ICT370 Data Analytics

Introduction

The Gross Domestic Product is defined as the total monetary value of all the goods and services produced in a country. It acts as a country’s scorecard of economic health. It is often calculated on annual basis but sometimes it can be calculated every quarter as well. A country like the USA releases annual GDP as well as GDP estimates for each fiscal quarter. The GDP is calculated using the data ascertained through surveys of the manufacturers, retails, builders and trade flows. It is used to estimate the growth of a county’s economic size and the economic growth rate. It is calculated using three ways that are, production, expenditure, and income. It is always adjusted using inflation and population to give clear and price insights. It is used by investors, policymakers, and businesses to guide them in decision-making.

In this project, we will determine the factors that influence GDP. The main factors that have been highlighted are life expectancy, the inflation rate, the population, the unemployment rate, and the birth rate. We will determine how these factors influence the deviation of the GDP.

This research will focus on the GDP of Australia from 1960 to 2019. The data that has been used has been collected from the data of Australia from the world development indicators. Seven variables have subsetted from the whole data set just for this study.

As earlier mentioned, GDP is the total monetary value of all the goods and services produced in a country. Life expectancy is the measure of time people within a country are expected to live. The population is the number of entire people living in a specific geographical location. The unemployment rate is defined as the total number of people who are not working against the total labor force i.e. it is the percentage of the labor force that is without jobs. Inflation is defined as the total rise of the price level of an economy after a while. The birth rate is defined as the total number of live births of over 1,000 people of a given population over some time. The data that was used for analysis was obtained from the data world bank The Australian data set was selected.

According to the study conducted by Acemoglu & Johnson (2007), life expectancy has a smaller impact on the GDP both initially and over 40 years horizon. The author also obtained that there was no significant evidence to shows that high life expectancy led to an increase in GDP. However, contrary results were obtained by Shafi & Fatima (2019) which showed from the evidence of several analyses that the increase in life expectancy is accompanied by the increase in GDP. The same results have been obtained by (Mahumud et al. 2013 and Kunze, 2014).

The relationship between population growth and GDP is controversial. According to Peterson, (2017), the low population growth in high-income countries is likely to create problems in economic growth while the high population growth in low-income countries is likely to slow down the development. According to Joshua & Dauda (2019), a large population size have high economic well-being. However, this can only work when other factors such as the unemployment rate and inflation are low.

Research conducted by Mosikari (2013) stated that there was no causality found between the unemployment rate and GDP growth. The research indicated that GDP growth can create employment for the people. Also, a similar result was obtained by a study conducted by Moh'd AL-Tamimi (2019) which stated that there was an insignificant impact of the unemployment rate on the GDP growth.

The relationship between inflation and GDP is most determined by the inflation threshold. The relationship between the inflation rate and GDP growth might differ below and above the inflation threshold. According to Munir & Mansur, (2009), inflation above the threshold (3.8 %) significantly retarded the GDP growth and below the inflation threshold, there was a positive and significant relationship between the inflation rate and the GDP growth rate. The inflation rate has influence power on the growth rate, this is according to the research conducted by (Saymeh & Orabi 2013) to determine the effect of inflation on economic growth in Jordan.

Research conducted by Ashraf, Weil, & Wilde (2013) showed a change in the birth rate increased the economic growth by 5.6 %. Research conducted was by Li & Zhang, (2007) to determine the effect of birth rate on the growth of the economy in China. It can be remembered that China government imposed a policy of 1 child as a way of controlling the population of the country. The policy only applied to the Han Chinese and not the minority group. The result from the study found that the birth rate has a negative influence on economic growth. This shows that the one-child policy led to the growth of China’s economy.

The result above shows that a unit increase in life expectancy increases the GDP by 9.17e+10. A unit increase in the rural population increases the GDP by 159248. A unit increase in the unemployment rate decreases the GDP by 7.13e+10 and finally, a unit increase in inflation increases the GDP by 1.4e+10.  The result from the regression shows that life expectancy had a significant influence on the country’s GDP (p<0.05). The rural population had an insignificant influence on the country’s GDP (p>0.05). The unemployment rate had an insignificant influence on the GDP (p>0.05) and finally, inflation had a significant influence on the country’s GDP (p<0.05). However, a combination of life expectancy, population, the unemployment rate had a significant influence on the country’s GDP at a 5 % significant level (F (40) =253.09, p<0.05).

