SABIIA - Sistema Aberto e Integrado de Informação em Agricultura (Sabiia)

Jongeneel, Roelof A..

This paper analyses the impact of the dairy quota scheme on the size distribution of the Dutch dairy industry. A non-stationary 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...

Spatial Disaggregation of Agricultural Production Data

Palavras-chave: Farm size structure; Dairy; Milk quota; Policy; Maximum entropy; Agribusiness.

Ano: 2002

URL: http://purl.umn.edu/24892

Howitt, Richard E.; Reynaud, Arnaud.

In this paper we develop a dynamic data-consistent way for estimating agricultural land use choices at a disaggregate level (district-level), using more aggregate data (regional-level). 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 district-level with an...

Dairy Farm Size Distribution in East and West: Evolution and Sensitivity to Structural and Policy Variables: Case-Studies of the Netherlands, Germany, Poland and Hungary

Palavras-chave: Disaggregation; Bayesian method; Maximum entropy; Land use; Production Economics; C11; C44; Q12.

Ano: 2002

URL: http://purl.umn.edu/24961

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 non-sample (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.

TRUNCATED REGRESSION IN EMPIRICAL ESTIMATION

Palavras-chave: Farm size structure; Dairy; Milk quotas; Policy; Maximum entropy; Livestock Production/Industries.

Ano: 2005

URL: http://purl.umn.edu/24772

Marsh, Thomas L.; Mittelhammer, Ronald C..

In this paper we illustrate the use of alternative truncated regression estimators for the general linear model. These include variations of maximum likelihood, Bayesian, and maximum entropy estimators in which the error distributions are doubly truncated. To evaluate the performance of the estimators (e.g., efficiency) for a range of sample sizes, Monte Carlo sampling experiments are performed. We then apply each estimator to a factor demand equation for wheat-by-class.

A Small-Sample Estimator for the Sample-Selection Model

Palavras-chave: Doubly truncated samples; Bayesian regression; Maximum entropy; Wheat-by-class; Research Methods/ Statistical Methods.

Ano: 2000

URL: http://purl.umn.edu/36391

Golan, Amos; Moretti, Enrico; Perloff, Jeffrey M..

A semiparametric estimator for evaluating the parameters of data generated under a sample selection process is developed. This estimator is based on the generalized maximum entropy estimator and performs well for small and ill-posed samples. Theoretical and sampling comparisons with parametric and semiparametric estimators are given. This method and standard ones are applied to three small-sample empirical applications of the wage-participation model for female teenage heads of households, immigrants, and Native Americans.

Stigler's approach to recovering the distribution of first significant digits in natural data sets

Palavras-chave: Maximum entropy; Sample selection; Monte Carlo experiments; Labor and Human Capital; Research Methods/ Statistical Methods.

Ano: 2001

URL: http://purl.umn.edu/25047

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. Fifty-seven 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 mid-1940s, 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...

PARAMETER ESTIMATION FOR A COMPUTABLE GENERAL EQUILIBRIUM MODEL: A MAXIMUM ENTROPY APPROACH

Palavras-chave: 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

Arndt, Channing; Robinson, Sherman; Tarp, Finn.

We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints. Second, it permits incorporation of prior information on parameter values. Third, it can be applied in the absence of copious data. Finally, it supplies measures of the capacity of the model to reproduce the historical record and the statistical significance of parameter estimates. The method is applied to estimating a CGE model of Mozambique.

Estimating State-Contingent Production Functions

Palavras-chave: Maximum entropy; Computable general equilibrium; CGE; Prior information; Mozambique.; Research Methods/ Statistical Methods; C51; C68.

Ano: 2001

URL: http://purl.umn.edu/42456

Rasmussen, Svend; Karantininis, Kostas.

The paper reviews the empirical problem of estimating state-contingent production functions. The major problem is that states of nature may not be registered and/or that the number of observation per state is low. Monte Carlo simulation is used to generate an artificial, uncertain production environment based on Cobb Douglas production functions with state-contingent parameters. The parameters are subsequently estimated based on different sizes of samples using Generalized Least Squares and Generalized Maximum Entropy and the results are compared. It is concluded that Maximum Entropy may be useful, but that further analysis is needed to evaluate the efficiency of this estimation method compared to traditional methods.

Entry, Exit, and Structural Change in Pennsylvania's Dairy Sector

Palavras-chave: Maximum entropy; State-contingent; Uncertainty; Production; Monte Carlo simulation; Production Economics; C13; C15; D80.

Ano: 2005

URL: http://purl.umn.edu/24529

Some Empirical Evidence on the Impact of Measurement Errors in Making Ecological Inferences

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

Palavras-chave: Dairy; Maximum entropy; Farm size; Markov chain; Simulation; Farm Management; Industrial Organization.

Ano: 2006

URL: http://purl.umn.edu/10218

Cho, Wendy K.; Judge, George G..

We seek to identify the impact of data measurement error problems in the context of ecological inference applications. We explore the statistical and substantive implications of using inaccurate proxy variables in the estimation and inference process. The focus of our analysis is on applications of ecological inference in cases involving the Voting Rights Act. We demonstrate our findings with a unique data set on racial registration and turnout in Louisiana and South Carolina.