This paper made an empirical analysis of China＇s agricultural growth path and influential factors using the province-level panel data of agricultural inputs and outputs during 1985-2010.The findings indicate that the...This paper made an empirical analysis of China＇s agricultural growth path and influential factors using the province-level panel data of agricultural inputs and outputs during 1985-2010.The findings indicate that the increase in agricultural inputs and TFP contributed 40.6 and 55.2% to the agricultural output growth,respectively;China＇s agriculture had jumped out of the pattern which output growth was mainly driven by increasing input.Of the total inputs,chemical fertilizer had the most important contribution to the output growth,followed by mechanical inputs.The contribution of land and labor was negative.China＇s agricultural output growth belonged to the type of induced technology innovation.China＇s agricultural TFP growth had characteristics of fluctuations over time and unbalanced between regions,but the gap between the eastern,the middle,and the western regions has been narrowed.展开更多
This paper estimates a stochastic frontier function using a panel data set that includes 4 961 farmer households for the period of 2005-2009 to decompose the growth of grain production and the total factor productivi...This paper estimates a stochastic frontier function using a panel data set that includes 4 961 farmer households for the period of 2005-2009 to decompose the growth of grain production and the total factor productivity （TFP） growth at the farmer level. The empirical results show that the major contributor to the grain output growth for farmers is input growth and that its average contribution accounts for 60.92% of farmer’s grain production growth in the period of 2006-2009, whereas the average contributions sourced from TFP growth and residuals are only 17.30 and 21.78%, respectively. The growth of intermediate inputs is a top contributor with an average contribution of 44.46%, followed by the planted area （18.16%）, investment in fixed assets （1.05%）, and labor input （-2.75%）, indicating that the contribution from the farmer’s input growth is mainly due to the growth of intermediate inputs and that the decline in labor inputs has become an obstacle for farmers in seeking grain output growth. Among the elements consisting of TFP growth, the contribution of technical progress is the largest （32.04%）, followed by grain subsidies （8.55%）, the average monthly temperature （4.26%）, the average monthly precipitation （-0.88%）, the adjusted scale effect （-5.66%）, and growth in technical efficiency （-21.01%）. In general, the contribution of climate factors and agricultural policy factor are positive and significant.展开更多
The purpose of this paper is to estimate total factor productivity （TFP） growth in China by industry. As well as reviewing some previous studies on TFP growth in China, the authors present their estimation of TFP gr...The purpose of this paper is to estimate total factor productivity （TFP） growth in China by industry. As well as reviewing some previous studies on TFP growth in China, the authors present their estimation of TFP growth in China for two periods, 1987-1992 and 1992-1997. During both periods, output growth was as high as double digits. However, the differences in TFP growth between these two periods were remarkable. In the first period, wide-ranging TFP growth was observed, whereas in the latter period, high TFP growth was concentrated in industries such as ＂transportation equipment＂ and ＂electric machinery＂, which are known for actively introducing foreign capital and technologies. In fact, positive relations were confirmed among TFP growth, export performance, and the introduction of foreign capital. Foreign capital made a large contribution to China＇s exportled growth.展开更多
China is switching from economic growth based on extremely rapid capital accumulation to economic growth based on structural reforms and accelerated total factor productivity growth. Meanwhile, China will also face a ...China is switching from economic growth based on extremely rapid capital accumulation to economic growth based on structural reforms and accelerated total factor productivity growth. Meanwhile, China will also face a serious excess saving problem as capital accumulation slows and, hence, needs to reduce its private saving rate. Based on this analysis, we estimated the economic impact of China＇s growth slowdown and hypothetical economic transformation on Japan, the USA and Germany using the worm input-output database. We compared the following three scenarios for China＇s final demand in 2020 and economic growth from 2015 to 2020： （i） an optimistic scenario （GDP growth rate = 6.2%, investment/GDP = 0.501）; （ii） a slowdown scenario （GDP growth rate = 4%, investment/GDP = 0.501）; and （iii） a structural reform scenario （GDP growth rate = 6.2%, investment/GDP = 0.3）. Our analysis suggests that Japan and Germany would suffer more from structural reforms in China than from a slowdown in growth. Meanwhile, for the USA, the employment decline triggered by structural reforms wouM be much smaller than the employment decline caused by a slowdown in growth.展开更多
基金supported by the Projects of National Survey of CASS (Survey of Grain Production in China)
文摘This paper made an empirical analysis of China＇s agricultural growth path and influential factors using the province-level panel data of agricultural inputs and outputs during 1985-2010.The findings indicate that the increase in agricultural inputs and TFP contributed 40.6 and 55.2% to the agricultural output growth,respectively;China＇s agriculture had jumped out of the pattern which output growth was mainly driven by increasing input.Of the total inputs,chemical fertilizer had the most important contribution to the output growth,followed by mechanical inputs.The contribution of land and labor was negative.China＇s agricultural output growth belonged to the type of induced technology innovation.China＇s agricultural TFP growth had characteristics of fluctuations over time and unbalanced between regions,but the gap between the eastern,the middle,and the western regions has been narrowed.
