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Important research once thought unassailable has failed to replicate. Not just in economics, but in all science. The problem is therefore not in dispute nor are some of the causes, like low power, selective reporting, the file drawer effect, publicly unavailable data and so forth. Some partially worthy solutions have already been offered, like pre-registering hypotheses and data analysis plans.

This is a review paper on the replication crisis, which is by now very well known.

This study offers another partial solution, which is to remind researchers that correlation does not logically imply causation. The effect of this reminder is to eschew “significance” testing, whether in frequentist or Bayesian form (like Bayes factors) and to report models in predictive form, so that anybody can check the veracity of any model. In effect, all papers could undergo replication testing.

The author argues that this, or any solution, will never eliminate all errors.

The purpose of this paper is to propose a semiparametric estimator for the tail index of Pareto-type random truncated data that improves the existing ones in terms of mean square error. Moreover, we establish its consistency and asymptotic normality.

To construct a root mean squared error (RMSE)-reduced estimator of the tail index, the authors used the semiparametric estimator of the underlying distribution function given by Wang (1989). This allows us to define the corresponding tail process and provide a weak approximation to this one. By means of a functional representation of the given estimator of the tail index and by using this weak approximation, the authors establish the asymptotic normality of the aforementioned RMSE-reduced estimator.

In basis on a semiparametric estimator of the underlying distribution function, the authors proposed a new estimation method to the tail index of Pareto-type distributions for randomly right-truncated data. Compared with the existing ones, this estimator behaves well both in terms of bias and RMSE. A useful weak approximation of the corresponding tail empirical process allowed us to establish both the consistency and asymptotic normality of the proposed estimator.

A new tail semiparametric (empirical) process for truncated data is introduced, a new estimator for the tail index of Pareto-type truncated data is introduced and asymptotic normality of the proposed estimator is established.

In this work, we estimated the different entropies like Shannon entropy, Rényi divergences, Csiszár divergence by using Jensen’s type functionals. The Zipf’s–Mandelbrot law and hybrid Zipf’s–Mandelbrot law are used to estimate the Shannon entropy. The Abel–Gontscharoff Green functions and Fink’s Identity are used to construct new inequalities and generalized them for m-convex function.

The purpose of this study is to extend the classical noncentral F-distribution under normal settings to noncentral closed skew F-distribution for dealing with independent samples from multivariate skew normal (SN) distributions.

Based on generalized Hotelling's T² statistics, confidence regions are constructed for the difference between location parameters in two independent multivariate SN distributions. Simulation studies show that the confidence regions based on the closed SN model outperform the classical multivariate normal model if the vectors of skewness parameters are not zero. A real data analysis is given for illustrating the effectiveness of our proposed methods.

This study’s approach is the first one in literature for the inferences in difference of location parameters under multivariate SN settings. Real data analysis shows the preference of this new approach than the classical method.

For the real data applications, the authors need to remove outliers first before applying this approach.

This study’s approach may apply many multivariate skewed data using SN fittings instead of classical normal fittings.

This paper is the research paper and the authors’ new approach has many applications for analyzing the multivariate skewed data.

Public libraries play a pivotal role in supporting education and literacy. They provide numerous services, activities, collections and resources for education and leisure. Bibliotheca Alexandrina (BA) is an international renowned public library that provides numerous services for different users worldwide. E-learning is an emergent and promising method for teaching and learning different subjects such as the science, technology, engineering and mathematics (STEM). The e-learning educational system is quite novel in Africa and the Middle East; hence, this paper presents the whole concept to the reader. In addition, it demonstrates number of e-courses tackling different domains provided by different educational institutions, national and public libraries worldwide.

In 2017, the BA inaugurated its e-learning services to cope with the new educational trend and to consolidate the lifelong learning concept in the community. The author showed special interest to the case of e-learning in the BA, as it is a regional public library. The main idea of this paper is to attract attention toward public libraries as a promising venue for e-learning implementation for general knowledge, library information sciences, soft skills, elementary and informal STEM education. The paper discusses in details e-learning and its characteristics.

In addition, the paper compares traditional education (face-to-face) with e-learning education, mentions both their pros and cons and recommends blending the two educational methods as they complement each other. Furthermore, the author has selected a sample of different STEM e-courses (203 different e-courses). These e-courses were selected to assert the possibility of presenting STEM topics in the form of e-courses.

