Data Science, Statistics and Agricultural Development: Evidence from Agricultural Data metrics and Budgetary Appropriation for Rural Development in Ni
64th ISI World Statistics Congress - Ottawa, Canada
Format: CPS Abstract
Session: CPS 58 - Data science
Tuesday 18 July 4 p.m. - 5:25 p.m. (Canada/Eastern)
Science are data driven, turning numbers into insight and translating data into information for application. Given a problem, what available data will help us answer it? Given a data set, what interesting problems can we apply it to? Statistics is: the fun of finding patterns in data; the pleasure of making discoveries; the import of deep philosophical questions; the power to shed light on important decisions, and the ability to guide decisions. This is the rationale in which this study was constructed. Public spending in the agricultural sector is seen as an engine for growth, because majority of Nigerian derived livelihood from agriculture and reside in rural areas. Therefore, developing an effectual agricultural policy in developing countries must be highly significant and efficient government mechanisms must be put in place to propel agricultural growth. The study embarks on a sustainability experiment to assess public expenditure in agriculture between 2001-2020. The institution and agencies responsible for Budgetary Appropriation for Rural Development in Nigeria were examined. Using public expenditure data between 1981-2020 and a cross-sectional data to test this hypothesis. Yearly budget data and composition spending were collected from public-expenditures on agricultural and related non-agricultural enterprises. Primary data of personnel involved (120 respondents) in public budget processing and implementation were collected and analyzed by Descriptive statistics and Multiple regression analysis using three-state least square as estimation technique. Results revealed that from 2001-2020, the share of statutory annual state budget (public spending) allocation to agricultural development was 3.53% across the states. Average agriculture contribution to GDP was 29.14%. Moreover, the total funding (shares) to the agricultural sector was 36.83%. Results indicated that public expenditures to agricultural sectors have been low under the year in review and cannot motivate serious development. Regression results revealed that public spending on agriculture in recent years has had a substantial positive influence on agricultural development as the marginal effect is assessed at 0.021. Thus, 1% increase in agricultural public expenditure is related with a 0.02 percent increase in the value of agricultural production per capita. Low return on investment was influenced by low execution rates which decreases actual expenditure on agriculture. Primary data analysis results indicated that personnel involved in budget processing and execution seldom have requisite education, were not adequately trained nor attended meaningful workshop/training on capacity-building to bring about meaningful results and effective public service delivery. The study adopts data science and statistics to assess public expenditure for agricultural development and where data will help us to address these gaps for effective application and development.