Analysis of Economic Development of Tanzania from 1984 to 2014 - Case Study Example

The Analysis of Economic Development of Tanzania Since 1984 to 2014 Name: Lecturer: Unit name: Date of submission: Table of Contents Table of Contents ii 1.0 INTRODUCTION 1 2.0 Literature Review 3 3.0 Data Analysis 4 4.0 Discussions 6 5.0 Conclusion 8 6.0 Recommendations 8 Reference: 9 Appendix: Data 10 1.0 INTRODUCTION Tanzania is a country in East Africa, covering approximately 945,000 square kilometers. It borders Kenya and Uganda to the North, Democratic Republic of Congo, Burundi and Rwanda to the west. Mozambique, Zambia and Malawi borders Tanzania to its South. It has 40 million hectares of Arable land and 6 million hectares is under cultivation. Majority of its land is covered by woodlands and grass lands. Tanzania has a population of about 27.5 million people occupying both its mainland and Zanzibar. Zanzibar consists of two islands, which are Unguja and Pemba. (Nafziger, 2012). Tanzania is a low-income country and is considered one of the poorest countries in the world. It was rated at number 14 of the world top 50 poorest nations by a report by worldwideblog, 2012. Despite being one of the poorest countries, Tanzania has however improved as compared to earlier reports. In 1997, the World Bank ranked Tanzania as the fourth poorest country only after Ethiopia, Mozambique and Rwanda in the same order (World Bank, 1997). As per the worldwide blog report, 2012, it has however improved to number 14 as of 2012.The basis of this report was in terms of per capita income. It had a GDP per Capita of $100 per annum and purchasing power parity of $620 per annum as of 1992. Human development index was at 0.374 which ranked Tanzania 147 out of the 173 countries (HDR, 1995). Tanzania has initiated various economic reforms strategies aiming at uplifting the country from the low income country to a high income country. These reforms include Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs). These reforms are aimed at alleviating poverty, economic growth, full employment and a balance of payments. These reforms also aims at encouraging the development of industrial sector so as to complement the Agriculture sector which contributes a large portion to the country’s GDP, since agricultural income is not consistent due to changing weather patterns. Tanzania has a large subsistence sector composed of Agriculture, fishing and livestock in rural areas where majority of population lives and some industries largely based on urban regions. Agricultural crops for exports include cotton, coffee, tea, sugar, cashew nuts, Agriculture contributes to 49% of GDP (1992-1994) and sisal and tobacco and contributes 60% of the foreign exchange. Industrial sector contributes to 18% to GDP of which manufacturing accounts for 7.6% (Economic Survey, 1995) and the rest (33%) of GDP is accounted for by services sector (World Bank, n.d.). The average economic growth for the period 1980-1985 was 2% and improved to an average of 4% for the period starting 1986 to 1994 (World Bank, n.d.). However, this growth was seen as having not benefited everyone because living conditions did not improved, nearly half of the population still lives in poverty. The majority of the poor population lives in rural areas. Tanzania’s population growth rate is among the fastest in the world standing at 2.9% and has the youngest population in the world with 44% of its population under the age of 15. 2.0 Literature Review Ricardian Theory Ricardian theory measures economic development as a function of the quantity of output produced by the economy. Ricardian views the economy as a machine transforming inputs (labor, capital and natural resources) into outputs (Devlin, 2010). The determinants of the output are the amount of inputs and technology of the machine (Economy). Output increases as result of larger amounts of input and better technology. An economy with lower output must be lacking inputs and technology. However, development economists have found this theory wanting because it does not explain the acceleration of human capital andtechnological progress in the West. Malthus theory of Economic Development According to Malthus, process of development requires consistent efforts by the country’s citizen (Devlin, 2010). He added that the process of development was rough, that is, involved up and downs, and was never smooth. His concern was that economic development