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The analysis draws on the Italian Household Budget Survey (HBS) conducted by ISTAT, covering the years 2014–2022."},"dsDescriptionDate":{"typeName":"dsDescriptionDate","multiple":false,"typeClass":"primitive","value":"2026-03-31"}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Social Sciences"]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationRelationType":{"typeName":"publicationRelationType","multiple":false,"typeClass":"controlledVocabulary","value":"IsSupplementTo"},"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Oncini, F. (2026). Anything but hard discount: Storevorousness and the social stratification of grocery shopping venues in Italy, 2014–2022. Journal of Consumer Culture, in press"}}]},{"typeName":"notesText","multiple":false,"typeClass":"primitive","value":"The package comprises the following do-files:\n\nDependent_variables_FINAL.do — construction of binary store-visit indicators and aggregate purchase measures across seven venue types\nControl_variables_FINAL.do — preparation of sociodemographic and socioeconomic control variables\nDescriptives_FINAL.do — summary statistics for all key variables\nDescriptives_over_time_FINAL.do and Summary_table_descriptives_over_time_FINAL.do — time-trend descriptives and tabulation (2014–2022)\nHistograms_FINAL.do — distribution plots of venue-specific purchase counts\nCountfit_for_nbreg_FINAL.do — overdispersion diagnostics to justify negative binomial estimation\nModel_1__total__FINAL.do — OLS regression of total store voracity on household characteristics, with marginal means by income decile and education\nModel_2__HHI__FINAL.do — zero-one-inflated beta (ZOIB) regression of the Herfindahl–Hirschman Index of shopping concentration\nModel_3__logit_and_nbreg__FINAL.do — two-part models (logit + negative binomial) for each of the seven store types, with combined margin plots\nPoisson_margins_FINAL.do — alternative Poisson-based margins for robustness\nModel_4_Margins_per_food_item_Q5-Q1_FINAL.do — Q5–Q1 margin differences by food product and store type\nHeatmap_Google_Colab_Script.txt — link to the Python/Google Colab script used to produce the food-item × store-type heatmap\n\nAll do-files are self-documented with inline annotation. File paths in the scripts refer to the authors' local environment and must be updated to match the replicator's directory structure."},{"typeName":"language","multiple":true,"typeClass":"controlledVocabulary","value":["English"]},{"typeName":"productionDate","multiple":false,"typeClass":"primitive","value":"2026-03-31"},{"typeName":"productionPlace","multiple":true,"typeClass":"primitive","value":["Maastricht"]},{"typeName":"contributor","multiple":true,"typeClass":"compound","value":[{"contributorType":{"typeName":"contributorType","multiple":false,"typeClass":"controlledVocabulary","value":"Data Curator"},"contributorName":{"typeName":"contributorName","multiple":false,"typeClass":"primitive","value":"Filippo Oncini"}}]},{"typeName":"grantNumber","multiple":true,"typeClass":"compound","value":[{"grantNumberAgency":{"typeName":"grantNumberAgency","multiple":false,"typeClass":"primitive","value":"HORIZON EUROPE European Research Council"},"grantNumberValue":{"typeName":"grantNumberValue","multiple":false,"typeClass":"primitive","value":"101163222"}}]},{"typeName":"depositor","multiple":false,"typeClass":"primitive","value":"Oncini, Filippo"},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2026-03-31"},{"typeName":"timePeriodCovered","multiple":true,"typeClass":"compound","value":[{"timePeriodCoveredStart":{"typeName":"timePeriodCoveredStart","multiple":false,"typeClass":"primitive","value":"2014"},"timePeriodCoveredEnd":{"typeName":"timePeriodCoveredEnd","multiple":false,"typeClass":"primitive","value":"2022"}}]},{"typeName":"kindOfData","multiple":true,"typeClass":"primitive","value":["Microdata"]},{"typeName":"series","multiple":true,"typeClass":"compound","value":[{"seriesName":{"typeName":"seriesName","multiple":false,"typeClass":"primitive","value":"Household budget survey by ISTAT"},"seriesInformation":{"typeName":"seriesInformation","multiple":false,"typeClass":"primitive","value":"See more information here (in Italian): https://www.istat.it/informazioni-sulla-rilevazione/spese/"}}]},{"typeName":"software","multiple":true,"typeClass":"compound","value":[{"softwareName":{"typeName":"softwareName","multiple":false,"typeClass":"primitive","value":"STATA"},"softwareVersion":{"typeName":"softwareVersion","multiple":false,"typeClass":"primitive","value":"18"}}]},{"typeName":"relatedDatasets","multiple":true,"typeClass":"primitive","value":["The microdata can be requested via the ISTAT website. For more information visit: https://www.istat.it/informazioni-sulla-rilevazione/spese/"]},{"typeName":"accessToSources","multiple":false,"typeClass":"primitive","value":"The underlying microdata are not included in this package, as access is restricted to authorised researchers via ISTAT. Information on how to apply for access is available at https://www.istat.it/informazioni-sulla-rilevazione/spese/"}]},"dansDataVaultMetadata":{"displayName":"Data Vault Metadata","name":"dansDataVaultMetadata","fields":[{"typeName":"dansDataversePid","multiple":false,"typeClass":"primitive","value":"doi:10.34894/2LO2RE"},{"typeName":"dansDataversePidVersion","multiple":false,"typeClass":"primitive","value":"1.0"},{"typeName":"dansBagId","multiple":false,"typeClass":"primitive","value":"urn:uuid:906b20b3-4bf6-40a5-84aa-4e9705a0586a"},{"typeName":"dansNbn","multiple":false,"typeClass":"primitive","value":"urn:nbn:nl:ui:13-24dd237e-412b-4cea-b7b6-62ecf3cdc910"}]}},"files":[{"description":"Prepares the sociodemographic and socioeconomic covariates used across all models, including household size, age group, sex, marital status, employment status, self-production, education, equivalised expenditure decile, macro-region, municipality size, absolute poverty status, and car 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