A project evaluation on the comprehensive agrarian reform program implementation using a logarithmic multivariate regression analysis
Date
2021-01-20
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Abstract
Land and agrarian reform are done to remove hindrances to economic and social
progress based on land ownership and tenure (Cox et. al., 2003). According to Department of Agrarian Reform (DAR) data as of June 2020, 32 years since land reform started, 90.49% of the land has been distributed to its scope of around 5.4 million hectares. A multitude of
factors come into play when looking at the totality of land reform. Our Logarithmic
Multivariate Regression model looks into levels of inequality, production, and judicial cases
and their relationship towards the completion of the Comprehensive Agrarian Reform
Program (CARP). The study used a 21-year long dataset from 1997-2018, which includes the
Gini Coefficient, total Agrarian Law Implementation (ALI) Caseload Cases per year, and
total production of all crops. Our model shows significant relationships among all the
variables, and the model explains 98.81% of the variation as seen in the adjusted R2
. It is
observed that there is a negative relationship between the Gini Coefficient of the country and
the CARP completion rate, while Production and the caseload of ALI cases show a positive
relationship. Unsurprisingly, inequality has the greatest magnitude over the other
determinants. Given these results, policies for the further completion of land reform can
tackle the efficiency and funding of our courts, and the creation of social services to alleviate
the gap can finally end the 32-year wait of our farmer-folk for land.