The purpose of this study is to attempt to contribute to the knowledge of the influence of price on the supply of agricultural production in Thailand. Seventy-two provinces in the country have been grouped into nineteen agroeconomic zones. Each zone is considered to be homogeneous in terms of climatic, agronomic conditions, and agricultural activities. The statistical analysis in this study is primarily at the zone level of aggregation. However, a national aggregate model is also estimated. The period under study is from 1969 through 1977 and the crops included are rice, corn, cassava, sugarcane, and kenaf.;The Nerlovian supply function, where the planted area of crop under study is a function of expected price and a time trend, is used. Three models regarding the formulation of expected price are tested and compared. The first model is the naive model where the expected price of the current year is equal to last year's price. The second model is the intermediate model where the expected price for this year is equal to a weighted average of price lagged one and two years. Finally, the third model is the adaptive expectation model which assumes that the expected price of this year is equal to last year's expected price plus some portion of the error made last year in forming the price expectation. For each model, at least two equations are estimated, using two different price variables, the absolute and the price deflated by the wholesale price index of agricultural products. For some crops in some zones, the price ratio of the crop under study to the single selected crop is also used in the three models.;In general, it is found that the Thai farmers are very price responsive except for rice producers. The price responsiveness of rice is very low as compared to other crops. Comparing the three models, the adaptive expectation model does not show uniformly better results than the naive model. The intermediate model does not fit the data well, except for sugarcane crop. Comparing the absolute price and the deflated price equations, in most cases, the deflated price equation tends to give a higher elasticity than the undeflated price equation. However, the deflated price equation tends to reduce the explanatory power of the model.