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This study evaluates the impact of number of parameters on the probability distribution. In this study, we have added one, two and three parameters in a single parameter exponential distribution and study the validation and precision of the probability models due to the added parameters. The primary objective of this research is to know about the impact of higher number of parameters on validation and precision of the probability models. We have generated a sample dataset of size hundred from two parameter exponential distribution newly formulated by adding a shape parameter to classical exponential distribution. For all models defined in this study, probability density curves and hazard rate curves are plotted and found that the models having more parameters are more flexible and valid compared to models having a smaller number of parameters. Plotting P-P and Q-Q plots is used to validate the models and estimate their parameters using the maximum likelihood function. Models with higher parameters have better validity, as seen by P-P and Q-Q plots. Calculations are made to determine the Akaike, Bayesian, Corrected Akaike, and Hannan-Quinn information criteria for model selection. Information criteria show that the model with larger number of parameters is more valid and flexible. To test the goodness of fit, Anderson darling test, Kolmogrov Smirnov test, and Cramer-von Mises methods are used. The R programming language is used to carry out all of the graphical and mathematical computations.

Keywords: Exponential distribution, Parameters Probability distribution, Model formulation, Validation, Maximum likelihood estimation

The study was conducted to investigate the impact of liability management on the performance of construction companies in Nigeria. The research was motivated by apparent paradigm shifts by construction companies which have brought about additional risks to their operations. Liability management is a management tool to maximize investment returns while minimizing risks. The effective management of liabilities of companies is essential to their sound financial success. Ex-post facto research design was adopted; data were obtained from annual reports of quoted construction companies on the Nigerian exchange group (NGX) which covers a period of ten (10) years from 2012 to 2021. The independent variables used were Debt to asset ratio (DAR), Debt to equity ratio (DER) and Quick ratio (QR) while the dependent variable is Return on assets (ROA). The influence of individual independent variables was tested against Return on assets (ROA) using simple regression technique,  PSS 23 package was used for analysis. An examination of the result for variable inclusion revealed that DAR, DER and QR have positive influence on ROA. It was recommended that Construction companies should endeavor to put in place proper liability management policies to help in maximizing their profit while simultaneously boosting the efficiency and effectiveness with which liabilities are utilized to generate turnover. Construction companies should make more investments in real assets and keep more of cash and cash equivalents as they are capable of yielding higher coefficients in generating profit. Construction companies should avoid high levels of debt as these have a negative impact on profitability.

UNDP defines human development in its different human development reports, mainly from the 1990 to 2010 reports. The core definition which emerges from these definitions considers human development as “the process of enlarging people’s choices”. A question is, Does this short sentence perfectly represent the reality behind the concept of human development? The paper testes the ability of this UNDP’s core definition to describe the reality behind the concept of human development. To this end, we consider the main approaches to human development by selected pioneers of the human development approach to draw human development characteristics. From this literature review of UNDP’s definitions of human development, we highlight that UNDP’s definition suffers from two main missing links. The first is related to the non-inclusion of the idea of sustainability. The second is linked to the failure to take into account interpersonal relationships. This observation has an implication in that UNDP’s definition of human development needs an adjustment to take into account these two concepts and, as a consequence, the human development index should be refined to take these two dimensions into account.

JEL Classification: F63, O15

This study examined the impact of oil price undulation and trade openness on industrial output in Nigeria. The study adopted descriptive statistics, unit root test, correlation matrix, ARDL estimation and Co-integration test. The probability values of the Jarque-Bera test for all the variables are high, except for exchange rate for oil price volatility which is 1.990957, which implies the acceptance of normal distribution of the variables. The unit root test shows that, realGDP is the only variable integrated of order zero while all other variables are integrated of order one. The correlation matrix result showed that, most of the values are very low and the correlation between exchange rate and industrial output is very high with 0.95.The coefficient of trade openness(TOPEN) shows that, it has a non-significant positive effect on industrial output in the short-run, indicating a 1percent increase in trade openness will reduce by 0.373394. hence, the volatility of oil price has affected industrial output more negatively, though trade openness has been of great help with the recent increase in foreign direct investment over time, yet, it has not transformed to the desired growth in the industrial sector, as evidence from the result and Nigeria economy. So the study recommends that, all the problems confronting the nation’s industrial sector should be tackle headlong.

Keywords: Oil price fluctuation, Industrial Output, Trade Openness, gross domestic output

The investigation analyzed the impact of green climate finance on industrial development in Africa from 2017 to 2023. Green climate finance refers to funding acquired from various financial sources, to support climate change adaptation and mitigation efforts for the benefit of humanity. It was considered as the independent variable. The process of developing and expanding industries in an economy through the utilization of innovative technologies that enhance efficiency, speed, and quality of work, resulting in a rise in a company’s production levels and profitability. Industry (including construction) value added represent Industrial development as the dependent variable. Inflation was utilized as the control variable in the analysis. Previous studies in this area often overlooked including all African countries benefiting from green climate finance in their sample, thus motivating this study. The sample comprised the African countries that received aid through green climate finance during the specified timeframe. Several preliminary tests were conducted, including panel unit root test, parameter stability test, co-integration test, and error correction model. Hypotheses were assessed using panel ARDL model. The coefficient of the explanatory variable is 6.5731 and its corresponding probability value is 0.5712 .There is evidence of positive and non-significant impact of green climate finance on industrial sector contribution to GDP in Africa. The study recommend that donors and host countries should jointly be engaged during the implementation stage for proper accountability.

Keywords: Green Climate Finance, Industrial Development, Panel ARDL, GDP. Inflation Rate