Lietuvos statistikos darbai

Journal Information
ISSN / EISSN : 1392642X / 20297262
Current Publisher: Vilnius University Press (10.15388)
Total articles ≅ 15
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Latest articles in this journal

Laima Okunevičiūtė Neverauskienė, Arūnas Pocius
Lietuvos statistikos darbai, Volume 59, pp 1-13; doi:10.15388/ljs.2020.16784

Straipsnyje atliekamas Lietuvos Respublikos Vyriausybės 2014–2020 metų užimtumo didinimo programoje pateiktų pagrindinių darbo rinkos rodiklių vertinimas. Remiantis šiais rodikliais analizuojama situacija darbo rinkoje bei tendencijos šalyje, stebimi nukrypimai nuo prognozuotų rodiklių (numatytų užimtumo programos įgyvendinimo siekių) reikšmių, įvertinamos jų tobulinimo galimybės. Nepaisant bendrųjų situacijos darbo rinkoje rodiklių analizės svarbos, vienas iš esminių šios publikacijos prioritetų – užimtumo programoje išskirtų tikslinių grupių integracijos galimybių įvertinimas, kurios išreiškiamos remiantis darbo rinkos politikos rezultatus atspindinčiais rodikliais. Atsižvelgiant į užimtumo programoje pateiktų darbo rinkos rodiklių sistemą, kurie daugiausia orientuoti į darbo vietų kaitą (kūrimą), prioritetas teikiamas užimtumo rodikliams. Be tiesiogiai darbo rinkos politikos rezultatus atspindinčių statistinių duomenų, straipsnyje analizuojami ir papildomi tikslinių grupių situaciją darbo rinkoje atspindintys rodikliai.
Vladislava Stankūnienė, Dalia Ambrozaitienė, Marė Baublytė
Lietuvos statistikos darbai, Volume 58, pp 4-15; doi:10.15388/ljs.2019.16665

The article analyzes the foreign-born population of Lithuania, its age and ethnic composition, and periods of arrival to Lithuania. The analysis is based on the 2011 Lithuanian Population Census data. The results of the analysis show that the foreign-born population of Lithuania is very heterogeneous and has three major groups formed at different times, by different immigration factors and flows, they are different by age and ethnic composition. Most of foreign-born population of Lithuania is formed during the Soviet era - those who arrived from the former USSR. Among them the majority are of Russians, but a quite large part - Lithuanians who arrived since the mid-sixties of 20th century (children of deportees). The youngest generation of the emerging foreign-born generation is from Western European countries.
Chinonso O. Okoro
Lietuvos statistikos darbai, Volume 58, pp 16-25; doi:10.15388/ljs.2019.16666

This paper focuses on the quality of household age distribution from two surveys in developing countries. Age and sex data serve as the base population for the estimation of demographic parameters (fertility, mortality, etc.) and other socio-economic indicators. The ultimate objective is to evaluate the age and sex data from two surveys to determine the one with better age and sex reporting that may provide quality base populations for the estimation of demographic parameters and socioeconomic indicators. Algebraic methods were applied to the data retrieved from the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). The overall results show that the quality of data from the two surveys is poor. It is observed that age and sex data from the Nigerian DHS appear to be better than that of MICS while in Bangladesh, Malawi, and Nepal the reverse is the case based on the Joint Scores (JS). The result further shows that Malawi with high literacy respondents had better JS than the other countries indicating that the level of education may be one of the determinants of the quality of age and sex data. Therefore, it is recommended that care and caution should be taken during data collection to reduce the effect of misreporting of age and the usual practice of eliciting vital records of the respondents such as age from the head of the household instead of birth certificates should be discouraged. More importantly, evaluation of age and sex data from different surveys should be done before usage to ascertain the survey with a better quality of data without always presuming that one survey is of better quality than the other.
Jekaterina Navicke, Aušra Čižauskaitė, Ugnė Užgalė
Lietuvos statistikos darbai, Volume 58, pp 26-38; doi:10.15388/ljs.2019.16668

We propose a methodology for estimating the cost of the basic needs and applying it on the data for Lithuania in a decade after the EU accession (2006-2016). The basic food costs account for the minimal nutrition requirements, while the cost of other needs is estimated in relative terms, taking actual consumption patterns in the population into account. A reduction in the cost of the basic needs for additional members of the household is accounted for by a specially constructed consumption-based equivalence scale estimated on the HBS data. We show that the cost of the basic needs in Lithuania is close to the relative at-risk-of-poverty line (at 60% of the median equivalized disposable income) for a single adult but exceeds it for larger households. The share of people with income below the basic needs’ cost was above the relative at-risk-of-poverty levels in the EU-SILC data for all years, except of 2016. Albeit, the actual level might be lower due to the under-reporting of shadow income in the EU-SILC. Ability to meet basic needs and related absolute poverty indicators shows anti-cyclical dynamics in times of the economic growth and recession. Children are consistently the most deprived group of the Lithuanian population when it comes to meeting the basic needs. The official absolute poverty indicator used in Lithuania under-estimates the cost of the basic needs for households with more than one member.
O. O. Chernova, Alexander Kukush
Lietuvos statistikos darbai, Volume 58, pp 39-47; doi:10.15388/ljs.2019.16669