which be achieved by increasing a country’s wealth. This wealth of a country depended on the quantity of goods and services produced by people of a country (labor). Therefore, Malthus linked the amount of labor (population) that produces wealth to economic development. However he argued that, population growth only was not sufficient for economic development to be attained. Later, this paper will try to present the relationship between economic growth of a country and its population size (Nafziger, 012). Effective demand of labor leads to economic development. Institutions These are social/political structures that either impede or facilitate economic activity. In study of institutions and their roles in economic progress, development economist put forward two fundamental questions, “How do institutional arrangements affect economic growth and development? How and why do ‘good’ institutions arise?” (Nafziger, 2012) The role of a political organization is to provide conditions conducive for economic development. An example of such roles is to contain and/or prevent violence. The main vehicle for political organization is the state and has a great influence on economic development. 3.0 Data Analysis The Average Growth Rate in GDP overall 1980-1997 1998-2014 average growth rate 4.7006 2.968211844 6.433009222 From the data provided, the average economic growth of Tanzania from 1980-2014 is 4.7%. When the period is split into two halves, we find that the growth is low in the first half of 1980-1997 (2.97%) compared to that of 1998-2014 (6.4%). Per Capita The Tanzania’s per capita income has been consistently rising. This implies that an increase is beneficial to a country. This trend is expected to continue until the economy has achieved full employment (Nafziger, 2012). Share of World GDP SHARE of world GDP Overall 1980-1997 1998-2014 Average 0.063429 0.059056 0.067333 The average share of world GDP for Tanzania for the entire period of analysis is 0.06%, while between 1980-1997 the Tanzania’s economy accounted for 0.059% and for the period 1998-2014 it share increased to 0.067%. Granger Causality Test This is to investigate the causal relationship between population growth rate and economic growth rate in Tanzania. This will tell us if Population growth causes economic growth or does economic growth causes population growth. Our hypothesis is: HO: GDP does not granger cause POPULATION and vice. HA: GDP Granger causes Population and Vice versa VAR Granger Causality/Block Exogeneity Wald Tests Date: 05/10/16 Time: 00:30 Sample: 1980 2014 Included observations: 33 Dependent variable: GDP Excluded Chi-sq Df Prob. POPULATION  0.870206 2  0.6472 All  0.870206 2  0.6472 Dependent variable: POPULATION Excluded Chi-sq Df Prob. GDP  4.390853 2  0.1113 All  4.390853 2  0.1113 From the results above, we can see that Population Granger causes Economic growth, since the P-value is less than 5% that is 0.64, in the other hand we can see that economic growth (GDP) also Granger causes Population because the P-Value is also less than 5%. Meaning the direction of causality is bidirectional. Relationship between population growth and economic growth Regression was carried out to establish whether there was a relationship betweenpopulation growth and economic growth. Regression Results SUMMARY OUTPUT Regression Statistics Multiple R 0.829155945 R Square 0.687499582 Adjusted R Square 0.677733944 Standard Error 1.462781028 Observations 34 ANOVA   Df SS MS F Significance F Regression 1 150.6365816 150.6365816 70.3998629 1.3782E-09 Residual 32 68.47130679 2.139728337 Total 33 219.1078884         Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.709391289 0.537782146 1.319105319 0.196495711 -0.386035095 1.804817673 -0.386035095 1.804818 Population 0.891470585 0.106248085 8.390462615 1.3782E-09 0.675050318 1.107890852 0.675050318 1.107891 4.0 Discussions Tanzania’s economy is moving in the right direction, this is evident from the increase in the share of world GDP. In the period of 1980-1997, Tanzania, on average, accounted for 0.058% of world GDP while for the period 1998-2014 Tanzania accounted for 0.067% of world’s GDP. The average economic growth for Tanzania also increased from 2% for the period 1980-1997 to 6% for the period 1998-2014. Granger Causality Granger tests aimed to establish whether population growth granger cause economic growth. Causality results indicate a bi-directional causality between population