Does National Gender Equality Matter? Gender Difference in the Relationship between Entrepreneurial Human Capital and Entrepreneurial Intention

Gender equality contributes to economic growth and social progress by promoting women’s social and economic participation. The national gender equality level can affect women’s education and opportunities for economic participation. In this work, we examine whether entrepreneurial human capital (entrepreneurial education and experience) affects entrepreneurial intention and whether these relationships depend on gender and a country’s gender equality level. We used Global Entrepreneurship Trend Report (GETR) data provided by the Korean Entrepreneurship Foundation. The global survey was conducted by the Korean National Statistical Office in 2016. The data were collected from 20 countries, including Korea, and contain at least 2000 individual responses from each country. We used HLM analysis with the HLM 6.0 program to examine the hypotheses. Our results show that entrepreneurship education increases entrepreneurial intention, and that the relationship is stronger among women than men. We also found that for women, the positive relationship between entrepreneurial education and entrepreneurial intention is stronger in countries with lower gender equality. As for prior entrepreneurial experience, neither gender nor national gender equality level moderated the relationship between experience and entrepreneurial intention. This study contributes to the extension of entrepreneurship theory, especially in the area of women entrepreneurship. We confirm that entrepreneurial human capital contributes to entrepreneurial intention, and that gender and national gender equality level comprise an important social context that influences the effects of education and experience on the entrepreneurial intention of women.

Model-based single-month unemployment rate estimates for the Brazilian Labour Force Survey1

The Brazilian Labour Force Survey (BLFS) is a quarterly rotating panel survey with 80% sample overlap between two successive quarters. Monthly unemployment rate estimates are regularly produced based on a three-month average of direct estimates. Due to the unforeseen situation of COVID19 pandemic and its effects in the economy and labour market, there was a need to investigate model-based estimation procedures to obtain unemployment rate single-month estimates. We present structural time series models developed to produce model-based single month estimates at national level as well as small area (state-level) estimates at a higher frequency than those currently being published. Using the state-space framework, the models account for the autocorrelation due to sample overlap and the increased dynamics in the labour force series in 2020. In addition, bivariate models that combine claimant count and survey data are investigated. The models not only yield estimates with better precision than direct estimates, since the latter were affected by a rise in non-response, but they can deliver reliable state-level official statistics at a monthly frequency that are presently required. The new improved model-based estimates were proposed as experimental statistics for the Brazilian national statistical office (IBGE).

Dinacharya: The Essential Daily Routine for Geriatric Care

The term Geriatrics is made by union of two Greek word first ‘geras’ (old age) and second ‘iatros’ (physician) and derived from Greek root “gergero- geronto” meaning old age or the aged or especially one receiving special care. Geriatrics is the branch of medicine that focuses on health promotion and prevention and treatment of disease and disability in later life. In India population of the elderly has been increasing steadily since 1961 as it touched 13.8 crore in 2021, growing faster due to decrease in death rate, according to a study by National Statistical Office (NSO). Ageing is the process in which structural and functional changes occur with passage of time. Thus study of all aspects of ageing including physiological, pathological, psychological, economical and sociological problems is termed as Geriatrics. With advancing age, several changes take place in the body, in the external appearance as well as in Dosha, Dhatu, Mala, Agni, Oja level, also on the mental functions. In Ayurvedic texts, there are many ways given for prevention and promotion of health, one of them is Dinacharya (daily regimen), which is most important part to maintain a healthy and happy life. The importance of appropriate daily routine cannot be underestimated. It set the wheels in motion for entire day, bringing a sense of calm and well-being. It gives the body, mind and spirit the chance to start afresh.

Attitude and Behaviour For Preventing COVID-19 Disease Infections in Mali: An Analysis Based On COVID-19 Panel Phone Survey

Background COVID-19 outbreak has been declared as an emerging and conflict situation by the World Health Organization (WHO) due to the multiple nature of infection through international spread that poses a serious threat to populations’ health and socio-economic conditions household in general. Objective This study aims to analyse the behaviour adopted by households’ heads for preventing COVID-19 infection in Mali. Methods We collected data from the COVID-19 Panel Households survey collected in Mali by the National Statistical Office, Institut National de la Statistique (INSTAT), in collaboration with the World Bank in October 2020. We used a multivariate logistic regression model. Results A total of 1,514 households heads were included. The age between 20 and 90 years old. The poor households represented 27%. Being a household with a low-income reduced the probability of using masks (p < 0.1). Being poor increased the probability to agree with vaccination (p < 0.01). The health services utilisation increased the probability of wear masks (p < 0.01), getting tested (p < 0.01), and agree with the vaccine (p < 0.01). People with a high occupation volume were more likely to wear protective masks (p < 0.1). Conclusion Behaviour and attitude prevention varied according to households characteristics. Local government and policymakers should continue to provide more economic, medical and social assistance to protect the population, which would reduce the spread of the disease, particularly to households living in vulnerable regions of the country most affected by conflict and food insecurity.

The Tool for Assessing Statistical Capacity (TASC)

Identifying strengths and limitations is crucial to building the statistical capacity of a national statistical office (NSO). The Tool for Assessing Statistical Capacity (TASC), developed by the U.S. Census Bureau, offers an efficient solution for statistical capacity assessments because it allows for one or two administrator(s) – who need not necessarily be expert in all census and survey operations – to obtain a comprehensive and objective picture of household-based census and survey operations at an NSO. Administering the TASC is cost effective and the results are widely accepted because of its participatory nature, making it an invaluable instrument for assessing an NSOs readiness to conduct surveys and censuses. Results from the TASC are used to target training to build statistical capacity. This paper describes the foundational framework, modality of measurement, strengths, and limitations of the TASC.