Discussion

The results from the regression show that life expectancy had a significant influence on the GDP. This is a similar result that was obtained by (Shafi & Fatima (019; Mahumud et al. 2013 and Kunze, 2014). Also, the result showed that inflation had a significant influence on the GDP as obtained by (Saymeh & Orabi 2013). The population was obtained to have an insignificant relationship with the GDP. However, a contrary result was obtained (Joshua & Dauda 2019). Unemployment was obtained to have an insignificant influence on the GDP. A similar result was obtained by (Mosikari 2013; Moh'd AL-Tamimi 2019).

Conclusion

The project aimed to obtain the effects of life expectancy, population, unemployment rate, inflation, and birth rate on GDP. The result from the regression analysis showed that a combination of these variables had a significant influence on the GDP of a country. However, the result showed that only life expectancy and inflation had a significant influence on the GDP on a personal level. The unemployment rate and population had an insignificant influence on the GDP.

It is therefore recommended that for a county’s economy to grow, the country should control the population and this is done by controlling the birth rate. Since life expectancy influences the GDP, Australia should improve its health facilities to increase its life expectancy. The government should control the inflation rate of the country to ensure that it does not increase.

References

Acemoglu, D., & Johnson, S. (2007). Disease and development: the effect of life expectancy on economic growth. Journal of political Economy, 115(6), 925-985.

Ashraf, Q. H., Weil, D. N., & Wilde, J. (2013). The effect of fertility reduction on economic growth. Population and development review, 39(1), 97-130.

Joshua Adeyemi Ogunjimi & Dauda Olarotimi Oladipupo, 2019. "Dynamics of Demographic Structure and Economic Growth in Nigeria," Asian Journal of Economics and Empirical Research, Asian Online Journal Publishing Group, vol. 6(2), pages 186-196.

Kunze, L. (2014). Life expectancy and economic growth. Journal of Macroeconomics, 39, 54-65.

Li, H., & Zhang, J. (2007). Do high birth rates hamper economic growth?. The Review of Economics and Statistics, 89(1), 110-117.

Mahumud, R. A., Rawal, L. B., Hossain, G., Hossain, R., & Islam, N. (2013). Impact of Life Expectancy on Economics Growth and Health Care Expenditures: A Case of Bangladesh. Universal Journal of Public Health, 1(4), 180-186.

Moh'd AL-Tamimi, K. A (2019). Effect of Unemployment Rate on Growth Rate of Gross Domestic Product of Jordan.

Mosikari, T. J. (2013). The effect of unemployment rate on gross domestic product: Case of South Africa. Mediterranean Journal of Social Sciences, 4(6), 429.

Munir, Q., & Mansur, K. (2009). Non-linearity between inflation rate and GDP growth in Malaysia. Economics bulletin, 29(3), 1555-1569.

Peterson, E. W. F. (2017). The role of population in economic growth. Sage Open, 7(4), 2158244017736094.

Saymeh, A. A. F., & Orabi, M. M. A. (2013). The effect of interest rate, inflation rate, GDP, on real economic growth rate in Jordan. Asian Economic and Financial Review, 3(3), 341.

Shafi, R., & Fatima, S. (2019). Relationship between GDP, Life Expectancy and Growth Rate of G7 Countries. International Journal of Sciences, 8(06), 74-79.

Are you seeking reliable essay help from academic experts in the UK? At Myassignmenthelp.co.uk, we have searched high and low to recruit the top paper writers in the UK who can provide you with the best assignment help. Most of these professionals have completed their PhDs from top universities in the UK. Therefore, they’re the best at resolving every "Who can do my assignment for me?" query.

These professionals undergo intense training to provide coursework help services within strict deadlines. Hence, you don’t have to waste precious seconds wondering, “Can your experts write my assignment within the deadline?" Instead, rest assured that our experts will consistently deliver top-quality work within the due date.