The evolution of farm size distribution: revisiting the Markov chain model

In this paper, a continuous version of the Markov Chain Model (MCM) is proposed to project the number and the population structure of farms. It is then applied to the population of professional French farms. Rather than working directly with transition probabilities as in the traditional, discontinuous, MCM, this approach relies on the close but not identical concept of growth rate probabilities and exploits the Gibrat’s law of proportionate effects which appears to be supported by the French data. It is shown that the proposed continuous MCM is a more general approach, since it enables to derive more in-depth detail on the distribution of the projected population and the traditional MCM transition probability matrix can be easily reconstructed from the estimated growth rate probabilities. Though the continuous MCM is presented in this paper in a stationary framework, it should be possible to develop a non-stationary version in a similar way traditional MCMs are now made non-stationary.Farm size distribution, Gibrat’s law, Markov Chain Model, Farm Management,

Assessing structural change in agriculture with a parametric Markov chain model. Illustrative applications to EU-15 and the USA

The Markov chain model (MCM) has become a popular tool in the agricultural economics literature to explain the past evolution of and simulate the future developments in the number and size distribution of farms. In this paper, I show that the way MCMs have been implemented by agricultural economists so far suffers from the fact that transition probabilities are estimated as almost independent variables (up to adding-up to unity constraints). The alternative parametric MCM I propose addresses the deriving issues since (i) it is parsimonious in terms of parameters; (ii) it can be estimated with simple econometric techniques; (iii) it reveals detailed information on the structural change processes at hand. Applying it to experimentally controlled data with noise shows that the proposed model behaves well and competes with the traditional approach without any significant shortcoming. Two illustrative empirical applications, one using data from the EU-15 Farm Accounting Data Network (FADN) and the other using data from the USA Agricultural Resource Management Survey (ARMS), reveal the rich information that can be derived regarding the economic size changes experienced annually by farms in both regions.Agribusiness, Farm Management,

Trends in the French commercial farm population

Knowledge and projection of farm numbers and the structure of their population is an important issue for agricultural economists and policy makers. Although Markov chain models have enjoyed decades of popularity in forecasting total farm numbers, they generally fail to provide a detailed insight of the farm population’s structure; to overcome this caveat we estimate a parametric distribution of the utilized agricultural area of French commercial farms. Our method provides detailed information on the structure of the population and accounts for the specificity of off-land farming. We also model the influence of variables such as the farm’s legal status, type of farming and farm holder’s age. The estimation leads to a relevant description of the entire population of professional farm. When compared with the 2005 Farm Structure Survey data, our simulations based on FADN data display a close match across a number of key variables.farm structures, farm size distribution, maximum likelihood and simulation

Mapping the Decoupling : Transfer Efficiency of the Single Farm Payment Scheme

This paper focuses on the question of the transfer efficiency of the SFP scheme and represents graphically the results of an analytical framework with the seminal Surplus Transformation Curve initiated by Josling (1974) and developed by Gardner (1983). The special feature of the SFP scheme resides in the paradox that exists between the tradability of the entitlements and the activation constraint that creates a particular link to the land. The main result is that redistributive effects between landowners and farmers depend on the total number of entitlements, so they have to be considered as a lever to increase the transfer efficiency of the scheme.Single Farm Payment, transfer efficiency, surplus transformation curve, Agricultural and Food Policy, Agricultural Finance,

