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This paper aims to introduce a novel family of probability distributions by the well-known method of the T–X family of distributions. The proposed family is called a "Novel Generalized Exponent Power X Family" of distributions. A three-parameters special sub-model of the proposed method is derived and named a "Novel Generalized Exponent Power Weibull" distribution (NGEP-Wei for short). For the proposed family, some statistical properties are derived including the hazard rate function, moments, moment generating function, order statistics, residual life, and reverse residual life. The well-known method of estimation, the maximum likelihood estimation method is used for estimating the model parameters. Besides, a comprehensive Monte Carlo simulation study is conducted to assess the efficacy of this estimation method. Finally, the model selection criterion such as Akaike information criterion (AINC), the correct information criterion (CINC), the Bayesian information criterion (BINC), the Hannan–Quinn information criterion (HQINC), the Cramer–von-Misses (CRMI), and the ANDA (Anderson–Darling) are used for comparison purpose. The comparison of the NGEP-Wei with other rival distributions is made by Two COVID-19 data sets. In terms of performance, we show that the proposed method outperforms the other competing methods included in this study. [ABSTRACT FROM AUTHOR]

This paper demonstrates, using a panel data model, that mainly firm-specific (microeconomic) versus macroeconomic variables affect the long-run profitability of a group of banks in Mexico in the pre- and COVID-19 periods. Interbank deposit, deposit rate, bank size, size of non-performing loan portfolio, delinquency, operating expenses, traditional deposit, salary, unemployment, and interest rate have statistical influence on bank profitability, but this relationship changes in the COVID-19 period. These results can be useful in the decisions of the different areas of banks, as well as for the design of public policies aimed at maintaining the stability of the banking system. [ABSTRACT FROM AUTHOR]

This paper presents evidence of large learning losses and partial recovery in Guanajuato, Mexico, during and after the school closures related to the COVID-19 pandemic. Learning losses were estimated using administrative data from enrollment records and by comparing the results of a census-based standardized test administered to approximately 20,000 5th and 6th graders in: (a) March 2020 (a few weeks before school closed); (b) November 2021 (2 months after schools reopened); and (c) June of 2023 (21 months after schools re-opened and over three years after the pandemic started). On average, students performed 0.2 to 0.3 standard deviations lower in Spanish and math after schools reopened, equivalent to 0.66 to 0.87 years of schooling in Spanish and 0.87 to 1.05 years of schooling in math. By June of 2023, students were able to make up for ∼ 60% of the learning loss that built up during school closures but still scored 0.08–0.11 standard deviations below their pre-pandemic levels (equivalent to 0.23–0.36 years of schooling). [ABSTRACT FROM AUTHOR]