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The gender gap in education has been a significant concern for Moroccan policymakers and researchers, but the quantitative measurement of this gap has often been overlooked. This study specifically examines the gender gap in academic achievement in reading and mathematics at both the national and residential levels. The objective is to identify the factors that influence gender performance differences and their magnitude. To achieve this, micro-level data from 5427 students extracted from the PIRLS 2016 and TIMSS 2015 surveys were analyzed. The Blinder-Oaxaca (1973) decomposition technique was employed to assess the significance of the differences and to break down the performance gaps by incorporating explanatory variables related to schools, teachers, and students' characteristics. The results reveal a significant gender difference in favor of girls in reading, both nationally and in urban areas. In mathematics, the gender gap is not statistically significant and is approximately 3 points at the national level. Only 29% of the reading gap can be explained by the selected variables, while this percentage is around 20% for the math gap. Pre-school attendance, maternal education, schools, and schools' characteristics are identified as significant factors influencing the reading gap at the national and urban levels. In contrast, at the rural level, home conditions and the characteristics of the school and teacher play a more decisive role.

This study aimed to unveil the evolving landscape of digital financial inclusion in African countries during the post‐COVID‐19 era. We examined factors influencing the access and usage of digital financial services and identified population segments facing increased exclusion due to the digital divide. First, by applying principal component analysis to data collected at the country level from 39 African countries in 2014, 2017, and 2022, we developed a digital financial inclusion index. Second, the empirical research utilized a microlevel dataset of 29,042 adults from 29 countries, sourced from the World Bank's Global Findex 2021 database, employing the instrumental variable probit methodology. Comparative analysis showed improvements in digital financial inclusion rankings for Kenya, Lesotho, and Botswana, while Egypt, Sudan, Tunisia, and Niger experienced declines, indicating limited access. Our empirical findings suggest that certain groups, such as women and individuals with limited education and lower incomes, encounter obstacles in accessing digital financial services. Factors such as education level, labor market participation and access to technology and internet infrastructure emerged as crucial in promoting digital financial inclusion. Our sample's representative nature enhances the study's practical implications, guiding public policies and international institutions to accelerate digital financial inclusion in Africa. [ABSTRACT FROM AUTHOR]

If the pattern of appliance use varies between households, then we expect that appliance replacement cycle also varies between households. Although many studies identified early adopters of new energy-efficient products, few studies have examined households that have been using old energy-inefficient products and how their characteristics are associated with product replacement. In this study, we initially modify a survival function and develop an economic model to evaluate the impact of household characteristics on appliance replacement. We subsequently apply the model in microlevel data analysis from the Survey on Carbon Dioxide Emission from Households obtained from the Ministry of the Environment of Japan. We use information about age distribution of refrigerators (REFs) and examine how family size, household income, and age of household's head affect the replacement cycle of REFs. Our empirical results reveal that (1) large-sized, (2) high-income, and (3) young households replace REFs more rapidly. These findings suggest that policies that encourage small-sized, elderly, and low-income households to replace old appliances are needed. [ABSTRACT FROM AUTHOR]

Many countries have promoted the replacement of conventional lamps with next-generation lamps to reduce electricity usage for lighting. In Japan, the majority of the lamps sold at home appliance mass merchant shops have been changed from incandescent lamps to energy-saving lamps. All conventional lamps are planned to be replaced with light-emitting diodes (LEDs) by 2020. Although the energy-saving effect of LEDs has been stressed in many engineering studies, the amount of electricity that is actually saved by the installation of LEDs has not been examined. Using microlevel data from the Survey on Carbon Dioxide Emission from Households (SCDEH), we compare monthly electricity usage between households using conventional lamps and those using LEDs. Our empirical results demonstrate that households have reduced their electricity usage by 1.96% through past LEDization. Households can reduce their electricity usage by an additional 6.99% when LEDization is completed. The empirical results further demonstrate that middle-income households have higher price elasticity of electricity demand and are more likely to receive greater benefit from LED installation. [ABSTRACT FROM AUTHOR]

The gender gap in education has been a significant concern for Moroccan policymakers and researchers, but the quantitative measurement of this gap has often been overlooked. This study specifically examines the gender gap in academic achievement in reading and mathematics at both the national and residential levels. The objective is to identify the factors that influence gender performance differences and their magnitude. To achieve this, micro-level data from 5427 students extracted from the PIRLS 2016 and TIMSS 2015 surveys were analyzed. The Blinder-Oaxaca (1973) decomposition technique was employed to assess the significance of the differences and to break down the performance gaps by incorporating explanatory variables related to schools, teachers, and students' characteristics. The results reveal a significant gender difference in favor of girls in reading, both nationally and in urban areas. In mathematics, the gender gap is not statistically significant and is approximately 3 points at the national level. Only 29% of the reading gap can be explained by the selected variables, while this percentage is around 20% for the math gap. Pre-school attendance, maternal education, schools, and schools' characteristics are identified as significant factors influencing the reading gap at the national and urban levels. In contrast, at the rural level, home conditions and the characteristics of the school and teacher play a more decisive role. [ABSTRACT FROM AUTHOR]

We develop a nowcasting framework, based on microlevel data, to provide faster estimates of the Finnish monthly real economic activity indicator, the Trend Indicator of Output (TIO), and of quarterly GDP. We use firm-level turnovers, which are available shortly after the end of the reference month, and real-time traffic volumes data, to form our set of predictors. We rely on combinations of nowcasts obtained from a range of statistical models and machine learning techniques which are able to handle high-dimensional information sets. The results of our pseudo-real-time analysis indicate that a simple nowcast combination based on these models provides faster estimates of TIO and GDP, without increasing substantially the revision error. [ABSTRACT FROM AUTHOR]

Differences in the adoption of light-emitting diodes (LEDs) across households have not been fully investigated. Using the microlevel data of Japanese households, we identify the determinants of LED adoption. We take two approaches in the empirical analysis. In the first approach, we define the adoption stage of each household based on whether LEDs are installed in different types of rooms. We then analyze the relationship between the adoption stage and household characteristics based on the ordered logit model. In the second approach, we apply the item response theory method to assess the household's ability to adopt LEDs. We then analyze the relationship between household adaptability and characteristics based on the two-sided truncation model. We find that the impacts of household characteristics on LED adoption are similar between the two approaches: low-income households do not use LEDs; household heads aged 65 to 74 are active in LED installation, although those older than 75 are less active; people living in old or rented houses do not use LEDs. Finally, we find a large variation in LED installation across prefectures. • We use LEDization stage and LEDization ability indexes as response variables. • LEDs are less popular among low-income households. • Household heads aged 65 to 74 are active in LED installation while those older than 75 are less active. • LEDs are less popular among households who live in old or rented houses. • There is a large variation in LED installation across prefectures. [ABSTRACT FROM AUTHOR]