2009) on the correlation between unemployment and economic growth, the researchers concluded that high unemployment rate results into a significant decline in economic growth. A high rate of an employment means many people are having little or no income, conseq8uently reducing the rate of real GDP per capita. On the other hand, many researchers have cited urbanization as one of the major catalysts od economic growth. People move to urban centers to find jobs and to invest in more economically viable business. Therefore, an increase in urbanization means people have more money to invest and create jobs. It is therefore imperative to say that an increase in the rate of urban population results into a corresponding increase in the rate of economic growth. This paper will investigate the influence of inflation rate, unemployment rate urbanization on real GDP per capita using countries.dta data obtained from Institute of Economic Studies. The real GDP per capita will be the dependent variable (DV) while inflation rate, unemployment rate and urban population are the independent variable (IV).
1. There is a positive correlation between real GDP per capita and Urbanization.
2. There is a negative correlation between real GDP per capita and inflation rate.
3. There is a negative correlation between real GDP per capita and unemployment rate.
A moderator variable is one that explains the relationship between the independent variable and the dependent variable. In this study, there are could be two mediator variables. First, the mediator variable on the relationship between real GDP per capita and unemployment is the rate of income. The amount of income per person would explain is unemployment rate in that country affects income levels in GDP per capita. Secondly, the consumer purchasing power would explain the relationship between GDP per capita and rates of inflation. On the other hand, the relationship between GDP per capita and urbanization can be mediated by the quality of life in the urban centers.
A moderator variable is one that strengthen he relationship between independent variable and dependent variable. This study could use two moderators. First moderator is the interaction between unemployment rate and individual income levels. This variable can moderate the relationship between real GDP per capita and unemployment rates. Secondly, the interaction between consumer purchasing power and inflation rates can be used as a moderator variable for the relationship between, GDP per capita and rates of inflations.
This research study used a total of four variables, that is, one dependent variable and three independent variables. The dependent variable is the real GDP per capita(gdp_pc). The independent variables are inflation rate (inflation), unemployment rate (unemp) and urban population (urban_pop). Table 1 below shows a descriptive statistics summary of both dependent and independent variables obtained from STATA.
Table 1: Descriptive statistics for variables
|GDP per Capita||Capita||142||15958.95||21658.65||279.241||113533|
For the two other independent variables, unemployment rate and urban population, the standard deviations are relatively low (6.210 and 23.377 respectively) compared to the means (8.962 and 55.336 respectively). This dispersion indicates that the values for both variables are concentrated around the mean. In other words, most values are close to the means. A standard probability normal distribution is shown in Figure 2 in the appendix part. From the distribution graph, the values are widely spread around the mean. Most of the values actually falls below the population mean. The figure also shows a thick right tale indicating that the data are not symmetrical.From the descriptive statistics table, the dependent variable, GDP per capita has a mean of 15,958.95 dollars and a standard deviation of 21,658.65. Since the standard deviation is large, we can conclude that the data are widely spread around the mean. Similarly, for the independent variable, Inflation, the standard deviation is relatively large (9.758) compared to the mean (1.593). Therefore, we can conclude that for this variable, the values are widely spread around the mean.
Bivariate hypothesis test
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