Catching Up or Falling Behind in European Agriculture: The Case of Milk Production

The paper explores and analyses the catching up and falling behind processes in the European dairy sector over the period 2004–2011, using a stochastic metafrontier multiple output distance function for 24 EU Member States. The metafrontier estimates reveal considerable productivity differences in milk production across the EU at the regional (NUTS‐2) level. Milk yield per cow is the highest in the old Member States, especially in those regions located in the northwest of the EU, while the lowest productivity is observed in Eastern Europe. The same structure was found for both the TFP (Total Factor Productivity) levels and TFP growth. Moreover, the results for technical change suggest that farm sizes are not optimal in many regions in Central and Eastern Europe from a dynamic perspective. The comparative analysis suggests that in the new compared to the old Member States, fewer farms could benefit from the movement of the frontier. Moreover, there are no signs that poorly performing farms are catching up with the best performing farms in the EU regions/countries.     

Assessing Total Factor Productivity Growth in Sub‐Saharan African Agriculture

The importance of the agricultural sector in the economic development process is well known. Improvements in agricultural productivity are often found to spill into other areas of a developing economy, potentially improving the standards of living of urban and rural workers alike. Given the importance of this sector, accurate measures of total factor productivity (TFP) across countries can be helpful in identifying conditions, institutions or policies that promote agricultural development. In this article, we estimate TFP growth in agriculture for a panel of 39 sub‐Saharan African countries from 1961 to 2007. We also develop a set of development outcome measures theoretically consistent with strong agricultural performance to serve as external validation of our results. We find that three estimation methods (stochastic frontier, generalised maximum entropy, and Bayesian efficiency) generate relative rankings that are consistent with the development outcome measures, providing external validation of the methods. However, the data envelopment analysis approach performs poorly in this regard.     

Impacts of Norwegian Milk Quotas on Output Growth: A Modified Distance Function Approach

Quota regulations that prevent output expansion of farms and reallocation of output between farms can cause lower growth in output and productivity. The aim of this study was to explain the output growth rate of Norwegian dairy farms since 1976, and to decompose it into output, input, socioeconomic and technical change components. Instead of using the standard distance function approach for multi‐output technologies, we use a growth rate formulation, which automatically removes the farm‐specific effects. This formulation also helps to impose non‐negativity constraints on marginal products of inputs (input elasticities), which are often violated for many observations, especially when flexible functional forms are used. The farm‐level panel data cover three periods: before the quota scheme was introduced (1976–1982); the period with the most output‐restricting quota scheme (1983–1996); and the period with a more flexible quota scheme (from 1997 onwards). Results show that the milk quota regulations had a significant constraining effect on output growth, in particular on milk output in the period 1983–1996. Furthermore, the output mix has shifted towards meat production for the average farm. What emerges from this study is that output growth and technical change are negatively influenced by policy aims where productive performance has not been the primary objective, and that there is scope for increased farm growth if the quota regime is liberalised.     

The influence of weather conditions on dairy production

Relatively little attention has been paid in the economics literature to the effects of meteorological conditions on milk production. Meteorological variables can be expected to affect milk production through their impact on the productivity of cows and the production of foodstuff. Rather than including meteorological variables as inputs in the milk production process, we propose a production function where these variables affect the productivity of cows and the production of forage, thereby indirectly affecting milk production. Using production and meteorological data from the Spanish region of Asturias corresponding to 383 dairy farms observed during a six‐year period from 2006 to 2011, the results from our estimated production function show that meteorological variables have a significant impact on milk production. We find that milk production is higher under warm weather conditions due to improvements in forage production.     

Agricultural Policies and Structural Change in French Dairy Farms: A Nonstationary Markov Model

The aim of this paper is to gain an understanding into how agricultural policies have affected structural change in the French dairy sector. A nonstationary Markov model is estimated using a Generalized Cross Entropy approach. Results show that while the price of cow's milk encourages farm growth, direct payments and quota restriction favor small farms. The price signal is a key factor of structural change. As a result, higher milk prices may accelerate the trend toward the further growth of dairy farms. Settlement policy and technical change seem not to slow this trend.     

Tracing the evolution of the aggregate U.S. milk supply elasticity using a herd dynamics model

The U.S. dairy sector is characterized by increasing volatility of milk prices, and consolidation in production as evidenced by declining number of dairy farms with an increasingly larger share of milk supplied from a small number of very large farms. Using aggregate national data, we build a mixed‐frequency herd dynamics econometric model of the U.S. milk supply that updates and substantially amends the model first proposed by Chavas and Klemme. We implement a dynamic residual‐based bootstrap technique that can be used in testing for changes in nonmarginal simulated long‐run supply responsiveness, and trace the evolution of long‐run milk supply elasticity from 1975 through 2010. Several papers in the past have suggested that long‐run supply elasticity increases with dairy farm size, which implies that increased importance of large farms would increase aggregate long‐run supply responsiveness. Contrary to this conclusion, we find a declining trend in long‐run supply elasticity from 1975 through 2005. Persistence of such a decline would be a major cause for worry, as ever larger price swings would be needed to equilibrate the market in face of demand shocks. However, we find that milk supply is becoming more responsive since 2005 both to milk and feed price changes. Increasing responsiveness to feed prices further justifies focusing the next generation of the dairy policy instruments on managing dairy profit margins rather than just revenue streams.     

