Chapter 73 Agricultural Productivity and Economic Growth

1. IntroductionDevelopment economists such as Rostow (1960) and Ranis and Fei (1961) have stressed a positive linkage between agricultural productivity and industrialization. The positive link, however, has been argued to be nonexistent by Matsuyama (1992) in a two-sector endogenous growth model of small-open economies with a low elasticity of agricultural goods and the existence of learning-by-doing only in the domestic manufacturing sector.1 As a result of comparative advantage, higher agricultural productivity solicits labor inputs from the manufacturing sector in his model, leading to lower learning-by-doing and economic growth.Matsuyama's results, however, may not be consistent with what has actually happened in Japan and other East Asian economies. In Japan a land reform has been implemented, and allocation of resources to agricultural research has been increased since the Meiji Restoration. As a result of agricultural technical progress,2 agricultural productivity in Japan is much higher than before the Meiji Restoration. In particular, evidence has shown that the agricultural technical change after the Meiji Restoration tends to increase nonagricultural output by pushing resources out of the agricultural sector into the nonagricultural sector. For example, see Yamaguchi and Binswanger (1975, table 7) for the quantitative effects of the agricultural technical change in Japan on nonagricultural output (column 3) and on input reallocation (columns 5 and 7) in 1880-1965. Similarly, the agricultural technical change was higher in Korea's and Taiwan's early stages of economic development, as they have founded agricultural research institutes and farmers' associations during the Japanese colonial period3 and implemented land reforms after World War II. For evidence, see Mason et al. (1980, chapter 7) for the case of Korea and Thorbecke (1979) for the case of Taiwan. A World Bank (1982, p. 45) study reports that for the 23 developing countries whose agricultural growth rate in the 1970s exceeded 3% a year, 17 countries had a GDP growth rate above 5% a year in the same period. Finally, using cross-country data for 14 Asian developing countries in 1960-1986, Mellor (1995) finds a positive and significant relationship between growth rate of per capita agricultural and nonagricultural GDPs, in which both agricultural and nonagricultural sectors grow more rapidly than 31 sub-Saharan and 20 Latin American countries. These above observations lead to interesting questions as to what mechanism lies in the positive impact of accelerated agricultural growth on nonagricultural growth. What policies might increase the efficiency with which a productive agricultural sector moves a nonagricultural sector forward?The purpose of this study is to revisit the linkages between agricultural productivity and economic growth with a government policy. Our model is based on Matsuyama's (1992) framework, with a small twist, so that we can clearly identify the mechanism leading to a positive relationship. The departure in this article lies in introducing a government, which collects taxes and then conducts expenditures on infrastructures. An important role played by higher agricultural productivity in an early stage of economic development is the one by which it renders the government larger tax revenues, so that larger expenditure on infrastructures is facilitated.4 In a study investigating Taiwan's rice-for-fertilizer bartering system in the 1950s and 1960s, Koo (1996, table 2) finds that the resulting hidden taxes on rice alone account for 10-20% of total tax revenue in the period extending from 1950 to 1969. Along with other taxes, the agricultural sector is thus an important source of government revenue in a developing economy.5 Following Barro (1991), public expenditure on infrastructures is assumed to be productive, in that the learning-by-doing effect of the manufacturing sector becomes enhanced with public expenditure on infrastructures. …

Shenggen FanInternational Food Policy Research Institute and Institute of AgriculturalEconomics of the Chinese Academy of Agricultural SciencesLinxiu ZhangCenter for Chinese Agricultural Policy of the Chinese Academy of SciencesXiaobo ZhangInternational Food Policy Research InstituteI. IntroductionChina is one of the few countries in the developing world that has madeprogress in reducing its total number of poor over the past 25 years.

PurposeThe purpose of this paper is to investigate determinants of regional disparities in China's agricultural labor productivity growth.Design/methodology/approachThis paper first decomposes the regional disparity in China's agricultural productivity growth into its components: technical change, efficiency change and input accumulation per worker. The convergence test is also used to analyze the determinants of regional disparity.FindingsThe paper finds that during 1987 and 2005, although the growth of China's agricultural labor productivity mainly depended on the accumulation of inputs, technical changes contributed more to regional disparities in agricultural productivity growth.Originality/valueThis paper, which studies the determinants of regional disparities in China's agricultural labor productivity growth, contributes to a better understanding of China's agricultural growth and how to reduce the regional inequality. It is indicated that improving efficiency to promote total factor productivity growth is important for agricultural labor productivity growth for the three regions – Eastern, Central and Western – of China. The increase in inputs for Western China, and the improvement in technical change for Central and Western China are significant aspects to promote the growth of agricultural productivity and narrow the gap with Eastern China.

