The global energy system is highly vulnerable to climate variability and change. This results in a vast range of impacts on the demand sector production supply channels. article aims estimate variables such as heating cooling temperatures, income, population, price residential electricity G7 countries. Methodologically, this study uses second-generation panel unit root cointegration approaches ...

The following study examined how energy use and technological advancement impacted environmental sustainability in QUAD (US, Japan, Australia, India) economies between 1991 2021. considers the generation of renewable energy, fossil fuel use, effects economic expansion on sustainability. research used moment quantile regression technique based outcomes slope heterogeneity, cross-sectional depend...

This paper examines the combined effect of interest rates and poverty levels of microfinance clients on loan size. Cross section data on 2,691 clients and non-clients households from Ghana is used to test the hypothesis of loan price inelasticity. Quantile regression and variants of least squares methods that explore endogeneity are employed. We find the expected inverse relationship only for t...

We consider numerical schemes for root finding of noisy responses through generalizing the Probabilistic Bisection Algorithm (PBA) to the more practical context where the sampling distribution is unknown and location-dependent. As in standard PBA, we rely on a knowledge state for the approximate posterior of the root location. To implement the corresponding Bayesian updating, we also carry out ...

This article considers the relationship between trade intensity, energy consumption, income per capita, and carbon dioxide emissions from 1970–2016 for Portuguese economy. Considering arguments of monopolistic competition, tests hypotheses consumption on climate change. We use autoregressive distributed lag-ARDL model, quantile regression, cointegration models such as fully modified ordinary le...

We investigate analytical cost distributions in the setting of a dynamic stochastic scheduling problem where customers are served from a central location within some given time-frame, for the case where customer locations are uniformly distributed on the boundary of the unit circle. Two distance metrics are considered and analytical expressions for the distribution of the resulting costs are de...

In this study, new unit quantile regression model, called the Unit Gamma/ Gompertz for bounded responses is developed by re-parameterizing Gamma/Gompertz distribution. To estimate parameters of maximum likelihood approach used to develop estimators parameters. Monte Carlo simulations are test consistency model. The application model illustrated using three real life datasets and results reveale...

We propose a notion of conditional vector quantile function and a vector quantile regression. A conditional vector quantile function (CVQF) of a random vector Y , taking values in R given covariates Z = z, taking values in R, is a map u 7→ QY |Z(u, z), which is monotone, in the sense of being a gradient of a convex function, and such that given that vector U follows a reference non-atomic distr...