Determinants of regional diversity of wages in Ukraine

Tokarski, Tomasz; Chugaievska, Svitlana; Chugaievska, Nataliia

doi:10.5604/01.3001.0013.8503

Cited by 2 publications

(4 citation statements)

References 5 publications

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“…The following conclusions can be drawn from the map and the chart presented below (see also e.g. Lysiuk and Kaflevska, 2012;Paniuk, 2013;Homiak, 2015;Jarova, 2015;Tokarski et al, 2019):…”

Section: Differences In Labour Productivity Wages and Unemployment Rates In Ukrainementioning

confidence: 73%

“…4 The trajectories of this variable in groups of oblasts are illustrated in Figure 1. Map 2 and Figure 1 present the following information (see also Pustovoit, 2016;Chugaievska et al, 2017;Tokarski et al, 2019): 5…”

Section: Differences In Labour Productivity Wages and Unemployment Rates In Ukrainementioning

confidence: 98%

“…The Ukrainian oblasts are divided into 5 groups (for more details see e.g. Chugaievska et al, 2017, Chugaievska and Tokarski, 2018or Tokarski et al, 2019. These groups consist of the following:…”

Section: General Characteristics Of Ukrainian Oblastsmentioning

confidence: 99%

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Determinants of spatial differentiation of labour markets in Ukraine

Dykas

Misiak

Tokarski

2020

Przegląd Statystyczny

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The aim of this paper is to present the differentiation of the situation in regional labour markets in Ukraine in the years 2004–2017. The analyses carried out for this purpose concern the diversity and dynamics of macroeconomic variables, such as labour productivity (measured by GDP per worker), wages, and unemployment rates. Moreover, using panel data from the Statistical Office of Ukraine, the authors estimate the parameters of a set of equations based on increments and levels by means of the system estimator of the generalized Blundell and Bond moments method from 1998. The estimates concern the parameters of equations describing the main determinants of the increase in unemployment rates and wages for the entire Ukrainian economy – both Left – and Right-Bank Ukraine.

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“…The following conclusions can be drawn from the map and the chart presented below (see also e.g. Lysiuk and Kaflevska, 2012;Paniuk, 2013;Homiak, 2015;Jarova, 2015;Tokarski et al, 2019):…”

Section: Differences In Labour Productivity Wages and Unemployment Rates In Ukrainementioning

confidence: 73%

Section: Differences In Labour Productivity Wages and Unemployment Rates In Ukrainementioning

confidence: 98%

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Determinants of spatial differentiation of labour markets in Ukraine

Dykas

Misiak

Tokarski

2020

Przegląd Statystyczny

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“…An important transport hub (road, railway, sea, river, and air transport) is located in Nikolayiv and the Nikolayiv Oblast in the south of Ukraine, while Lviv is by far the most economically developed city with the largest population in the western part of the country (cf. also Chugaievska and Tokarski, 2018;Chugaievska et al, 2017or Tokarski et al, 2019; • all groups of oblasts (except Eastern Ukraine) show similar trends in labour productivity. Between 2004 and 2008, the value of this variable increased, but then decreased significantly in 2009.…”

Section: Differences In Labour Productivity Wages and Unemployment Rmentioning

confidence: 86%

A proposal for perception measurement on a linguistic scale coded with unconventional fuzzy numbers

Dziechciarz–Duda

2020

Przegląd Statystyczny

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The aim of this paper is to formulate a new proposal for perception measurement on a linguistic scale coded with fuzzy numbers. Additionally, an attempt is made to show the assessment process of the adequacy of a linguistic scale. The basis for the proposal is the discussion of issues related to the ambiguity of the results of measurements made by means of a subjective type of measurement scales. The proposed assessment technique is relevant when the results of the measurement based on a linguistic scale are coded with numerical equivalents in the form of e.g. unconventional fuzzy numbers. The issue the subjective perception of the products’ quality illustrates the objectivity level of measurement results. Subjective perception is measured with a specially designed IT tool allowing the respondent to determine all the characteristics of the resulting fuzzy numbers. The scale adequacy assessment tool is based on the Item Response Theory, and particulary so on the model devised by Georg Rasch. The measurement of socio-economic phenomena, including material and subjective wellbeing of households, the quality of households’ durable goods, and the assessment of the quality of goods available on the market requires special tools. It seems that one of the most useful and powerful tools for the measurement of socio-economic phenomena is a linguistic scale. The problematic issue in the analysis presented in the paper is coding verbal terms with their numerical equivalents.

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Determinants of regional diversity of wages in Ukraine

Cited by 2 publications

References 5 publications

Determinants of spatial differentiation of labour markets in Ukraine

Determinants of spatial differentiation of labour markets in Ukraine

A proposal for perception measurement on a linguistic scale coded with unconventional fuzzy numbers

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