STRUCTURAL CHANGE AND THE INTERSECTORAL TERMS OF TRADE: SOUTHEAST ASIAN EXPERIENCE

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.

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.

Many authors have estimated and found that the productivity growth in agriculture is higher than that in non‐agriculture in today's richest countries. Several papers suggested that growth in agricultural productivity was essential for today's richest countries to take off early. However, few articles noticed that growth in agricultural productivity is critical in driving structural change in today's richest countries. This paper studies a two‐sector neoclassical growth model with subsistence agricultural consumption and shows that growth in agricultural productivity plays a more important role than growth in non‐agricultural productivity in governing massive structural change in today's richest countries.

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.

In recent decades, the debate on economic growth has largely focused on the role of its fundamental causes: institutions, geography, trade, and culture. This study analyses the underlying causes of agricultural productivity growth in Europe during the second half of the twentieth century. To determine the importance of fundamental causes, Total Factor Productivity growth in European agriculture was calculated for the period 1950-2005 and several econometric models are discussed. This study highlights inclusive institutions, agricultural support policies that encourage innovation, qualified human capital and openness to international trade as key factors that favour productivity growth in agriculture.

In many developing countries, a high proportion of the population resides and works in rural areas. Agriculture is the dominant sector in rural areas and has the greatest concentration of poverty: landless workers, small tenant farmers, and small farm owners. Thus, any development strategy that is directed towards increasing employment and alleviating a country's hunger must concentrate on sustainable agricultural growth. Historically, economic development in most countries has been based on exploitation of natural resources, particularly land resources. Soil erosion and land degradation have been serious worldwide. Due to reasons such as high population pressure on land and limited fossil energy supplies, land degradation is generally more serious in the developing world. Empirical studies show that soil erosion and degradation of agricultural land not only decrease the land productivity but they can also result in major downstream or off-site damage which may be several times that of on-site damage. In promoting industrialization, governments of many developing countries adopt a package of price and other policies that reduce agricultural production incentives and encourage a flow of resources out of agriculture. Increasing evidence shows that these policies cause a substantial efficiency or social welfare loss, and a great loss in foreign exchange earnings. In addition, a World Bank study on the effect of price distortions on economic growth rates concluded that neither rich resource endowments, nor a high stage of economic development, nor privatization are able to make up the adverse effects caused by high price distortions. This analysis is primarily concerned with identifying the factors that determine the agricultural production growth rate and in testing the effects these factors have on agricultural growth in developing countries. Specifically, this study involves statistical estimation of an aggregate agricultural growth function based on cross-country data for 28 developing countries. Special attention is devoted to land degradation and agricultural pricing policy, and to the policy implications resulting from the effects these variables have on agricultural and food production growth. The overall results of this study show that price distortions in the economy and land degradation had statistically significant negative impacts while the change in arable and permanent land was positively related to the growth of agricultural production and food production in 28 developing countries from 1971 to 1980. These results emphasize the importance of ‘getting prices right’ and implementation of sustainable land and water management practices if future growth in food and agricultural output is to be realized and sustained in developing countries.

In this paper, we study the transformation process Indian agriculture exhibited in the recent past, studying its policy implications. Between the years 2005-06 and 2015-16, more than 52 million workers left agriculture, which did not have any effect on agricultural output due to productivity improvements. We estimate the contribution of productivity growth and structural change in agriculture to national productivity growth during 1981-2016. We estimate differentials in agricultural productivity and in their ability to contribute to the structural change process for 21 major states of India. Using revised employment estimates, we trace major changes during the pre-reforms (before 1991) and post-reforms periods. Results show that in the pre-reforms period, the impact of productivity improvements in agriculture on agricultural output was equated by the new workforce entering into this sector, leading to a stagnant labor productivity trend. The labor-shift from agriculture during the early years of the post-reforms period, which increased further in the next decade, has led to a consistent rise in agricultural productivity. In the absence of reforms and the associated labor shift, the productivity growth in Indian agriculture would have been much lower. A similar labor shift during the last decade has not affected agricultural output, which has risen more rapidly. This result holds true for almost all states studied. There exists a positive relation between labor-shift and agricultural output in a cluster of states. Decomposition results indicate ‘within-sector’ productivity growth is the major source of overall growth, with a rising contribution of ‘structural change’. Studying the sources of growth across states offers new scope to achieve inter-sectoral productivity convergence.

