Agricultural productivity growth and drivers: a comparative study of China and India

This study aimed to analyze the trends and causes of productivity growth in the Philippine agriculture by estimating the total factor productivity (TFP) level and growth in the sector using the Tornqvist index number approach. Likewise, the factors causing the movements in TFP over a period of time, and the policy alternatives for increasing productivity growth were identified. The most recent agricultural data set covering 12 administrative regions and years 1974–2004 was used to determine the TFP level and growth. Results showed that output growth in Philippine agriculture was mainly driven by productivity, and minimally by the inputs of production. Productivity gaps were observed among the different regions. Central Luzon was the most productive region, whereas Bicol was the least productive. TFP growth was at its peak in the late 1970s, followed by a deceleration in the 1980s, and resurgence in the 1990s until the early part of the recent decade. The highest TFP growth rate recorded has not been paralleled despite government efforts and initiatives to revive the less dynamic agricultural sector of the Philippines. Across time, revenue growth was also seen to be declining, which may be due to the decrease in growth contribution of output prices (which remained relatively large), and to the decrease in growth contribution of input quantities (which was relatively small). Lastly, output prices contributed substantially to agricultural revenues, and TFP growth accounted mostly for growth in quantities of agricultural outputs. The TFP growth substantiated the importance of infrastructure, rural electrification, and investments in research and development to enhance agricultural productivity. Overall, this study recommends further examination of the role of agricultural output prices in determining farm incomes, and for initiatives to be undertaken to boost agricultural productivity through investments in infrastructure and research and development.

Decomposition of climate-induced productivity growth in Indian agriculture

Provincial panel data from the agricultural sector and stochastic frontier production function model were employed to study the total factor productivity (TFP) growth since the 1980s in China. We decomposed the TFP growth into technological progress and technical efficiency changes (efficiency gains) as well as the aggregate agricultural TFP growth into crop-specific subsector's TFP growths. We found that Chinese agriculture experienced significant productivity growth in the last few decades, although the growth rates vary considerably among the subsectors. During this period, the source of productivity growth comes from either technological progress or efficiency gains, not from both of them simultaneously. Particularly since the 1990s, Chinese agriculture experienced a great technological progress and yet a considerable efficiency loss. The differences among sources of productivity growth and among subsectors call for distinct policy responses.

Previous research on agricultural productivity in Africa has focused on conventional Total Factor productivity (TFP) growth rather than Green Total factor productivity (GATFP) growth, thus ignoring the effect of undesirable outputs such as emissions. This has raised concerns about the sustainability of agricultural productivity growth in the continent. The study was designed to examine GATFP growth in agricultural productivity for 49 African nations from 2000 to 2019. We apply the Global Malmquist–Luenberger (GML) Productivity Index, which complies with the sustainable development agenda that promotes greater production of desirable outputs and minimising unwanted outputs. This approach is also compared to Global Malmquist (GM) Productivity Index which ignores unwanted outputs, yielding to conventional TFP growth. We found an average GATFP growth of 0.6% and TFP growth at 0.9% suggesting that the actual agricultural productivity growth is overstated if agricultural emissions are disregarded. Both estimates fell short of the desired annual target of 7% from the Comprehensive African Agriculture Development Programme (CAADP). Regional growth is mostly characterised by high (low) GATFP and TFP except in Southern Africa and East Africa. The two regions represent an ideal situation where GATFP exceeds TFP. At country level growth can be divided into three scenarios: desired growth, where GATFP exceeds TFP; balanced growth with both estimates equivalent; and undesired growth, where TFP exceeds GATFP. Unfortunately, most African nations fall in the last scenario. We conclude that policies must be developed to encourage sustainable agricultural productivity growth in Africa.

We measure and compare agricultural total factor productivity (TFP) growth and its components (efficiency and technical change) in China and India and test the TFP series for the existence of structural breaks relating the evolution of TFP to policy milestones. Our results show that agricultural TFP growth accelerates in China after 1979 and in India after 1974, although China’s agricultural sector clearly outperforms India’s. The main explanation of these differentials is that agricultural growth in China benefited from more fundamental institutional and policy reforms in agriculture than India. There is some evidence that the transformation of industry in China was also important for agricultural TFP growth. Manufacture growth absorbed labor and reduced employment in agriculture, creating incentives for capital investment and technical change that kept output per worker in agriculture growing at high rates. Fewer changes in agricultural policies and in the dynamics of manufacturing in India resulted in slower growth in agricultural productivity, despite policy changes that accelerated economic growth in recent years.

