The paper illustrates a clusterwise regression procedure applied to the prediction of per capita disposal income (PCDI) in Italian municipalities. The municipal prediction is derived from the provincial PCDI taking into account the discrepancy between municipality and province in some indicators like per capita taxable income, per capita bank deposits, employment rate, etc. The relation between PCDI and indicators is shaped by a regression model. A single regression model doesn’t fit very well all territorial units, but different regression models do it in groups of them. The aim of clusteriwise regression is just that: detecting clusters where the correspondent regression models explain the data better than an overall regression model does. The application of the procedure to a real case shows that a significative reduction of the regression standard error can be achieved.

A Clusterwise Regression Method for the Prediction of the Disposal Income in Municipalities

CHIRICO, PAOLO
2013-01-01

Abstract

The paper illustrates a clusterwise regression procedure applied to the prediction of per capita disposal income (PCDI) in Italian municipalities. The municipal prediction is derived from the provincial PCDI taking into account the discrepancy between municipality and province in some indicators like per capita taxable income, per capita bank deposits, employment rate, etc. The relation between PCDI and indicators is shaped by a regression model. A single regression model doesn’t fit very well all territorial units, but different regression models do it in groups of them. The aim of clusteriwise regression is just that: detecting clusters where the correspondent regression models explain the data better than an overall regression model does. The application of the procedure to a real case shows that a significative reduction of the regression standard error can be achieved.
2013
Classification and Data Mining
Springer-Verlang
173
180
9783642288937
Clusterwise regression; per capita disposal income
Chirico, Paolo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/98955
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