While it is beyond the scope of this article to explain the relative performance of China’s breeding programs, most likely, it is a combination of historic investment priorities, fortunate breakthroughs and availability of international germplasm. China’s breeding efforts also have enhanced the quality of its seed stock. Using experiment station yields of each major variety during the year that the variety was certified, two measures of quality were developed: a “yield frontier” variable and an “adopted yield potential” variable.The yield frontier, which is created by using the highest yield of any one major variety in the field in each province during a given year, is a measure of the ultimate yield potential of the current technology used by farmers in each province’s research system. The other variable, adopted yield potential, is the average of the experiment station yields of all major varieties that have been adopted by farmers. According to the two measures, China’s research system has created a steady stream of quality technology . The yield frontiers for rice moved up at 2.3 percent per year those for maize at 2.5 percent at year between 1980 and 1995, most likely a function of the development of hybrid cultivars. Although more modest, the yield frontier of wheat also has risen significantly during the reforms . Farmers, however, have not always chosen  the highest yielding varieties. The average adopted yield potential of major varieties in the sample area has risen between 1.0  and 1.4  tons/ha per year during the reforms . When compared to the farmers’ actual yields in 1980 , the differences ranged from 31 to 58 percent, gaps that are not high by the standard of developing countries . In part reflecting the rapid rise in material inputs , the gap fell for all crops, though that for wheat narrowed morethan those for rice and maize . There are two ways to interpret the yield gaps that currently exist in China. On the one hand, there appears to be a great deal of yield potential left in varieties in the field ,grow table and even more when considering the differences between the yield frontier and the actual yield.On the other hand, it can be argued that, in fact, the relatively low level  and narrowing trend of the percentage difference between actual yields and adopted yield potential mean that China’s yield potential is not that large, and the nation will need more breeding breakthroughs if the pace of yield growth is to be maintained on the effort of its domestic research system.

The gap between adopted yield potential and actual yield for rice is small compared to wheat and maize, it is even smaller when compared to other rice countries. In 1987, China’s gap was only 1.0 ton per hectare , similar  gaps ranged from 5 tons per hectare  for the Philippines and 3.5 tons per hectare  for India . Relatively low yield gaps may imply that the further gains in realized total factor productivity of rice in China may be more difficult since most of it must come from increases in the creation and adoption of new varieties. The narrowing gap between the yield frontier  and adopted yield potential  has a number of other implications for China’s future yield growth. It may be that high yielding varieties are not moving out into the field because of some physical, policy, or infrastructure constraint. On the other hand, it could be that farmers are finding other varieties rather than the highest yielding ones, are the most effective in enhancing farm level profits. The large changes in the rice markets  may partially explain the fact that the gap between the yield frontier and adopted yield potential has grown by two to three times that for either wheat or maize.One of most impressive accomplishments of China’s research system is that it has been able to consistently create and deliver to the field varieties demanded by farmers, inducing them to constantly upgrade their seed stock. Our data shows that Chinese farmers adopt new varieties with great regularity .6 For example, maize farmers turn their varieties over the fastest, averaging more than 33 percent per year. Every 3 years farmers on average replace all of the varieties in their fields. In the case of rice, farmers replace all of the varieties in their field every 4 years and wheat farmers adopt varieties at the slowest rate, changing their varieties every 5 years. From conversations with those familiar with grain cultivation in the US, Mexico, and India, as national averages, the turnover rates rival those found in the rice bowls and wheat baskets of the developing and developed world. China’s domestic research system has produced most of the new technology. The rise of the stock of research in the early reform era mostly reflects the commitment of the leadership during the Mao era . In our analysis, however, we only want to include that part of the research stock that is used to produce new varieties. To make the adjustment to our research investment series to make it include only crop research, we note that according to the Ministry of Agriculture Statistics , since at least 1980 , research administrators have consistently invested between 69 and 71 percent of its annual research budget to crop research.

