Productivity growth in Indian agriculture: is there evidence of convergence across states?

This paper explores the question of convergence in total factor productivity (TFP) in agriculture across fourteen major agricultural states of India. Using a Törnqvist–Theil index for TFP growth for the period 1973–1993, we find no evidence to support convergence to a single TFP level (σ‐convergence). After grouping the various states on the basis of their productivity performance, we find that the high‐performing states show a gradual movement towards the trend, whereas the low‐performing states generally show more volatility. Testing for long‐run convergence in levels of agricultural productivity, we find evidence of conditional beta‐convergence after controlling for state‐specific factors and idiosyncratic year‐specific volatility. The results are robust to alternative specifications of tests of unit root in panel data developed recently.     

Nonparametric estimates of productivity and efficiency change in Australian Broadacre Agriculture

This paper computes and decomposes Färe‐Primont indexes of total factor productivity of Australian broadacre agriculture by estimating distance functions. Using state‐level data from 1990 to 2011, the empirical results show that TFP grew at an average rate of 1.36 per cent per annum in the broadacre agriculture over the period 1990–2011. There are variations of total factor productivity (TFP) growth across states and fluctuations over time within each state and territory. However, overall, there is a clear movement towards slower TFP growth across the sample period. Further decomposition of TFP growth shows that it is declining growth in technical possibilities (technological progress) that is the main driver of the declining trend in productivity growth in broadacre agriculture in Australia.     

Asian Agricultural Productivity and Convergence

This paper measures agricultural total factor productivity (TFP), for eighteen Asian countries, from 1965 to 1996. TFP is measured by calculating the Malmquist index with respect to the sequential frontier, which is appropriate when the cross section is relatively small. The results show that half the countries have experienced negative productivity growth, due to losses in technical efficiency combined with stagnation in technological progress. Both cross‐section and time series tests show that there is no evidence of convergence in agricultural productivity for these countries. The less productive countries are falling further behind, rather than catching up. Finally, comparisons with Africa show that although Asia has had faster TFP growth than Africa, three of the five African regions (East, Central and Southern) have grown faster than any of the Asian regions.     

Explaining agricultural productivity growth: an international perspective

This article presents multi-output, multi-input total factor productivity (TFP) growth rates in agriculture for 88 countries over the 1970–2001 period, estimated with both stochastic frontier analysis (SFA) and the more commonly employed data envelopment analysis (DEA). We find results with SFA to be more plausible than with DEA, and use them to analyze trends across countries and the determinants of TFP growth in developing countries. The central finding is that policy and institutional variables, including public agricultural expenditure and proagricultural price policy reforms, are significant correlates of TFP growth. The most significant geographic correlate of TFP growth is distance to the nearest OECD country.     

Structural and productivity change in US agriculture, 1950–1982

This paper tests whether structural change in US agriculture is an important channel to TFP growth and evaluates the relative impact of (i) public research and education policies, (ii) private R&D and market forces, and (iii) government farm programs on structural change. We specify a structural econometric model, fit it to US state aggregate data, 1953–1982, and use the associated reduced‐form model to perform counter‐factual policy simulations. The findings include: structural change is a channel to TFP growth in both crop and livestock subsector, i.e. specialization, size, and part‐time farming do impact TFP, holding other variables constant. Public R&D and education have been at least as important as private R&D and market forces for changing livestock specialization, farm size, and farmers’ off‐farm work participation over the study period, but private R&D and market forces have been relatively more important for crop specialization. Changes in farm commodity programs had little impact on farm structure over these study period. Overall, we conclude that if public R&D and education policies had been unchanged at their 1950 values over 1950–1982, major structural changes in US agriculture would have occurred anyway. The forces of private R&D and market forces were at work, including a decline in the price of machinery services and agricultural chemicals, relative to the farm wage.     

Exploring the impact of R&D and climate change on agricultural productivity growth: the case of Western Australia*

This article empirically examines the impact of R&D and climate change on the Western Australian Agricultural sector using standard time series econometrics. Based on historical data for the period of 1977–2005, the empirical results show that both R&D and climate change matter for long‐run productivity growth. The long‐run elasticity of total factor productivity (TFP) with respect to R&D expenditure is 0.497, while that of climate change is 0.506. There is a unidirectional causality running from R&D expenditure to TFP growth in both the short run and long run. Further, the variance decomposition and impulse response function confirm that a significant portion of output and productivity growth beyond the sample period is explained by R&D expenditure. These results justify the increase in R&D investment in the deteriorating climatic condition in the agricultural sector to improve the long‐run prospects of productivity growth.     

