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This paper uses micro data from Tanzanian manufacturing firms to examine the influence of education policy on returns to schooling. The question stems from the fact that over time education systems and policies are likely to change, hence workers who attended the same level of schooling in different years are likely to display differences in returns to schooling. The paper contributes knowledge in the empirical estimation of returns to schooling where instrumental variables are usually individual characteristics such as parental background or education background. In this paper, education policy differences that affect school attendants differently are used as instruments instead. There are views that education policy is non-exogenous, and hence cannot be instrumental in endogenous schools. In this paper an attempt is made to see the extent to which this view can hold in our empirical estimations. This paper has the advantage of making use of panel data to directly estimate the effect of education policy on earnings, while controlling for schooling. The resulting estimates of the study strongly support that returns to education have changed over time. The results based on years of schooling also support this finding, but when we control for firm fixed effects, they lose their statistical significance.

This paper uses macro data to analyse the effects of population growth on economy-wide productivity. Specifically, it looks at how increased labour participation due to change in population size affects productivity. Since labour-intensive technology is dominant in major economic sectors of rural agriculture and urban informal and service sectors, the paper anticipated that an increase in population size would create demographic dividend in the form of increased workforce and higher output per labour. The paper estimates a Cobb Douglas production function using time series data from the censuses of 1967 (12.3m people), 1978 (17.5m people), 1988 (23m people), 2002 (34.4m people), and of 2012 (44.9m people). The results reveal a positive effect of population size on labour productivity, controlling for other production inputs like capital, intermediate inputs, raw materials, and others. The estimated difference in underlying productivity was 30 percent higher in the early 1970s, and peaked in the mid-1970s, reaching 45 percent higher than what we observe in 2012. The paper concludes that there are evidences of positive effects of population growth on the economy through increased output. This calls for the need to consider labour-intensive production when setting up new economic enterprises.

This paper examines the effect of population growth on the size of Tanzania's forest cover by assessing the extent to which the growing demand for forest goods and services from rapid expanding population lead to deforestation. Using long span of data, the paper predicts future demand of forest products, size of forest cover, and population in the next ten years (up to 2018). The statistical analysis of forecasting models estimated in the paper confirms that unprecedented growth in population of Tanzania accounts for the loss of forest cover in Tanzania. Considering the annual population growth rate of about 3%, the paper demonstrates that the population will reach 53.4 millions in the next ten years. Furthermore, the forecasting model estimates that forest cover will decline by 11%. The paper further shows that within a time span of ten years from 1990 to 2000 the forest cover changed by 10.8%. The aggregate forecasting results on forest cover change show that in a time span of 25 years, forest cover in the country will have declined by nearly a quarter. The paper concludes that a positive correlation between growth in population and use of forest products calls for an integration of population policies and programs with forest management strategies. Use of alternative resources such as LPG and natural gases to reduce pressure on wood fuel, tree planting, and sustainable forest management plans can potentially help to reduce pressure on the forest cover, thereby curbing deforestation in Tanzania that is fuelled by expanding needs of a growing population.

The creation of a long-term linkage between economic growth and environmental protection is a subject of an ongoing discussion among scholars and policymakers. The relationship between environmental quality and economic growth is viewed from two different angles. According to the first, it is impossible to protect the environment and increase the economy at the same time since doing so will inevitably result in the extinction of either one or both. The other contends that economic advancement and higher environmental quality can be achieved simultaneously since increasing economic growth raises income levels, which in turn increases the demand for environmental protection. However, there is a disagreement over how much environmental resources should be exploited to support rapid economic expansion. This study used the approach of the Environmental Kuznets Curve (EKC) hypothesis to investigate the relationship between economic growth and environmental pollution in Tanzania. Tanzania's economy annual data from 1970 to 2018 was used in the ARDL bounds testing for cointegration procedures. The evidence suggests that environmental pollution and economic growth have a U-shaped relationship, which rules out the existence of a traditional EKC in Tanzania. Like in many emerging economies, environmental pollution is anticipated to rise in Tanzania if economic expansion continues beyond a threshold level. The U-shaped link between economic growth and environmental pollution is important for policy formulation because both economic growth and a clean environment are welfare-enhancing; therefore, it is possible to have two policies that are mutually supportive rather than antagonistic. This can be achieved by having a proper environmental, legal, and institutional frameworks.