Due to the significant role of agricultural chemicals in increasing agricultural production and ensuring food security, the excessive use of chemical fertilizers and pesticides has been intensified in Iran. These chemical inputs are important environmental pollutants that threaten human health. In the recent years, in agricultural sector, the balance between the growth of agricultural economy and the spread of pollution in Iran has been one of the major challenges. In this regard, the use of decoupling index to decouple the link between agricultural production and pollution caused by the consumption of chemical inputs, such as fertilizers and pesticides, has been emphasized; Therefore, in the present study, the decoupling index first is calculated in relation to the emission of pollution caused by the use of chemical inputs in the process of agricultural production during the period of 1991-2016 in Iran. Then, by reviewing the existing literature systematically, the factors affecting the decoupling index in the agricultural sector of Iran are evaluated using the autoregressive distributed lag (ARDL) model. The results showed that in the recent years, pollution indicators in relation to chemical inputs have not had ideal trends, and despite the further growth of agricultural production, the quality of the environment has experienced a declining trend. The results of the decoupling index related to the use of chemical pesticides and fertilizers in Iran show that during a period of 26-year, only 5 and 4years of using these inputs have had a sustainable state compared to the production growth; besides, a strong negative decoupling state occurred as the most unsustainable state in relation to chemical fertilizer for 7years. Moreover, among the factors affecting the decoupling index, the value-added variable of the agricultural sector has had the most positive effect on this index, and thus, in the long run, it increases the level of pollution in the agricultural sector. The variables of gross domestic product (GDP) per capita and the area under cereal cultivation in the agricultural sector would also increase the decoupling index. Accordingly, adopting effective strategies to improve resource efficiency, planning for the implementation of biotechnological methods, and doing investment for creating green infrastructure in the agricultural sector can be effective in the ideal decoupling of pollution and agricultural economy growth in Iran.

This edited volume of 15 chapters collects contributions by well-known experts on China's agricultural economy. It comprises three parts. Part 1, ‘Overview of the challenges and options’, identifies the main obstacles to China's agricultural and rural development and suggests policy measures to overcome them. Part 2, ‘The performance and potentials of China's agriculture’, discusses major drivers of China's growth in agricultural production over time and across space, and engages in trend extrapolation as well as in assessments of factor productivity. Part 3, ‘Agricultural risk management’, further describes the impact of risk on agricultural production and farmer's well-being and the willingness of the rural population to buy health and other types of insurance. The book reviews China's agriculture in terms of achievements, challenges and prospects. China's economic achievements are obviously quite impressive. Since its economic reforms initiated between 1978 and 2005, China's agricultural GDP has grown by about 11 times, at an overall average annual growth rate of 9.6 per cent. Associated with the high agricultural and overall economic growth, China has been making unprecedented progress in poverty alleviation and farmers' well-being. Based on China's official poverty line, the level of rural poverty fell from 33 per cent in 1978 to 2.5 per cent in 2005. Since accession to the WTO in 2001, China has also further integrated into world markets.

In this article, we reconsider the work of Matsuyama (Journal of Economic Theory, 58(2): 317–334, 1992). Matsuyama (1992) concluded that, for a small open economy, a negative relationship exists between agricultural productivity and economic growth. Our study questions Matsuyama’s (1992) conclusion. We aim to demonstrate a theoretical possibility in which Matsuyama’s (1992) conclusion for a small open economy does not always hold. We extend Matsuyama’s (1992) model by introducing government services that enhance household utility. Unlike Matsuyama’s (1992) model, our model implies that, even in a small open economy, under certain conditions, a positive relationship may exist between agricultural productivity and economic growth when a small country initially has a comparative advantage in agriculture.

