Бидний тухай
Багш ажилтан
Abstract: In Mongolia, since the early 2000s, female labor force participation is declining down to 50.6 percent in 2023 (National Statistics Office, 2024). It raises serious concern about the long-term economic growth and the country's future in general. In this paper we investigate the existence and the extent of the parental wage penalty including motherhood wage penalty as a potential factor that prevents young women to enter and re-enter into the labor force. Relying on the data from the Mongolian Labor Force Survey 2018, we find that the parental wage premium is 12.06 percent while motherhood wage penalty at 18.15 percent respectively, controlling for individual unobserved heterogeneity, a number of human capital characteristics, actual time in the labor force, and selection into employment. We also find that the parental wage penalty differs by education, age, location, marital status and occupation.
This study attempts to map out the size and shape and measure the paid care sector based on the most available data in Mongolia for the first time. Estimating spending on childcare, elderly care and care for the disabled in monetary terms is essential for the welfare of care receivers and has macroeconomic implications. Using the central government budget spending data, the Labor Force Survey, and the Household Socio-Economic Survey we estimate the approximate size of paid care sector financed by the government and households in Mongolia. We find that Mongolia's preliminary measure of the paid care sector is equal to 10.6 percent of the GDP in 2021. Also, we identified the data gap for measuring paid care.
Abstract: In this study, we estimated the tendency and probability of absolute social mobility in education since the 1940s in Mongolia using a historical data from the Census of 1989, 2000, 2010, and 2020 and measured transitional probabilities and intergenerational persistence. Despite potential sample selection bias, our approach overcomes the existing data limitation that has hampered research on trends in intergenerational mobility in the country. The research ndings suggest that absolute intergenerational mobility has been rising in Mongolia, especially among women. In contrast, mobility for men has been substantially slower. Especially during the rst decade of the transition from the centrally planned to the market economy, the educational mobility for men born between 1975 and 1984 was downward. This educational loss, in turn, hurts men's upward mobility in the labor market. Where people are born strongly aects intergenerational social mobility as well. Between 1940 and 1960, upward intergenerational educational mobility was higher among people born in the capital city and central provinces than in other places. While after 1960, the upward intergenerational educational mobility was higher among people born in the Western and Highland regions than in other areas.
This paper examines the survey results on e-learning implementation, which covered 726 lecturers from Mongolian universities and colleges. The authors determined factors that influence e-learning course classification. We applied methods such as regression analysis and factor analysis. It revealed that institutional factors such as ownership, LMS, size, and personal factors such as age, gender, prior training, team, field of science, qualification, and locations influence the tendency to develop e-learning courses. The study is beneficial for policymakers and practitioners by broadening the understanding of institutional and personal factors influencing e-learning course development. Implications for practice and policy: 1) Mongolian higher education institutions primarily practice web-facilitated courses with few blended and online courses. 2) Institutional factors such as ownership, LMS, size, and personal factors such as age, gender, prior training, team, field of science, qualification, and locations influence the tendency to develop e-learning courses. 3) There is a strong need for faculty development as every third lecturer does not know about the learning theories and does not apply them to the e-learning course development. 4) The higher education management should address challenges faced by the faculty members. 72.65% of respondents raised environment and faculty development challenges.
Based on the big data sample, we found that during the first year of COVID-19, although per month, per person expenditures of female-headed households were higher, on average, compared with male-headed households in Mongolia, but it is not because of the gender of the household head, but because these heads of households on average have more education, smaller household sizes, and living more in urban areas. They also register their expenditures in the VAT e-receipts system more consistently, which means that male-headed households’ expenditures are underestimated. Overall, expenditure of both male- and female-headed households has increased in 2020 compared with 2019, while poverty slightly declined. The major reasons for expenditure increase and poverty decline in 2020 a rapid rollout of a fiscal stimulus with a sizable social protection componen
Монгол Улсын ТЕГ-аас 2016 оноос цахимаар цуглуулж эхэлэсн НӨАТ их өгөгдлийн ашиглан нийгэм эдийн засгийн байдлыг судалх аргачлалыг танилцуулсан юм.
