Data Modeling
Mathematical and Computational Data Modeling | Online ISSN 3143-9217
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Volume 2 Number 1 2021
RESEARCH ARTICLE (Open Access)
Exploratory Analysis of Government Employee Financial Data in Bangladesh: A Case Study for Evidence-Based Budget Forecasting
Sabya Sachee Das 1*
Data Modeling 2 (1) 1-8 https://doi.org/10.25163/data.2110894
Submitted: 15 April 2021 Revised: 02 June 2021 Accepted: 10 June 2021 Published: 12 June 2021
Abstract
Background: Public-sector wage and benefit spending is one of the largest recurring items in Bangladesh's national budget, yet allocation for pay, allowances, provident-fund nominees, and staff loans is often planned without systematic reference to the demographic composition of the workforce that draws on it. Methods: This case study applies exploratory data analysis (EDA) to administrative records for 200 employees of a single Bangladeshi government office, examining associations between age and four variables: pay grade, General Provident Fund (GPF) nominee type, loan category, and religious affiliation. Histograms, scatter plots, and a correlation heat map were used to summarise distributions and relationships. Results: Loan uptake and nominee choice varied by age band and by grade, with spouse most commonly recorded as nominee and house-building loans concentrated among mid-career employees. The office's religious composition was overwhelmingly Muslim (98%), with a small Hindu minority (2%), a pattern relevant chiefly to festival-allowance planning at this site. Conclusion: Even a modest, office-level EDA can surface patterns useful for local budget planning, though the small, single-site, non-random sample limits generalisation to the national civil service. We argue that scaling this approach across ministries, with proper sampling and inferential modelling, could meaningfully improve forecasting of pay-related expenditure.
Keywords: exploratory data analysis; public expenditure management; Bangladesh civil service; provident fund; budget forecasting
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