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All Journal International Journal of Business, Management and Economics International Journal of Finance Research
Bundala, Ntogwa N.
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Economics, Econometrics & Finance Social Sciences

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The Hidden Demographics Barriers of the Economic Growth: A Psychometric Approach Bundala, Ntogwa N.
International Journal of Business, Management and Economics Vol. 3 No. 1 (2022): International Journal of Business, Management and Economics
Publisher : Training & Research Institute - Jeramba Ilmu Sukses (TRI-JIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/ijbme.v3i1.471

Abstract

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)
Homo-Hetero Pairing Regression Model: An Econometric Predictive Model of Homo Paired Data Bundala, Ntogwa N.
International Journal of Finance Research Vol. 3 No. 2 (2022): International Journal of Finance Research
Publisher : Training & Research Institute - Jeramba Ilmu Sukses (TRI-JIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/ijfr.v3i2.792

Abstract

The study aimed to examine the technical and fundamental hypotheses in NYSE, NASDAQ and S&P 500 stock exchange markets. The main determinants (variables) that were examined were stock trading volumes, closing stock prices and stock information available in the stock exchange market. The 240 days, 197 days and 253 days data of closing stock prices and trading volumes at NYSE, S&P500 and NASDAQ stock exchange markets were systematically collected from June 2021 to June 2022. The data was analysed by using the Homo-Hetero Pairing (HHP) Regression Model. This model was developed to detect the linear and non-linear behaviour of data. The study evidenced that both the technical and fundamental hypotheses in  NYSE, S&P500 and NASDAQ stock exchange markets are defined by the inverse and S-curved models in two distinctive pairing classes called the positive-positive pairing (PPP) class and the negative-positive pairing (NPP) class. The study concluded that the optimal prediction of the stock price or return is achieved by the fundamentalists in the stock exchange markets. The study recommends that stock investors should priorities the use of the fundamental hypothesis to make their portfolio investment decision. Moreover, the study recommends the application of the HHP regression model in financial markets, economics, psychology, sociology, and medicine studies.  In addition, the HHP regression model is recommended for the prediction of water waves in the investigation of hydrodynamic and erosion-accretion processes
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