Modeling of farmer exchange rate in aceh province using longitudinal data analysis

Farmer's Exchange Rate (FER) is one indicator to see the level of farmers' welfare. From 2014 to 2020, Aceh Province's FER was below 100 which indicates that farmers have not yet reached the level of welfare. This happens because of various factors including the price received by farmers (IR) is smaller than the price paid by farmers (IP). To find out the factors that influence the FER, it is necessary to do an analysis by forming a model. In this study, modeling of the FER data will be carried out, and see the factors that influence the index number with the longitudinal data regression approach. There are three estimation models, i.e. Common Effect Model, Fixed Effect Model, and Random Effect Model. Model selection of the best model is by using the Chow, Hausman, and Lagrange Multiplier tests. Furthermore, test the significance of the parameters using the simultaneous and partial tests and also see the value of the coefficient of determination (R2). The results obtained indicate that the appropriate model for the IR and IP data is the Random Effect Model where the R2for the IR and IP models are 67.06% and 85.42 respectively.