Is a slowdown in agricultural productivity growth contributing to the rise in commodity prices?

A slowdown in the rate of agricultural productivity growth is thought by many observers to be contributing to the recent rise in agricultural prices. In this article I decompose sources of output growth in global agriculture into aggregate input and total factor productivity (TFP) components and examine whether productivity growth slowed substantially in the years leading up to the recent rise in commodity prices. Contrary to widely held perceptions, I find no evidence of a general slowdown in sector‐wide agricultural TFP, at least through 2006. If anything, the growth rate in agricultural TFP accelerated in recent decades. However, the results do show a slowdown in the growth of agricultural investment. Accelerating TFP growth largely offset decelerating input growth to keep the real output of global agriculture growing at about 2% per year since the 1960s. Regionally, however, agricultural productivity performance has been uneven. These findings have important implications for the appropriate supply‐side policy response to the current agricultural price crisis.     

The public R&D and productivity growth in Australia's broadacre agriculture: is there a link?

This paper investigates the dynamic relationships between research and development (R&D) expenditure and productivity growth in Australian broadacre agriculture using aggregate time series data for the period 1953 to 2009. The results show a cointegrating relationship between R&D and productivity growth and a unidirectional causality from R&D to TFP (total factor productivity) growth in Australian broadacre agriculture. Using the dynamic properties of the model, data from beyond the sample period are analysed by employing the variance decomposition and the impulse response function. The findings reveal that R&D can be readily linked to the variation in productivity growth beyond the sample period. Furthermore, the forecasting results indicate that a significant out‐of‐sample relationship exists between public R&D and productivity in broadacre agriculture.     

Six Decades of Total Factor Productivity Change and Sources of Growth in Bangladesh Agriculture (1948–2008)

This study applies the Färe–Primont index to calculate total factor productivity (TFP) indices for agriculture in 17 regions of Bangladesh covering a 61‐year period (1948–2008). It decomposes the TFP index into six finer components (technical change, technical‐, scale‐ and mix‐efficiency changes, residual scale‐ and residual mix‐efficiency changes). Results reveal that TFP grew at an average rate of 0.57% p.a. led by the Chittagong, Rajshahi, Rangpur, Dinajpur and Noakhali regions. TFP growth is largely powered by technological progress estimated at 0.74% p.a. Technical efficiency improvement is negligible (0.01% p.a.) due to stagnant efficiency in most of the regions. Decline in scale efficiency is also negligible (0.01% p.a.), but the decline in mix efficiency is high at 0.19% p.a. Decomposition of the components of TFP changes into finer measures of efficiency corrects the existing literature’s blame of a decline in technical efficiency as the main cause of poor TFP growth in Bangladesh. Among the sources, farm size, R&D investment, extension expenditure and crop specialisation positively influenced TFP growth, whereas the literacy rate had a negative influence on growth. Policy implications include encouraging investment in R&D and extension, land reform measures to increase average farm size, promotion of Green Revolution technology and crop diversification.     

Publicly-funded UK agricultural R&D and 'social' total factor productivity

Most studies concerned with measuring the rate of return to publicly‐funded agricultural R&D investment have found high returns, suggesting under‐investment, and calls for increased expenditure have been common. However, the evaluation of returns tends to measure the effect of research expenditure against growth in total factor productivity (TFP), based on market inputs and outputs. When compared against growing public unease over the environmental effects of pursuing agricultural productivity growth, TFP indices become a misleading measure of growth. This paper integrates some non‐market components into the TFP index. The costs of two specific externalities of agricultural production, namely fertiliser and pesticide pollution, are integrated in a TFP index constructed for the period 1948–1995. This adjusted, or ‘social’, TFP index is measured against UK public R&D expenditures. The rates of return to agricultural R&D are reduced by using the ‘social’ as opposed to the traditional TFP index. Whilst both remain at justifiable levels, previous studies appear to have over‐estimated the effect of agricultural R&D expenditures. Furthermore, with changes in policy towards more socially acceptable but non‐productivity enhancing outcomes, such as animal welfare, rural diversification and organic farming, the future framework for analysing returns to agricultural R&D should not be so dependent on productivity growth as an indicator of research effectiveness.     