In the past two decades, the performance of agricultural production within the Southern African Development Community (SADC) was characterized by sluggish growth rates. Cross-sectional time-series data of 1974 to 1990 were used to examine the factors that determine total agricultural and food production growth in the region. The results show that agricultural workers, cropped land, fertilizer and use of tractors had significant effects on the regional total agricultural and food production growth. These factors together accounted for between 37 and 41% of the total variation in food and agricultural production growth. This suggests that other variables, not included in the models due to data problems do play a very crucial role. These findings have important implications for improving food and agricultural performance in the region. In promoting food and agricultural growth, SADC governments should not only concentrate on improvements in the productivity of the four conventional factors of production, also on other parameters. Other policy-related variables such as producer prices, weather factors, and irrigation and land degradation indices should be given due consideration.

The growth of agricultural productivity is widely believed to be low. But this study finds the productivity growth rate in agriculture to be higher than that in manufacturing, both on average and for groups of countries at different stages of development. This suggests that a large agricultural sector need not be a disadvantage for growth performance - and may be an advantage. Martin and Mitra examine the growth and convergence of total factor productivity in agriculture and manufacturing in a large sample of countries spanning many levels of development over the period 1967-92. There is a widely held but rarely tested view that the rate of growth in agricultural productivity is invariably low. But Martin and Mitra find that the rate of productivity growth in agriculture has been higher than in manufacturing both on average and for groups of countries at different stages of development. Martin and Mitra find evidence of high rates of technical progress in both agriculture and manufacturing. At all levels of development, however, technical progress appears to have been faster in agriculture than in manufacturing. Moreover, there appears to be a stronger tendency for levels and growth rates of total factor productivity to converge in agriculture than in manufacturing - suggesting that international dissemination of innovations has been relatively rapid in agriculture. These results may well reflect the important investments in agricultural research and development in recent decades. They also highlight the need to continue developing and disseminating innovations if countries are to maintain high rates of productivity growth. This paper - a product of Trade, Development Research Group - is part of a larger effort in the group to understand the links between trade and growth.

The growth of agricultural productivity is widely believed to be low. But this study finds the productivity growth rate in agriculture to be higher than that in manufacturing, both on average and for groups of countries at different stages of development. This suggests that a large agricultural sector need not be a disadvantage for growth performance - and may be an advantage. Martin and Mitra examine the growth and convergence of total factor productivity in agriculture and manufacturing in a large sample of countries spanning many levels of development over the period 1967-92. There is a widely held but rarely tested view that the rate of growth in agricultural productivity is invariably low. But Martin and Mitra find that the rate of productivity growth in agriculture has been higher than in manufacturing both on average and for groups of countries at different stages of development. Martin and Mitra find evidence of high rates of technical progress in both agriculture and manufacturing. At all levels of development, however, technical progress appears to have been faster in agriculture than in manufacturing. Moreover, there appears to be a stronger tendency for levels and growth rates of total factor productivity to converge in agriculture than in manufacturing - suggesting that international dissemination of innovations has been relatively rapid in agriculture. These results may well reflect the important investments in agricultural research and development in recent decades. They also highlight the need to continue developing and disseminating innovations if countries are to maintain high rates of productivity growth. This paper - a product of Trade, Development Research Group - is part of a larger effort in the group to understand the links between trade and growth.

The agricultural sector plays a crucial role in Indonesia, serving as both a provider of food and a key driver of economic growth. This study aims to analyze the factors influencing Indonesia’s agricultural sector from 1981 to 2021, focusing on agricultural production and its economic value. Climate change has emerged as a critical issue affecting agriculture, with greenhouse gas emissions serving as proxies for measuring its impact. This study employs the Autoregressive Distributed Lag (ARDL) model to examine both short- and long-term relationships. The findings indicate that, in the long run, agricultural land area and economic growth significantly affect the agricultural sector. In the short term, agricultural land area, economic growth, and fertilizer usage are the key factors. However, climate change did not have a significant negative impact on agricultural decline. In contrast, fertilizer usage was positively correlated with agricultural production. These findings highlight the essential role of government policy in fostering agricultural sector development in Indonesia. Strategic initiatives should focus on ensuring an adequate fertilizer supply, expanding agricultural land, and promoting key economic sectors that drive growth and support agricultural sustainability. Keywords: agricultural sector, ARDL model, climate change, Indonesia