Of this, most of the crop research budget goes for plant breeding and closely related research projects. Therefore, in the creation of our research stock figure, we multiply the total annual research expenditure by the proportion of the budget that is allocated to crop research and apply the procedure used in Pardey et al., to create our measure of crop research stock.7 The resulting series trend up sharply through the 1980s and the early 1990s until the rising trend decelerates in the mid- 1990s, reflecting slowing rates of research investment in the 1980s. Once the new technology has been created, China’s agricultural leaders have extended new varieties to the farmer through the national extension system. In the counties, extension agents work with village officials and farmers to get them to adopt new products. We measure extension effort by the amount of funding dedicated by the government to support such work. Researchers differ in their view about the record of performance of the government in their investment in research and extension in recent years and the implication of the trends for the state of China’s research system. Adjusting the data as suggested by Rozelle, Pray, and Huang, research investment falls or is stagnant from 1985 to early 1990.8 In the early 1990s, investment levels rise at a slow pace, until 1995 when they move up sharply. Extension expenditure trends follow a similar pattern. Slowing investment trends for long stretches of time during the 1980s, given research lags, would most likely start to show up as stagnating research stock in the mid- to late 1990s. China also has access to genetic materials from international sources for all the three crops . Especially for rice, China has drawn heavily on the international research system for genetic material.9 For example, material from the International Rice Research Institute  comprises a large share of China’s rice germplasm. Nationwide, we can trace around 20 percent of the germplasm to IRRI varieties. The proportion varies over time  and also varies by province, reaching more than 40 percent in Hunan Province, one of China’s largest rice growing provinces, in the late 1980s. Although the national use of wheat and maize materials from the CG system  is lower , there does exist great variability among provinces, and in some provinces material from the CG system  makes up around half of the germplasm.10 The new varieties and germplasm material, once they are introduced into the country, are used by breeders in China’s NARS and then extended through the domestic extension system. In summary, China’s research system has created large amounts of new technology and it has succeeded in getting farmers to adopt it at an impressively rapid pace. The technology appears to embody significant levels of yield-increasing material that may prove to be an important determinant of productivity. The national research effort also is aided by the international agricultural researchsystem. The rate of adoption of the highest yielding material, however,ebb flow table is somewhat slower than the rise in yields; yields and output have grown in the past, at least in part due to increased use of inputs. If future yield increases from higher input levels are limited by already high levels of input use, future growth in yields will more increasingly rely on rise in TFP, which most likely needs to be driven by new technology.For equation  to be a measure of technology improvement, we implicitly assume that farmers are rational and replace varieties when a new variety is of a higher “quality” than the variety it is replacing. A new variety is higher quality if it helps the farmer enhance yields or reduce costs or if it includes a new taste characteristic.

A potential statistical issue arises, however, when VT is used as a measure to test the effect of technology on TFP, as in equation . Since the farmer may be simultaneously making decisions affecting both TFP and technology adoption, an OLS regression of TFP on VT likely is problematic because the error term may be correlated with VT. To avoid the endogeneity of VT in the estimation of the TFP equation, we take an instrumental variable  approach. Using predictions from an equation explaining technology as an instrument , our identification strategy assumes that the varieties created by national and international research institutes affect technology, but do not affect TFP except through the seeds farmers adopt. If the assumptions are valid, we can use three variables as instruments: the investments made by the government in crop breeding research ; germplasm flowing into each province from international agricultural research centers ;11 and, yield-enhancing germplasm from China’s NARS . To specify a technology adoption equation, we turn to Feder and Umali’s review of the agricultural innovation adoption literature for guidance. Their article shows that a large number of factors affect adoption. The size of the technology set – that is the range of choices of new technology that farmers have when they are making planting decisions – is one of the most important determinants. In addition, researchers have found that the quality of information about available technology is also necessary. In particular, a good extension system provides information to the agricultural community about available new technology while farmer learning and human capital facilitate its adoption.In areaswith better natural climate and improved infrastructure,farmers were found to adopt new varieties more rapidly. Finally, the completeness of markets facilitates technology adoption, as does the existence of other local institutions that support the search for and adoption of new technology. Hence, a close reading of Feder and Umali suggests a model of technology adoption should include measures of the availability of new technology, the extension system, the nature of the physical environment, infrastructure, and market environment, and, if possible, measures of human capital. In both their role of creating instruments for the TFP equations and as equations of interest in their own right, the technology  equations perform well . The R-squares in OLS versions of the technology equations exceed 0.90 for all three crops. Hausman tests for exclusion restrictions that are designed to test the validity of the instruments show our three instruments are statistically valid.13 Substantively, the first-stage equations provide interesting insights on the process of the technology creation in China. The positive and highly significant sign on the Research Stock variable in all of the specifications for all crops demonstrate the effectiveness of investments in the research system. Higher levels of national stocks accelerate the pace of varietal turnover . If technology is the engine driving China’s food supply in the future , the results here emphasize the necessity of maintaining the level and growth of public investment in crop research and development. The negative sign on the market liberalization period dummy variable in all but one of the first stage equations  calls for heightened attention to the health of the research system. The factors that have slowed technological change in the 1990s appear to be the source of fall of TFP in the 1994 and 1995. However, this may be too strong of a conclusion;the negative sign may only be picking up the fact that this just happens to be a period when China’s agricultural TFP growth is temporarily stagnant, a phenomenon that periodically occurs in every country. For example, even in the U.S. where researchers have documented the fact that TFP has grown steadily during the entire post-WWII period , there have been at least two 5-year time periods in which TFP growth has been near zero or negative and two more that the growth rate of TFP has been only one percent, less than the rate of growth of the U.S. population.