Statistika: Statistics and Economy Journal - No. 1/2020

 
Code: 320197-20
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Economic Growth, Business Cycles and Okun’s Law: Unobserved Components Approach
Andrea Čížků
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Abstract

Clark’s (1989) bivariate unobserved components model is applied in order to estimate and analyse the trend and cycle of GDP and the unemployment rate as well as to quantify and discuss the relationship known as Okun’s law. Empirical analysis is performed for 28 European countries for a time period including the current economic crisis – the end period is 2018 Q4 for all economies and the beginning period ranges from 1983 Q1 to 2000 Q1 according to data availability. Important results indicate that in virtually all European countries: (1) the growth of the trend component of GDP decreased systematically after the crisis; (2) the output gap improved in the last five years – this finding proved to be quite robust as it was also confirmed by Hodrick Prescott estimates of the output gap for different smoothing parameter values; (3) the trend component of the unemployment rate turned out to be constant over time, indicating that possible hysteresis effects have not played an important role in European labour markets; (4) the output gap and cyclical unemployment rate are highly negatively correlated, confirming the strength and validity of Okun’s law across European countries.

Keywords

Unobserved components, Clark’s bivariate model, Okun’s law, Kalman filter, HP filter

 

 
Estimation of the Optimal Parameter of Delay in Young and Lowe Indices in the Fisher Index Approximation
Adam Juszczak
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Abstract

The Cost of Living Index (COLI) enables to show changes in the cost of household consumption assuming the constant utility level. The most commonly used way to approximate COLI is the Consumer Price Index (CPI) calculated by using the Laspeyres index. Many economists consider superlative indices such as the Fisher index as the best proxy for the COLI. However, it uses quantity data not only from a base but also the current period, which limits its usefulness. Thus, the indices like the Lowe index and the Young Index are used in order to approximate the Fisher index value without using current period expenditure data. Both of these indices use an additional parameter of delay. The purpose of this paper is to examine the influence of the parameter mentioned above on the Fisher index approximation using the empirical and simulation data.

Keywords

CPI, Young index, Lowe index, Laspeyres index, Fisher index, COLI, Cost of Living Index, Consumer Price Index, inflation

 

 
Remarks on Price Index Methods for the CPI Measurement Using Scanner Data
Jacek Białek
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Abstract
Scanner data are a quite new data source for statistical agencies and the availability of electronic sales data for the calculation of the Consumer Price Index (CPI) has increased over the past 16 years. Scanner data can be obtained from a wide variety of retailers (supermarkets, home electronics, Internet shops, etc.) and provide information at the level of the barcode, i.e. the Global Trade Item Number (GTIN, formerly known as the EAN code). One of new challenges connected with scanner data is the choice of the index formula which should be able to reduce the chain drift bias and the substitution bias. In this paper, we compare several price index methods for CPI calculations based on scanner data. In particular, we consider bilateral index methods with chained versions of direct weighted and unweighted indices, and also selected multilateral index methods, i.e. the quality adjusted unit value method (QU method) and its special case (the Geary-Khamis method), the augmented Lehr method, the so called “real time index”, the GEKS method and the CCDI method. We consider different weighting schemes in quantity weights on the price index. We compare all these methods using a real scanner data set obtained from one supermarket chain.. The main aim of the paper is to show how big differences among bilateral and multilateral indices may rise while using real scanner data sets. In particular our results lead to the conclusion that the choice of the multilateral formula and the weighting scheme does matter in inflation measurement. It is shown that differences between values of all discussed formulas may exceed several percentage points even in the case of only one homogeneous group of products.
 