Explaining the Decline in UK Agricultural Productivity Growth

This paper reports the results of a study of total factor productivity (TFP) growth in UK agriculture, from 1953‐2000. It shows that prior to 1984 TFP grew at 1.68% per annum and after that date at only 0.26%. International comparisons show that the UK has fallen far behind the leading EU countries. Yield growth declined even more and only labour productivity continues to grow rapidly. In part, the result is due to better data that incorporates more quality adjustment, but the real decline can be explained mainly by cuts in R&D, less patents, less growth in farm size and the demise of public extension. There are other negative factors, which have not been quantified, including asset fixity, convergence and ozone pollution, and a background argument that recent growth rates cannot be sustained.     

Is there a slowdown in agricultural productivity growth in South America?

This article estimates agricultural productivity growth in 10 South American countries in 1969–2009 with the objective of investigating if the slowdown being measured in other countries is present in the region. Results show that productivity growth accounts for half of the three‐fold increase in agricultural output during this period and that performance is sensitive to R&D investments in the sector. The slowdown found for the 1990s to 2000s in the U.S. and some European economies does not seem to be present yet in South America. The region's total factor productivity (TFP) growth rate increased steadily from 1.07% during the 1970s to 2.29% during the 2000s. Given lags in adoption and the adaptive nature of innovations in these economies, we have yet to see the potential effects in South American agriculture of decreases in R&D in advanced economies.     

Modeling the length and shape of the R&D lag: an application to UK agricultural productivity

This article updates total factor productivity (TFP) growth in UK agriculture from 1953–2005 and shows that public and private research and returns to scale explain TFP. Cointegration and causality tests are used to investigate the validity of attempts to explain UK agricultural productivity with R&D and related technology variables. Then, the length and shape of the lag structures are modeled and compared with the structures that are commonly imposed on the data. The rates of return (ROR) to R&D using the data determined lags differ considerably from those obtained by imposing lag shapes. These comparisons show that the ROR to public R&D are sensitive to the lag shape as well as its length and that the omission of other technology variables, such as mechanical and chemical patents pertaining to agriculture and farm size can bias the ROR.     

Efficiency and total factor productivity in Ukrainian agriculture in transition

This article analyzes efficiency and total factor productivity (TFP) change of large agricultural enterprises during their transition to a market economy in Ukraine. Efficiency is calculated by Data Envelopment Analysis and productivity change is measured by the Malmquist Productivity Change Index in the period between 1990 and 1999. On average, TFP declined by 6% annually, dropping a total 42%. The main reason for the observed TFP decline is a decrease in technical efficiency, which is found to be remarkably significant. At the same time there is a high variation among individual enterprises: the distribution of efficiency scores widens, which indicates that the farms diverge with respect to their economic performance. A Tobit regression analysis is conducted in which efficiency scores are related to factors such as farm type, farm size, initial conditions, and legal form.     

中国大宗淡水鱼养殖户技术效率、TFP增长及分解——基于25个省份微观调查数据

本文基于2011—2017年养殖户的微观调查数据,利用超越对数的随机前沿生产函数实证分析了大宗淡水鱼养殖户的技术效率、TFP增长及其分解。研究发现,(1)大宗淡水鱼养殖户的技术效率为0.827,表明养殖户的技术利用水平还存在较大的改进空间;(2)不同养殖规模对养殖户技术效率影响不显著,但专业化养殖对技术效率具有显著的正向影响;(3)养殖户TFP年均增长率为3.29%,且呈持续增长趋势;(4)养殖户TFP增长主要来源于技术进步,但技术效率的下降阻碍了TFP的增长;(5)技术效率和TFP增长都具有明显的区域性特征,总体表现为从西部到东部递减的趋势。     