Care work, both paid and unpaid, is extremely important for any social system as well as the economy to survive. The utmost importance of care work was highlighted in the pandemic, when it became challenging to move ahead without the facilities of care staff. The ILO: doubling investment from 2015 levels would result in 117 million additional jobs opportunities by 2030. Because of the nature of care, such professions are less probable to automation. (ILO, 2021) Countries which invest in a care economy have a higher maternal employment to population ratio as per the ILO.
Жил болгоны Асрахуйн эдийн засгийн хэмжилтийн талаар хийдэг ОУХ-д илтгэл тавьсан
Микро эдийн засаг: жендэр Эрэгтэй эмэгтэй хүмүүсийн ханамжийн функцийн ялгаатай байдал Эдийн засгийн шийдвэрийг өөр байдлаар гаргахад Наймаалцах хүч (вargaining power), өрх гэр доторхи наймаалцал, хэлэлцээ эдийн засгийн загваруудад ялгаатай байдлуудыг хэмжих Хөдөлмөрийн зах зээлийн жендерийн асуудал Ялгаварлан гадуурхлалт АХОТ, мэргэжлийн ялгаа, цалингийн ялгаа, албан бус ажил эрхлэлт, ажилгүйдэл Орлогын ялгаа, ядуурал, тэгш бус Зах зээлийн алдаа, эмзэг байдал, эрсдэлд илүү өртөх түвшин, Хүн амын насжилтийн асуудал өрх гэрийн хөдөлмөр хуваарилалтанд нөлөөлөх нь Цалинтай, цалингүй асрах хөдөлмөрийн өөрчлөлт, асрах ажлын нийгмийн болон эдийн засгийн зардал нийгмийн бодлогууд, нийгмийн халамжийн, нийгмийн даатгалын, нийгмийн хамгааллын бодлогууд Макро эдийн засаг: жендэр Хөрөнгийн зах зээлийн жендэрийн асуудал ОХУ ба ГШХО-ын ба эмэгтэйчүүдийн ажил эрхлэлт, орлогын түвшин, цалингийн ялгаа, хадгаламжийн түвшинд үзүүлэх нөлөө Эдийн засгийн өсөлт, мөчлөг, санхүүгийн хямрал ба жендерийн асуудал Жендэрийн мэдрэмжтэй төсөвлөлт Шууд ба шууд бус татвар, төсвийн зарцуулалт нь эрэгтэй, эмэгтэй татвар төлөгчдийн хөдөлмөрийн нийлүүлэлт, үйл хөдлөлд нөлөөлөх нь Kalecki-ийн онол, Darity-гийн загвар: ОУВС-гийн тогтворжуулах хөтөлбөрүүдийн эмэгтэйчүүдийн ажил эрхлэлт, орлого, хадгаламж, бизнес эрхлэлт, өрийн түвшинд үзүүлсэн нөлөө Глобальчлалын тэгш бус байдал, ядууралд үзүүлж буй нөлөө тэр дундаа эрэгтэй, эмэгтэйчүүдийн орлогын, цагийн, сайн сайхан байдлын тэгш бус байдал Эдийн засгийн хямрал ба жендэрийн асуудлууд зэрэг асуудлуудыг судалдаг эдийн засгийн нэг чухал салбар юм.
Women’s role in herding and their empowerment in Mongolian herding households has been little studied, and their participation in decision-making can have important implications for rural households. We draw on a unique sample of 60 Mongolian herding households carried out in 2017 to provide evidence for how herding work and related decision-making is shared between husbands and wives. We extend previous work by using a much more detailed survey, asking about participation in 22 different activities related to herding and 39 decisions, and by analysing factors associated with greater participation in herding decisions by Mongolian women. We show that most herding tasks are not gendered, and, in many tasks, women contribute more time than men. Women made few herdingrelated decisions alone, and they participate jointly with their spouses in about half the decisions, many fewer than men. Women who contribute more to herding income through milk and cashmere production have more input into many decisions; more educated women have greater participation in some decisions. These findings suggest policy paths toward greater equality and improved outcomes in Mongolian herding households.
