Methodology of Industry Statistics: Averages, Quantiles and Responses to Atypical Value

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dc.contributor.authorBoďa, Martin
dc.contributor.authorÚradníček, Vladimír
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2020-09-02T09:42:31Z
dc.date.available2020-09-02T09:42:31Z
dc.description.abstractThe paper notices troublesome aspects of compiling industry statistics for the purpose of inter-enterprise comparison in corporate financial analysis. Whilst making a caveat that this issue is unbeknownst to practitioners and underrated by theorists, the goal of the paper is two-fold. For one thing, the paper demonstrates that financial ratios are inclined to frequency distributions characteristic of power-law (fat) tails and their typical shape precludes a simple treatment. For the other, the paper explores different approaches to compiling industry statistics by considering trimming and winsorizing cleansing protocols, and by confronting trimmed, winsorized as well as quantile measures of central tendency. The issues are empirically illustrated on data for a great number of Slovak construction enterprises for two years, 2009 and 2018. The empirical distribution of eight financial ratios is studied for troublesome features such as asymmetry and power-law (fat) tails that hamper usefulness of traditional descriptive measures of location without considering different possibilities of handling atypical values (such as infinite and outlying values). The confrontation of diverse approaches suggests a plausible route to compiling industry statistics that consists in reporting a 25% trimmed mean alongside 25% and 75% quantiles, all applied to trimmed data (i.e. data after discarding infinite values). The paper also highlights the sorely unnoticed fact that the key ratio of financial analysis, return on equity, may easily attain non-sense values and these should be removed prior to compiling financial analysis; otherwise, industry statistics is biased upward regardless of what measure of central tendency is made use of.en
dc.formattext
dc.identifier.doi10.15240/tul/001/2020-3-008
dc.identifier.eissn2336-5604
dc.identifier.issn1212-3609
dc.identifier.urihttps://dspace.tul.cz/handle/15240/157484
dc.language.isoen
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisher.abbreviationTUL
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dc.relation.ispartofEkonomie a Managementcs
dc.relation.ispartofEconomics and Managementen
dc.relation.isrefereedtrue
dc.rightsCC BY-NC
dc.subjectIndustry statisticsen
dc.subjectfinancial ratiosen
dc.subjecttrimmed meanen
dc.subjectwinsorized meanen
dc.subjectquantileen
dc.subjectnon-sense valuesen
dc.subjectpower law in the tailen
dc.subject.classificationC19
dc.subject.classificationM10
dc.subject.classificationM40
dc.titleMethodology of Industry Statistics: Averages, Quantiles and Responses to Atypical Valueen
dc.typeArticleen
local.accessopen
local.citation.epage137
local.citation.spage120
local.facultyFaculty of Economics
local.filenameEM_3_2020_8
local.fulltextyes
local.relation.abbreviationE+Mcs
local.relation.abbreviationE&Men
local.relation.issue23
local.relation.volume3
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