Does ‘Geography’ matter? Mapping the Spatial Dependence in Quality of Living (QOL) in India

Abstract For a long time, studies in social sciences focused on various dimensions but somehow talked less about the spatial dimension of inequality as well as the spatial dimension of quality of living in India. Therefore the primary objective of this study is modelling the spatial dependence of quality of living (QOL) across Indian districts using various spatial econometric tools. First of all we calculated quality of living index by using principal component analysis. Then we calculated descriptive statistics and used Choropleth mapping to understand the nature of variables distribution. After that, we used Moran’s I statistics and LISA statistics to understand global and local spatial dependence. Lastly, we used spatial error model to understand the spatial dependence with covariates. The high Moran’s I value suggests that the clustered nature of QOL across districts. LISA mapping reflects the localized nature of spatial clustering of QOL. It is evident from the SEM model that level of urbanization, workforce in service sector, female literacy rate and higher education have significantly positive impact on QOL. On the contrary, QOL decreased with the increasing concentration of SCs and STs population. It can be argued that geography plays a vital role in determining the spatial patterning of QOL of the districts of India. From the perspective of policy implication, spatially targeted policies and programmes are required. In this context, spreading economic development and the growth outcome to the districts having low QOL should be a primary step in the policy response.