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Title Predicting Structural Changes in Danish Agriculture
Author Gao, Eryu
Supervisor Christiansen, Lasse Engbo (Mathematical Statistics, Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Institution Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
Thesis level Master's thesis
Year 2011
Abstract In this thesis, different models are built to examine the structural change of the pig farms in Denmark and predict the farm distribution in 2030. At first, aggregate data are used in the modelling with only the number of farms in each size category from 1982 to 2009. Regression models are estimated and and make predictions, but the results do not accord with the practical experience. Then the Markov model is estimated using both generalised cross entropy (GCE) method and the ordinary least squares (OLS) method. The GCE estimator may give the results not as precise as the OLS, but when the data points are limited the GCE can always provides a robust estimation, but the OLS may have a large variance. And the predictions made by the Markov model are more plausile than the result from the regression model. Then the CHR data are used to estimate the transition probability matrix (TPM) in the Markov model. And both the time variation and regional effect of the estimated TPM are checked. It is concluded that the TPM can be supposed to be stationary while the TPM on the farms from different regions may vary. The estimated TPM are use to predict the farm distribution in 2030, and a restructuring of the pig farms are detected. Finally the spatial distribution of the pig farms are displayed to see the areal concentration of the pig farms of certain types.
Imprint Technical University of Denmark (DTU) : Kgs. Lyngby, Denmark
Series IMM-M.Sc.-2011-02
Fulltext
Original PDF ep11_02.pdf (25.33 MB)
Admin Creation date: 2011-02-03    Update date: 2011-02-03    Source: dtu    ID: 274707    Original MXD