Eliciting Risk Preferences: A Field Experiment on a Sample of French Farmers

We designed a field experiment involving real payments to elicit farmers’ risk preferences. Farmers are a very interesting sample to study since risk has always played an important role in agricultural producers’ decisions. Besides, European farmers may face more risky situations in the future. In this context, it is very important for any economic analysis focusing on agriculture to correctly assess farmers’ behaviour in the face of different sources of risk. We test for two descriptions of farmers’ behaviour: expected utility and cumulative prospect theory. We use two elicitation methods based on the procedures of Holt and Laury (2002) and Tanaka et al. (2010) on a sample of 30 French farmers. The experiment consists in asking subjects to make series of choices between two lotteries with varying probabilities and outcomes. We estimate parameters describing farmers’ risk preferences derived from structural models. We find farmers are slightly risk averse in the expected utility framework. In the cumulative prospect theory frame, we find farmers display either loss aversion or probability weighting, tending to overweight small probabilities and to underweight high probabilities. In our study, expected utility is not a good description of farmers’ behaviour towards risk.Risk Attitudes, Field Experiment, Farming, Risk and Uncertainty, C93, D81, Q10,

Trends in the French commercial farm population

.Knowledge and projection of farm numbers and the structure of their population is an important issue for agricultural economists and policy makers. Although Markov chain models have enjoyed decades of popularity in forecasting total farm numbers, they generally fail to provide a detailed insight of the farm population’s structure; to overcome this caveat we estimate a parametric distribution of the utilized agricultural area of French commercial farms. Our method provides detailed information on the structure of the population and accounts for the specificity of off-land farming. We also model the influence of variables such as the farm’s legal status, type of farming and farm holder’s age. The estimation leads to a relevant description of the entire population of professional farm. When compared with the 2005 Farm Structure Survey data, our simulations based on FADN data display a close match across a number of key variables.farm structures, farm size distribution, maximum likelihood, simulation

How the EU Single Farm Payment should be modelled: lump-sum transfers, area payments or… what else?

The 2003 Common Agricultural Policy (CAP) reform radically changes the way the European Union (EU) supports its agricultural sector by decoupling direct payments. Production is no longer required to get the payment attached to Single Farm Payment (SFP) entitlements. However, the new scheme maintains a specific link between payments and hectares; in addition, SFP entitlements can be exchanged among farmers. These features question the way SFP entitlements should be regarded, hence modelled, i.e., as lump-sum transfers, area payments or… something else. We develop a microeconomic analytical framework which shows that the answer crucially depends on the total number of entitlements which are initially made available relative to the number of hectares, more specifically the number of cultivated hectares in a zero support regime, the number of cultivated hectares in a policy support regime trough per-hectare direct aids, and the number of cultivated or idled hectares in a policy regime where support is granted through direct aids per hectare and production is not required.European Union, Common Agricultural Policy, Single Farm Payment, modelling, area payments, lump-sum transfers

Does land fragmentation affect farm performance? A case study from Brittany. Factor Markets Working Paper No. 40, April 2013

Agricultural land fragmentation is widespread and may affect farmers’ decisions and impact farm performance, either negatively or positively. The authors investigated this impact for the western region of Brittany, France, in 2007, regressing a set of performance indicators on a set of fragmentation descriptors. The performance indicators (production costs, yields, revenue, profitability, technical and scale efficiency) were calculated at the farm level using Farm Accountancy Data Network (FADN) data, while the fragmentation descriptors were calculated at the municipality level using data from the cartographic field pattern registry (RPG). The various fragmentation descriptors enabled the authors to account for not only the traditional number and average size of plots, but also their geographical scattering. They found that farms experienced higher costs of production, lower crop yields and lower profitability where land fragmentation (LF) was more pronounced. Total technical efficiency was not found to be significantly related to any of the municipality LF descriptors used, while scale efficiency was lower where the average distance to the nearest neighbouring plot was greater. Pure technical efficiency was found to be negatively related to the average number of plots in the municipality, with the unexpected result that it was also positively related to the average distance to the nearest neighbouring plot. By simulating the impact of hypothetical consolidation programmes on average pre-tax profits and wheat yield, the study also showed that the marginal benefits of reducing fragmentation may differ with respect to the improved LF dimension and the performance indicator considered. The analysis therefore shows that the measures of land fragmentation usually used in the literature do not reveal the full set of significant relationships with farm performance and that, in particular, measures accounting for distance should be considered more systematically