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Indicators that reflect the transition from unemployment to employment are an important element of the monitoring systems of employment services in EU countries. Monitoring employment trends is a complex task that usually goes beyond quantitative parameters. The correct application and interpretation of the indicators is inseparable from contextual phenomena, and the use of comparative analyses at different scales, e.g. time, territory, makes it possible to increase the informativeness of this indicator. The aim of the paper is to identify, on the basis of the available data, the trends in the transition from unemployed to employment at the national and territorial level, and to forecast possible shirt-term development scenarios for the selected jobplacement indicators. The methodological part of the paper assesses the links between unemployment trends and jobplacement indicators. The methodological approach to the assessment of differentiation of jobplacement indices are described there. On the basis of the data from the customer service units of the national Employment Service, an analysis of the spatial distribution of the transition of the registered unemployed to employment was conducted. The forecast of the indicators was based on short-term historical data from the customer service units and economic context variables. In the face of relatively unfavourable forecasts for the EU economic situation, the paper presents the assumptions for changes in the situation on the Lithuanian labour market in the short term.

In this paper Nelson-Siegel model has been examined. The main purpose of this paper is to fit the best Nelson-Siegel model to the Euro Area yield curves and to compare with Lithuanian yields in order to draw conclusions about readiness of Lithuania to join the Euro Area. In order to succeed in achieving the goal, Euro Area zero coupon bonds have been examined and various static Nelson-Siegel models were developed. Also, the mean of absolute errorof the Lithuanian government treasury bills was calculated using the best-fitting Nelson-Siegel model of the Euro Areayields. The results have shown that if the static model is calculated for each year, the yield are described precisely in the model.

This paper investigates models for the euro exchange rate against the currencies of Denmark, Poland, theUnited States, and the United Kingdom. The objective of this paper is to compare different methods of modeling andout-of-sample forecasting. One of the techniques is cointegration relation, which is implemented through a vector errorcorrection model. The existence of cointegration supports the long-run relationship between the nominal exchange rateand a number of fundamental variables. The evidence presented in this paper shows that a simple multivariate randomwalk model tends to have superior predictive performance, compared to other exchange rate models, for a period of lessthan one year.

The aim of the paper is to construct a universal classifier to discriminate short Lithuanian text excerpts of poetry from that of prose. Here the universality means that the classifier is relatively insensitive to a text content and author's style. Since syllables represent phonetic properties and are less sensitive to text content as compared to words, the classifier training is based on frequencies of syllables in texts to be classified. The text data is taken from digitized library http://ebiblioteka.mkp.emokykla.lt. The error rate of the trained classifier applied to testing excerpts of 100 words is less than 5\%.

Extending the research started in [31], the paper uses econometric methods for the short-term forecasting of quarterly values of sector indexes of stock prices from the OMX Baltic stock exchange. The ARMA models and modelling methodology that was used to build the statistical models in the previous paper are now augmented with the algorithms of time series aggregation and identification of special features of the series. Here, the search for informative factors relies on the study of related literature. The specification of models is further tailored using the traditional significance (p-value) analysis of regressors and a cross-validation analysis. The latter is implemented in this paper using the Jack-knife approach. The data period analysed covers the years 2000–2013. The results of the analysis indicate that the inclusion not only of recent autoregressive terms but also of some aggregated characteristics (as certain special features of indexes) improves the precision of forecasting substantially. The calculations were performed using the statistical analysis software SAS.

The Winter Olympics have been held since 1924, and each time host countries spend billions on organization, so it is important for them to know if this pays off in the future. This paper examines whether hosting the Winter Olympic Games yields long-term economic benefits. To achieve this, the difference-in-difference model for relative changes in Gross Domestic Product per capita was estimated. A difference-in-difference estimator examines post-Olympic impacts for host countries between 1972 and 2014. Regression results provide no additional long term impacts of hosting the Winter Olympics on GDP per capita.

