Cultivating Success: The Role of Institutions, Policies and Investments in Driving Rural Transformation in Australia

• 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 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.

Agriculture is particularly vulnerable to climate change because it faces open weather conditions. In uncontrolled open weather circumstances, it's difficult to attain better total factor productivity (TFP), which characterizes agriculture growth in an economy. The study estimated the TFP growth of Pakistan’s agriculture in first step by employing the Tornqvist- Theil index number approach for the period 1990-2019. The time series data for thirteen crops and four livestock categories from 1990 to 2019 were collected from different sources to estimate the TFP. The average annual TFP growth of agriculture was estimated to be 2.14 percent for the study period, and it contributed about 56 percent to total agricultural output growth. The results also indicated that TFP growth in agriculture sector was highest (0.05 percent) during the 1990-2000, while lowest (-2.14 percent) during the last decade. After, TFP index that was calculated in first step was used as dependent variable in second step of analysis. Then we estimated the impact of climate change on TFP in agriculture sector in Multan district. For this first we used ARDL bound test approach for estimation of long run impact of climatic variables. The results showed that there are positive effects of both minimum and maximum temperature on TFP in the study area. The drought and floods have negative impact on TFP but in first lag their effects became positive on TFP. One of the important variables of climate is rain that had positive impact on the TFP growth, with 1% increase in rainfall there was 0.22% increase in TFP at first lag. Improving the adaptation and mitigation practices related to floods and droughts would be required for sustainable growth in TFP in agriculture sector in Multan District.

The scientific and reasonable measurement of agricultural green total factor productivity is helpful to grasp the direction of rural-factor-market reform. This study constructs a Malmquist productivity index based on a non-radial and non-angular SBM directional distance function. This study calculates the agricultural green total factor productivity of 28 provinces (cities and autonomous regions) in China from 1997 to 2020 by considering unexpected outputs such as carbon emissions and agricultural non-point-source pollution. Finally, this study uses the spatial Dobbin model to explore the spatial impact of agricultural green total factor productivity under the distortion of the factor market. The results show that the agricultural green total factor productivity, considering the unexpected outputs, is more in line with the level of high-quality green development in China’s agriculture. Regardless of whether the unexpected output is included, the increase in China’s agricultural total factor productivity is primarily due to progress in agricultural technology, and the double boost is little in agricultural technology progress and technical efficiency. Agricultural green total factor productivity shows an increasing trend, but the growth rate is slow, and differences in different regions are significant. Factor market distortion negatively impacts agricultural green total factor productivity, and other factors improve the agricultural total green factor productivity. However, factor market distortion has a particular spatial spillover effect, which hinders the synchronous growth of agricultural green total factor productivity in different regions. Therefore, the government should promote the reform of the agricultural mode of production and agricultural green production, eliminate the blocking effect of factor market distortion on the improvement in agricultural green total factor productivity, narrow the regional gap of agricultural total factor productivity, and establish a policy system for high-quality green development of modern agriculture.

Rising prices of agricultural commodities have renewed concerns about constraints to agricultural productivity. To assess productivity trends, total factor productivity (TFP) is generally preferred to partial productivity indexes as an indicator of technical and efficiency changes because it is more closely related to the unit costs of production. But measuring TFP is demanding of data, and developing comprehensive and comparable indexes of international agricultural TFP has been challenging. This study proposes a growth accounting approach, using FAO data on quantity changes in inputs and outputs and aggregating input changes using cost shares derived from other sources, as a consistent way of constructing agricultural TFP indexes for world agriculture. This produces aggregate growth rates for agricultural output, input and TFP at the country, regional and global levels. Results suggest that the rate of agricultural TFP growth accelerated in recent decades, especially in developing countries. Most regions of the world now rely on productivity-based growth rather than resource-based growth to raise agricultural output.

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.

Most of the growth in agricultural output in the last thirty years comes from increases in the efficiency with which both land and non-land inputs are used. Recent work calls for a better understanding of whether this efficiency, known as total factor productivity (TFP), contributes to a more sustainable food system. Key to this understanding is the documented phenomenon that, instead of saving lands, the introduction of technologies that improve agricultural productivity encourage cropland expansion. We extend the results of a recently published econometric model of cross-country cropland change and TFP growth to explore the extent to which improvements in technology were associated with lower greenhouse emissions from land conversion to agriculture as well as with lower land conversion pressures in biodiversity-rich biomes. We focus on the decade of 2001–2010, a period in which our sample of 70 countries (≈75% of global croplands) experienced net land contraction. Except in sub-Saharan Africa and South and East Asia, regional TFP growth was associated with regional land expansion, thus confirming the existence of Jevons paradox in most regions of the world. However, such expansion was more than offset by indirect land use effects stemming from increases in productivity somewhere else. These indirect effects are far from trivial. In the absence of TFP growth, our estimates suggest that ≈125 Mha would have been needed to satisfy demand, half of which are in the four most biodiverse biomes of the world; estimated land use emissions from the ensuing changes in land use range from a lower bound of 17 Gt CO2eq to an upper bound of 84 Gt CO2eq, depending on whether the expansion would have occurred on pasturelands or forest, in contrast to the ≈1 to 15 Gt CO2eq imputed to observed cropland expansion. Our projections of the land needed to satisfy projected growth in TFP per capita during 2018–2023 indicate that current rates of TFP growth are insufficient to prevent further land expansion, reversing in most cases the in-sample trends in land contraction observed during 2001–2010.

