Purpose: This paper aimed to establish a latent content (LC) model of economic growth that integrates both economic and non-economic variables. Methodology: The study used a cross-sectional survey research design. The checklist questionnaires were used to collect primary data. The sample size of the study was 2011 individuals, randomly sampled from Mwanza and Kagera regions in Tanzania. Cronbach’Alpha and principal component analysis (PCA) were used to test reliability and validity of questionnaires respectively. The study used both linear and non-linear modelling data analytics methods to examine assumptions of the LC model of economic growth.  Clearly, the study used automatic linear modelling, stochastic structural-factor frontier analysis, and structural equation modelling to test the linearity assumption of the LC model. Moreover, the probit model and neural network analysis were used to examine the non- linearity assumption of the LC model. Findings: The study evidenced that the LC model was significantly determined by capital, psychological well-being (PWB), and labour. However, the labour was found significant negatively impacts economic growth. The subjective well-being (SWB) indicators were found insignificantly impacting the economic growth, however they have indirect impacts. Furthermore, the study confirmed that non-economic variables had less probabilistic power than economic variables. The paper concluded that an optimal economic growth (GDP) was direct related to capital, psychological wellbeing and inversely proportional to labour. However, the effectiveness of capital and labour were due to mediation effects of subjective well-being and psychological well-being respectively. Unique contribution to theory, practice and policy: The LC model of economic growth introduces a modern theory of economic growth, that its adoption will affect the traditional economic theories, practices and policy settings. The model was found empirically valid, hence, the paper recommended the adoption of the LC model in pre-and post micro and macro-economic policy and strategy designs/planning. The adoption of the model will increase the probability of an individual of getting a high economic growth (output) as well as the strengthening of psychosocial resources. However, this study suggested further study by using longitudinal data to attest the LC model as the current study only limited on the cross-sectional data.

The study aimed to uncover the unobserved heterogeneity of the population in Mwanza and Kagera regions. The study examined if living in Mwanza region is more economically better and happier than living in Kagera region. The cross-sectional survey research used with the cross-sectional data from 211 individuals sampled randomly from 4 districts, Nyamagana and Misungwi from Mwanza region, and Bukoba and Muleba from Kagera region. The FIMIX-PLS used to analyse the data. The study found that the population of Mwanza and Kagera regions can be grouped into two mains classes which are class one with a lower annualised income below 1.5 TZS millions per capita and a lower mean score of fundamental psychological factors for happiness (FPFH) in comparing to the class two. The class two is characterised with a higher annualised income about 2.45 TZS millions per capita and a higher mean score of FPFH in comparing to class one. The study evidenced that respondents of Mwanza region have a higher annualised income and FPFH scores than respondents of Kagera region in each class. Therefore, the study concluded that living in Mwanza region is more economically better and happier than living in Kagera region. The study recommended the immigration to seek the economic opportunity and happiness, for example immigration from Kagera region to Mwanza region or nation to nation is encouraged. Moreover, further study recommended by using a panel data to attest the posed facts because this study limited to the cross-sectional data.

The study was based on determination of influences of capital structure on the working capital and growth opportunity of the listed companies in Tanzania. The study targeted to meet three objectives.  These objectives are to investigate  on how Tanzanian listed companies behave in their capital structure, working capital intensity and growth opportunity, to examine the influence of the capital structure on working capital intensity and growth opportunity of Tanzanian listed companies and to examine the potency of working capital (current asset) in advocacy of growth opportunity of Tanzanian listed companies. The study used descriptive study strategy on ten listed companies at Dar Es Salaam Stock Exchange as per October, 2012.  The documentary analysis and website survey used to collect the secondary data.  The multivariate multiples regression model used to analyses data. The findings of the study lay that the listed companies of Tanzania are unleveraged and growing fast and are illiquidity. It is found that there is no significant relation of capital structure, working capital and growth opportunity of Tanzanian listed companies. The potency of current asset to generate sales of companies is averaged at 0.555 Tanzanian shillings per one shilling of sales. It is recommended that companies aiming for growing should adhere to investment opportunity available in their companies and should prefer internal financing to external financing.

This paper examined the hidden demographic barriers of economic growth. The study used a cross-sectional survey researches design. The primary data were collected by using a psychometric scale from 211 individuals who were randomly sampled from the Mwanza and Kagera regions in Tanzania. The data were linearly analysed by the weighted least squares (WLS) and Analysis weighted- automatic linear modelling (AW-ALM), and non-linearly analysed by Gaussian mixture model (GMM) and neural network analysis (NNA). The study found that the main hidden demographic barrier to economic growth is the negative subjective well-being of an individual’s current age and education level. Moreover, the GMM revealed that there is no significant data or regional clusters or classes in the study population. Furthermore, NNA evidenced the most effective predictor of economic growth is age, followed by education. The study concluded that the most hidden demographic factors that hinder economic growth are negative perceptions of an individual on his/her current age and level of education, not the age maturity, and education level. Operationally or practically, the paper implicates several socio-economical policies, mostly the national aging policy (NAP), the National Education and Training policy (NETP), the National Employment Policy (NEP), and regulations /laws on national social security funds schemes at national, regional and global levels. Therefore, the paper recommended that government and other education stakeholders increase the policy commitment on the mathematics, science, and technology subjects to be compulsory for primary and secondary schools, and the extension of the retirement age from 60 years (voluntary) to 65 years (compulsory)

This paper analysed the effects of taxes and benefits on income inequality and poverty in Latin America. The study used an exploratory research design, with both linear and nonlinear regression models.  The paper found that both direct and indirect taxes have no direct influence on income inequality and poverty in a short-term.  Significantly, the social spending is found to reduce both poverty and inequality. The paper concluded that, taxes –benefits system in Latin America is   effective to eradicate income inequality and poverty, but it is ineffective to reduce the poverty rate and income inequality amongst the countries. The paper recommended that the countries in Latin America should set the policy priority on increasing the social spending in term of direct benefits, in-kind benefits and contributory pensions and subsidies as found to have a linear relationship with   the income inequality and poverty.