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.

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.

[full article, abstract in English; abstract in Lithuanian] The present paper introduces the main principles of the quality management system of Statistics Lithuania, which is based on the ISO 9001 standard, and explains how the system promotes user confidence in statistics through the regular quality monitoring and reporting exercise. It is explained how the quality of statistics is measured and presented to the public; the usefulness of quality reports to the users, especially to researchers and academia, is discussed. Moreover, some results from the monitoring exercise and examples of quality reports are presented.

The article is based on the results of National science program ‘Welfare society’ project ‘Regional disparities of welfare inLithuania’ (project number GER-005/2017). The project is funded by the Lithuanian Council of Science. The aim of the work is toestimate features of index distribution of labor market and labor resources (working-age people) in the main country regions.Considering the fact about migration changes, a lot of attention in the paper is paid to the estimation of demographic situation impacton the labour market. Apart from the ordinary statistical data, we use results of systemic poverty problem analysis in Lithuania.According to the disposition of information and its opportunities comparison, the data of counties and municipalities were usedduring the research. Different levels of information have helped to detect more detailed differences between labour markets in theregions. The comparison of different sources of information has revealed peculiarities of unemployment change and differentiationthat have not been explored as yet.

The first part of the paper presents major concepts and theoretical statements on prediction of processes. The second part presents the obtained results on the geometric renewal process by indicating its distribution which has a binomial distribution and is a process with independent and stationary increments. Further, having applied the theory introduced in the first part to the geometric renewal process, the sufficient and unbiased prediction with the minimum-variance has been found.

In this paper, we have derived the probability density function of the size-biased p-dimensional Rayleigh distribution and studied its properties. Its suitability as a survival model has been discussed by obtaining its survival and hazard functions. We also discussed Bayesian estimation of the parameter of the size-biased p-dimensional Rayleigh distribution. Bayes estimators have been obtained by taking quasi-prior. The loss functions used are squared error and precautionary.

The paper analyses whether arterial hypertension, overweight, excessive drinking, smoking andinsufficient sports activity have an impact on the behaviour and emotional well-being of young people aged17–18. A questionnaire of Achenbach is used for investigating teenagers’ psychological difficulties. Categoricalvariables are analysed using logistic regression and log-linear models.

The aim of this paper is to study the interplay between balanced sampling, non-response and calibratedestimator by simulation. The results of seven strategies, embracing a combination of balanced sampling via the cubemethod, simple random cluster sampling, adjustment for non-response, Horvitz–Thompson estimator of the total andcalibration of design weights, are compared. Auxiliary information is used for all strategies at least at one of the stages(sampling or estimation). This auxiliary information consists of indicator variables for sex, age groups and urban/ruralliving area, and their totals. Real Labour Force Survey data of Statistics Lithuania are used for simulation. Bias, varianceand relative mean squared error are measures of accuracy for the comparison of results.

The paper examines Lithuanian texts of different authors and genres. The main points ofinterest – the number of words, the number of different words and word frequencies. Structural type distributionand Zipf’s law are applied for describing the frequency distribution of words in the text. It is obvious that thelexical diversity of any text can be defined by different words that are used in the text, also called vocabulary.It is shown that the information contained in a reduced vocabulary is enough for dividing the texts analyzedin this article into groups by genre and author using a hierarchical clustering method. In this case, distancesbetween clusters are measured using the Jaccard distance measure, and clusters are aggregated using the Wardmethod.

The paper analyses employment, activity and unemployment trends in Lithuania by sex and age, with thefocus on the monitoring of the labour market situation of different demographic groups. The possibilities of integratingwomen and men, elderly and young people into the labour market are evaluated using key labour market indicators. Differentunemployment estimation methods are used for the assessment of changes in the labour market situation of differentdemographic groups in Lithuania. Statistical data analysis is supplemented by the results of individual research.

