Stochastic production function and estimating risk in rice production
Date
10-1980
Abstract
Risk is primarily defined as variability of outcome in conjunction with expected outcome. In broader sense, risk estimation covers, in the case of rice production, the estimation of the probability distribution of rice yield. The major intent of this study is to investigate the sensitivity of risk measurement to functional form of and estimation technique for the production function. Specifically, the effect of nitrogen input on the probability distribution of rice yield outcome at nine agronomic zonal levels stratified according to season and water stress conditions is measured.
Stochastic production functions incorporating manageable inputs and environmental factors are estimated for 1972-1977 rice data from farmers' fields in Central Luzon, Philippines. Five basic models with different sets of linear and interaction stress variables are used. The multiple regression model with normally distributed zero mean constant variance errors is assumed to approximate the production process. Initial coefficient estimates are obtained by ordinary least squares.For a sweep among empirical models indexed by transformation of the response variables, Box-Cox regression is performed. With the obtained response functions as input information, rice yield distributions at fixed levels of nitrogen and given solar radiation and water stress conditions are simulated. As descriptors of risk effects of nitrogen, the means, variances and skewness of simulated yield distributions are analyzed. It is observed that the risk effect of nitrogen is highly conditioned by solar radiation and water stress. Results indicate that the method of risk measurement used is not sensitive to the production function estimation technique. Therefore, the superiority of the simple and computationally economical least squares estimation for the standard multiple regression model is asserted. Differences in inferences on risk effects between models indicate that model formulation poses a greater problem.
Document Type
Master Thesis
Degree
Master of Science in Statistics
College
Graduate School (GS)
Adviser/Committee Chair
Ann Inez N. Gironella
Co-adviser
Isidoro P. David
Committee Member
Manuel L. Bonita
Language
English
Location
UPLB Main Library Special Collections Section (USCS)
Call Number
LG 995 1980 S81 M45
Recommended Citation
Mendoza, Maria Nimfa Francisco, "Stochastic production function and estimating risk in rice production" (1980). Graduate Student's Output. 3051.
https://www.ukdr.uplb.edu.ph/etd-grad/3051
DOI
https://www.ukdr.uplb.edu.ph/cgi/ir_submit.cgi?context=etd-grad&edbypass=1&editpanel=