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

Background: Recently, agricultural productivity growth has experienced a sharp downward turn across the countries of Southeast Asia partly due to population aging, increasing pace of urbanization, and industrialization.
 Objective: To provide empirical evidence to the elasticity of prevailing health spending as a proxy of human capital stock on agricultural productivity growth in Southeast Asia.
 Methods: This study analyses data obtained from the World Development Indicators for 2000-2016 using panel data regression models.
 Results: The empirical evidence suggests that prevailing health expenditure, though statistically significant, exerts a strong positive effect on agricultural productivity growth. Therefore, a unit rise in prevailing health spending relative to GDP would increase agricultural productivity growth by 28% across countries of Southeast Asia, all else constant.
 Conclusion: The trend of rapid agricultural productivity declines in Southeast Asia could be altered by augmenting investment to the prevailing health spending as an indicator of human capital stock.
 Policy implications: The governments of Southeast Asia should increase investment in prevailing health spending relative to GDP, to stimulate more growth in agricultural productivity, greatly improved human capital stock, and eventually increase economic growth.

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.

Based on the panel data of provincial units in China from 2000 to 2020, this paper uses the entropy method to calculate agricultural environmental regulation level in China from the perspectives of afforestation projects, water conservancy projects and environmental protection projects. Then, this paper calculates agricultural non-point source pollutant emissions in China by using the unit survey and evaluation method, and calculates agricultural green productivity growth in China by using the SBM directional distance function and Luenberger productivity index. On this basis, the influence of environmental regulation on agricultural green productivity growth in China and its mechanism are empirically analysed. The results show that:(1) During the sample period, agricultural environmental regulation level and agricultural green productivity growth increased significantly, while the emission density of agricultural non-point source pollution decreased significantly; (2) On the whole, environmental regulation significantly promoted agricultural green productivity growth in China, which was mainly reflected in the promotion of agricultural green technology progress change; (3) Environmental regulation can significantly promote agricultural green productivity growth in China through the channel of agricultural innovation investment. The innovation of this paper lies in the measurement of agricultural environmental regulation, and the analysis of the moderating effect of agricultural innovation investment on the impact of environmental regulation on agricultural green productivity growth in China. The research conclusions of this paper verify the ‘Porter Hypothesis’ theory in the field of agriculture, and have guiding significance for China to promote agricultural green productivity growth by relying on environmental regulation.

Agriculture employs two-thirds of Sub-Saharan Africa’s (SSA) workforce and a majority of the continent’s poor (IFPRI 2004). As a result, agricultural productivity growth offers a singularly powerful lever for raising incomes and reducing poverty across the continent (Thirtle et al. 2003; de Janvry and Sadoulet 2010; Christiaensen et al. 2010). Recent estimates from Kenya and Rwanda, for example, indicate that a 1 % increase in national income coming from the agricultural sector leads to three to four times as much poverty reduction as comparable income gains in nonagricultural sectors of the economy (Diao et al. 2012). Agricultural growth is, likewise, a key driver of economic growth and structural transformation. Because agriculture accounts for 25 % of Sub-Saharan Africa’s gross domestic product, and up to 50 % in poor countries, productivity gains in agriculture translate directly into broad-based per capita income gains (IFPRI 2004; Diao et al. 2012). Over the long run, improved agricultural technology, agronomic practices, and marketing systems will enable a minority of well-managed smallholder farms to transition into high-value commercial agriculture. In contrast, the majority of today’s smallholder farmers will follow an alternate pathway, as elsewhere, gradually exiting agriculture in favor of nonfarm occupations. But in Africa, as in other settings before, this exit will require prior broad-based agricultural productivity growth on small family farms (Lipton 2005). Even the continent’s many noncommercial, primarily subsistence farmers require early, sustained productivity gains in agriculture so they can free their children from farm labor obligations, generate the surpluses necessary to send them to school, and help them transition into successful nonfarm career trajectories over the next generation (Chapoto et al. 2013). Despite the importance of agricultural growth to African economies and to the welfare trajectories of its people, farm productivity remains generally low in SSA. Labor productivity, as measured by the value of agricultural output per worker, stands at roughly two-thirds of the level prevailing in developing Asia. Land productivity, as measured by cereal yields, lies closer to onehalf of the levels attained in Asia and Latin America (Table 1). Why has African agriculture underperformed? In part, Africa’s historical land abundance has allowed African governments to underinvest in agricultural research, extension, and other key drivers of agricultural productivity growth. For many decades, African leaders have spent half as much (per $100 of agricultural output) as Asian countries on the core public goods that drive