A Guidebook on Mapping Poverty through Data Integration and Artificial Intelligence

The “leave no one behind” principle of the 2030 Agenda for Sustainable Development requires appropriate indicators to be estimated for different segments of a country’s population. The Asian Development Bank, in collaboration with the Philippine Statistics Authority, the National Statistical Office of Thailand, and the World Data Lab, conducted a feasibility study that aimed to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics in the Philippines and Thailand. This accompanying guide to the Key Indicators for Asia and the Pacific 2020 special supplement is based on the study, capitalizing on satellite imagery, geospatial data, and powerful machine-learning algorithms to augment conventional data collection and sample survey techniques.

Impact of COVID-19 Pandemic on Total Mortality in Poland

Background: According to published data the number of deaths attributed to COVID-19 is underestimated between 30 and 80%. Aim: The aim of this study is to assess the impact of COVID-19 on total mortality of Poland and the Silesian voivodship. Methods: Secondary epidemiological data on COVID-19 deaths were obtained from the Ministry of Health registry and data on total mortality were gathered from the National Statistical Office and Registry Office in Poland. Three scenarios were used to estimated COVID-19 deaths: real number + an extra 30%, 60%, and 70% excess total deaths. Results: In 2020, there were 73,254, 64,584, and 67,677 excess deaths in comparison to 2017–2019, respectively. For the Silesian voivodship, it was 8339, 7946, and 8701, respectively. The total mean increase in deaths was 16% for the whole country and the Silesian voivodship. The simulation for 30% extra COVID-19 deaths gave COVID-19 mortality equal to 12.5%; n = 50,708 deaths, for extra 60%; 17.9% n = 72,866 and for extra 70%; 19.7% n = 80,251 for Poland; and 11.9% (n = 6072), 17.2% (n = 8740), 24.2% (n = 12,297), respectively, for the Silesian voivodship. Conclusions: The participation of COVID-19 in total deaths should not exceed 20% for Poland and 24% for the Silesian voivodship in 2020.

Mapping the Spatial Distribution of Poverty Using Satellite Imagery in Thailand

The “leave no one behind” principle of the 2030 Agenda for Sustainable Development requires appropriate indicators for different segments of a country’s population. This entails detailed, granular data on population groups that extend beyond national trends and averages. The Asian Development Bank (ADB), in collaboration with the National Statistical Office of Thailand and the Word Data Lab, conducted a feasibility study to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics in Thailand. This report documents the results of the study, providing insights on data collection requirements, advanced algorithmic techniques, and validation of poverty estimates using artificial intelligence to complement traditional data sources and conventional survey methods.

National report 2009-2019 - Rural NEET in Serbia

The situation of rural Youths Neither in Employment nor in Education or Training (NEET) aged between 15 and 34 years old, over the last decade (2010-2019) in Serbia is presen-ted in this report. The main criterion for analysis was the degree of urbanisation, where the comparison was done between rural areas, towns and suburbs, cities, and the whole country. The data available on EUROSTAT and the national Statistical office of Serbia were used as main resources for statistical interpretation. The statistical procedures used in the report rely on descriptive longitudinal analysis, using graphical displays (e.g. overlay line charts) as well as the calculation of proportional abso-lute and relative changes between observed years. The analysis of the youth population in Serbia aged 15-24 years in total as well as the youth population for different degrees of urbaisation, for the period 2010-2019, showed a de-creasing trend. In the period 2014-2019 (which is with available data for the case of Serbia) it can be ob-served that the youth employment rate is increasing in all areas of urbanisation. In contrast to the employment, the level of unemployment in Serbia is constantly decreasing in the period 2014-2019. This trend is similar for all three areas of urbanisation.The decrease in the number of early school leavers is registered in the case of entire Serbia, cities, and rural areas. The only trend of increasing of early school leavers’ rate is recorded for the towns and suburbs, for the observed period 2014-2019.In the period 2010-2019, the NEET rate is declining in Serbia for all three degrees of ur-banisation. In comparison to EU countries, Serbia is still significantly above the European average, but with a tendency of reducing the gap.

Covid-19 and Cost of Living in Developing Countries

We document some evidence about effects of the Covid-19 pandemic on the cost of living in developing countries. We use data from the National Statistical Office of the Democratic Republic of Congo (DRC). Data are in weekly frequency. We propose a simple two-step strategy to evaluate the Covid-19 effect on the cost of living in the DRC. We consider two types of households: a typical household for the DRC and a typical household for Kinshasa –Kinshasa is the national capital and the largest city of the DRC. Then we compute the quasi-causal effect and the volatility differential for each household type. We show: First, in absolute terms, the consumption basket for a typical household in Kinshasa exhibits both a higher quasi-causal effect and a higher volatility differential than those observed from the consumption basket of a typical household for the whole country (i.e. the DRC). Second, in relative terms, the consumption basket for a typical household in Kinshasa exhibits higher quasi-causal effects than that for a typical household only in prices of food and non-alcoholic beverages and in prices of transport. Finally and more importantly, unlike developed countries where consumers spent more on food and other groceries during the pandemic, our results suggest that in response to the Covid-19 crisis, both the typical household in DRC and the typical household in Kinshasa spent more on health and communication. These findings highlight deep structural differences between developed countries, where health insurance is functional, and developing countries where patients generally face a deficit or lack of viable health insurance. Moreover, we argue expenditures on communication increased in response mainly to the lockdown measures, mobility restrictions or closing of national borders.