Climate change has been a major concern in recent years. It would affect all nations
and sectors of society. The purpose of this thesis is to study the potential effects
of climate change on agricultural productivity in China. If China had a shortage of
food, there would be worldwide effect. The five essential crops, rice, wheat, maize,
soybean and potato were individually regressed against twelve explanatory variables.
The coefficient of each independent variable is in fact the elasticity of a crop output
with respect to the corresponding input variable. Effective land, mechanization, fertilization,
irrigation, labor force, mean temperature and total precipitation were found
to be positively significant at least at 5% confidence level. Among all the independent
variables, the effective land has the highest elasticity for rice, maize and potato,
whereas for wheat is irrigation and for soybean is fertilization.
A robust and flexible tool was developed for data extraction which enable users to
extract data for other countries to be studied. The data extraction tool was written
entirely in C++, with the use of stream manipulations. It was designed in such that
subsequent extension of the tool would be straightforward. Macros and visual basics
were also written for data organization.