


Registros recuperados: 12  

 

 


Jongeneel, Roelof A.. 
This paper analyses the impact of the dairy quota scheme on the size distribution of the Dutch dairy industry. A nonstationary Markov model approach is use, where the transition probabilities are explained by a set of exogenous (policy) variables. Using an information theoretical approach, a model is estimated for The Netherlands and used to simulate the impacts of alternative EU dairy policies. Several results emerged: a) There is an autonomous over time decline in farm numbers (implying increase in farm size). b) The dairy quota regime positively influences 'small' and 'medium' farm sizes; c) Abolition of the dairy quota will negatively affect the total number of active farms and favours further increase of farm scale. d) Targeting support according to... 
Tipo: Conference Paper or Presentation 
Palavraschave: Farm size structure; Dairy; Milk quota; Policy; Maximum entropy; Agribusiness. 
Ano: 2002 
URL: http://purl.umn.edu/24892 
 


Jongeneel, Roelof A.; Longworth, Natasha; Huettel, Silke. 
This paper analyses the dynamics in the farm size distribution for The Netherlands, Germany, Poland and Hungary. A (non)stationary Markov model approach is used. The transition probabilities are explained by a set of exogenous (policy) variables. The models are estimated using an information theoretical approach, including nonsample (prior) information. The models can be used to simulate the impact of alternative dairy policies on the dairy sector structure. For all countries there is an autonomous decline in farm numbers over time (implying increase in average farm size). This trend continues irrespective of the EU dairy policy type. For both Hungary and Poland the role of the subsistence sector is expected to substantially decrease over time. 
Tipo: Conference Paper or Presentation 
Palavraschave: Farm size structure; Dairy; Milk quotas; Policy; Maximum entropy; Livestock Production/Industries. 
Ano: 2005 
URL: http://purl.umn.edu/24772 
 


Stokes, Jeffrey R.. 
Data on the number of Pennsylvania dairy farms by size category are analyzed in a Markov chain setting to determine factors affecting entry, exit, expansion, and contraction within the sector. Milk prices, milk price volatility, land prices, policy, and cow productivity all impact structural change in Pennsylvania's dairy sector. Stochastic simulation analysis suggests that the number of dairy farms in Pennsylvania will likely fall by only 2.0 percent to 2.5 percent annually over the next 20 years, indicating that dairy farming in Pennsylvania is likely to be a significant enterprise for the state in the foreseeable future. 
Tipo: Journal Article 
Palavraschave: Dairy; Maximum entropy; Farm size; Markov chain; Simulation; Farm Management; Industrial Organization. 
Ano: 2006 
URL: http://purl.umn.edu/10218 
 

 

 

 


Howitt, Richard E.; Reynaud, Arnaud. 
In this paper we develop a dynamic dataconsistent way for estimating agricultural land use choices at a disaggregate level (districtlevel), using more aggregate data (regionallevel). The disaggregation procedure requires two steps. The first step consists in specifying and estimating a dynamic model of land use at the regional level. In the second step, we disaggregate outcomes of the aggregate model using maximum entropy (ME). The ME disaggregation procedure is applied to a sample of California data. The sample includes 6 districts located in Central Valley and 8 possible crops, namely: Alfalfa, Cotton, Field, Grain, Melons, Tomatoes, Vegetables and Subtropical. The disaggregation procedure enables the recovery of land use at the districtlevel with an... 
Tipo: Conference Paper or Presentation 
Palavraschave: Disaggregation; Bayesian method; Maximum entropy; Land use; Production Economics; C11; C44; Q12. 
Ano: 2002 
URL: http://purl.umn.edu/24961 
 


Lee, Joanne; Cho, Wendy K.; Judge, George G.. 
In 1881, Newcomb conjectured that the first significant digits (FSDs) of numbers in statistical tables would follow a logarithmic distribution with the digit “1” occurring most often. However, because Newcomb’s proposal was not presented with a theoretical basis, it was not given much attention. Fiftyseven years later, Benford argued for the same principle and showed it was relevant to a large range of data sets, and the logarithmic FSD distribution became known as “Benford’s Law.” In the mid1940s, Stigler claimed Benford’s Law contained a theoretical inconsistency and supplied an alternative derivation for the distribution of FSDs. In this paper, we examine the theoretical basis of the Stigler distribution and extend his reasoning by incorporating FSD... 
Tipo: Working or Discussion Paper 
Palavraschave: Benford's law; Stigler's law; Power law; Maximum entropy; Distance measures; Research and Development/Tech Change/Emerging Technologies; Research Methods/ Statistical Methods; C10; C24. 
Ano: 2009 
URL: http://purl.umn.edu/47000 
 


TOURNE, D. C. M.; BALLESTER, M. V. R.; JAMES, P. M. A.; MARTORANO, L. G.; GUEDES, M. C.; THOMAS, E.. 
Aim: Amazonnut (Bertholletia excelsa) is a hyperdominant and protected tree species, playing a keystone role in nutrient cycling and ecosystem service provision in Amazonia. Our main goal was to develop a robust habitat suitability model of Amazonnut and to identify the most important predictor variables to support conservation and tree planting decisions. Localization: Amazon region, South America. Methods: We collected 3,325 unique Amazonnut records and assembled >100 spatial predictor variables organized across climatic, edaphic, and geophysical categories. We compared suitability models using variables (a) selected through statistical techniques; (b) recommended by experts; and (c) integrating both approaches (a and b). We applied different... 
Tipo: Artigo de periódico 
Palavraschave: Expert knowledge; Maximum entropy; Model evaluation; Protected Amazonian species; Spatial filtering; Species distribution model; Conhecimento especializado; Entropia máxima; Avaliação de modelo; Análise de componentes principais; Filtragem espacial; Modelo de distribuição de espécie; Castanha; Principal component analysis. 
Ano: 2019 
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1114461 
 

 
Registros recuperados: 12  