Deregulation reforms,resource reallocation and aggregate productivity growth in the Australian dairy industry

Deregulation reforms in the Australian dairy industry had long‐lasting repercussions for Australian agriculture and the wider Australian economy. Using farm‐level data from 1979 to 2013, we investigate the effect of these reforms on productivity in the Australian dairy industry which arose from correcting resource misallocation between farms and across segregated state milk markets. Our results demonstrate that after the dairy reforms in 2000, relative market share shifted from less productive farms to more productive ones, and between farms using different production systems – generating additional productivity gains for the farm sector, but imposing some costs on downstream manufacturers by strengthening the seasonality of milk supply. Lessons from the Australian experience provide timely guidance for those countries exploring deregulation now or in the future to improve the industry‐level agricultural productivity growth through facilitating resource reallocation from less efficient to more efficient farms.     

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.     

Measuring productivity growth when technological change is biased–a new index and an application to UK agriculture

Productivity growth is conventionally measured by indices representing discreet approximations of the Divisia TEP index under the assumption that technological change is Hicks-neutral. When this assumption is violated, these indices are no longer meaningful because they conflate the effects of factor accumulation and technological change. We propose a way of adjusting the conventional TFP index that solves this problem. The method adopts a latent variable approach to the measurement of technical change biases that provides a simple means of correcting product and factor shares in the standard Tornqvist-Theil TFP index. An application to UK agriculture over the period 1953–2000 demonstrates that technical progress is strongly biased. The implications of that bias for productivity measurement are shown to be very large, with the conventional TFP index severely underestimating productivity growth. The result is explained primarily by the fact that technological change has favoured the rapidly accumulating factors against labour, the factor leaving the sector.     

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.     

Labor productivity measurement in Japanese agriculture, 1956–90

This paper investigates the factors responsible for a drastic decline in the growth rate of labor productivity of the agricultural sector for the 1956–90 period. This investigation is carried out by a newly devised procedure which decomposes the growth rate of labor productivity into (1) the total substitution effect which consists of the effects due to factor price changes and biased technological change, and (2) the TFP effect composed of the effects due to scale economies and technological progress. Based on empirical estimation of the translog cost function, it was found that the total substitution effect contributed to the growth of labor productivity much more than the TFP effect did for the period under question.     

The relationship between the ecologisation of farms and total factor productivity: A continuous treatment analysis

The European Green Deal aims to mitigate the environmental impact of food production while improving the income of primary producers and strengthening the EU's competitiveness. We examine how the degree of ecologisation affects farms' total factor productivity (TFP). Our analysis combines a random-parameter stochastic production frontier model with a composite indicator and a dose–response function approach. Results show a monotonically decreasing relationship between ecologisation and expected TFP level. On average, a one-step increase in the degree of ecologisation results in a 12% decrease in TFP. However, the results indicate a non-linear relationship. Three regions of the dose–response function can be distinguished; associated with high, medium and low degrees of ecologisation. In a region with a low degree of ecologisation, farms can increase the degree of ecologisation without reducing TFP. Both efficiency and technological differences contribute to these differences, but the main reason is technological. With increasing ecologisation, farm technology becomes more ‘land using’. Therefore, farms can increase their TFP and degree of ecologisation simultaneously by using land-saving technologies or through sustainable intensification.     

Internal and contextual drivers of dairy restructuring: evidence from French mountainous areas and post‐quota prospects

The end of the milk quota system in Europe has resulted in substantial structural changes to the dairy industry, calling its future into question, especially in mountainous areas. This study analyzes the internal and contextual factors that influence dairy restructuring in French mountainous areas. Three complementary logit models are used to specify farmer decisions (e.g., dairy production exit, stability, and growth). Original and exhaustive geo‐located administrative datasets are combined to create a farm longitudinal dataset and characterize farm‐restructuring patterns on a fine geographical scale. Farm size, corporate legal status, and specialization are positively associated with farm growth. Viable diversification strategies through either farm processing or agro‐environmental scheme contracting are also highlighted. Farm sustainability is supported by the economic success of the local industry and the propensity to adopt extensive practices. With respect to public policy, dairy policy appears to have the strongest impact. Thus, the liberalization of dairy policy threatens the future of dairy farming, particularly in areas with low milk density and no production under labels. This work calls for a policy that promotes the collective dimension of dairy farm performance. The current rural development policy alone may be insufficient to support farms’ long‐term sustainability.     