In the last several decades, many countries have been paying a lot of attention to mortality forecastingbecause of high longevity risk. The purpose of this paper is to analyze mortality characteristics of Baltic countries andmake predictions using ARMA models. Research shoved that mortality rate distribution is almost the same in Lithuania, Latvia and Estonia and all of them represent longevity trends. It means that men and women, children and adults have thesame mortality structure in all Baltic countries and live longer than before.

This paper presents a method for the analysis of price index changes in each branch of thecountry’s economy given changes in production factors. Cobb–Douglas production functions were evaluated foreach sector separately enabling the forecasting of production quantities. The country’s total production functionwas estimated using conditional regression. Later, an inter-branch balance problem of price and productionvolume relationship evaluation was solved using a Lithuanian input–output table. Finally, combining the estimatedproduction functions and estimated price–output relationship, Lithuanian economy-relevant scenarios ofre-emigration and retail chain Lidl investment were analysed.

The aim of the paper is to assess the distributional non-homogeneity of texts in the usage of functional words andother linguistic units. Our empirical study is based on recommended school fiction works taken from a digital library athttp://ebiblioteka.mkp.emokykla.lt. Sets of frequent word forms, called markers, are made, and their frequency counts in blocks of 50successive sentences are calculated. The frequency counts of the markers show significant excess variability (overdispersion) withrespect to a text homogeneity model usually assumed in linguistics. For chosen markers, different kinds of hierarchical binomiallogistic regression models with the author's identifier, the block length and the frequency counts of the remaining markers as explanatory variables are fitted to the block data in order to explain the observed overdispersion of the markers chosen.

The Ghanaian informal sector is characterized by underemployment, bad working conditions, uncertain workrelationships and low earnings. This sector employs 80% of the workforce. Consequently, establishing an efficient tax systemthat can raise sufficient revenue to finance essential expenditures without recourse to government borrowing has been achallenge. Using time series data extracted from a revenue mobilization unit in Ghana, this paper examines the inequalities infour revenue mobilization instruments, namely self-employed tax, company tax, Pay As You Earn (PAYE) tax andmiscellaneous taxes. The study uses the theory of two-way ANOVA as the main approach for exploring the differences. Weassessed the adequacy of our theoretical approach using numerical methods. Revenues generated from the mobilizationinstruments differed significantly with exception of self-employed tax and company tax. Generally, revenue from company,self-employed and miscellaneous taxes were low, compared to Pay As You Earn (PAYE) tax. This study draws attention tothe importance of enhancing the informal sector in order to improve revenue from self-employed tax.

The paper describes various methods that can be applied to the ranking of sports teams. Using the real data of theNational Basketball Association (NBA) from the first half of the 2014–2015 season (from 2014-10-28 to 2015-02-12), teams areranked using different ranking methods. All methods are compared with each other.

The paper deals with the assessment of the performance of Lithuanian credit unions applying a cluster analysismethod, in particular the Probit regression model, substantiates their relevance and reliability for the evaluation of the resultsobtained, checks the model stability taking into account the time lag, assesses the relevance of the model for the performance analysisof Lithuanian credit unions.

Problems of finite population parameters estimation are analyzed in this paper. Four methods have been used for parameterestimation: sampling design-based unbiased estimator, multiple regression and logistic regression model-based estimators and James–Stein estimator. The design-based estimator is unbiased, but its standard deviation is usually high. Model-based estimators are notunbiased, but their standard deviations are low. In order to minimize the standard deviation and the bias, the James–Stein estimator isapplied. Labour force survey data of Statistics Lithuania are used for simulation to study model-based estimators for the number ofunemployed and employed persons in districts and counties, and the role of information on registered unemployment in these models.

