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A Dimension Reduction Approach to the Study of City Family-income Distributions Via Sliced Inverse Regression

Author

Listed:
  • Aragon, Y.
  • Li, K.C.
  • Thomas-Agnan, C.

Abstract

Sliced inverse regression is a dimension reduction technique for exploring non-linear relationships between an output variable and a vector of input variables. Motivated by a data set of income distributions and economic indicators of french cities, we adress the problem of modelling a family of empirical distribution functions in terms of some covariates. SIR allows us to visually explore the ralationship between the covariates and several important features of the income distributions. A stochastic ordering is revealed for the French city income distributions.

Suggested Citation

  • Aragon, Y. & Li, K.C. & Thomas-Agnan, C., 1996. "A Dimension Reduction Approach to the Study of City Family-income Distributions Via Sliced Inverse Regression," Papers 96.438, Toulouse - GREMAQ.
    • Handle: RePEc:fth:gremaq:96.438
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    Keywords

    ECONOMETRICS;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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