Since the onset of the COVID-19 pandemic, there has been an increased focus on research concerning individual well-being and its global impact. Understanding the factors that contribute to or detract from subjective well-being can enable practitioners to better support individuals affected by life events and crises. This study employs a single mediator model through structural equation modeling to explore the relationship between subjective happiness, life satisfaction, and subjective well-being. Furthermore, the model assesses whether these relationships are mediated by individual characteristics such as gender, social class, and relationship satisfaction. The paper presents the results of testing eight hypotheses related to Subjective Well-being, utilizing data from the Subjective Happiness Scale, the Satisfaction with Life Scale, the Brief Resilience Scale, the Relationship Assessment Scale, the Adverse Childhood Events inventory, the Adult Attachment Scale, and demographic information provided by the research participants. JEL classification numbers: C1, C3, C4, C9. Keywords: Structural equation modeling, Mediator model, Subjective well-being, Satisfaction with life, Resiliency, Adult attachment.
A new generalization of the Topp-Leone Lomax distribution was developed. The new distribution is a half logistic transformation of the Topp-Leone Lomax distribution. Some important statistical properties of this new distribution were explored that include raw moments, moment generating function, probability weighted moments, distribution of order statistics, R´enyi entropy, and Shannon entropy. The maximum likelihood estimation (mle) technique was used to estimate the unknown model parameters estimates. Consistency of the mles was assessed via Monte Carlo simulation studies. The mle technique produced consistent estimates based on the simulation studies results and applications to real datasets as demonstrated by means of log-likelihood profile plots. The usefulness the half logistic-Topp Leone Lomax distribution was assessed by means of applications to real world datasets. The model was compared to other generalizations of the Lomax distribution. The new distribution emerged as a good contender to the other generalizations involving the Lomax distribution. JEL classification numbers: E18, HO, I1, J64, J88. Keywords: Half Logistic Transformation, Topp-Leone Lomax Distribution, Maximum Likelihood Estimation, Log-Likelihood Profile Plots, Lomax Distribution.
Abstract The Topp-Leone generalized power Weibull distribution, which is an extension of generalized power Weibull, is proposed and its properties explored. The failure rate of the proposed distribution exhibits increasing, reversed J, upside-down bathtub, and bathtub shapes. Some statistical properties are obtained: quantile function, moments, moment generating function, incomplete moment, mean and median deviations, mean residual life function, and Lorenz as well as Bonferroni curves. The maximum likelihood estimation approach is deployed to estimate the model parameters. Simulation studies are conducted to evaluate the performance and accuracy of the maximum likelihood estimates of the model parameters. Applications of the model to real datasets are presented. A location-scale regression model is also developed for the proposed model and its application has been demonstrated with a real dataset. Keywords: Bonferroni, Deviation, Mimicked, Simulation, and Upside-down Bathtub.
Abstract This paper aims to study the short-run and long-run cointegration relationships between the total population, the cumulative number of new COVID-19-infected cases, and the cumulative number of deaths due to COVID-19 in different states in the US. The short-run relationship is assessed using the ARDL model, and the long-run relationship is assessed using the ARDL bounds test. To assess the consistency of the model parameters, the cumulative sum of recursive residuals test and the cumulative sum of recursive residuals squares tests are used. JEL classification numbers: E18, HO, I1, J64, J88. Keywords: Autoregressive distributed lag model, Error correction model, Unit root tests, Residual diagnostics, Bounds cointegration test, Stability tests.
Abstract This study investigates fertilizer consumption patterns across 41 countries from 1961 to 2021. Descriptive statistics reveal substantial variation in average fertilizer use (kg/hectare) and variability between countries. Statistical analyses confirm significant differences in consumption patterns, with fertilizer consumption identified as a major explanatory factor. Cluster analysis further differentiates countries into two groups based on their consumption levels. These findings highlight the need to consider fertilizer use within a country-specific context. Further research exploring the underlying factors driving these variations and their impact on crop yields could inform strategies for optimizing fertilizer use and promoting agricultural sustainability. JEL classification numbers: E18, HO, I1, J64, J88. Keywords: ANOVA, MANOVA, Cluster analysis, Inter and intra-cluster distance.