Scale Economies,Technical Efficiency,and the Sources of Total Factor Productivity Growth of Quebec Dairy Farms

Canada's average cost for milk production is among the highest in the world. This paper focuses on specific potential causes by estimating economies of scale and technical efficiency for a panel of Quebec dairy farms that spans the 2001–10 period. Additionally, this paper investigates the sources of total factor productivity growth. The stochastic frontier analysis, based on an input‐distance function, is used to estimate returns to scale relationships across dairy farms. The results show that there is significant economies scale to be exploited and that cost of production could also be reduced by improving technical efficiency. Accordingly, the paper indicates that input‐mix effect is the main source of total factor productivity growth. The results have important implications for Canada's supply management policy, and more specifically for the trading of production quota between dairy farmers, as well as for the delivery of targeted extension services.     

Growth of milk production in German dairy farms: an empirical study based on event history analysis

This article investigates determinants of growth of milk production in German dairy farms with the use of event history analysis. This methodology enables the analysts to consider time as a proxy for not measurable effects on growth. The likelihood of a farm's moving from a nongrowth episode into a growth episode is estimated and the impact of various covariates on that likelihood is assessed. The analysis is based upon a balanced panel of annual farm accounts from 616 specialized dairy farms in Germany, covering the financial years 1995/1996–2008/2009. The results from event history analyses are presented for low and high growth rates. For both groups, it was found that the probability of entering a growth episode, defined as the event to be analyzed, increases over time, e.g., as a consequence of an increasing need to improve competitiveness. Moreover, several covariates, such as the share of subsidies in returns, farmer's age, and milk price, had a significant impact on growth in a farm's milk production. The analysis revealed, however, that the effect‐direction of some explanatory variables differed between the two groups.     

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.     

Small U.S. dairy farms: can they compete?

The U.S. dairy industry is undergoing rapid structural change, evolving from a structure including many small farmers in the Upper Midwest and Northeast to one that includes very large farms in new production regions. Small farms are struggling to retain competitiveness via improved management and low‐input systems. Using data from USDA's Agricultural Resource Management Survey, we determine the extent of U.S. conventional and pasture‐based milk production during 2003–2007, and estimate net returns, scale efficiency, and technical efficiency associated with the systems across different operation sizes. We compare the financial performance of small conventional and pasture‐based producers with one another and with large‐scale producers. A stochastic production frontier is used to analyze performance over the period for conventional and pasture technologies identified using a binomial logit model. Large conventional farms generally outperformed smaller farms using most economic measures—technical efficiency, various profitability measures, and returns to scale.     

Convergence and divergence in regional agricultural productivity growth: evidence from Italian regions, 1951–2002

This article analyzes long‐term agricultural Total Factor Productivity (TFP) growth at regional level by testing its time‐series properties and identifying factors associated with divergence as opposed to convergence. The empirical application concerns Italian regions over the 1951–2002 time period. TFP growth decomposition ultimately attributes the observed productivity growth performance to these contrasting (convergence vs. divergence) forces. We find that technological spillovers are the key convergence force regardless of how the spillover effects are computed. At the same time, forces favoring convergence are almost offset by divergence forces (mainly scale or learning effects). This decomposition may explain the persistence of TFP growth rate differences in Italian agriculture, and could be applicable elsewhere.     

Measuring farm productivity under production uncertainty

This research introduces a novel empirical application to the assessment of farm productivity growth. While the existing research on productivity change has primarily focussed on ex post output observations, it has been shown that ignoring production uncertainty can lead to unreliable results. Using a state-contingent framework to represent the stochastic production environment, we extend the recent line of research that merged the state-contingent approach and efficiency measurement to productivity change using the Malmquist and Luenberger productivity indices. Using a balanced panel of 117 arable crop farms surveyed in 2011 and 2015, we show through the study results that productivity decreased, with technological regress being the major source of productivity change. Differences in productivity change between nonstochastic and stochastic modelling show the relevance to consider the state-contingent framework when assessing farms' productivity.     

Assessing the Impacts of Pillar 1 and 2 Subsidies on TFP in French Crop Farms

This article analyses the impact of common agricultural policy (CAP) subsidies on total factor productivity using a FADN dataset of French crop farms between 1996 and 2003. We first estimate a production function using a system GMM approach and then recover farm‐level total factor productivity (TFP). Further, the impact of Pillar 1 and 2 subsidies on TFP is investigated and results show that several subsidies have a negative impact on productivity during the period covered in the dataset. CAP reforms have also had an impact on the relationship between subsidies and productivity.