Keywords
Scanner data, Consumer Price Index, superlative indices, elementary indices, chain indices, QU-GK index, Geary-Khamis method, real time index, GEKS, bilateral indices, multilateral indices
 

 
Figures - F9a, F9b, F9c GIF GIF GIF
Income and Consumption Inequalities in Palestine: a Regression-Based Decomposition Approach
Mohsen Ayyash, Siok Kun Sek, Tareq Sadeq
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Abstract
The inequality in the households' living standards is commonly measured by either income or consumption. Different household's attributes may affect inequality in these living standards. This study aims to investigate the factors affecting income and consumption, quantifies their proportionate contributions to income and consumption inequalities, and compares them. The data are collected from the Palestinian Household Expenditure and Consumption Survey (PECS) in 2017. To cast light on this issue, the study applies a regression-based decomposition approach to income-generating function. The results suggest that household attributes better explain adjusted consumption inequality than adjusted income inequality, which should be a better measure of living standards. Moreover, the results indicate that the region, education, and employment status are the major factors of adjusted income and consumption inequalities, while the other factor's contributions have been minimal. For policy interventions, multidimensional policies should be formulated to reduce inequality in all dimensions for achieving an overall equal society.
 
Keywords
Inequality, regression-based decomposition, income, consumption, Palestine
 
 
 
Profiling: a New Way to Increase the Quality of Statistics on Research and Development
Thomas Balcone
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Abstract
Currently, statistics on Research and Development (R&D) carried out in the business sector are computed in France on the sole basis of legal units: firstly, a survey is addressed to them to collect the data and then, statistics on R&D are disseminated at legal unit level. Considering the increasing importance of the enterprise group in the French economy, it seems difficult today to go on using only the legal units to calculate business statistics. Indeed, assimilating the legal unit to the enterprise is not relevant anymore for group's affiliates and subsidiaries. Taking into account the European definition of an enterprise will help to disseminate more consistent and relevant R&D statistics on the business sector.
The French business statistical register established by the French National Statistical Institute (INSEE), called SIRUS, contains notably all the legal units and all the enterprises. The main contribution of this register is to make possible the calculation and dissemination of statistics at another level than the legal unit one: the enterprise level.
This article first describes why the data should go on being collected at the legal unit level and not at the enterprise one. Indeed, it seems that such a change in the data collection can be dangerous because it could result in a substantial increase of the response burden. Then, this article presents the process based on SIRUS that leads to the computation of key indicators on R&D at enterprise level. To conclude, it compares these key indicators with the ones calculated at the legal unit level to show the impact of moving to the enterprise level on French R&D statistics.  
 
Keywords
Business statistics, business R&D statistics, statistical unit, data collection, surveys
The Improvement of Response Rates and Data Quality of Direct Business Surveys by Centralized Data Collection Approach: the ISTAT Experience
Giampaola Bellini, Francesca Monetti, Pasquale Papa
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Abstract
In April 2016 ISTAT (Italian National Statistical Institute) started a corporate restructuring process that interested all the statistical production structures and that led to a completely renewed organizational setup. Before the above mentioned reorganization, the statistical processes were organized according to the classical ‘stovepipe’ model, that involved independent, non-integrated, statistical processes including all the necessary skills: statisticians, information technology experts, thematic experts, methodologists.The new model restricts the production processes only to the thematic experts, while all the “cross” expertise isare all assigned to specialized structures. The main advantage of the new setup concerns the overall system efficiency, while the main disadvantage concerns the increased fragmentation of the production processes.  
Before the restructuring process, response rates in economic structural surveys were quite low and unsatisfactory. After two years from the introduction of the new organization the medium response rate increased from 48.8 to 59.5 per cent for structural surveys and from 59.0 to 79.0 for short-term surveys. At the same time, the duration of the data collection periods for structural surveys reduced from 152 to 115 days.

Keywords
Data collection, response rates, process efficiency, official statistics, business stastistics, quality of statistics, non-response, statistical survey

 
International Conference Mathematical Methods in Economics (MME 2019)
Petra Zýková, Josef Jablonský
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13th Year of the International Days of Statistics and Economics (MSED 2019)
Tomáš Löster, Jakub Danko
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International Conference Applications of Mathematics and Statistics in Economics (AMSE 2019)
Stanislava Hronová
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International Conference Interdisciplinary Information Management Talks (IDIMT 2019)
Petr Doucek, Lea Nedomová, Gerhard Chroust, Antonín Pavlíček
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Published: 20.03.2020
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