Sample and population auxiliary information have been demonstrated to be useful and yield approximately equal resultsin large samples. Several functional forms of weights are suggested in the literature. This paper studies the properties of calibrationestimators when the functional form of response probability is assumed to be known. The focus is on the difference between populationand sample level auxiliary information, the latter being demonstrated to be more appropriate for estimating the coefficients in theresponse probability model. Results also suggest a two-step procedure, using sample information for model coefficient estimation inthe first step and calibration estimation of the study variable total in the second step.

While Lithuania is among the countries with the highest at-risk-of-poverty rates in the European Union, povertyresearch has so far been dominated by cross-sectional poverty analysis. This paper is aimed at contributing to better understandingof poverty as a dynamic process in Lithuania by examining poverty risk persistence, transitions and triggers. Theanalysis is based on the longitudinal component of the Survey on Income and Living Conditions. The longitudinal at-risk-ofpovertyrate within the four-year panels is estimated to be at around a third of the Lithuanian population within a period of2005–2012. Poverty risk in Lithuania proved to be both widely spread and persistent. The major role of income events forpoverty risk entries and exits highlights the importance of activation into work, especially as concerns secondary householdearners and better income protection in Lithuania. While no robust evidence of poverty penalty was found for poverty exits,the incidence of poverty re-entries within the initial three-year period after poverty exit substantially exceeds poverty entryrates in the general population.

Lithuanian labour market indicators, such as the total number of employees, the number of employees in the private and public sectors, the number of the unemployed, labour force, employment and unemployment rates, the relative number of employees, average monthly gross income are analysed in the paper. The experience of foreign countries and Lithuania in creating labour market models and econometric methodology has been examined. As a result, a new model of the Lithuanian labour market is produced, comprising five regressive equations, which are part of the recursive SVAR model, and four identities, which are part of balance equations. According to the logic of economic and other research, relevant connections in the economy have been specified, unknown parameters of equations have been estimated. Finally, forecasts of endogenous indicators for 2014 have been provided, and results have been compared with the projections of the main labour market indicators for 2014−2017, published by the Ministry of Finance. Calculations have been made using a statistical package Gretl.

The paper analyses the use of a nonlinear regression model, generalised linear model and generalised additive model(semi-parametric regression model) for creating real estate valuation models. These models are applied to data on transactions inKlaipeda city apartments. The aim is to create real estate valuation regression models applying various statistical methods and tocompare them with each other. The practical aspects of creating regression models are analysed and conclusions are presented in thepaper.

The goal of this paper is to analyze the tendencies of social exclusion and inequality in Lithuania and in the context of Europe. By using statistical methods such as Gini coefficient and Lorenz curve, firstly we analyze the inequality of average county disposable household income per month. In the second part of the study, we analyze an indicator of people at-risk-of poverty or social exclusion in 26 different countries of Europe. In this section, we want to test the fixed and random effects models on our data. Based on them, the average effect of the at-risk-of poverty or social exclusion indicator can be measured. Based on real expenditure per capita analysis, Lithuania can be classified to a group of post-Soviet countries, where tendencies of poverty or social exclusion risk are similar.

The paper presents a short history of international cooperation in statistics, formation of statisticalassociations and their activities in the world and in the Nordic countries. The cooperation background for Baltic and Nordicstatisticians before 1992 is presented. The contents of the activities of the Baltic–Nordic–Ukrainian Network on SurveyStatistics is highlighted.

This paper presents the results of a study on sociodemographic mortality differentials in Lithuania based on censuslinked mortality data. Population data come from the individual records of the 2011 Population and Housing Census of the Republic of Lithuania. The results of the research demonstrate that education and marital status are very strong predictors of alcohol-related mortality. Among males aged 30 and older, the alcohol-related mortality risk in non-married groups is up to 3.4 times as high as in the group of married males. The alcohol-related mortality risk in lower-education groups is up to 3.7 times as high as in the group of those with higher education. The findings of the study suggest that the elimination of educational differences would allow avoiding 55.7 %, the elimination of marital status differences – 40.2 %, the elimination of ethnic group differences – 11.1 % of alcohol-related deaths.