Agricultural endeavour in India has moved from being a traditional farming practice to a more modern and mechanized enterprise. One of the important prerequisite for raising agricultural production and mitigating supply constraints is enhancing agricultural productivity. Since traditional input resources are limited, an increase in agricultural production has to come from enhancing agricultural productivity. With the onset of Green Revolution in India, the contribution of modern technology towards raising agricultural production has been immense. Total Factor Productivity (TFP) growth in agriculture assesses the contribution of knowledge and efficiency towards raising agricultural production. For a comprehensive study of growth of the agriculture sector, TFP analyses should include the allied sectors like livestock, forestry and fishing as well. However, in estimating agricultural TFP growth, it is essential to account for the type of land being used for crop production. An addition of an acre of irrigated land will be much more productive than an addition of rainfed land. Similarly, an acre of rainfed land will yield more crop than an acre of pastureland, which is usually used for grazing purpose for livestock. Access to irrigated land protects farmers from the risks and uncertainties of vagaries of weather. In this study we derive weights for rainfed cropland, irrigated cropland and pastureland based on their relative productivity. Using the traditional Solow index method and accounting for different land type viz. rainfed land, irrigated land and pasture land, we measure TFP growth of the agriculture and allied sector in India from 1981 to 2008. Our results show that agricultural TFP growth in India for this period ranged between 1% during 1981-1990 to about 1.7% during 2000-2008. Growth in TFP was higher during the post reform period than during the pre reform period. We also find that usage in agricultural inputs has declined during the post reform period compared to the pre reform period. Our findings also show that, though contribution of TFP towards output growth was declining during the initial years, it however shows a rising trend towards explaining output growth during the last decade.

• By 2050, global agricultural demand is projected to grow by 70-100 percent due to population growth, energy demands, and higher incomes in developing countries. Meeting this demand from existing agricultural resources will require raising global agricultural total factor productivity (TFP)1 by a similar level. Maintaining the U.S. contribution to global food supply would also require a similar rise in U.S. agricultural TFP. • TFP growth in U.S. agriculture is predicated on long-term investments in public agricultural research and development (R&D). Productivity growth also springs from agricultural extension, farmer education, rural infrastructure, private agricultural R&D, and technology transfers, but the force of these factors is compounded by public agricultural research. • The rate of TFP growth (and therefore output growth) of U.S. agriculture has averaged about 1.5 percent annually over the past 50 years. Stagnant (inflation-adjusted) funding for public agricultural research since the 1980s may be causing agricultural TFP growth to slow down, although statistical analyses of productivity growth trends are inconclusive. • ERS simulations indicate that if U.S. public agricultural R&D spending remains constant (in nominal terms) until 2050, the annual rate of agricultural TFP growth will fall to under 0.75 percent and U.S. agricultural output will increase by only 40 percent by 2050. Under this scenario, raising output beyond this level would require bringing more land, labor, capital, materials, and other resources into production. • Additional public agricultural R&D spending would raise U.S. agricultural productivity and output growth. Raising R&D spending by 3.73 percent annually (offsetting the historical rate of inflation in research costs) would increase U.S. agricultural output by 73 percent by 2050. Raising R&D spending by 4.73 percent per year (1-percent annual growth in inflation-adjusted spending) would increase output by 83 percent by 2050.

This paper applies the Malmquist productivity index method to measure total factor productivity (TFP) growth in Vietnamese agriculture using panel data from 60 provinces in Vietnam during 1985–2000 when Vietnam implemented widespread de-collectivization, trade liberalization, and reformed her agriculture sector. This study indicates that most of the early growth in Vietnamese agriculture during the first reform period 1985–1990 was due to TFP growth in response to incentive reforms. During the second reform period 1990–1995, the growth rate of TFP fell, and Vietnam’s agricultural growth was mainly caused by drastic investment in capital. In the post-reform period (1995–2000), TFP growth increased again, though still much lower than 1985–1990. Overall, the TFP growth rate in the whole period is estimated at 1.96 percent, contributing to 38% of Vietnam’s agricultural growth.

Improving agricultural productivity is a priority concern in promoting the sustainable development of agriculture in developing countries. In this study, we first apply stochastic frontier analysis (SFA) to analyze the growth of agricultural total factor productivity (TFP) and its three components (technical change—TC, technical efficiency change—TEC and scale change—SC) in 15 south and southeast Asian countries covering the period 2002 to 2016. Then, the determinants of agricultural TFP growth are identified using dynamic panel data models. The results reveal that the south and southeast Asian countries witnessed an overall decline in agricultural productivity during the sample period, thereby creating concerns over sustaining future agricultural growth. Technical progress was the major source of TFP growth, but its contribution has slowed in recent years. On the other hand, declining scale change and technical efficiency change resulted in the deterioration of productivity over time. Variable levels of productivity performances were observed for individual countries, mainly driven by technological progress. Overall, southeast Asia achieved a more stable and sustained agricultural growth as compared to south Asia. Among the determinants, human capital, level of urbanization, and development flow to agriculture positively influenced agricultural TFP growth, while the level of economic development and agricultural import were negatively associated with TFP growth. Policy recommendations include the suggestions that south and southeast Asian countries should increase investment in human capital, focus on technological innovation and make use of financial assistance and development flow to agriculture to increase and sustain agricultural productivity. In addition, frontier countries of the two regions (e.g., India and Indonesia) should take the lead on regional agricultural development ventures by enhancing cooperation with neighboring countries on technological innovations, and countries facing diseconomies of scale (i.e., Afghanistan and Iran) should consider the rational reallocation of agricultural inputs.

