Skip to main content
SpringerLink
Log in

Analyzing spatial variations in farm income distributions—a multivariate approach

  • Published:
The Annals of Regional Science Aims and scope Submit manuscript

Abstract

Many studies have explored the size distribution of income, but empirical analysis has usually involved the examination of statistics which, in effect, summarize characteristics of the distribution, or the relation of a statistic (usually average income) to a set of explanatory variables.

The present study differs from previous empirical work by relating observations in specified income intervals to a set of explanatory variables. This multiple equation model appears to be an innovation in income distribution studies.

Census data on family unit income distributions by county were taken as observations on a set of dependent variables. Each income class interval is associated with a corresponding dependent variable. The dependent variable consists of the proportionate number or frequency of income units measured in percentage terms. For each dependent variable, then, there will be as many observations as counties reported.

Each of the dependent variables is related to a given set of independent variables using multivariate analysis. Observations on these variables are the same for all cases; that is, each dependent variable is related to the same set of independent variables.

The multivariate approach employed here allows an investigation of the behavior of a coefficient in each income class in turn. A good deal of additional information (relative to work with income class averages and economic development) is thereby generated. The model was estimated for two time points on California data. The paper includes an interpretation of the results for several independent variables including education and location, and also some comparisons of the results over time.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Anderson, T. W.An Introduction to Multivariate Statistical Analysis. New York: John Wiley and Sons, Inc., 1958. 374 p.

    Google Scholar 

  2. Elsner, Gary and Irving Hoch.Analyses of California Farm Income Relationships. Giannini Foundation Research Report No. 297, Giannini Foundation of Agricultural Economics, Berkeley, California, August 1968, 100 p.

    Google Scholar 

  3. O'Regan, William Gerard. “An Experimental Approach to the Determination of Demand for Orange Concentrate.” (Unpublished Ph.D. dissertation, Department of Agricultural Economics, University of California, Berkeley, 1962, 74 p.)

    Google Scholar 

  4. Schultz, Theodore.The Economic Organization of Agriculture. New York: McGraw-Hill Book Co., Inc., 1953.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Pacific Southwest Forest and Range Experiment Station, Forest Service, Berkeley, California

    Gary H. Elsner (Project Leader of Forest Recreation and Landscape Management Research)

  2. Resources for the Future, Inc., Washington, D. C.

    Irving Hoch (Research Associate)

Authors
  1. Gary H. Elsner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Irving Hoch
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Elsner, G.H., Hoch, I. Analyzing spatial variations in farm income distributions—a multivariate approach. Ann Reg Sci 7, 13–22 (1973). https://doi.org/10.1007/BF01283481

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01283481

Keywords

Search

Navigation