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| Piet, Laurent. |
| 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... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Farm size distribution; Gibrat’s law; Markov Chain Model; Farm Management. |
| Ano: 2008 |
URL: http://purl.umn.edu/44269 |
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| Bougherara, Douadia; Gassmann, Xavier; Piet, Laurent. |
| 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... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Risk Attitudes; Field Experiment; Farming; Risk and Uncertainty; C93; D81; Q10. |
| Ano: 2011 |
URL: http://purl.umn.edu/114266 |
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| Piet, Laurent. |
| 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... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Agribusiness; Farm Management. |
| Ano: 2011 |
URL: http://purl.umn.edu/114668 |
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