The paper estimates Total Factor Productivity (TFP) growth in six agro-economic zones of Northern Thailand covering a 23 year period (1977 to 1999) and tests convergence amongst regions using a stochastic production frontier approach. Results revealed that all the inputs excluding fertilizer significantly contribute to agricultural productivity. Increasing returns to scale prevail in these regions. Land, labor, irrigation and loan capital have substitution relationships but all are within the inelastic range. The mean technical efficiency level is low (0.88). The overall TFP declined slightly due to technical regress and modest improvement in technical efficiency change over time. However, convergence in productivity has been reached in all regions towards the end. The government’s initiative to support investment through Bank of Agriculture and Agricultural Cooperative loan had a significant influence on technical efficiency improvements. Policy implications include provision of capital through loan, investments in irrigation, and proper functioning of land and labor markets to improve agricultural productivity. Key words: Thailand, stochastic production frontiers, total factor productivity growth, convergence, technical efficiency change, technical change, agro-economic zone.

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.

This article develops new estimates of historical agricultural productivity growth in Jordan. It investigates how public policies such as agricultural research, investment in irrigation capital, and water pricing have contributed to agricultural productivity growth. The Food and Agriculture Organization (FAO) annual time series from 1961 to 2011 of all crops and livestock productions are the primary source for agricultural outputs and inputs used to construct the Törnqvist Index for the case of Jordan. The log-linear form of regression equation was used to examine the relationship between Total Factor Productivity (TFP) growth and different factors affecting TFP growth. The results showed that human capital has positive and direct significant impact on TFP implying that people with longer life expectancy has a significant impact on TFP growth. This article concludes that despite some recent improvement, agricultural productivity growth in Jordan continues to lag behind just about every other region of the world.

This article develops new estimates of historical agricultural productivity growth in Jordan. It investigates how public policies such as agricultural research, investment in irrigation capital, and water pricing have contributed to agricultural productivity growth. The Food and Agriculture Organization (FAO) annual time series from 1961 to 2011 of all crops and livestock productions are the primary source for agricultural outputs and inputs used to construct the Törnqvist Index for the case of Jordan. The log-linear form of regression equation was used to examine the relationship between Total Factor Productivity (TFP) growth and different factors affecting TFP growth. The results showed that human capital has positive and direct significant impact on TFP implying that people with longer life expectancy has a significant impact on TFP growth. This article concludes that despite some recent improvement, agricultural productivity growth in Jordan continues to lag behind just about every other region of the world.

Science, Technology, and Competitiveness in Alberta's Agriculture and Food Sector

In the backdrop of the demand for bifurcation of Andhra Pradesh state based on growing regional disparities, the paper examines the regional disparities in agricultural productivity growth in Andhra Pradesh from 1956 to 2007 at district level by using Malmquist productivity indices (MI). Overall, total factor productivity (TFP) growth in agriculture and allied activities in Telangana is 1.3 per cent per annum, 1.1 per cent per annum in Coastal, while in Rayalaseema TFP growth is stagnant. It indicates that, there is a convergence in TFP growth among districts of developed Coastal and less developed Telangana regions, but districts in Rayalaseema region are left out of this growth process, as this region is not able to catch up with other two regions in agricultural productivity. Irrespective of region most backward districts in agriculture, Srikakulam, Visakhapatnam, Anantapur, Kadapa, Adilabad, Nalgonda, Mahbubnagar and Nizamabad showed stagnation in TFP growth during last 50 years. With the existing resource endowment and technology, Telangana can increase its output by 28 per cent from the existing level, while Rayalaseema region can enhance its output by 25 per cent, Coastal region by only 14 per cent as revealed from efficiency estimates. Shadow input shares indicate that, still gross irrigated area, fertiliser use and availability of labour are limiting factors to increase production at district level. Inefficiency effects model (Battese and Coelli, 1995) reveals that, market infrastructure and credit availability are essential to increase efficiency. There is significant influence of base year resource endowment both physical and human for subsequent agricultural growth.