Scientific publications on environmentally sustainable or green growth in agriculture are increasingly becoming more important but empirical research is scarce. In empirical studies, the most commonly accepted way to assess environmentally sustainable or green growth in agriculture is based on measures of total factor productivity (TFP) or multifactor productivity (MFP) growth. Both measures are important for analytical and monitoring tools that can help to better understand the factors affecting output growth as well as the determinants of changes in production factors (labour and produced capital) in agriculture. Growth of TFP or MFP is achieved through the application of technologies and advanced production practices that result in higher output from the same amount, or lower inputs (labour and produced capital).Conventional TFP and MFP are not suitable for the assessment of environmentally sustainable growth in agriculture because both indicators do not include environmental variables such as environmental pollution and natural capital. There is a lack of comparative empirical studies between EU countries. This study focuses on the problem of measuring environmentally sustainable growth in agriculture. The aim of this study is twofold: firstly, to develop a framework for the assessment of environmentally sustainable growth in agriculture, based on information collected in public databases; and secondly, to empirically analyse environmentally sustainable growth in agriculture in EU countries over the long period. The environmentally adjusted multifactor productivity (EAMFP) growth measure was applied to assess environmentally sustainable growth in agriculture of the EU’s countries. For analysis, the environmental pollution of agricultural production was expressed as net GHG emissions, and natural capital was expressed as the quality-adjusted agricultural land area.The research was conducted using literature overview, decomposition technique and cluster analysis method. The 28 EU countries (including the United Kingdom, which was a member of the EU until January 1, 2020) were included in the empirical analysis. The analysis covered the period between 2005 and 2019 and a five-year average annual change rates (2005-2009 and 2015-2019 respectively) were used to compare the environmentally sustainable growth in agriculture between the beginning and the end of the considered period, as is common in most agricultural growth studies.The findings show that pollution-adjusted GDP growth in agriculture was achieved in less than a five of the EU countries at the beginning of the considered period, and in most of the EU countries at the end of the considered period. In most of the EU countries, the environmentally sustainable growth in agriculture was mainly determined by technological progress, while the slow change in environmental pollution (net GHG emissions) did not have a significant contribution to agricultural growth in all EU countries. Following the hierarchical clustering method, three significantly different clusters of the EU countries were identified in terms of gross added value growth and technological progress in agriculture of EU countries in the context of environmentally sustainable growth.

Raising agricultural productivity in developing countries is often said to reduce poverty more than comparable growth arising from other sectors. This claim has frequently been based on casual theorising, rather than empirical evidence. Productivity growth generates additional income and must benefit someone, though not necessarily the poor. It is conceivable that most, or even all of the benefits might go to others. Using region‐level data from Thailand, we study the relationship between agricultural productivity growth and rural poverty incidence. The dependent variable for our regression analysis is the annual rate of change in rural poverty incidence at the regional level between the years for which poverty data are available. Agricultural productivity is measured as the annual rate of change in regional total agricultural productivity, covering the same time intervals as the poverty observations, but lagged one calendar year. Other control variables include regional non‐agricultural incomes and the real price of food. The estimated coefficient on the change in agricultural productivity is negative and highly significant, implying that agricultural productivity growth does reduce rural poverty, holding other variables constant, though not more so than non‐agricultural sources of income growth. The poverty‐reducing contribution of recent agricultural productivity growth has been small. The poverty‐reducing effects of long‐term drivers of agricultural productivity growth are also analysed, using simulations based on the estimated model.