Adoption of modern technology in Philippine agriculture: A limited-dependent variable model approach
Abstract
This dissertation identifies the factors affecting the adoption of modern technology in Philippine rice agriculture using limited-dependent variable models. Probit and Tobit models are estimated to examine the factors affecting the use/non-use as well as the intensity of use of high-yielding seed varieties, chemical fertilizers, chemical pesticides and weedicides, and tractors. The results show that access to physical infrastructure such as irrigation, information, credit, and access to input and output markets tend to promote the adoption of modern technology. For the same underlying model, the probit and Tobit analyses yield conflicting results regarding the significance of various explanatory variables which cannot readily be accounted for by the inefficiency of the probit estimates. A Monte Carlo simulation experiment is undertaken to study the effects of measurement errors on statistical tests of explanatory variables in the model. Simulation results show that the presence of measurement error affects the probit and Tobit coefficients of the explanatory variable but not in a uniform manner. With measurement error in the explanatory variable, the Tobit model has greater power but more adversely affected in terms of size of the test for sample size 100 in comparison to the probit. For sample size 500, the probit performs better than the Tobit in terms of lower size of the test and comparable power to the probit. With measurement error in the dependent variable so that misclassification occurs, the Tobit results are more reliable. When only the positive values of the dependent variable are subject to error, the probit yields better results than the Tobit.
Subject Area
Agricultural economics|Statistics
Recommended Citation
Reyes, Celia Manalaysay, "Adoption of modern technology in Philippine agriculture: A limited-dependent variable model approach" (1991). Dissertations available from ProQuest. AAI9125736.
https://repository.upenn.edu/dissertations/AAI9125736