Multivariate Statistical Methodology to Uncover Regional Disparities: (Case Study: Yazd Province, Iran)

The aim of this paper is to present a methodology to classify the levels of a Province’s territory urban development. In order to support regional development policy, we focus on two main objectives: first, to identify dimensions that adequately summarize the information contained in a range of regional indicators; second, to look for homogeneous regions in terms of development. This classification isobtained through the use of multivariate statistical methods – factor Analysis (FA) and cluster analysis (CA), and is based on a wide number of demographics, economic, health, education, employment and culture indicators Yazd Province is used as the working example. Results lead to the identification of seven axes of characterization, and the division of the Yazd territory into three regions with differing degrees of development. The conducted urban safety factor analysis allows one to assess the level of livability and safety of an inhabited area. These findings are helpful for the urban sustainable development and resources management.

Keywords:

Multivariate data statistics , Factor analysis , Cluster analysis , urban safety development