Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/62498
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dc.contributor.authorPathak, Amriten
dc.contributor.authorLeu, Chen-Yuen
dc.contributor.authorSiriwardana, Anandaen
dc.date.accessioned2024-09-03T02:27:31Z-
dc.date.available2024-09-03T02:27:31Z-
dc.date.issued2023-05-06-
dc.identifier.urihttps://hdl.handle.net/1959.11/62498-
dc.descriptionThis research has been conducted with the support of the Australian Government Research Training Program Scholarship.en
dc.description.abstractThis study uses the National Census of Manufacturing Establishments (NCME) of Nepal which is conducted by the Central Bureau of Statistics (CBS). The CBS is the main government organisation in Nepal responsible for the collection, management, and dissemination of statistical information. These censuses are conducted quinquennially. This study utilises data from the census year 1981/82 to 2018/19 which gives eight time points for the panel dataset. Censuses 1981/82 and 1986/87 cover manufacturing establishments using automachines irrespective of the number of persons engaged, whereas censuses from 1991/92 to 2018/19 cover establishments engaging 10 or more persons. Each census contains an average of 4000 establishments. Following international practices, these establishments are categorised into 66 different industries according to the four-digit Nepal Standard Industrial Classification (NSIC). Therefore, each industry comprises of a group of establishments. As each census provides a combined value for different variables for establishments that belong to the same industry, analysis is conducted at the industry level since establishments are not uniquely identified in the census data. Industries with just one or two establishments in any census are omitted from the dataset as they do not reveal their data because of confidentiality issue. The censuses cover only industries that are government-registered and operate within the geographic boundary of Nepal. Given different industrial classification revisions that have occurred during the study period, conversion charts are used to confirm that industries are correctly categorised according to the latest NSIC for each census year. Some industries with one or two observations during the study period are merged with their closest allies based on the nature of their activities in the census year. This makes sure that they belong to the same 3-digit NSIC classification. This study also utilises the United Nations Conference on Trade and Development (UNCTAD) – Trade Analysis Information System (TRAINS) database to extract tariff data via the World Integrated Trade Solution (WITS) portal. Extracted tariffs for each of the 4-digit 66 industries are effectively applied tariffs (AHS). WITS defines these tariffs as the lowest available import tariffs. The most favoured nations (MFN) tariffs are also used as an alternative measure. The tariff rates for each industry are matched to their respective census years.en
dc.format.extent.xlsx, .dta, .doen
dc.languageenen
dc.publisherUniversity of New Englanden
dc.relation.urihttps://hdl.handle.net/1959.11/60258en
dc.titleTrade Liberalisation, Productivity, and Protection: The Case of an Open Developing Economy - Dataseten
dc.typeDataseten
dc.identifier.doi10.25952/g7rq-1n98en
dcterms.accessRightsMediateden
dcterms.rightsHolderAmrit Pathaken
dc.subject.keywordsTrade liberalisationen
dc.subject.keywordsmanufacturing productivityen
dc.subject.keywordstechnical efficiencyen
dc.subject.keywordsendogenous protectionen
local.contributor.firstnameAmriten
local.contributor.firstnameChen-Yuen
local.contributor.firstnameAnandaen
local.profile.schoolUNE Business Schoolen
local.profile.schoolUNE Business Schoolen
local.profile.schoolUNE Business Schoolen
local.profile.emailamrit.pathak48@gmail.comen
local.profile.emailcleu@une.edu.auen
local.profile.emailasiriwar@une.edu.auen
local.output.categoryXen
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeArmidale, New South Wales, Australiaen
local.title.subtitleThe Case of an Open Developing Economy - Dataseten
local.contributor.lastnamePathaken
local.contributor.lastnameLeuen
local.contributor.lastnameSiriwardanaen
dc.identifier.staffune-id:cleuen
dc.identifier.staffune-id:asiriwaren
local.profile.orcid0000-0002-3620-537Xen
local.profile.orcid0000-0003-2960-9701en
local.profile.rolecreatoren
local.profile.rolesupervisoren
local.profile.rolesupervisoren
local.identifier.unepublicationidune:1959.11/62498en
dc.identifier.academiclevelStudenten
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleTrade Liberalisation, Productivity, and Protectionen
local.relation.fundingsourcenoteAustralian Government Research Training Program (RTP)en
local.output.categorydescriptionX Dataseten
local.search.authorPathak, Amriten
local.search.supervisorLeu, Chen-Yuen
local.search.supervisorSiriwardana, Anandaen
dcterms.rightsHolder.managedbyAmrit Pathaken
local.datasetcontact.nameAmrit Pathaken
local.datasetcontact.emailamrit.pathak48@gmail.comen
local.datasetcustodian.nameAmrit Pathaken
local.datasetcustodian.emailamrit.pathak48@gmail.comen
local.datasetcontact.detailsAmrit Pathak - amrit.pathak48@gmail.comen
local.datasetcustodian.detailsAmrit Pathak - amrit.pathak48@gmail.comen
dcterms.ispartof.projectTrade Liberalisation, Productivity, and Protection: The Case of an Open Developing Economyen
dcterms.source.datasetlocationUniversity of New Englanden
local.uneassociationYesen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2023en
local.subject.for2020380110 International economicsen
local.subject.for2020380204 Panel data analysisen
local.subject.for2020380201 Cross-sectional analysisen
local.subject.seo2020150103 Trade policyen
local.subject.seo2020150199 International trade policy not elsewhere classifieden
local.subject.seo2020150304 Productivity (excl. public sector)en
dc.coverage.placeArmidale, New South Wales, Australiaen
dc.coverage.placeKathmandu, Nepalen
local.profile.affiliationtypeUNE Affiliationen
local.profile.affiliationtypeUNE Affiliationen
local.profile.affiliationtypeUNE Affiliationen
Appears in Collections:Dataset
UNE Business School
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