The present paper discusses total factor productivity (TFP) in China, including its past success, the current slowdown, and the potential for future growth. It begins by documenting the development of TFP growth over the past three and a half decades, its driving forces and its contribution to the economic growth of the country. It then analyses the reasons for the current slowdown of TFP and economic growth, addresses the institutional imperfections that hinder growth, and explains the government policies and strategies aimed at fostering TFP. Next, it explores the potential for TFP growth from the perspective of institutional reform, investment in research and development and human capital. The paper concludes that although the resources of the past successful TFP have decreased or diminished, further institutional reform, increasing investment in research and development and human capital, and strategies promoting indigenous innovation will become new engines for future TFP growth in China. As the country’s TFP is still at a low level compared with advanced economies, there is large scope for China to maintain relatively high TFP growth, although uncertainty and risk are associated with this process.

Trade Liberalization, domestic input and sustainability of agricultural TFP growth: A new Perspective Based on TFP growth structure

India’s decelerating wheat- and rice-yield growth rates have led to questions of whether India’s agricultural sector will be able to meet future food demands. To explore this issue, ERS researchers measure sector-level agricultural total factor productivity (TFP) growth and evaluate how public policies affected TFP from 1980 to 2008. During this period, substantial regional differences in TFP growth emerged: the Indian West and South achieved faster TFP growth than the rest of the country, largely due to rapid growth in horticulture and animal products. Of the policies hypothesized to stimulate TFP, India’s public agricultural research and higher education programs had the greatest effect on TFP growth, followed by public investments in irrigation infrastructure. These effects propelled TFP in Northern and Western India more than in the rest of the country. Groundwater irrigation from wells accelerated TFP more than surface-water irrigation from canals. Other drivers of TFP growth included research investments of international institutions and an emerging private sector. Public investment in rural education has had mixed effects, depending on education levels. These findings support an optimistic view that Indian agriculture will be able to meet the broadening spectrum of future food demands. Critical to that optimism, though, is continued innovation from public and private research systems, especially in seed development, and from irrigation and high-value-commodity production technologies.

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.

Under the strategy of rural revitalization, the development of digital inclusive finance is an effective way to alleviate the long-standing problem of "difficult and expensive financing" in the "three rural areas", and is an inherent requirement for achieving high-quality development of Chinese agriculture. Based on the panel data of Chinese provinces from 2011 to 2021, this paper adopts a three-stage SBM-DEA model to measure the total factor productivity of agriculture and analyzes the impact of digital financial inclusion on total factor productivity of agriculture. The study shows that, firstly, the development of digital inclusive finance plays a more significant role in enhancing total factor productivity in agriculture, and the depth of use plays the strongest contributing role among the sub-indicators. Second, there is heterogeneity in the effects of digital inclusive finance on agricultural total factor productivity in terms of time and geographical location. Third, the mechanism analysis shows that deepening human capital and regional innovation capacity can effectively drive the growth of agricultural total factor productivity. The research in this paper contributes to a deeper understanding of how agricultural total factor productivity is measured, and the theoretical mechanisms by which digital inclusive finance drives agricultural total factor productivity.

As China enters the twenty-first century the health of the agricultural economy will increasingly rely, not on the growth of inputs, but on the growth of total factor productivity (TFP). However, the tremendous changes in the sector—sometimes back and sometimes forwards—as well as evolving institutions make it difficult to gauge from casual observation if the sector is healthy or not. Research spending has waxed and waned. Policies to encourage the import of foreign technologies have been applied unevenly. Structural adjustment policies also triggered wrenching changes in the sector. Horticulture and livestock production has boomed; while the output of other crops, such as rice, wheat and soybeans, has stagnated or fallen. At a time when China’s millions of producers are faced with complex decisions, the extension system is crumbling and farmer professional associations remain in their infancy. In short, there are just as many reasons to be optimistic about the productivity trends in agriculture as to be pessimistic. In this paper, we pursue one overall goal: to better understand the productivity trends in China’s agricultural sector during the reform era—with an emphasis on the 1990–2004 period. To do so, we pursue three specific objectives. First, relying on the National Cost of Production Data Set—China’s most complete set of farm input and output data—we chart the input and output trends for 23 of China’s main farm commodities. Second, using a stochastic production frontier function approach we estimate the rate of change in TFP for each commodity. Finally, we decompose the changes in TFP into two components: changes in efficiency and changes in technical change. Our findings—especially after the early 1990s are remarkably consistent. China’s agricultural TFP has grown at a healthy rate for all 23 commodities. TFP growth for the staple commodities generally rose around 2% annually; TFP growth for most horticulture and livestock commodities was even higher (between 3 and 5%). Equally consistent, we find that most of the change is accounted for by technical change. The analysis is consistent with the conclusion that new technologies have pushed out the production functions, since technical change accounts for most of the rise in TFP. In the case of many of the commodities, however, the efficiency of producers—that is, the average distance of producers from the production frontier—has fallen. In other words, China’s TFP growth would have been even higher had the efficiency of production not eroded the gains of technical change. Although we do not pinpoint the source of rising inefficiency, the results are consistent with a story that there is considerable disequilibrium in the farm economy during this period of rapid structural change and farmers are getting little help in making these adjustments from the extension system.

The paper considers the role and determinants of capital formation in Chinese agriculture and, in particular, the effects of capital formation on agricultural total factor productivity (TFP) growth. The results show that capital investment in agriculture by both government and farmers has risen significantly in the past two and a half decades, particularly in recent years. As China remains in the early stages of agricultural policy transition, its political economy would suggest that there will likely be more public investment in, and more subsidies to, agriculture in the coming years. Increased public investment in agriculture appears to have also induced increased farmers' capital formation in agriculture. Credit policy, the overall growth of farmer's income, rural wages, and comparative advantage of commodities are important factors that may facilitate farmers' investment in agriculture. The results also show that the successful growth of China's agriculture has been associated with its high TFP growth. Both public and private agricultural capital formations have played an important role in raising China's agricultural productivity. The TFP decomposition analyses show that technological change is a primary driver of the TFP growth in China's agriculture.