【作者】 石慧；

【导师】 王怀明；

【作者基本信息】 南京农业大学 ， 农业经济管理， 2009， 博士

【摘要】 从经济增长的理论来看,农业增长的来源有两个方面,一是资源投入的增加,二是生产率的提高,资源尤其是土地资源的有限性决定了农业生产的可持续性增长不可能依靠投入的无限制增加,而必须依靠生产率的提高,即当投入不能高速增加的时候,农业的长期增长能力来自于生产率的累积和提高。改革开放以来,中国经济取得了举世瞩目的成就,以家庭联产承包责任制为开端的农村改革也给农业的发展带来了春天,以粮食,棉花等为代表的主要农作物产量不断增长,农民收入不断增加,农村的生活水平也有了显著的提高。那么该时期的农业生产及其增长到底是投入的增加所致还是生产率提高所致?这种增长是否是可持续的以及这种增长背后的生产率问题仍不容忽视。在农业总体产出不断增长的同时,地区差异也有所扩大,差异的扩大如果是生产要素投入的差异造成,则相应增加落后地区的农业生产要素的投入就可以解决地区间的差距,如果农业生产的差距主要是生产率的差距带来,意味着不同地区农业可持续增长的能力不同,因这种能力的差距的趋势也将影响到未来农业生产地区差距的趋势。因此不论从促进农业增长的可持续性角度来讲,还是从寻找地区问农业增长差异的来源角度来说,农业生产率问题都是值得关注的。就已有的研究来看,改革开放至80年代早期,制度改革带来的农业TFP的提高解释了的农业产出的快速增长的绝大部分。而制度因素的作用会随时间推移逐渐减弱,在80年代中后期之后的农业增长及地区差异来源的研究中,一些学者认为中国农业增长主要是要素投入带来的,也有人认为是生产率带来的增长和地区差异。本文从这个分歧出发,旨在考察生产率因素是否是农业产出地区差异的主导因素,并以生产率水平为研究对象,对生产率差异的变化趋势做出判断,在判断的基础上考察各省区生产率向上或向下转移的可能性,以及包括空间因素,农村工业化程度,人力资本,对外开放程度,城市化,市场化程度和地区农业科研支出对各地区农业生产率增长的影响和作用。为提高落后地区生产率水平,缩小地区差异提供实证支撑。为此,文章使用1985—2005年较长历史时期,中国28个省区的农业生产数据,综合使用增长核算办法,非参数方法,收敛检验办法和空间统计方法,通过必要地实证分析和经验检验,得出以下几点基本的研究结论：1)农业全要素生产率的地区差异是造成农业产出地区差异的主导因素。首先从地区间农业产出的差异变化趋势,要素投入差异的变化趋势和要素生产率的变化趋势三个方面入手,对改革开放以来的地区差异进行了统计分析,发现地区间农业产出差异不断扩大,同时要素投入的差异变化却不明显,将投入和产出放在一起考察的话,地区间单要素生产率差异(化肥生产率除外)也有逐渐扩大的趋势。从该现象出发提出一个统计推断也是待验证的假说：农业产出的差异来自于要素投入以外的其他因素。然后用计量方法定量分析差异来源。考虑到采用的是21年较长时期的历史数据,相同要素在不同地区和不同时期对产出的回报会有差异,因此使用了超越对数生产函数的办法来确定各地区不同时期的各要素的产出弹性。然后借鉴增长核算的办法,将产出的差异分解为生产要素和生产率两个部分,使用方差分解的办法来考1985到2005年间农业产出差异的主要来源问题。从传统的C-D函数出发,采用了K-R方法将产出差异分解为地区间要素差异的贡献和生产率差异的贡献,又使用E-L方法在上述分解的基础上将产出差异分解为三个部分：要素差异,生产率差异和要素与生产率共同作用的差异。不论采用哪种方法分解,结果都显示出地区间全要素生产率的差异是1985—2005年以来地区间农业产出差异的主要来源,即便考虑到要素与生产率间交叉作用,全要素生产率的差异对地区间产出差异也至少贡献了55%以上。2)样本期间内,28个省级地区的农业全要素生产率没有显示出绝对收敛,也不存在条件收敛和俱乐部收敛,即地区差异没有缩小的迹象。首先在认为全要素生产率是影响省际间农业产出差异主要因素的基础上,采用了一种可以进行双边比较的指数方法,测算了全要素生产率的相对水平,进而为研究地区差异奠定了基础。其次在生产率水平面板数据集的基础上,文章对测算结果进行了简单的统计分析,发现全要素生产率差异的变化趋势与农业产出差异的变化趋势具有一致性,可再次此证明全要素生产率是影响地区间产出差异的重要因素。另外通过简单的统计指标发现,地区间农业全要素生产率的水平差异有不断扩大的趋势,生产率增长的地区差异也有扩大的趋势。再次,为检验地区间农业TFP水平的差异是否有缩小的趋势,考察是否是低水平地区相对于高水平地区获得了更快的增长,文章使用三种收敛检验,得到了如下结论：从1985-2005年,地区之间农业生产率差异不会随着时间的推移而逐渐缩小,反而有显著扩大的趋势。通过绝对β收敛检验也发现落后地区并没有从技术的传播和扩散中获得更大的好处,取得比生产率水平高地区更快的增长率。即便是控制了地区和时间固定效应的话,地区间农业生产率差异也没有显示出条件收敛。最后按照一般的对中国地区划分的方法,从东中西部的角度来考察三大经济地带内部省份间的生产率水平是否出现了缩小的趋势,即进行了俱乐部收敛的检验,发现三个地区内部省份的生产率差异随着时间的推移也在不断扩大,只是扩大的程度有所不同,东部地区作为生产率增长率最高的地区,其内部省份间差异扩大的趋势也是最强的。并且通过在地区内部的绝对β收敛检验,也没发现三个地区内部落后的地区获得较快的增长率。检验结果证明,不仅地区之间差异扩大,三大地带内部各省份间的生产率水平也没有缩小的趋势。3)从空间上寻找俱乐部收敛的证据,结果发现存在不同的生产率水平的俱乐部,但是每个俱乐部内部地区差异没有缩小的趋势,即不存在俱乐部收敛。其次通过比较普通空间马尔科夫链和空间马尔科夫链结果,发现中高和高水平的邻居可以提高一个地区生产率提高的可能性,并且两种马尔可夫链矩阵的元素存在差异,表明邻居的生产率水平对某地区生产率有影响,即地区生产率水平存在空间依赖性。两种链条矩阵相同位置的元素是不相等的,即便是对角线上的元素也有比较大的差异,这说明各地区其所处的不同区域背景即邻居的生产率水平,对自身农业生产率水平向上或向下变化产生了一定的影响,各地区生产率水平的变化不是独立的,而是与周围邻居有密切的关系。4)采用空间统计和计量的办法考察了影响地区农业生产率收敛与否的因素。首先空间统计分析的结果显示,样本期间内各省区间的农业全要素生产率水平存在局部空间相关性,因而在研究影响因素时,需要控制空间因素。然后,在收敛的空间计量模型中逐一引入农村工业化程度,地区人力资本,开放程度,城市化率,市场化程度和农业科研投入六个可能影响地区生产率的因素,结果发现农村工业化程度对生产率的提高具有显著的正向作用,人力资本的作用在不同的样本时期有差别,本文认为可能与劳动力的流动有关。城市化可以显著地促进地区生产率的提高,对外开放和市场化指数的作用不明显。此外可能是由于地区农业科研支出指标的选择的问题,使得代表地区对农业创新重视程度的变量回归结果不显著,同时也降低了整个模型的解释力。更多还原

【Abstract】 The source of agricultural growth has two aspects from the theory of economic growth, first is the increase in investment of resources, and second is the productivity improvement. The limited resources, especially the land decides the sustainability of agricultural growth can not depend on the unlimited increase of input, but the increase in productivity. That is, without the input increases quickly, the capacity of long-term agriculture growth needs to rely on the accumulation and improvement of productivity. China’s economy has made remarkable achievements since reform and opening up, rural reform, which starts with the household contract responsibility system, also induces the development of agriculture, the main agricultural output continues to increase, such as crop, cotton, and so on, the income of farmers keeps increasing, living standards in rural areas also have been significantly improved. Whether this growth of agriculture production is due to its inputs increase or the productivity improvement? Whether this growth is sustainable and the productivity behind this growth can not be ignored. Regional difference has expanded with the overall agricultural output growing at the same time. If the differences is caused by the former, then the gap among regions can be resolved by a corresponding increase of agricultural production factors in the backward areas, but if the gap of agricultural production is mainly the productivity gap, which means the different ability of sustainable