DSpace Collection:https://mt.osce-academy.kg/handle/123456789/4162024-02-19T11:05:13Z2024-02-19T11:05:13ZStructural Time Series Modelling and Forecasting of Energy Demand: The Case of UzbekistanKeldiyorov, Diyorjonhttps://mt.osce-academy.kg/handle/123456789/4562022-04-15T05:24:52Z2020-12-01T00:00:00ZTitle: Structural Time Series Modelling and Forecasting of Energy Demand: The Case of Uzbekistan
Authors: Keldiyorov, Diyorjon
Abstract: This study investigates the energy (considering electricity) demand drivers and future
estimates through time series data in Uzbekistan. The research focuses on both aggregated
(total electricity demand) and disaggregated (residential, industrial and agricultural) levels.
Initially, the paper briefly outlines the global and Uzbek energy market with specific
considerations such as energy efficiency, renewable energy development, legislative
developments and practical issues happening in the sector. Then based on the econometric
techniques developed by renowned researchers such as Hunt and Harvey, the research
estimates energy demand models through the sectors. Moreover, the study investigates the
forecasting estimations based on out-of-sample method considering the differentiated values
of the dependent variables. The findings show that the GDP has much effect on estimating the
demand models through all sectors. In most of the models, GDP shows statistically significant
values, but in some exceptions gives wrong signs. On average, the GDP affects the electricity
consumption around 0.5-1%. Consumer price index effect is not seen as considerable across
models. Also, annual average temperature does not have any relationship with electricity
demand at all levels. Similar to GDP, lagged values of electricity demand including per capita
use or per GDP USD show significant values. Alternative sources such as coal and gas have
some effects at residential level, but not at other sectors. The effect of population does not give
plausible results. Constant terms are found to be significant, but inconsistent values. On the
other hand, forecasting estimates show that residential electricity demand will have stable
growth both in short- and long-run. Other sectors including aggregated level will be affected
by variances in the short-run meaning that they will fluctuate for short period, then reach their
steady rate (stable growth). Overall, demand models have met the conditions based on the
previous papers. They point out that not all the time factors have the significance level or
expected signs. Besides, forecasting estimations were affected by the seasonality and low
stationarity rates with high variance, but still give consistent results. In conclusion, some
policy recommendations are followed by the results not only considering the derived results,
but current state of the energy sector stated through chapters.2020-12-01T00:00:00ZThe Economic Importance of Mobile Phone Ownership in Poverty Reduction in the Kyrgyz RepublicTashmatova, Kunduzhttps://mt.osce-academy.kg/handle/123456789/4332022-04-06T05:56:37Z2020-12-01T00:00:00ZTitle: The Economic Importance of Mobile Phone Ownership in Poverty Reduction in the Kyrgyz Republic
Authors: Tashmatova, Kunduz
Abstract: Reduction of poverty is one of the main challenges of economy. Many studies have investigated the potential impact of mobile information and communication technologies on poverty alleviation from the agricultural perspective on the example of developing countries. However, no research has been conducted to identify the relationship between poverty and mobile communication networks in Central Asian countries. The paper examines the potential effect of mobile phone ownership on poverty reduction in the Kyrgyz Republic. Poverty is measured by daily per capita consumption. The cross-sectional analysis is based on the Kyrgyz Integrated Household Survey data of 2010. An endogenous switching regression model that considers both observable and unobservable factors that may affect households’ decision to own mobile cell phones, is applied to examine proposed estimating model. The findings of this study illustrate significant and positive relationship between mobile phone ownership and daily per capita consumption. Moreover, the sample households’ decision to own mobile phones is based on demographic, economic and social factors such as fixed landline connection availability, household size, age of the household head, years of education of the household heads, owned land, remittances, off-farm work employment, and peer households that own mobile cell phones.2020-12-01T00:00:00ZThe Effect of Labor Migration on Children's Health Outcomes in Kyrgyz Republic: Based on Life in Kyrgyzstan Survey of 2010-2013Kozhomgeldieva, Zhannathttps://mt.osce-academy.kg/handle/123456789/4322022-04-06T05:50:15Z2020-12-01T00:00:00ZTitle: The Effect of Labor Migration on Children's Health Outcomes in Kyrgyz Republic: Based on Life in Kyrgyzstan Survey of 2010-2013
Authors: Kozhomgeldieva, Zhannat
Abstract: The study uses Life in Kyrgyzstan (LiK) dataset, considering 4 years in total (2010-2013) to examine the correlation and sign between the labor migration of parents and the health of children left behind. Results of the Hauman and Taylor estimation have found the negative significant correlation between the labor migration of parents and health outcomes of children. Children whose at least one of the parents is staying abroad are considered to be more vulnerable compared to children whose parents did not migrate. Moreover, variables like income of the household, share of food in total consumption and education of the parents have a significant impact on the health outcomes of children.2020-12-01T00:00:00ZThe Influence of Income on Migration Intentions in Afghanistan (2016-2019)Badri, Yahyahttps://mt.osce-academy.kg/handle/123456789/4312022-04-06T05:45:31Z2020-12-01T00:00:00ZTitle: The Influence of Income on Migration Intentions in Afghanistan (2016-2019)
Authors: Badri, Yahya
Abstract: The main objective of this paper is to find out how income and other socio-economic and demographic factors affect migration intentions of the Afghan people. The data for the study comes from the survey of the Afghan people, which is conducted by the Asia Foundation Afghanistan. In this paper the data is used both as a cross sectional for 2019 in order to find the impact of income on migration intention in 2019, and panel datasets for 2016 to 2019, for the purpose of addressing reverse causality. Since, the dependent variable is a binary variable which consists of 0 and 1 values, and the Probit regression is used for estimation of the model. As well as, a random effect logit estimation method is used as a panel model.
Form the outcomes of the research we can conclude that, increasing in income levels of the households and also increase in land ownership which is the asset of the household has significantly indirect impact on decisions of people for leaving the country.
On the other hand, the results of the panel model suggest that, income levels do not have significant impact on migration intentions of people. As well as, other economic factors such as income of a female member, land ownership, and employment did not have significant impact on migration intention of Afghans.2020-12-01T00:00:00Z