The evidence on agricultural productivity growth and competitiveness

In the last decade, agricultural productivity growth has decreased in many high level countries, but it is strong in Brazil, China and South Africa, as well as in major transition economies. Situations are contrasted in developing countries and overall, there is no widespread evidence that Total Factor Productivity (TFP) growth is slowing. Rates of TFP growth at European Union level are variable by member state, as is the contribution of technical efficiency and technological progress. In OECD countries, labour productivity increased faster than land productivity as farm labour declined faster than farm land. At the global level, the growth rate of crop yields has declined in the last 15 years compared to previous periods, but at a different pace across commodity. Evidence on competitiveness in the agricultural and agri-food sector based on trade or cost-related measures is relatively scarce.

The recent surge of interest for productivity growth is primarily linked with concerns about the ability of the sector to meet higher food demand from a growing and richer population in the longer term, as well as higher demand for non-food use, rather than competitiveness per se. Given that land, water and other inputs are not infinite, there is a consensus that productivity growth is necessary. In this context, there is growing interest in returns from R&D expenditures on productivity growth and more general debate on the role of government in innovation systems. At the same time, improving the productivity, efficiency and competitiveness of individual farms and the sector remains an important objective of agricultural policies in many countries.

Earlier work showed that productivity growth had strong links with competitiveness. Studies were often carried out in the context of greater exposure to regional or global competition following policy reforms, multilateral trade negotiations, regional free trade agreements or EU enlargement. Some studies looked at long-term trends of productivity growth, while others at developments in more recent periods. The purpose of many studies was to draw information on relative competitiveness through comparing productivity growth rates over the same period across countries. Generally speaking, macro-level data has been widely used to examine the long-term trends of productivity growth across countries, while more recently farm-level data has been used to compare across farm types.

This chapter focuses on the most recent studies, while the tables in Annex A summarise the coverage, choice of indicator, and main results of many studies reported in Latruffe (2010). Long-term developments in total factor productivity (TFP) are first reported, then results of studies decomposing TFP change into technological change and technical efficiency change, and evidence from partial productivity indicators. Finally, studies using measures of relative competitiveness across countries or agro-food sub-sectors other than productivity are briefly reviewed. Most studies focus on agriculture with only a few on the agro-food sector (i.e. food processing industries).

As there is no consensus on how to measure agricultural TFP across countries, estimation methods in the reviewed literature, as well as sources of data, vary widely. There is thus limited scope for cross-country comparisons of TFP estimations across sources mentioned, with the exception of a few studies where consistent data collection and methodology has enabled comparison over time and across countries (e.g. Ball et al., 2010; Butault and Requillart, 2010). In addition, there are also some accounting problems related to data collection for the TI P measurement, in particular capital and labour used on farm, and output. For example, TFP measures in many previous studies do not take account of those outputs related to agricultural production not valued in the market because these outcomes are externalities or have public good characteristics. They use output estimates that are reported in official statistics (e.g. national accounts). Similarly, changes in the quality of soil and water may affect productivity but are difficult to measure.1

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