Analyzing crop production statistics of the Philippines using the newcomb-benford law

Abstract

The agricultural sector plays a crucial role in the Philippines, contributing significantly to its food security and economic growth. However, the sector faces various challenges that hinder its productivity and growth. To address these challenges and promote sustainable agricultural practices, accurate and reliable crop production statistics are essential for informed decision-making and resource allocation. The Newcomb-Benford Law (NBL) provides a statistical distribution pattern for leading digits in numerical datasets, offering insights into data reliability. In this research study, we applied the NBL to analyze crop production statistics for major crops (rice, corn, coconut, sugarcane, banana, cassava, and pineapple) in the Philippines. We assessed the conformity of the datasets to NBL expectations and identified significant deviations, indicating potential data accuracy issues, collection method discrepancies, or reporting irregularities. Although these deviations do not conclusively suggest fraud, they underscore the need for meticulous data validation. The first two-digit test further strengthened the findings, providing a comprehensive understanding of dataset conformity. Transparent data collection and validation processes are crucial for trustworthy agricultural statistics, supporting effective policy-making and resource allocation. Future research should investigate the root causes of the deviations, explore data processing errors, and implement stringent data validation procedures. Additionally, expanding the analysis to include other crops and conducting comparative studies between regions and time periods would enhance data integrity and contribute to sustainable agricultural practices and food security in the Philippines.