Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/29190
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMahnoor Anjum-
dc.date.accessioned2024-07-05T03:47:14Z-
dc.date.available2024-07-05T03:47:14Z-
dc.date.issued2023-
dc.identifier.urihttp://hdl.handle.net/123456789/29190-
dc.description.abstractResearchers in recent days are found studying digital economy putting special emphasize on its different dimensions. From this renewed attention, this study undertakes a research agenda to investigate the impact of digital economy on female employment in Pakistan based on time series data from 1990 to 2021. The digital economy is measured by five different variables i.e., subscriptions for fixed telephones, subscriptions for fixed broadband, subscriptions for mobile phones, secure internet servers, and individuals using the internet. To obtain empirical outcomes, this study uses the ARDL. The empirical evidence shows that there is a positive association between female employment and digital economy in both short and long run. It also finds that digital economy and control variables explain 91% of the variability in female employment. Similarly, few control variables (education, fertility rate and GDP) used in the study have also resulted in positive relations with female employment. ECM reports the speed of adjustment of 74 percent from disequilibrium to equilibrium. The principal implication of our findings directs that Pakistan can empower females by upgrading its digital infrastructure and presence. The study suggests that Pakistan needs to ensure enough funds available for supporting digital innovation in public services and improving access to the internet by regulating prices which will engage female counterparts to get benefitted from the digital divide.en_US
dc.language.isoenen_US
dc.publisherQuaid I Azam University Islamabaden_US
dc.subjectEconomicsen_US
dc.titleDoes Digital Economy Improve Female Employment in Pakistan? An Empirical Investigation using Autoregressive Distributed Lag Modelen_US
dc.typeThesisen_US
Appears in Collections:M.Phil

Files in This Item:
File Description SizeFormat 
ECO 1179.pdfECO 1179844.19 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.