Measuring and Decomposing of China's Agricultural Productivity and Environmental Efficiency
China's agricultural productivity has achieved remarkable accomplishments in agricultural sector after China's accession to World Trade Organization (WTO). According to National Bureau of Statistics of China (NBSC), the total meat production in 2018 is 43% more than in 2000, and the total cereal production in 2018 is 51% more than in 2000. However, the rapid development of agriculture is associated with environmental pollution. Since China's rice output has quadrupled compared to the level in 1949, the rice production growth has serious repercussions on environment, which results in severe chemical fertilizer pollution. The amount of nitrogen fertilizer applied (209 kg ha-1) during rice production in China is 90% higher than global average level (Chen et al., 2014), and the N taken by rice is only 30-35% (Peng et al., 2009; Xu et al., 2012). In general, this research focuses on two empirical issues: one is the trade effects on China's agricultural productivity, the other is measuring environmental efficiency and finding solutions for N pollution problem. First, we try to investigate the trade impacts on China's agricultural productivity change and answer following questions. How productivity changes after China's entry to WTO? Is there a substantial productivity growth behind yield growth? What's the main factor behind TFP change? Second, we focus on evaluating environmental performance within the framework of productivity analysis and tackling N pollution issue. We try to measure China's environmental efficiency and nitrogen use efficiency in particular to examine whether NUE is low, what factors lead to current NUE and what are the possible ways to abate N pollution. To measure China's productivity change before and after China's entry to WTO and analyze trade impacts on agriculture, the Stochastic Frontier Analysis (SFA) method is adopted. For the measurement of environmental efficiency, both Data Envelopment Analysis (DEA) and SFA are applied to estimate environmental productivity. Furthermore, based on empirical researches, both agricultural and environmental TFP are decomposed into explicit components to explore the decisive factors accounted for productivity change. In Chapter 2, we measure total factor productivity change in China's agricultural sector before and after China's entry to WTO, and obtain following conclusions. First, land, labor, intermediate input and capital could all lead to output growth. Second, China's productivity increases during the whole research period, and TFP growth rate rises slightly after China's entry to WTO. Third, the main contributors to TFP growth are not the same for the two sub-samples. Before China's accession to WTO, productivity growth majorly owes to allocative effect of pork and other meat and the considerable technical progress, while allocative effect of crop and land and technical progress are contributing factors after China's accession to WTO. Fourth, the development of technology achieves steady and substantial progress during the research period. Fifth, export has significant positive effect on technical efficiency before China's entry to WTO, while import presents negative effect on technical efficiency after China's entry to WTO. In Chapter 3, we measure and decompose China's environmental productivity when production technology exhibits VRS. Based on the empirical research on rice production, we obtain following findings. First, the annual INE scores experience a mild fluctuation in 2004-2010, and the average INE indicates there is large potential to reduce current N input by 39%. Second, rice farmers in Hubei Province are already located at the most productive scale size. Third, RDTFP presents an annual decreasing rate owing to technical regress. Fourth, due to time lags and overestimation of inefficiency, the changing direction of TEC and TC are different. Fifth, rice farmers could decrease 19% of the nitrogen emissions based on the technical-efficient point on the CRS frontier. Sixth, NASEC is found to be more strongly correlated with NTFPC. Seventh, the changing direction of NTFP is consistent with RDTFP. In Chapter 4, we measure current TFP in rice production using SFA and analyze factors behind environmental productivity variation. After our empirical research on rice production, the main findings are as follows. First, increases in fertilizer N contents, land N contents, rice output, labor and intermediate input could all lead to N growth. Second, compared with fertilizer N contents, land N contents variation could lead to a larger rise in total N. Third, due to the complementary relationship between fertilizer and quasi-fixed input, increases in labor and intermediate input can also lead to total N growth indirectly through fertilizer increase. Fourth, technical efficiency in rice production remains stable during 2004-2010. Fifth, TFP is decreasing at an average annual rate of 2%, which is attributed to the negative impacts of the allocative effect of fertilizer nutrient, the effect of capital and technical regress. Sixth, the negative allocative effect of fertilizer N contents indicates that farmers use more fertilizer than they need. Seventh, due to the improvement of industrialization and low NUE, total N slightly increases at a rate of 1.6% every year. The empirical findings provide several policy implications. First, encouraging technological innovation and developing an efficient fertilizer application approach may be a prior choice for promoting agricultural development and soil conservation in the future. Second, to become crop production allocative-efficient, government could cut subsidies and national support concerning crop production. Third, enacting more proposals and regulations on perfecting the land circulation market and protecting arable land from using for commercial purpose could help reduce land allocative inefficiency. Fourth, government's intervention and punishment on overuse of N fertilizer is necessary, due to the great potential of reducing N pollution by using less N. Fifth, after satisfying the current minimum amount of N input to become technical-efficient and scale-efficient, policy makers could guide farmers to reallocate their input combination to become environmental-efficient, since it is an effective way to prevent N pollution. Sixth, using less fertilizer, integrating small fragmented land and using land efficiently are beneficial to eliminating nutrient allocative inefficiency and improving TFP. Seventh, developing sustainable agriculture instead of high energy consumption, high waste and low efficiency agriculture could help to prevent N pollution growing over the years. ; 2021-06-07