We investigate linear and nonlinear hypotheses testing in a Cox proportional hazards model for right-censored survival data when the covariates are subject to measurement errors. In Kukush and Chernova (2018) [Theor. Probability and Math. Statist. 96, 101–110], a consistent simultaneous estimator is introduced for the baseline hazard rate and the vector of regression parameters. Therein the baseline hazard rate belongs to an unbounded set of nonnegative Lipschitz functions, with fixed constant, and the vector of regression parameters belongs to a compact parameter set. Based on the estimator, we develop two procedures to test nonlinear and linear hypotheses about the vector of regression parameters: Wald-type and score-type tests. The latter is based on an unbiased estimating equation. The consistency of the tests is shown.
Gindra Kasnauskienė, Tomas Šiaudvytis
Lietuvos statistikos darbai, Volume 49, pp 12-19; doi:10.15388/ljs.2010.13942

Migration flows have increased since the EU enlargement in 2004. In many European countries, they are sufficiently large to have significant economic effects. These effects are among the most popular topics in public debate. In this paper, the authors attempt to quantify the effects of emigration on wages, welfare and in­come redistribution in the selected new EU member states. Emigration reduces labour supply and in­creases national wage generating income redistribu­tion from the owners of capital to the labour force. Emigration also results in welfare loss as emigrants no longer produce output in their home country. The au­thors of the article adopt a simple theoretical model of the labour market which allows quantifying these effects through the use of basic economic and demo­graphic statistics. The research on the effects of emigration on wages uses a simple supply and demand framework, where labour demand is derived from a marginal pro­ductivity condition using the Cobb–Douglas produc­tion function. The authors also assume perfectly ine­lastic labour supply, in case of which the effect of emigration on wages is entirely determined by labour demand. Wage elasticity estimation uses the fact that the capital share parameter in the Cobb–Douglas function also measures labour demand elasticity. This property of the production function allows the au­thors to estimate the elasticity using national ac­counts data. The estimates of labour demand (wage) elas­ticity for Lithuania range from 0.44 to 0.55, implying that due to emigration wages might have increased from 0.75 to 0.94 per cent a year, on average. In the period of 2001–2008, emigration might have resulted in a wage increase of 5.9 to 7.3 per cent. However, these estimates require caution as the beginning of the period was characterised by high unemployment. Emigration loss amounts to 0.4 per cent of GDP, and 2.8 per cent of GDP is redistributed to labour every year. Due to the poor quality of migration data, the impact of emigration on wages, welfare and income redistribution in other countries is most likely signifi­cantly underestimated. The assumption that the share of declared emigration is similar across countries would imply that those affected by emigration the most are Slovenia, Czech Republic and Estonia.
Arūnas Pocius
Lietuvos statistikos darbai, Volume 54, pp 18-32; doi:10.15388/ljs.2015.13877

The author analyses the state of the shadow economy, informal employment and their trends based on differentstatistical calculation methodologies and survey data. The evaluation of the situation in Lithuania is based on the data of StatisticsLithuania, State Social Insurance Fund Board (SODRA), special surveys and results of statistical calculations. According to researchexperience, the methodological issues of evaluation of informal employment are discussed. Assiduous attention is paid to theevaluation and the scope of the shadow economy and the comparative analysis of informal employment issues in the EU. Whileassessing the trends in the shadow economy, the indicators from the research of different authors or institutions are compared usingdifferent calculation methods – to determine relative trends in the shadow economy.
Rūta Simanavičienė, Jovita Cibulskaitė
Lietuvos statistikos darbai, Volume 54, pp 110-118; doi:10.15388/ljs.2015.13886

The tasks of making the most appropriate decisions taking into account a number of criteria are dealt with in variousfields such as engineering, industry, finance, economics and others. If the aim is to arrange the alternatives in a priority lineaccording to quantitative attributes, then multiattribute decision-making methods are suitable. Analysts using these methods usuallydo not take into account initial data errors – deviations in attribute values, in which case the decision may be unreliable. In thisarticle, several statistical analysis methods are proposed for the multicriteria decision to measure reliability: formulation of statisticalhypotheses and calculation of confidence intervals for parameters. Based on statistical analysis results, conclusions about thereliability of a multicriteria decision obtained using the TOPSIS method are formulated.
Danutė Krapavickaitė
Lietuvos statistikos darbai, Volume 55, pp 1-1; doi:10.15388/ljs.2016.13860

Aleksandras Plikusas
Lietuvos statistikos darbai, Volume 57, pp 1-3; doi:10.15388/ljs.2018.12831

[text in English and Lithuanian]
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