The Analysis of the Farmland Productivity and its Influencing Factors in Shandong
This paper measures the Arable Land use efficiency of Shandong Province during 1999-2008 by utilizing the method of data envelopment analysis (DEA), and ana-lyzes the main factors influencing arable productivity based on the Tobit model. the re-sult indicates that the mean value of comprehensive efficiency of arable land use in Shandong Province over the past decade is 0.883; by dividing the arable land production efficiency into three categories, we can find that the first-class regions have the optimal arable land production efficiency, distribution with wider range, concentration in the cen-tral of Shandong province. the pure technical efficiency of the second category is low, with distribution more dispersing, mainly including Dezhou, Jining Qingdao and Weifang;The third kind in scale is low efficiency, pointing to the east coast of Shandong province, including Binzhou, Dongying, Weihai; Besides, the result shows that the effec-tive irrigation area, cultivated land crop multiple index, the unit power consumption rate of cultivated land and other factors have an impact on arable land production efficiency with different direction and the influence of different intensity, of which, cultivated land multiple crop index of arable land production efficiency with significant impact of the biggest, the unit power consumption rate and effective irrigation area play a significant negative correlation role in arable land production efficiency, while the combined propor-tion of secondary and tertiary industry to the influence of cultivated land production effi-ciency is high but not significant. To promote the arable land production efficiency, we should act according to the actual situation of the region, not only pay attention to the reasonable resources input scale during production, but also improve the external environ-ment of arable land production.
arable land production efficiencydata envelopment analysisTobit modelShandong Province
NETL
NSTL
万方数据
维普