agricultural growth in different regions, then the trend of this capacity will also affect the future trend of regional disparity of agricultural production. Therefore, the agricultural productivity is a question worthy of our attention no matter from the promotion of the sustainability of agricultural growth perspective or from the sources of inter-regional differences in agricultural growth. Regarding the existing literature, the improvement of agricultural TFP which is brought by the reform of the institutions brought can explain most of the rapid growth of agricultural output from the reform and opening up to the early 80s. And the effect of institutional factors will gradually decrease over time, among the researches about the agricultural growth and regional differences after the mid-and late 80’s, some scholars argued it was brought by the inputs of main factors, others believed it was caused by growth and regional differences of productivity. This paper starts from such a argument, designed to study whether the productivity dominates the regional differences of agricultural output and focus on the productivity level, study the trend of productivity differences, find the possibility of up or down trend of productivity of each province, as well as the impacts and effects of factors, such as space spillover, rural industrialization, human capital, the degree of opening, urbanization, market construction and regional R&D expenditures on agriculture, on agricultural productivity growth. This research will provide empirical evidence for improving productivity level of underdeveloped areas and reducing the regional differences.We use a long period panel data from 1985 to 2005 with Chinese 28 provinces and autonomous regions, agricultural production data, adopted growth accounting approach, non-parametric methods, the convergence test and spatial statistical methods, we get the following basic conclusions:1) The agricultural total factor productivity is the dominant factor of the regional differences agricultural output. First, we analyze the difference changes of the agricultural output of regions, the differences changes in factor inputs and total factor productivity since the reform and opening, find that regional differences in agricultural output expanding with the differences in factor inputs does not change obviously at the same time. The single-factor productivity, except for fertilizer productivity, is also gradually expanding when we combine the inputs and outputs together. Then we propose a hypothesis of statistical inference which is to be tested:difference in agricultural output comes from other factors besides the factor inputs.Then we try to figure out the source of this difference with quantitative analysis methods. The return of same factor varies in different regions and different periods when taking into account the 21 years are used in this long period of historical data, therefore we use the translog production function approach to calculate the output elasticity of the various regions in different periods. We decompose differences in output into the difference of productivity and factors based on the growth accounting approach, and use the Analysis of Variance (ANOVA) to the exam the major source of agricultural output difference within the period 1985-2005. From the traditional C-D function, we not only use the K-R method to decompose differences in output into input differences and the differences of productivity, but also the E-L method to decompose the difference of output into three parts:the input difference, difference of total factor productivity and interaction difference of factors and the productivity, based on the decomposition above. No matter which decomposition method is used, the results show that inter-regional difference in total factor productivity is the dominant source of the differences in agricultural output from 1985 to 2005; the total factor productivity difference at least contributes 55% of the differences of output even taking into account the interaction of factors and total factor productivity.2) The agricultural total factor productivity of all the 28 provinces shows no absolute convergence, nor conditional convergence and club convergence within the sample period, that is, there is no sign of regional disparities narrowing. Firstly, we conclude that the total factor productivity is the main source of the difference of provincial agricultural output, then