Statistika: Statistics and Economy Journal - No. 3/2019

 
Code: 320197-19
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The Recovery ot the Input-Output Analysis in the Czech Republic
Jaroslav Sixta
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Abstract
The input-output analysis has a long tradition in the former Czechoslovakia starting in the 1960s. These models were originally used for central planning and price re-construction during socialism. Since the 1970s, there have been three sets of tables, for Czechoslovakia, the Czech Republic and the Slovak Republic. After 1989, input-output models gained a label of socialist planning instrument and they were mostly abandoned in Eastern countries. On the contrary, sophisticated input-output models became accessible for the most researchers in the West because of common usage of personal computers. Matrix computations that took months in the past became available to everyone. Alongside with the supply of input-output tables of the EU countries, also researchers in the Central and East Europe started to use these sets of models again. In the recent time, the input-output models are widely used both on national and international level, ranging from private agencies to the OECD. Nowadays, the recovery of Leontief models and theory has been used in the Czech Republic, as well. Such models have become a standard part of the research for macroeconomic, environmental, regional and similar purposes.
 
Keywords
Input-output analysis, supply and use tables, national accounts
 
The Impact of the Price Index Formula on the Consumer Price Index Measurement
Jacek Białek, Elżbieta Roszko-Wójtowicz
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Abstract
The Consumer Price Index (CPI) is a common measure of inflation. Similarly to the Harmonised Index of Consumer Prices (HICP), it is determined using the Laspeyres index, thus data on the consumption of the basket of goods do not have to be current. The Laspeyres index, using weights only from the base period, may not reflect changes in consumer preferences that occurred in the studied year. In the ideal case, the CPI should be measured by one of the so called superlative price indices, such as the Fisher, Törnqvist or Walsh index formulas. The main problem with such indices is that they need expenditure data from the current period. The aim of the article is to assess the impact of the choice of the price index formula on the CPI measurement. We verify differences among known index formulas at the lowest and some higher data aggregation levels. We use known bilateral unweighted and weighted formulas together with their chained versions.
 
Keywords
Inflation measurement, Consumer Price Index (CPI), price indices, elementary price indices, chain indices, formula bias, scanner data
 

 
Modeling of Currency Covolatilities
Tomáš Cipra, Radek Henych
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Abstract
The paper deals with dynamic modeling of currency portfolios. In contrast to univariate models of exchange rates and their returns one applies multivariate time series models of the type GARCH that are capable of capturing not only conditional heteroscedasticities (i.e. volatilities) but also conditional correlations for common movements of exchange rates (so called covolatilities). One makes use of recursive estimation algorithms suggested by authors for such models which enable to control, evaluate and manage currency investment portfolios in real time. The main task of the paper is to assess whether the recursive estimation procedures suggested by the authors are applicable for real currency portfolios. It is realized by performing an extensive numerical study for bivariate portfolios of the EU currencies and US dollar concentrating on the role of the Czech crown.
 
Keywords
Currency covolatilities, investment index, multivariate GARCH models, pay off ratio, recursive estimation
 
Comparative Analysis of Results of Assessing the Central Federal Distict´s Regions´ Economic Development by Using Linear and Non-Linear Models
Roman Zhukov, Gennadiy Kuznetsov, Sergey Gorodnichev, Evgeniy Manokhin, Ekaterina Nazyrova, Elena Melay
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Abstract
This paper provides a comparative analysis of results of estimating specific efficacy that characterizes the amount of gross regional product depending on expenditure on technological innovations, the fixed capital and the average annual number of persons employed. This approach includes comparison of actual data with normative values calculated for three types of models: linear, logarithmic, and power multiplicative. The particular performance indicator is determined as a relation between actual and normative values for the Russian Federation’s Central District’s regions. The investigation’s information base was statistical data on the regions of the RF CFD for 2007–2016. The issues under discussion are differences in results of evaluation obtained in using the first, second and third type models.
 
