Lietuvos statistikos darbai <p>Founded in 1990. Publishes articles on the statistical theory and methodology, on the application of statistics in economic, physical, technological, biomedical and social sciences, analyses statistical methods in official statistics, on the investigation of the history of statistics.&nbsp;</p> Vilniaus universiteto leidykla / Vilnius University Press en-US Lietuvos statistikos darbai 1392-642X <p>Please read the Copyright Notice in&nbsp;<a href="">Journal Policy</a>.&nbsp;</p> Editorial Board and Table of Contents <p>&nbsp;&nbsp;</p> Marijus Radavičius Copyright (c) 2019 Authors 2019-12-20 2019-12-20 58 1 1 2 Subpopulation of Immigrants in Lithuania: Foreign-Born Generations <p>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 20<sup>th</sup> century (children of deportees). The youngest generation of the emerging foreign-born generation is from Western European countries.</p> Vladislava Stankūnienė Dalia Ambrozaitienė Marė Baublytė Copyright (c) 2019 Authors 2019-12-20 2019-12-20 58 1 4 15 10.15388/LJS.2019.16665 Comparing the Quality of Household Age Distribution from Surveys in Developing Countries: Demographic and Health Survey vs Multiple Indicator Cluster Survey <p>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.</p> Chinonso O. Okoro Copyright (c) 2019 Authors 2019-12-20 2019-12-20 58 1 16 25 10.15388/LJS.2019.16666 Basic Needs and Absolute Poverty in Lithuania: Method and Estimation <p>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.</p> Jekaterina Navickė Aušra Čižauskaitė Ugnė Užgalė Copyright (c) 2019 Authors 2019-12-20 2019-12-20 58 1 26 38 10.15388/LJS.2019.16668 Testing Linear and Nonlinear Hypotheses in a Cox Proportional Hazards Model with Errors in Covariates <p>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.</p> Oksana Chernova Alexander Kukush Copyright (c) 2019 Authors 2019-12-20 2019-12-20 58 1 39 47 10.15388/LJS.2019.16669