Zobrazit minimální záznam

dc.contributor.authorAdamec, Václav
dc.date.accessioned2021-06-28T00:02:11Z
dc.date.available2021-06-28T00:02:11Z
dc.date.issued2018
dc.identifier43916216
dc.identifier.issn1211-8516 Sherpa/RoMEO, JCR
dc.identifier.urihttps://repozitar.mendelu.cz/xmlui/handle/20.500.12698/1359
dc.description.abstractActivities in the construction sector are assumed to be influenced by inflow of mortgage funding in the private housing sector and public finances targeted at large infrastructure projects, apart from climate variables. In this study, we modeled seasonal time series representing monthly output in the Czech construction sector in CZK mil. during 2000:1 through 2016 : 12 (T = 204) adjusted for calendar variations and seasonal movements via TRAMO-SEATS and then transformed to natural logarithms of gross returns. A Markov-Switching model with two states, no intercept, average monthly temperature, average monthly precipitation and parameters of first-order autoregression process was specified and estimated by the Expectation-Maximization. In State 1 of regular performance, the log-differenced returns were significantly and positively influenced by precipitation levels, but not by ambient outdoor temperature. In State 2 of non-standard operation of the construction sector, the transformed series was unaffected by precipitation levels, but instead by ambient outdoor temperatures. First-order autocorrelation dependency in both regimes was established. Changes in legal and macroeconomic environment pertinent to tax law amendments affecting VAT or corporate tax, country's accession to EU or large construction project deadlines were shown to induce nonstandard regime in the construction sector (State 2). The model classified 91 % observations in the first state, while only 9 % data belonged to the State 2. Transition probability matrix indicates that change from model State 1 to State 2 is difficult to attain. At the same time, once State 2 was established, it tends to persist or change to State 1 with near equal probability. Ability of the Markov-Switching model to identify both states is reasonably good.en
dc.format1383-1391
dc.publisherMendelova univerzita v Brně
dc.relation.ispartofActa Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
dc.relation.urihttps://doi.org/10.11118/actaun201866061383
dc.rightsCC BY-NC-ND 4.0
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectconstruction sectoren
dc.subjectTRAMO-SEATSen
dc.subjectMarkov-Switching modelen
dc.subjectValue Added Taxen
dc.subjectcorporate taxen
dc.subjecttransition probabilityen
dc.subjectR-softwareen
dc.titleDisparity in Performance of the Czech Construction Sector: Evidence from the Markov-Switching Modelen
dc.typeJ_ČLÁNEK
dc.date.updated2021-06-28T00:02:11Z
dc.description.versionOA
local.identifier.doi10.11118/actaun201866061383
local.identifier.scopus2-s2.0-85060209268
local.number6
local.volume66
local.identifier.obd43916216
local.identifier.e-issn2464-8310
dc.identifier.orcidAdamec, Václav 0000-0002-4153-0644
local.contributor.affiliationPEF


Soubory tohoto záznamu

Thumbnail

Tento záznam se objevuje v následujících kolekcích

Zobrazit minimální záznam

CC BY-NC-ND 4.0
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je CC BY-NC-ND 4.0