Disparities and Regional Convergence of Literacy Rate in India: A Spatial Econometric Approach
University of Manouba, Tunisia

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Income growth and convergence also known as the catch-up effect has been studied extensively in the literature and become a topic of considerable interest in both developing and developed economies. The purpose of this paper is to study empirically the evolution of the disparities between Indian districts considering the spatial dependence and to explore a non-parametric approach for characterizing convergence of literacy rate. This study utilizes growth theory as the theoretical foundation to explore the convergence hypothesis. The methodology consists in identifying the shape of the long run spatial associations through the use of Markov chains which make it possible to derive a unique stationary distribution. The results of the analysis indicate the persistence of regional disparities and the importance of geography to explain the global convergence process with positive spatial spillover effects. The proportion of high-income districts surrounded by similar districts has significantly increased detrimentally to the other spatial associations. This non-parametric approach complements the standard parametric method (absolute and conditional Beta-convergence) which shows that convergence process can be accelerated by beneficial spatial interaction effects. These results have strong policy implications with regard to national and territorial policies in these districts.


Spatial Econometrics, Stationary Moran Scatter Plot, Exploratory Spatial Data Analysis, Regional Convergence, Indian Literacy, Markov Chain.


1) Ahamed. A. M (2014). Disparities in Literacy Rate of Dalits in Karnataka – An Inter- District Level Analysis. Scholarly Research Journal for Interdisciplinary Studies, 2014, vol 2.

2) Ambert. M , Chapelle. K (2003). Education, dualisme régional et développement économique : le cas de 14 Etats indiens (1970-1993). Revue Région et Développement, n 17, 2003.

3) Anselin. L (1988). Spatial Dependence and Spatial Structural Insta-bility in Applied Regression Analysis. Journal of Regional Science, 30, 185-207.

4) Anselin. L (1992). Spatial data analysis with GIS: An introduction to application in the social sciences. Technical Report, 92-10.

5) Anselin, L. (1995). Local Indicators of Spatial Association – LISA. Geographical Analysis 27, 93-115.

6) Anselin. L(1998). Interactive techniques and exploratory spatial data analysis. Techniques, Management and Applications, Wiley, New York.

7) Anselin. L (2001): Spatial Econometrics. Working paper in Regional Science.

8) Anselin. L & Bera.A (1998). Spatial dependence in linear regression models with an introduction to spatial econometrics. Handbook of Applied Economics Statistics, 237-290.

9) Anselin. L & Florax. R (1995). New Directions in Spatial Economet-rics, Springer, Berlin.

10) Aten. B (1996). Evidence of spatial autocorrelation in international prices. Review of Income and Wealth, 42, 149-163.

11) Aten. B (1997). Does space matter? International comparisons of the prices of tradable and non-tradable. International Regional Science Review, 20, 35-52.

12) Bailey.T , Gatrell. A (1995). Interactive Spatial Data Analysis, Long-man, Harlow.

13) Baumont. C, Ertur. C & Le Gallo. J (2000). Convergence des régions européennes : Une approche par l’économétrie spatiale. Revue d’Economie Régionale et Urbaine, 2002, vol. 2, pp. 203-216.

14) Biswas. B (2016). Regional disparities pattern of literacy in rural and urban area of west Bengal, India. Global Journal Of Multidisciplinary Studies, 2016, vol 5.

15) Bernard. A , Durlauf. S (1996). Interpreting Tests of the Convergence Hypothesis. Journal of Econometrics, 71, 161-173.

16) Bourdin. S (2013). Pour une approche géographique de la convergence-Les inégalités régionales dans l’Union Européenne et leur évolution. L’espace géographique.

17) Cliff. A , Ord. K (1981). Spatial Processes, Models and Applications. Pion, Londres.

18) Cressie. N , Ngai. H (1989). Spatial Modelling of Regional Variables . Journal of the American Statistical Association, 84, 393-401.

19) Durlauf. S , Johnson. P (1995). Multiple Regimes and Cross-Country Growth Behavior. Journal of Applied Econometrics, 10.

20) Englemann. F , Walz (1995). Industrial Centers and Regional Growth in the presence of Local inputs. Journal of regional science, 35, 1027-1049.

21) Ertur. C, Thiaw. K (2005). Croissance, capital humain et interactions spatiales : une étude économétrique. Université de Bourgogne, Pôle d’Economie et de Gestion.

