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In census enumeration a person is counted as literate if he or she can read and write in any language with understanding. In earlier censuses the whole population has been classified into literates and illiterates. From 1951 the questions on literacy have been canvassed among those aged 5 and above only. Since 1991 this classification has been confined to the age group 7 years and above. As such these estimates of percent literate obtained from census documents are not strictly comparable over time. Census documents also contain total population and the number of literates among various population groups. Dividing the later by the former we obtained the estimates of literacy rates in total population – we have cetted General Literacy Rates which are comparable over time and various population groups under consideration. Discussion and analysis that follow are in terms of these estimates of literacy among population in all age groups. This paper makes a comparative assessment of relative performance of major states in growth of literacy during 1961 – 91 with emphasis on the performance of backward communities like Scheduled Castes (SCs) and Scheduled Tribes (STs). Even after prolonged efforts we have failed to make satisfactory progress in raising literacy among certain population groups. Education is a subject in the concurrent list with state government as the main actor. State policies and sociocultural factors have a bearing on the differential performance of the states and the population groups within the state. A comprehensive study of these factors and state policies iottowed so far is celled for.

Welfare judgements on distribution of income has often been made on the basis of weighted sum of individual incomes. Scholars proposed various axioms to determine the weights. The set of weights proposed by Chakrabarty (1982) led to a Social welfare function (SWF) involving the normalised Theil’s Entropy Measure. We have proposed a few alternative sets of weights here which lead to SWFs involving the Theil’s measure as such and a new measure of inequality. An alternative formulation leads to another pair of SWFs involving the Variance of Income Power. These SWFs are seen to have certain interesting properties and interpretations.

The success of anti-inflationary stabilization policy depends on the stable demand for money function. Recent developments in econometrics emphasize the need to verify the time series properties of the variables in the demand for money function. In studies with conventional approaches to the estimation of demand for money, this was taken for granted. In this paper, we test for the stability of the demand for money in India. Using cointegration and the corresponding error-correction approach we test for long and short-run relationships respectively. This paper concludes that both narrow and broad measures of money exhibit long-run-stable relationships with real income and the rate of interest. The results presented here have implications for the design of macroeconomic stabilization policy in India.