The Philippines is one of the countries in Southeast Asia considered vulnerable to the impact of climate change. Variability in the amount and intensity of precipitation and increasing temperature are some observed shifts in meteorological parameters in the Philippines. Rice is a staple food and a significant contributor to the Philippine economy; however, it is highly susceptible to climate variability. This study used a bin-based framework with daily climate data, which allows the estimation of weather effects even without high-frequency rice harvest data. In addition, a panel data regression with feasible generalized least squares estimation was employed to investigate the impact of climate variables, specifically daily precipitation, temperature, and wind speed, on rice harvest. Results indicate a nonlinear relationship between average daily climate variables and rice harvest. It also shows an increase in the number of days with high temperatures and heavy rainfall compared to the past decade. An additional day with an average wind speed of at least 10 m/s reduces the quarterly volume of rice harvest by 8.85%. Moreover, an additional day with an average rainfall level of at least 54 mm and an average maximum temperature of at least 34 °C reduces the quarterly volume of the rice harvest by as much as 4.13% and 0.581%, respectively.
Rowena A. Dorado (Sun,) studied this question.