we adopt a bilateral comparison method to calculate the level of the total factor productivity, which built the foundation for further research about the regional difference. Secondly, this paper uses a simple statistical analysis based on the panel data set of productivity levels; found that there is a consistence of the change in trends of differences in total factor productivity and the trends of differences in agricultural output, which can prove that total factor productivity is important to the differences in output. We also found that the growing trend of the difference of agricultural total factor productivity level and the differences in productivity growth through a simple statistical indicators.Finally, we use three types of convergence test in order to test whether there are narrowing trends of the level of differences in agricultural TFP, exam whether the regions who’s TFP are grow faster than the higher areas. We get the following conclusion:the differences of the agricultural productivity will not be narrowing gradually over time but expanding from 1985 to 2005. The backward areas did not derive greater benefits through the technology spillover or achieve faster growth rate using the absoluteβconvergence test. The differences of agricultural productivity did not show the conditional convergence even we control the region and time fixed effects. Finally in accordance with the general district of China, we use the club convergence test which exams whether there is a narrowing trend of productivity level within the eastern, central and western three major economic zones, found that the internal productivity differences among province within the three regions has been expanded with the time, but the extent of expansion is different, the eastern region is the region with the highest productivity growth rates with the strongest trend of expansion of the internal differences among provinces. And through the absolute P convergence test, we did not find backward areas get faster growth within the three regions. The results of test prove that not only the difference among the three regions keeps expanding, but also there is no narrowing trend of the productivity level among the various provinces within the three regions.3) We try to find the spatial evidence of the club convergence, found that different province with different productivity level converge to different clubs, but internal disparities within each club have not narrowed, that is, there is no club convergence. Then by comparing the general spatial Markov chain and spatial Markov chain, we found that middle-high and high-level neighbors of a region can enhance the possibility of productivity increase. And the elements of these two Markov matrixes are different, which means the productivity of a province is affected by the neighbor’s productivity levels, there is spatial dependence of productivity levels among regions. The elements with the same location in two chain matrixes are not equal, even the diagonal elements also have relatively large differences, indicating the productivity level of the region to which each province belongs has impacts on the upward or down change of its level of agricultural productivity, the changes of the level of regional productivity in each region is not independent, but a close relationship with the surrounding neighbors.4) We use spatial statistical and spatial econometric methods to find the causes of the convergence of agricultural productivity. Firstly, the spatial statistical analysis shows that there is local spatial correlation of agricultural total factor productivity level during the period range of the sample, thus we need to control the spatial factor during the study of the influencing factors.Then we introduce the six factors that may affect the productivity into the spatial econometric model one by one, the rural industrialization, human capital, openness, urbanization, market construction and agricultural R&D input, found that the rural industrialization improved the productivity significantly, the role of human capital is different in different sample period which may be relevant to the labor mobility. Urbanization promoted the productivity significantly, the opening and market construction are not significant. The variable which represents the agricultural R&D expenditure is not significant may be due to the index selection problem, and also reduces the explanatory capability of the model.更多还原