growth and economic growth (Harvey and Johnson, 1971).This bi-directional causality means that population growth causes economy growth and vice versa is true. This results suggest that population is one of the most important factors that determine the population growth of a country. Therefore, Tanzania should check on its population growth to ensure that it does not derail the achievement of various macroeconomic objectives including economic growth. Regression Results From the analysis above, the goodness of fit OR/ Adjusted R-Squared indicates a goodness of fit indicating that there is a relationship between economic growth and population growth (Harvey and Johnson, 1971). The relationship between population growth and economic growth is positive. We can see that a unit change in population growth causes economic growth to increase by 0.7 units. This supports the hypothesis of population-driven economic growth that states a country’s population growth promotes its economic development. 5.0 Conclusion The results show that there is a relationship between population and economic growth in Tanzania and therefore it supports the hypothesis that economic growth is driven by the population growth. Granger tests shows that there is a bi-directional causality meaning that causality runs from population growth to economic growth or runs from economic growth to population growth (Harvey and Johnson, 1971). 6.0 Recommendations The results of our data analysis indicates that population growth in Tanzania has a strong positive correlation with economic growth. Therefore Tanzania should devise a strategy for population growth such that an increase in population will be beneficial to the economy. The government should ensure that population growth leads to an economic and not challenges such as an environmental degradation and famines. Human capital is the most valuable asset of a country, however the government should ensure that economic growth is at higher rate than population growth. This is to make it able to have an educated, healthier and workforce that is manageable. An increase in Tanzania population has been beneficial to the country because every time population increases there is an increase in per capita income, implying that the economy has not attained full employment. Reference: Devlin, J. (2010). Challenges of economic development in the Middle East and North Africa region. Singapore: World Scientific. Harvey, J. and Johnson, M. (1971). Introduction to macro-economics. London: Macmillan. Mah, J. (2015). Export Expansion and Economic Growth in Tanzania. Global Economy Journal, 15(1). Nafziger, E. (2012). Economic Development. Cambridge: Cambridge University Press. Pasinetti, L. (1974). Growth and income distribution. London: Cambridge University Press. Rowan, D. (1974). Output, inflation and growth. London: Macmillan. World Bank, (n.d.). World Development Indicators| World DataBank. [online] Databank.worldbank.org. Available at: http://databank.worldbank.org/data/reports.aspx?source=2&country=SOM&series=&period=# [Accessed 16 Apr. 2016]. Appendix: Data Years GDP (US$ Billions) Per capita Income (US$ Billions) Population (Billions) Share of World GDP % 1980 4,654.66 441.745 18.15 0.063 1981 4,711.09 473.803 18.726 0.062 1982 4,713.70 487.951 19.322 0.062 1983 4,672.02 487.211 19.938 0.06 1984 4,693.73 491.202 20.573 0.057 1985 4,880.40 510.83 21.227 0.057 1986 5,154.77 532.535 21.94 0.059 1987 5,476.02 561.173 22.683 0.06 1988 5,799.00 595.086 23.445 0.061 1989 6,017.70 620.846 24.226 0.061 1990 6,441.45 671.017 24.881 0.063 1991 6,574.91 685.963 25.67 0.063 1992 6,613.30 684.196 26.476 0.057 1993 6,693.08 687.61 27.297 0.056 1994 6,797.96 692.208 28.127 0.056 1995 7,040.68 710.817 28.96 0.055 1996 7,360.64 735.789 29.782 0.056 1997 7,620.12 754.278 30.591 0.055 1998 7,902.71 769.2 31.448 0.056 1999 8,181.67 800.901 31.748 0.056 2000 8,585.34 831.398 32.822 0.056 2001 9,100.28 879.625 33.633 0.058 2002 9,752.18 934.583 34.444 0.061 2003 10,423.74 988.76 35.492 0.062 2004 11,239.73 1,064.05 36.541 0.064 2005 12,068.09 1,146.33 37.589 0.065 2006 12,881.16 1,226.93 38.638 0.066 2007 13,801.92 1,313.96 39.686 0.067 2008 14,828.35 1,402.32 40.735 0.07 2009 15,721.30 1,460.46 41.783 0.074 2010 16,828.56 1,543.69 42.832 0.076 2011 17,913.80 1,637.08 43.88 0.077 2012 19,155.77 1,740.42 44.929 0.08 2013 20,489.15 1,834.28 46.277 0.083 2014 21,967.09 1,941.30 47.665 0.086 Source: World Bank Read More