This study would be one of the emergent research studies that connect e-learning to both STEM disciplines and public libraries. Additionally, this research highlights the importance of public libraries and all the services they provide. In the mean time, it shed light on the important and unique role of specialized librarians. Briefly, public libraries with all their resources, services and expert librarians could provide an exceptional e-learning experience to their community and be of great help to educational institutions and organizations.

This study analyzes the impact of the procedures followed by the Central Bank of Jordan during the COVID-19 pandemic on the financial performance of Jordanian banks listed on the Amman Stock Exchange over the period (2019Q1–2021Q3).

The panel fixed effect model was used to measure the impact of each of the required reserve ratios and the deferred loans on the profitability of Jordanian banks represented by the return on total assets.

The results revealed a negative relationship at the significance level of 10% between the required reserve ratio and the return on total assets. Also, there is a negative relationship at the significance level of 5% between the deferred loans and the return on total assets.

The paper recommends the Central Bank of Jordan following a precautionary policy to encounter systematic risks that cannot be eliminated by using diversification.

With the severe impact of the Coronavirus pandemic on the overall economic performance of the national economic sectors and the subsequent negative impact on the living standard of society’s members, this study shows the government’s role represented by the procedures of its monetary authority (Central Bank of Jordan) to mitigate the effects of this pandemic, as well as measuring the impact of these procedures on the financial performance of Jordanian banks listed on the Amman Stock Exchange.

The main purpose of this research is to examine the influence of macroeconomic stability on economic growth of SAARC (South Asian Association for Regional Cooperation) countries.

Using panel data of 1991–2020, fixed effect regression analysis, pooled ordinary least squares and generalized method of moments techniques have been conducted to demonstrate whether macroeconomic stability contributes to economic growth. Moreover, cross-sectional dependency test, unit root test, correlation analysis and granger causality tests have been run.

Robust findings indicate that inflation has negative impacts on economic growth which indicates that lower level of macroeconomic instability promotes countries’ economic growth. This study also observed that foreign direct investment, domestic credit delivered to private sector, currency exchange and institutional difference across countries are affirmatively connected while labor force is negatively associated with economic growth.

Empirical findings of this study signify that macroeconomic stability have significant effects on economic growth. Findings of this study have superior contributions for the policy makers to achieve sustainable economic growth.

The purpose of this article is to show the gains that can be made if researchers were to use gain-probability (G-P) diagrams.

The authors present relevant mathematical equations, invented examples and real data examples.

G-P diagrams provide a more nuanced understanding of the data than typical summary statistics, effect sizes or significance tests.

Gain-probability diagrams provided a much better basis for making decisions than typical summary statistics, effect sizes or significance tests.

G-P diagrams provide a completely new way to traverse the distance from data to decision-making implications.

This paper aims mainly at introducing applied statisticians and econometricians to the current research methodology with non-Euclidean data sets. Specifically, it provides the basis and rationale for statistics in Wasserstein space, where the metric on probability measures is taken as a Wasserstein metric arising from optimal transport theory.

The authors spell out the basis and rationale for using Wasserstein metrics on the data space of (random) probability measures.

In elaborating the new statistical analysis of non-Euclidean data sets, the paper illustrates the generalization of traditional aspects of statistical inference following Frechet's program.

Besides the elaboration of research methodology for a new data analysis, the paper discusses the applications of Wasserstein metrics to the robustness of financial risk measures.

The purpose of this paper is to investigate and review the impact of the use of statistical quality control (SQC) development and analytical and numerical methods on average run length for econometric applications.

This study used several academic databases to survey and analyze the literature on SQC tools, their characteristics and applications. The surveys covered both parametric and nonparametric SQC.

This survey paper reviews the literature both control charts and methodology to evaluate an average run length (ARL) which the SQC charts can be applied to any data. Because of the nonparametric control chart is an alternative effective to standard control charts. The mixed nonparametric control chart can overcome the assumption of normality and independence. In addition, there are several analytical and numerical methods for determining the ARL, those of methods; Markov Chain, Martingales, Numerical Integral Equation and Explicit formulas which use less time consuming but accuracy. New ideas of mixed parametric and nonparametric control charts are effective alternatives for econometric applications.

In terms of mixed nonparametric control charts, this can be applied to all data which no limitation in using of the proposed control chart. In particular, the data consist of volatility and fluctuation usually occurred in econometric solutions. Furthermore, to find the ARL as a performance measure, an explicit formula for the ARL of time series data can be derived using the integral equation and its accuracy can be verified using the numerical integral equation.