Evaluating research and education performance in Indian agricultural development

India's agricultural research spending has long been regionally uneven. Regional research intensity ratios, which account for size differences, indicate research spending has consistently favored southern and western states over northern, central, and eastern ones. Farm production patterns have, however, changed in recent years and regional output growth is being driven by new commodity mixes. In this article, we ask which region had the highest factor productivity growth and rate of return to investments in public agricultural research and higher education. Our analysis relies on a 1980–2008 Indian agricultural production and policy data set together with a dual heteroscedastic production frontier to decompose total factor productivity (TFP) growth into formal technical progress and efficiency elements. The model's regional flexibility affords region‐to‐region comparison of multiple research return rates, TFP growth, and the elements influencing them. Regardless of return‐rate measure or allocation scenario evaluated, the North has enjoyed the highest return to research spending, and the Central and East the lowest. Factor productivity growth has however been strongest in the South, primarily on account of efficiency gains. Overall, though, the technical progress and productivity growth easily attributable to government‐supported research has accounted for about one‐quarter of the sector's TFP growth.     

District-level total factor productivity in agriculture: Western Cape Province, South Africa, 1952–2002

This article measures total factor productivity (TFP) growth in Western Cape agriculture for 31 magisterial districts from 1952 to 2002 to illustrate the benefits of disaggregation compared with national TFPs. There is negative or low growth in the eastern districts and rapid growth in the western districts. The regions with substantial chicken, pigs, dairy, and, especially, export fruit production grew rapidly, whereas the sheep-dominated Karoo had negative growth. Productivity growth correlates mostly with output mix, which in turn depends on irrigation investment. A similar program will be needed at the national level if prosperity is to be extended to black smallholders who currently lack access to water and other modern infrastructure.     

Technology catch-up in agriculture among advanced economies

We examine whether countries with low initial levels of agricultural total factor productivity (TFP) tend to ‘catch up’ with the technology leaders. We first compare relative levels of agricultural TFP, capital services and labour input levels in agriculture for 17 OECD countries between 1973 and 2011. Then we apply (conditional) convergence analysis to the panel data to examine the speed of convergence and test whether the convergence is transitory or permanent by analysing TFP changes over the business cycle. Capital intensities, quality improvement of capital, factors such as human capital spillovers, and certain agricultural policies are conditioning variables. We examine how differences in relative capital intensities affect agricultural productivity convergence over the business cycle. We find evidence that the speed of convergence increases during periods of contraction in economic activity.     

Three decades of productivity change in French beef production: a Färe‐Primont index decomposition

The Färe‐Primont index is used to evaluate total factor productivity (TFP) change and its components for a sample of French suckler cow farms in grassland areas in 1985–2014. The results reveal an increase in TFP of 6.6 per cent over the whole observation period, with technological progress being the major source of productivity growth. Meanwhile, efficiency decreased. Farms experienced great technological progress from 1991 to 2000. From a methodological point of view, the comparison with results obtained with Malmquist indexes shows similar trends but different magnitudes, with the Malmquist index overestimating the TFP and technological changes compared to the Färe‐Primont index. In addition, the use of a sequential approach that restricts technological change to being positive or null allows for the precise calculation of technology changes, disregarding the effects of external conditions that are captured in efficiency changes. Finally, the estimation of full dimensional efficient facets (FDEFs) that guarantees the positivity of all shadow prices used to assess the mix efficiency component of TFP change is promising.     

China's regional agricultural productivity growth in 1985–2007: A multilateral comparison1

In this study, we estimate total factor productivity (TFP) growth as well as multilateral TFP index for 25 contiguous China provinces over the 1985–2007 period. Agricultural output growth for each province was decomposed into TFP growth and input growth, where input growth was further disaggregated into contributions from growth of labor, capital, land, and intermediate goods. Over the study period, TFP growth contributed 2.7 percentage points to output growth annually, which was slightly higher than the input growth contribution of 2.4 percentage points per annum. On average, the annual rate of productivity growth peaked during 1996–2000, at 5.1%. It slowed in 2000–2005 to a rate of 3.2% per annum and declined in the most recent years (2005–2007) to ?3.7%. Differences in productivity among regions persisted over the entire period. The tendency toward faster TFP growth in relatively well‐off coastal regions may imply a widening of regional inequality.