The paper analyzes the impact of institutional changes on the dynamics of economic growth in Russian agriculture. The authors identified six specific periods of the development of Russian agriculture (1952–1958; 1959–1970; 1971–1981; 1982–1990; 1991–1998; 1999–present), associated with qualitative changes in institutions and affecting the economic dynamics of the industry. The violation in combining dominant and complementary institutions throughout the studied period is considered as the main mistake in building an institutional environment that causes stagnation and a decline in agriculture. The necessary changes are highlighted in the existing institutes of market and state regulation in Russia, which allow achieving sustainable economic growth in the agricultural sector.

Purpose – China and India have made significant strides in transforming their agricultural sectors to cut hunger and poverty for the masses through improved agricultural productivity. Given limited land and shift of labor to non-agricultural sector, increasing productivity will continue to be central in agricultural growth in the twenty-first century. The purpose of this paper is to provide comparative analysis of the agricultural total factor productivity (TFP) growth in the two countries. It complements existing literature by examining the evolution and drivers of TFP at disaggregated sub-national level. Richer data allows a deeper understanding of the nature and drivers of TFP growth in the two countries. Design/methodology/approach – This paper applies different analytical framework to address different research questions using data since 1980. China study estimates a parametric output-based distance function using a translog stochastic frontier function. Productivity growth index and its multiple components are calculated using parameters derived from the parametric approach to identify the characteristics of technology such as structural bias. India study first applies data envelopment analysis to estimate the aggregate productivity growth index, technical change (TC), and efficiency change. Next productivity indexes by for traditional crops are estimated using growth accounting framework at state level. Finally, a panel regression links TFP on its determinants. Findings – Several common themes emerge from this comparative study. Faced with similar challenges of limited resources and growing demand, improving productivity is the only way to meet long-term food security. Agriculture sector has performed impressively with annual TFP growth beyond 2 percent in China and between 1 and 2 percent in India since the 1980s. The TFP growth is mainly propelled by technological advance but efficiency had been stagnant or even deteriorated. This study provides a granular picture of within country heterogeneity: fast growth in the North and Northeast part of China, South and East of India. Research limitations/implications – The study suggests some possible policy interventions to improve agricultural productivity, including investment in agricultural R & D to create advanced production technology, effective extension programs and supportive policies to increase efficiency, and diversification from staple crops for sector-wide growth. The India study suggests certain policies may not be contributing much to productivity growth in the long run due to a negative impact on environment. Further studies are needed to expand the productivity analysis to take into consideration of the negative externalities to the society. Data enhancement to account for quality-adjusted inputs could improve the estimation of productivity growth. Originality/value – Each country study reveals certain prospects of the agricultural sector and production technology. China analysis statistically confirms the existence of technical inefficiency and technology progress, suggests the translog form is appropriate to capture the production technology and satisfies conditions stipulated in theoretical models. The results indicate TC does not influence the contribution of output or input to the production process. India study pinpoints the lagging productivity growth of traditional crops, which still derives growth from input expansion. Although different states benefited from different crops, sector-wide productivity gain is primarily the result of diversification to high-value crops and livestock products.

Water and land resources are related to the security and stability of agricultural production, and the degree of matching in time and space directly affects regional agricultural production capacity and sustainable agricultural development. This paper intends to use the panel data of nine provinces in the Yellow River Basin from 2000 to 2019 and incorporate the static and dynamic spatial Durbin models with spatial effects under the geographical adjacency matrix and the comprehensive weight matrix of economic geography, so as to explore the direct effects and indirect effects, short-term effects and long-term effects of the matching coefficient of agricultural water and land resources on the agricultural economic growth in the Yellow River Basin. The results show the following: (1) The matching situation of agricultural water and land resources in different provinces along the Yellow River Basin are different; some are relatively short of water resources, some are relatively balanced in water and land resources, and some are relatively short of land resources. (2) The static spatial Durbin model shows that the direct effect of the matching coefficient of agricultural water and land resources on the agricultural economic growth of the province is not significant; the indirect effect and the total effect of the spatial spillover is significantly positive. (3) The dynamic spatial Durbin model under the two matrix forms shows that the short-term total effect of the matching coefficient of agricultural water and land resources on agricultural economic growth is significantly positive, while the long-term total effect is significantly negative, and the direction and degree of the short-term and long-term effects are inconsistent. This study provides a comprehensive analysis framework from the perspective of local and neighborhood effect, and short-term and long-term effect, which can provide a reference to reasonably adjust the matching of agricultural water and land resources to promote agricultural sustainable economic growth, especially for developing countries.

