Hazem Mohamed

University of Manouba, TUNISIA

Although there are claims that inequality in India has stagnated or even increased in the post-liberalization period, careful analysis of data shows that these views are mostly unsubstantiate. The main aspects of social inequality can be structured, to a large extent, along urban-rural and gender lines. In this paper, we explore a nonparametric approach to highlight the form of the long-term spatial associations of the georeferenced units. Relying on the method of Markov chains, we develop a stationary form for the Moran scatter plot, one of the techniques of the exploratory spatial data analysis. As an illustration, we highlight the forms of spatial autocorrelation and heterogeneity of long-term literacy rates in rural districts in India observed by the two censuses of 1991 and 2001. We use the same data to estimate a spatial β-convergence model. It appears that the growth of literacy rate is higher in rural districts with the lowest literacy and proceeds by spatial diffusion. Beyond his correspondence with the β-convergence model, the proposed nonparametric approach has the advantage of identifying the location of spatial associations

Stationary Spatial Associations, Regional Convergence, Exploratory Spatial Data Analysis, Spatial Econometrics, Literacy Rate, Rural Districts, India.

C14 ; C31 ; I24.

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VOLUME 04 ISSUE 03 MARCH 2021