Paper Title
An Analysis of Rubber Yields in Thailand Using Generalized Estimating Equations Models
Abstract
The objectives of this research are to estimate the rubber yield in each month of 63 provinces growing rubber trees
in Thailand, to investigate factors influencing on the rubber yields, and to construct the maps of rubber yields. The
generalized estimating equation model (GEE) is used. The estimated rubber yields are used to construct the rubber yield
maps. The dependent variables are the rubber yield in each month of the provinces. The data are secondary data at a
provincial level. The factors considered are rainfall, averaged temperatures, seasons, and regions. The results show that the
factors influencing on the rubber yields are, averaged temperature, regions, and seasons. The amount of regional effect on
the rubber yields, ranking from largest to smallest values, are southern region, eastern region, northeastern region, and
central region, respectively, where western region and northern region have no regional effect. The amount of seasonal
effect on the rubber yields, ranking from largest to smallest values, are Aug-Oct, May-July, Nov-Jan, and Feb-Apr. The top
ten provinces with high rubber yields, ranking from largest to smallest values, are Surat Thani in August) (16,597.34 ton),
Yala in September ( 16,572.57 ton), Phatthalung in August (16,553.09 ton), Songkhla in August (16,537.12 ton) ,Chumphon
in September (16,477.23 ton), Yala in August (16,458.35 ton) , Phatthalung in September (16,418.09 ton), Pattani in
August (16,400.21 ton) , Pattani in September (16,382.76 ton) , Nakhon Si Thammarat in August (16,364.22 ton) ,
respectively. The rubber yields maps are easy for readers to identify which areas have high or low yields. They are a useful
tool for planning rubber production.
Keywords- Generalized Estimating Equations (GEE), Rubber Yield, Rubber Yield Mapping.