Ethiopia’s national development strategy, A Plan for Accelerated and Sustained Development to End Poverty for 2005/06 to 2009/10 (PASDEP) places a major emphasis on achieving high rates of agricultural and overall economic growth. Consistent with the PASDEP, Ethiopia is also in the process of implementing the Comprehensive Africa Agriculture Development Programme (CAADP) together with other African governments. As part of CAADP, the country has committed itself to meeting targets of devoting at least 10 percent of public expenditures to agriculture and to achieving a 6 percent growth rate in agricultural GDP. Ethiopia has already met these targets in recent years. The challenge remains, however, to continue to devote these public resources and to achieve high growth rates through 2015. This paper analyzes agricultural growth options that can support high levels of agricultural development using a new computable general equilibrium (CGE) model for Ethiopia based on data from the EDRI 2005/06 Ethiopia SAM (Ahmed et al. 2009). The CGE model results indicated that if Ethiopia can meet its targets for crop yields and livestock productivity, then it should be possible to reach and sustain the six percent agricultural growth target during 2006-2015. Even though these yield targets are below the maximum potential yields identified by agricultural field trials, they are still ambitious given the short timeframe of the CAADP initiative (i.e., seven years). Achieving agricultural growth of six percent per year would reduce national poverty to 18.4 percent by 2015, lifting an additional 3.7 million people out of poverty compared to a base simulation using medium term growth rates. Most households are expected to benefit from faster agricultural growth. However, some agro-ecological zones that grow higher value cereals and export-oriented crops and which are better situated to larger urban markets (e.g., the rainfall sufficient highlands) stand to gain more than other parts of the country. Both rural and urban households benefit from faster agricultural growth (and thereby overall economic growth), as rural producers benefit from increased agricultural productivity and incomes, while net purchasers of food in both rural and urban areas benefit from moderate declines in real food prices. Composition of agricultural growth matters, though. Additional growth driven by cereals has larger impacts on poverty reduction, because these crops already constitute a large share of rural incomes and so can contribute substantially to achieving broad-based agricultural growth. Yield improvements in these crops not only benefit farm households directly, by increasing incomes from agricultural production, but also by allowing farmers to diversify their land allocation towards other higher-value crops. Increased productivity of cereals that reduces real cereal prices is also effective at raising rural real incomes and reducing poverty, especially amongst the poorest households. Thus, high priority should be afforded to improving cereals yields and opening market opportunities for upstream processing to reduce demand constraints.

A salient theme in D. Gale Johnson’s work is the importance of agricultural development for general prosperity and for economic diversification (e.g., Johnson 2000). Johnson has also noted that most of the world’s poor are engaged in farming, so that a key focus of development policy is to raise the incomes of farmers. From a global perspective, increasing the productivity of agriculture, given the fixity of land, is necessary for both poverty reduction and the development of the nonagricultural sector. At the level of the world, agricultural productivity gains, poverty reduction, and the growth of the nonfarm sector are complements. However, the question remains whether these observations imply that every poor country should focus its public resources on agricultural development in order to raise the incomes of people now engaged in farming and whether such a policy is necessary for obtaining economic diversity. In this article, we use the experience of India over the past 30 years to address the issue of whether agricultural technical change actually leads to economic diversification and income growth within the rural sector in the context of an open-economy country in which there are cross-area trade and capital flows. We focus in particular on the rural sector because this is the sector in which linkages between agricultural and nonagricultural sectors are thought to be the strongest. We exploit the fact that India has maintained a policy of openness with respect to agricultural technology over this period, permitting and actively supporting agricultural development, and has moved to a reformed regime in which goods are traded and capital is more mobile in the 1990s. Evidence on the relationship between agricultural growth and nonfarm