22) Ferrer. E (2017). Regional convergence and productive structure in Iberian regions: A spatial approach, Revista Portuguesa de Estudos Regionais, nº 47.

23) Flahaut. B, Mouchart. M, Martin. E ,Thomas. I (2002). The local spatial autocorrelation and the Kernel method for identifying zones: A comparative approach. Journal of Accident Analysis and Prevention, 35, 991-1004.

24) Fukuda. S, Okumura. K (2020). Regional convergence under declining population: The case of Japan. Japan and the world Economy, Elsevier, vol 55 .

25) Haining. R (1990). Spatial Data Analysis in the Social and Environ-mental Sciences, Cambridge University Press, Cambridge.

26) Hubert. L, Golledge. R , Costanzo. C, Gale. N (1985). Measuring association between spatially de…ned variables: an alternative procedure. Geographical Analysis, 17, 36-46.

27) Hill. R, Knight. J , Sirmans. C (1997). Estimating capital asset price indices. Review of Economis and Statistics ,78; 226 233:

28) Kourtellos , Mankin. A (2001). The Local Solow Growth Model. Eu-ropean Economic Review,45.

29) Kuma. J. K (2020). Comprendre la convergence économique : résumé théorique et revue de littérature. Note technique n°002/CER3/12-19 du CER-3/CREQ, décembre.

30) Jayet. H (1993). Analyse Spatiale Quantitative : Une introduction, Economica.

31) Juan. W, Mingming. H , Joao. F. D (2019). The impact of regional convergence in energy-intensive industries on China’s CO2 emissions and emission goals. Energy Economics, vol 80, 512-523.

32) Laura. B (2006). Initiative pour l’alphabétisation : savoir pour pouvoir, perspectives et stratégie, UNESCO.

33) Le Gallo. J (2001). Econométrie spatiale, Hétérogénéité spatiale. Document de travail du LATEC, Dijon, n 2001-01 (Janvier 2001).

34) Le Gallo. J (2002). Econométrie spatiale : L’autocorrélation spatiale dans les modèles régression linéaire. Economie et prévision, 155, 139-157.

35) LeSage. J (1999a). Spatial Econometrics, Webbook of Regional Science.

36) LeSage. J (1999b). Bayesian estimation of limited dependent variable spatial autoregressive models, Geographical Analysis, 32, 19-35.

37) Lesage. J , Pace. K (2004). Spatial and Spatiotemporal Econometrics, Advances Econometrics, vol 18.

38) Liu. Z , Stengos. T (1999): Non-linearities in Cross-Country Growth Regressions: A Semiparametric Approach. Journal of Applied Econometric, 14.

39) Manier. B (2006). Quand les femmes auront disparu. L’élimination des filles en Inde et en Asie.

40) Marie. B (1999). L’Inde et la Chine : problèmes démographiques et fécondité. 8emeCongrès International. Liver Development, gene regulation and disease, Palazzo del Popolo Orvieto, Italie, 2-5 juin 1999.

41) Mehta. C (2001). Impact of Primary Education on Literacy: An Analysis of Census 2001 Preliminary Data , Seminar on Progress of Literacy in India: What the Census 2001 Prevails.

42) Ord. (1975). Estimation methods for models of spatial interaction. Journal of the American Statistical Association, 70, 120-126.

43) PNUD, Human Development Report, 2005.

44) Upton. G , Fingleton B (1985). Spatial Data Analysis by Example. vol 1, John Wiley, New York.

45) Véron. J (2006). Stabiliser la population de l’Inde: plus facile à dire qu’à faire. Population et Sociétés, Bulletin mensuel d’information de l’institut national d’études démographiques.

46) William. M , Anthea. B (2005). A Spatial Econometric analysis of the irreversibility of long-term unemployment in Australia. Centre of Full Employment and Equity. The University of Newcastle, Callaghan NSW 2308, Australia.

47) Xie.Y, Hunter. B , Bao. S (2000). Exploratory Spatial Data Analysis with Multi-Layer Information. Work Site Alliance-Community Based GIS Education.

48) Zachary. S, Harper. A. (2013). Spatial Econometric Analysis of Regional Income Convergence: The Case of North Carolina and Virginia. International Journal of Economics and Business Research, Vol 8.


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