基金supported by Japan International Research Center for Agricultural Sciences
文摘This paper estimates a stochastic frontier function using a panel data set that includes 4 961 farmer households for the period of 2005-2009 to decompose the growth of grain production and the total factor productivity （TFP） growth at the farmer level. The empirical results show that the major contributor to the grain output growth for farmers is input growth and that its average contribution accounts for 60.92% of farmer’s grain production growth in the period of 2006-2009, whereas the average contributions sourced from TFP growth and residuals are only 17.30 and 21.78%, respectively. The growth of intermediate inputs is a top contributor with an average contribution of 44.46%, followed by the planted area （18.16%）, investment in fixed assets （1.05%）, and labor input （-2.75%）, indicating that the contribution from the farmer’s input growth is mainly due to the growth of intermediate inputs and that the decline in labor inputs has become an obstacle for farmers in seeking grain output growth. Among the elements consisting of TFP growth, the contribution of technical progress is the largest （32.04%）, followed by grain subsidies （8.55%）, the average monthly temperature （4.26%）, the average monthly precipitation （-0.88%）, the adjusted scale effect （-5.66%）, and growth in technical efficiency （-21.01%）. In general, the contribution of climate factors and agricultural policy factor are positive and significant.
文摘The purpose of this paper is to estimate total factor productivity （TFP） growth in China by industry. As well as reviewing some previous studies on TFP growth in China, the authors present their estimation of TFP growth in China for two periods, 1987-1992 and 1992-1997. During both periods, output growth was as high as double digits. However, the differences in TFP growth between these two periods were remarkable. In the first period, wide-ranging TFP growth was observed, whereas in the latter period, high TFP growth was concentrated in industries such as ＂transportation equipment＂ and ＂electric machinery＂, which are known for actively introducing foreign capital and technologies. In fact, positive relations were confirmed among TFP growth, export performance, and the introduction of foreign capital. Foreign capital made a large contribution to China＇s exportled growth.
基金We gratefully acknowledge financial support from the Japan Society for the Promotion of Science （Grant No. 16H06322）, the Social Science Foundation of China （Grant No. 11AJY006） and the Key Project of Chinese Ministry of Education （Grant No. 12JJD790038）.
文摘China is switching from economic growth based on extremely rapid capital accumulation to economic growth based on structural reforms and accelerated total factor productivity growth. Meanwhile, China will also face a serious excess saving problem as capital accumulation slows and, hence, needs to reduce its private saving rate. Based on this analysis, we estimated the economic impact of China＇s growth slowdown and hypothetical economic transformation on Japan, the USA and Germany using the worm input-output database. We compared the following three scenarios for China＇s final demand in 2020 and economic growth from 2015 to 2020： （i） an optimistic scenario （GDP growth rate = 6.2%, investment/GDP = 0.501）; （ii） a slowdown scenario （GDP growth rate = 4%, investment/GDP = 0.501）; and （iii） a structural reform scenario （GDP growth rate = 6.2%, investment/GDP = 0.3）. Our analysis suggests that Japan and Germany would suffer more from structural reforms in China than from a slowdown in growth. Meanwhile, for the USA, the employment decline triggered by structural reforms wouM be much smaller than the employment decline caused by a slowdown in growth.
