Dairy farming on permanent grassland: Can it keep up?

Abstract

Based on an extensive data set for southern Germany, we compared the productive performance of dairy farms that operate solely on permanent grassland and dairy farms using fodder crops from arable land. We allowed for heterogeneous production technologies and identified more intensive and extensive production systems for both types of farms, whereby we based our notion of intensive versus extensive dairy production on differences in stocking density and milk yield per cow and year. To be able to compare the productivity levels and productivity developments of the various groups of farms, we developed a group- and chain-linked multilateral productivity index. We also analyzed how technical change, technical efficiency change, and a scale change effect contribute to productivity growth between the years 2000 and 2008. Our results revealed that permanent grassland farms can generally keep up with fodder-crop farms, even in an intensive production setting. However, extensively operating farms, especially those on permanent grassland, significantly lag behind in productivity and productivity change and run the risk of losing ground.

Grasslands—more important for ecosystem services than you might think

“…Furthermore, grassland dairy and meat production systems may not necessarily have the large climate effects attributed to intensified meat production based on cropland (Soussana et al 2010, Peyraud 2011, Bellarby et al 2013. Grasslands, because of their lower productivity, will probably not be able to fully substitute for cropland-based meat production to meet projected trends of increased meat demand globally (Garnett 2011, Kellermann andSalhofer 2014). However, with diet changes toward lower cropland meat consumption in developed countries and increasing concern about mitigating climate change and developing sustainable agricultural production systems, grasslands have great potential to contribute to food security, along with other important benefits related to biodiversity and a range of ES (see, e.g., Bullock et al 2011, Garnett 2011.…”

Latent Class Modelling for a Robust Assessment of Productivity: Application to French Grazing Livestock Farms

“…Here we provide a methodological contribution by extending the LCSFM to estimate productivity and its components with robust indices. While a few studies have examined TFP change of intensive and extensive farming systems using LCSFM (Alvarez and del Corral, 2010;Kellermann and Salhofer, 2014), none of those studies have used the new class of 'proper' productivity indices (which includes the Färe-Primont, the Geometric Young and the Lowe indices 2 ) that satisfy more axioms (O'Donnell, 2018). Among those axioms, the transitivity property allows for multi-lateral and multi-temporal comparisons.…”

“…Among those axioms, the transitivity property allows for multi-lateral and multi-temporal comparisons. As shown by O'Donnell (2011), chained indices, as proposed for example by Kellermann and Salhofer (2014), fail to satisfy the identity property. We extend the Färe-Primont productivity index to the LCSFM.…”

Technological Change in Dairy Farming with Increased Price Volatility

“…Our main interest lies in the estimates of technological change. On average for the whole sample period, specialised farms realised technical progress at a rate of 1.0% per year (Table 3), which is in line with the results of other studies (Emvalomatis, 2012; Cechura et al ., 2017; Kellermann and Salhofer, 2014). However, when examining the estimated rate of technological change per year, we see a slowdown in technological change.…”