Climate change impact is particularly severe in developing countries like the Philippines mainly because of low incomes, geographic state or condition, dependence on climate-sensitive sectors and inadequate capability to adapt to global warming. This paper aimed at analyzing the risk posed by climate change using climatic variables on Philippine agriculture. Likewise, it focused on the empirical measurement of the hypothesized relationship between agricultural output and the condition or predicted economic variables. This paper employed not only the Cobb-Douglas production function using time series data from 1980 to 2014 but also the modeling techniques - Cointegration and Granger causality to simulate the impact of changes of the aforementioned variables on output of Philippine agriculture. Results show that only three variables indicated considerable significance on agricultural production in the Philippines based on their respective t-ratios: Agricultural Employment (EA), temperature (TEMP), and La Nina (D1). Other things equally, a 1% rise in agricultural employment paves a 0.2% increase in agricultural production. On the other hand, a 1% increase in temperature, cet. par., decreases agricultural production by 0.08%. Correspondingly, the incidence of El Nino, other things equally, deceases agricultural output by 0.02%. The other variables are not statistically significant but are interpreted in the same way. With this, government expenditure should be redirected toward R&D in agriculture to improve resilience, competence and sustainability of the agriculture sector.

Authors:
Jennifer Madonna Dait, Ifugao State University, Philippines

About the Presenter(s)
Professor Jennifer Madonna Dait is a University Assistant Professor/Lecturer at Ifugao State University in Philippines

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