Keywords
Indicators, gross domestic product by region, modeling

 
Estimating Criminal Populations from Administrative Registers
Antonella Baldassarini, Valentina Chiariello, Tiziana Tuoto
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Abstract
This study proposes a methodology for estimating the hidden criminal population working in markets of drug trafficking, prostitution exploitation and smuggling in Italy during the period 2006–2014. These estimates represent the first step of a wide procedure that has the final objective of measuring the economic flows of illegal transactions in national accounts. We exploit administrative registers coming from the Ministry of Justice, and consider these registers as lists of potential criminals. Unique codes for denounced criminals are not available, limiting so far its exploitation at micro level. This drawback has been overcome in this work by proposing an adjustment of the Zelterman estimator that accounts for the potential linkage errors caused by the lack of exact unique identifiers in the dataset. We obtain yearly estimates of the population size of criminals including also the unknown population, for the crimes of drug trafficking, prostitution exploitation and smuggling during the period 2006–2014.
 
Keywords
Illegal economy, population size estimation, Capture-recapture, Zelterman estimator, linkage errors
 

 
Determining Factors of Volunteer Work Participation in Japan
Kenichi Shimamoto
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Abstract
With the growing awareness of the sustainability concept, society’s interest towards the consideration for the wider community and the environment has developed. Local Agenda 21 has supported the voluntary process of local community consultation with the aim to create local policies and programs that work towards achieving sustainable development. This has stimulated the need for community participation through local volunteer participants. This paper will apply prefecture level panel data for Japan to examine the determining factors of volunteer work participation. The main results show that prefectures with higher children and senior citizen population and prefectures with higher usage of the internet and media are more active in the overall participation of volunteer work. On the other hand, prefectures with stronger urbanization are less likely to participate in volunteer work.
 
Keywords
Volunteer work, linear regression panel model, senior citizen, urbanization, Japan
 

 
Multilevel Analysis of Wage Inequality in Palestine
Mohsen Ayyash, Sek Siok Kun
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Abstract
Historical data exhibit the imbalance participation rate between genders in the Palestinian labour market in which female participation is among the lowest worldwide. On the other hand, occupational discrimination and wage inequality still exist between males and females. Combining both issues, this study seeks to examine the gender pay gap across occupational groups in Palestine. The data are collected from the Palestinian Labour Force Survey (PLFS) for the year 2017. The multilevel linear regression is applied to model the wage equation. For the robustness purpose, three estimation techniques are applied which are maximum likelihood (ML), restricted maximum likelihood (REML), and Bayesian estimation. The results reveal that occupational groups account for about 23.6% of wage differentials. The gender wage gap varies significantly across occupational groups, where it is decreased after correcting for self-selection bias. Moreover, the Bayesian estimation method provides more efficient estimates than ML and REML methods. Schooling, age, and other socioeconomic variables also contribute significantly to wage inequality in Palestine. 
 
Keywords
Multilevel modelling, maximum likelihood, restricted maximum likelihood, Bayesian estimation, wage inequality, intra-class correlation coefficient
 

 
Enhancing the Awareness of Official Statistics in Egypt: the Approach to Increase their Value
Ayman Hathoot
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Abstract
The paper demonstrates the role of the Central Agency for Public Mobilization and Statistics (CAPMAS) in increasing official statistics value in Egypt using the two following methods. First, the applied approach to facilitate the use of understood official statistics. It involves enhancing statistics literacy for the public, training the current staff members who produce official statistics and summer training for university graduates. Second, the indicators used to monitor the progress, which provides information on a specific aspect of the value of official statistics. The number of downloads, the number of citations of media, evaluation of training the staff members and university graduates, and user satisfaction are the essential means for evaluation. Media and internet are important means to facilitate statistical literacy in CAPMAS.
Training staff members and university graduates enhances their statistical literacy, which raises their performance in the official statistics field. A great effort is still needed to increase the value of official statistics. Collaboration with The International Statistical Literacy Project (ISLP) is important to promote statistical literacy.
 
Keywords
Enhancing statistical literacy, academic bodies, media, NCST, metadata
 
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Published: 20.09.2019
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