Based on the big data sample, we found that expenditures of female-based households were higher, on average, compared with male-headed households. However, female-headed households in Mongolia have higher expenditures not because of the gender of the household head, but because these heads of households on average are more education, have smaller household sizes, and living in more urban areas. They also register their expenditures in the VAT e-receipts system more consistently, which means that male-headed households’ expenditures are underestimated. Expenditures of both male- and female-headed households moved generally in tandem throughout 2020, having declined (year-on-year) in the first quarter of 2020, as well as in November-December 2020 – the periods of the strictest lockdowns, especially in urban areas. Overall, expenditure of both male- and female-headed households has increased in 2020 compared with 2019, while poverty slightly declined. However, there was a large volatility of expenditures month-by-month. Poverty decline decelerated in 2020 compared with 2019. The major reasons for expenditure increase and poverty decline in 2020 a rapid roll out of a fiscal stimulus with a sizable social protection component.
The current article presents the results of the analysis of the online course development process on the example of the 2-credit hour English course taught for the master students of the Mongolian National University of Medical Sciences (MNUMS). The rationale was to determine, understand the processes of the online course development, define its inputs and outputs of each process and compare it with the traditional course. The purpose is to conduct a process analysis of online course development. The process analysis methodology, ADDIE framework was used. The business process can be divided into 2 scenarios such as “as-is” which depicts the current state, “to-be” which presents the future state. The current state process analysis revealed that 30 activities lasted for 138 business days to develop and deliver the course. “To-be” or future state has 2 scenarios. We’ve estimated that the “to-be” state to last for 147.5 days for higher education institutions (HEIs) without the studio, 188 days for HEIs with the studio for the online course development, delivery, and evaluation.
The current article presents the results of the analysis of the online course development process on the example of the 2-credit hour English course taught for the master students of the Mongolian National University of Medical Sciences (MNUMS). The rationale was to determine, understand the processes of the online course development, define its inputs and outputs of each process and compare it with the traditional course. The purpose is to conduct a process analysis of online course development. The process analysis methodology, ADDIE framework was used. The business process can be divided into 2 scenarios such as “as-is” which depicts the current state, “to-be” which presents the future state. The current state process analysis revealed that 30 activities lasted for 138 business days to develop and deliver the course. “To-be” or future state has 2 scenarios. We’ve estimated that the “to-be” state to last for 147.5 days for higher education institutions (HEIs) without the studio, 188 days for HEIs with the studio for the online course development, delivery, and evaluation.
Using data from the LSMS 2002 and HSES 2012 in Mongolia, we have estimated the educational Gini coefficients by years of schooling for adults and by school attendance rate for children. The Gini coefficient measured by using years of schooling for the population aged 19 and above decreased from 0.274 in 2002 to 0.178 in 2012. For adults of both genders, educational inequality has declined while the Gini coefficients are consistently higher in rural areas than in urban areas in both periods. The Gini coefficient for children aged 2–18 years and currently attending school has also declined. Between 2002 and 2012, the educational Gini coefficient for preschool decreased from 0.307 to 0.233 and for primary from 0.422 to 0.388. For secondary education, the Gini coefficient decreased from 0.388 in 2002 to 0.201 in 2012. For high school level, the coefficient decreased also from 0.299 in 2002 to 0.254 in 2012. The distribution in higher education remains at the similar level of 0.491. For all levels of education, except for higher education, the distribution is getting closer to the perfect equality line on the education Lorenz curve. Finally, we have shown that child’s age, gender, mother’s and father’s education, household size and income, and urban location are statistically significant determinants of children’s school attendance and thus educational equality. The pooled estimates using probit model indicate that the reduction in inequality due to household income and location are major factors which led to lower Gini Coefficient in 2012.
