Pub Date : 2023-02-24DOI: 10.59170/stattrans-2023-008
V. Sarioglo, Maryna Ogay
Estimating the size and places of residence of the population of Ukraine has been this country’s problem for the past decade, and is related to the lack of census data for the 2010 round, large-scale processes of external and internal labour migration, and Russia's armed aggression against Ukraine that started in 2014. This already disadvantageous situation has been significantly exacerbated by Russia’s full-scale war against Ukraine which began on 24th February 2022. Conducting statistical surveys, especially surveys regarding the population, turned out to impossible under war circumstances. Therefore, the task of developing effective approaches to estimating the population size using data from existing sources, in particular the data of mobile operators regarding the number, location and mobility of subscribers, has become even more pressing. The article highlights the results of a study on the use of data from mobile operators, data from administrative registers, and the results of a special population sample survey on the use of mobile communication for the purpose of estimating the population. It also provides the results of experimental calculations of the population size in Ukraine as a whole and in particular regions. The study moreover showed that the size of Ukraine’s population in November 2019, unlike the official estimate of 41,940.7 thousand people, was probably about 37,289.4 thousand people. The developed approaches can be used to estimate the number and location of the population of Ukraine during the intercensal period or significant population movements due to environmental disasters or military conflicts.
{"title":"Approach to population estimation in Ukraine using mobile operators’ data","authors":"V. Sarioglo, Maryna Ogay","doi":"10.59170/stattrans-2023-008","DOIUrl":"https://doi.org/10.59170/stattrans-2023-008","url":null,"abstract":"Estimating the size and places of residence of the population of Ukraine has been\u0000 this country’s problem for the past decade, and is related to the lack of census data\u0000 for the 2010 round, large-scale processes of external and internal labour migration, and\u0000 Russia's armed aggression against Ukraine that started in 2014. This already\u0000 disadvantageous situation has been significantly exacerbated by Russia’s full-scale war\u0000 against Ukraine which began on 24th February 2022. Conducting statistical surveys,\u0000 especially surveys regarding the population, turned out to impossible under war\u0000 circumstances. Therefore, the task of developing effective approaches to estimating the\u0000 population size using data from existing sources, in particular the data of mobile\u0000 operators regarding the number, location and mobility of subscribers, has become even\u0000 more pressing. The article highlights the results of a study on the use of data from\u0000 mobile operators, data from administrative registers, and the results of a special\u0000 population sample survey on the use of mobile communication for the purpose of\u0000 estimating the population. It also provides the results of experimental calculations of\u0000 the population size in Ukraine as a whole and in particular regions. The study moreover\u0000 showed that the size of Ukraine’s population in November 2019, unlike the official\u0000 estimate of 41,940.7 thousand people, was probably about 37,289.4 thousand people. The\u0000 developed approaches can be used to estimate the number and location of the population\u0000 of Ukraine during the intercensal period or significant population movements due to\u0000 environmental disasters or military conflicts.","PeriodicalId":37985,"journal":{"name":"Statistics in Transition","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48150351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-24DOI: 10.59170/stattrans-2023-009
Taisiia Bondaruk, L. Momotiuk, I. Zaichko
Ukraine has recently experienced a significant economic downturn as a result of the COVID-19 pandemic and the war caused by a large-scale military aggression of the Russian Federation. In conditions of the constant fluctuations of the national economy, the stimulating effect of the budgetary policy aimed at minimizing the consequences of such fluctuations and guaranteeing a sufficient level of financial security of the state becomes especially important. The aim of the study is to deepen the theoretical and methodological foundations of the creation and implementation of budgetary policy in Ukraine, evaluation of its impact on the financial security in time of challenges. The study uses methods of comparative analysis, grouping in the process of evaluating the current state of budgetary policy indicators, methods of normalization and standardization of data, modelling, and graphical analysis of data for normalizing the financial security indicators and determining the dynamics of financial security components. The materials and reports containing statistical data from the Ministry of Finance of Ukraine and the State Statistics Service of Ukraine served as the basis of the study. We found out that the components of the financial security of the state in the face of the challenges posed by martial law and the pandemic do not take into account the impact of budgetary policy. We substantiated the thesis that the creation of Ukraine's budgetary policy under martial law requires adjustments to the financial security assessment system. The most statistically significant and reliable models of interrelation were selected for further use in multifactor modelling and forecasting the financial security of the state (on the basis of ranking the linear, polynominal, exponential, logarithmic and power dependencies within one-factor equations). It was experimentally proved that out of 122 statistically significant indicators, budgetary policy indicators such as the coefficient of financing the national functions, the coefficient of public debt service and redemption, and the coefficient of the proportionality of financing the national security agencies had the greatest impact on the financial security of Ukraine. We also substantiated the scientific provisions behind the modelling of the level of financial security of Ukraine taking into account the impact of budgetary policy in the period of challenges. In the process of modelling, the indicators of budgetary policy were identified, while regression analysis revealed the factors influencing the budgetary policy.
{"title":"Budgetary policy of Ukraine in time of challenges and its impact on financial\u0000 security","authors":"Taisiia Bondaruk, L. Momotiuk, I. Zaichko","doi":"10.59170/stattrans-2023-009","DOIUrl":"https://doi.org/10.59170/stattrans-2023-009","url":null,"abstract":"Ukraine has recently experienced a significant economic downturn as a result of\u0000 the COVID-19 pandemic and the war caused by a large-scale military aggression of the\u0000 Russian Federation. In conditions of the constant fluctuations of the national economy,\u0000 the stimulating effect of the budgetary policy aimed at minimizing the consequences of\u0000 such fluctuations and guaranteeing a sufficient level of financial security of the state\u0000 becomes especially important. The aim of the study is to deepen the theoretical and\u0000 methodological foundations of the creation and implementation of budgetary policy in\u0000 Ukraine, evaluation of its impact on the financial security in time of challenges. The\u0000 study uses methods of comparative analysis, grouping in the process of evaluating the\u0000 current state of budgetary policy indicators, methods of normalization and\u0000 standardization of data, modelling, and graphical analysis of data for normalizing the\u0000 financial security indicators and determining the dynamics of financial security\u0000 components. The materials and reports containing statistical data from the Ministry of\u0000 Finance of Ukraine and the State Statistics Service of Ukraine served as the basis of\u0000 the study. We found out that the components of the financial security of the state in\u0000 the face of the challenges posed by martial law and the pandemic do not take into\u0000 account the impact of budgetary policy. We substantiated the thesis that the creation of\u0000 Ukraine's budgetary policy under martial law requires adjustments to the financial\u0000 security assessment system. The most statistically significant and reliable models of\u0000 interrelation were selected for further use in multifactor modelling and forecasting the\u0000 financial security of the state (on the basis of ranking the linear, polynominal,\u0000 exponential, logarithmic and power dependencies within one-factor equations). It was\u0000 experimentally proved that out of 122 statistically significant indicators, budgetary\u0000 policy indicators such as the coefficient of financing the national functions, the\u0000 coefficient of public debt service and redemption, and the coefficient of the\u0000 proportionality of financing the national security agencies had the greatest impact on\u0000 the financial security of Ukraine. We also substantiated the scientific provisions\u0000 behind the modelling of the level of financial security of Ukraine taking into account\u0000 the impact of budgetary policy in the period of challenges. In the process of modelling,\u0000 the indicators of budgetary policy were identified, while regression analysis revealed\u0000 the factors influencing the budgetary policy.","PeriodicalId":37985,"journal":{"name":"Statistics in Transition","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49253896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}