A Problem on the Feasibility of Rural Digital Economy
| dc.contributor.author | Pramanik, Chanchal | |
| dc.contributor.chair | Pingali, Prabhu | |
| dc.contributor.committeeMember | Basu, Arnab K. | |
| dc.date.accessioned | 2021-03-12T17:44:24Z | |
| dc.date.available | 2021-03-12T17:44:24Z | |
| dc.date.issued | 2020-08 | |
| dc.description | 171 pages | |
| dc.description.abstract | The rural digital economy is progressing in developing countries with the advent of widespread mobile phone networks and the affordability of mobile technologies. This paper analyzes around 1 million farmers' queries recorded at farmers' call center [Kisan Call Center (KCC), governed by the government of India] for four selected states of India for the years 2012 and 2018. The database of KCC is prepared by text analysis of farmers' queries and integrated with other databases accessed through government sources. The other data sets include; agricultural yield, night light luminosity, and meteorological data, mobile subscription database, and foretasted data on population based on the observed trend on three recent censuses. A methodological framework is developed by analyzing the integrated database to evaluate the key parameters that are influencing the growth of farmers' queries at KCC and agricultural yield. The identified parameters for each state are then modeled based on the growth of population parameters by solving sets of partial differential equations. The developed models estimate the growth of queries at the district level based on the base year 2018 from 2019 to 2024. The districts are ranked based on the predicted growth of queries, combined ranks of the districts based on growth parameters, and growth of queries in two years and growth of major crop yields for 2012 and 2018. The robustness checks have evaluated identification of the parameters and selection of the districts based on major crop yields for the selected years and average crop yields and compound annual growth rate (CAGR) of crop yields for the periods 2013-2018 and 2007-2012. The study has selected four states; Punjab, Haryana, Bihar, and Odisha. The identified digitally progressive districts and regions for agri-business for Punjab are Mansa and Bathinda located in the southern region. In the case of Haryana, the identified districts are Sirsa and Mahendragarh located in the western part of the state. Samastipur and Begusarai districts are predicted to be in a progressive cluster in the south-central region of the state of Bihar. Odisha's cluster of districts is towards the western part and the identified districts are Subarnapur and Kalahandi. The paper has placed an argument to consider the incidence of farmers' queries as a proxy for agricultural yield. | |
| dc.identifier.doi | https://doi.org/10.7298/t05b-zc95 | |
| dc.identifier.other | Pramanik_cornell_0058O_11002 | |
| dc.identifier.other | http://dissertations.umi.com/cornell:11002 | |
| dc.identifier.uri | https://hdl.handle.net/1813/103161 | |
| dc.language.iso | en | |
| dc.rights | Attribution 4.0 International | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | agricultural Productivity | |
| dc.subject | application of information and communication technologies in agriculture | |
| dc.subject | mathematical modeling | |
| dc.subject | parameter selection by statistical analysis | |
| dc.subject | parameters of the growth of population | |
| dc.subject | rural digital economy | |
| dc.title | A Problem on the Feasibility of Rural Digital Economy | |
| dc.type | dissertation or thesis | |
| dcterms.license | https://hdl.handle.net/1813/59810 | |
| thesis.degree.discipline | Applied Economics and Management | |
| thesis.degree.grantor | Cornell University | |
| thesis.degree.level | Master of Science | |
| thesis.degree.name | M.S., Applied Economics and Management |
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