Prediction of housing deficit in Mérida, Venezuela, by artificial neural networks

Gerardo A. Colmenares Lacruz () and Annjulie A. Gil Ruiz ()
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Gerardo A. Colmenares Lacruz: Ph. D., Profesor Titular. Facultad de Ciencias Económicas y Sociales. Instituto de Investigaciones Económicas y Sociales. Universidad de Los Andes. Núcleo Universitario Liria. Edif. G “Leocadio Hontoria” 3er. Piso, código postal 5101, Mérida, Venezuela. Teléfono: 0274-2401080.
Annjulie A. Gil Ruiz: Ingeniero de Sistemas. Vía principal Los Chorros de Milla. Centro Comercial Empresarial Villa Los Chorros. Piso 3 Oficina 3-8. Código postal 5101, Mérida. Venezuela. Teléfono: 0274-4148656.

Economía, 2010, vol. 35, issue 29, 109-140

Abstract: This work combines the tools of Radial Basis Function (RBF) and Multivariate Analysis to predict insufficient housing supply in the state of Merida, Venezuela. An alternative indicator to the commonly one used was built in order to evaluate this phenomenon. Data covering the number of families at the same house, house property, overcrowding level, housing physical condition, and public utilities condition were extracted from The Household Sampling Survey (HSS), 1994-2005. It is outstanding that RBF showed an acceptable level of effectiveness and capacity of adapting itself to this kind of problem. In general, results obtained during training and generalization stages reached very low average quadratic errors, a good level of success in the prognosis and robustness of the trained models.

Keywords: Qualitative deficit; quantitative deficit; multiple correspondence analysis; artificial neural networks; scores. (search for similar items in EconPapers)
JEL-codes: C67 C80 C83 C88 (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:ula:econom:v:35:y:2010:i:29:p:109-140

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