MODELING THE DYNAMIC OF FOOD PRODUCTION IN THE PHILIPPINES: AN ARDL AND ERROR CORRECTION APPROACH (1936-2022)

Abstract

Abstract

The trends of food production from the 1963-2022 period in the Philippines are thoroughly discussed in this research study using the Food Production Index, the most appropriate indicator for measuring the performance of agriculture. In an effort to examine the trend and pattern of farm production year after year with so much scrutiny, the study employs a time series analysis technique in the ARDL (Autoregressive Distributed Lag) and ECM (Error Correction Model) forms. Both models allow for the short-run volatility of specification in the form of long-run convergence to farm output equilibrium. The ARDL estimates imply that about 45% of the current level of variation in food levels of production is explained by their lags, showing a degree of persistence that is moderate in the system. The ECM results also show a very strong mean-reverting tendency, which means that the sector reacts very strongly whenever it goes off its long-term trend. This is shown by an adjustment of 211%, which is very high. This means that the agriculture industry in the Philippines is very vulnerable to both short-term shocks and long-term imbalances. Also, the model diagnostics make sure that there are no major problems with multicollinearity or autocorrelation. This means that the statistical estimates are reliable, which is in line with the empiricist approach's reliability. The study says that looking at historical production trends and short-term shocks is important for providing essential policy implications for agricultural policy development. Additionally emphasizing the need of basing decisions on evidence to guarantee long-term food stability. Consistent with Sustainable Development Goals (SDGs) 2 (Zero Hunger) and 13 (Climate Action), the findings provide us a solid starting point for developing focused solutions assisting agricultural growth in a sustainable and resilient manner.

Keywords: Food Production Index, ARDL Model, Error Correction Model (ECM), Time Series Analysis, Agricultural Policy