INFRASTRUCTURAL DEVELOPMENT IN INDIA: PRE AND POST ...

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22 Kaur, G.; Ghuman, R.S.6. RESULTS OF REGRESSION ANALYSISTo work out the nature and magnitude of relationship between compositeindices of infrastructural development and its various determinants, the simpleregression analysis, with composite indices of infrastructural development asdependent variable and possible determinants as independent variable, has been carriedout. The results are given in table 6.Table 6. Results of Simple Regression Analysis with Composite Indices ofInfrastructural Development as Dependent Variable (2001-02)Variable ConstantReg. cuffr 2 F( T-value)(D f. 1, 13)DENP 0.70680.1171(0.3071)0.0072 0.09URBP 0.56250.2570*(3.885)0.5373* 15.09PMNSDP 0.38580.6172*(5.680)0.7128* 32.26GLR 0.66680.9922(1.142)0.0912 1.30VCVP 0.8331-0.1197(-0.990)0.00075 0.01PCPED -0.34900.9293*(3.787)0.5245* 14.34Source: As that in Table 1Note: 1. *significant at 1 percent level of significance, ** significant at 5 percent level of significance2. rdenotes coefficient of determination3. The data for VCVP pertains to thirteenth Lok Sabha elections held in Oct 1999The results highlight that only three variables viz., level of industrialization,level of urbanization and per capita public expenditure on development playedsignificant role in determining the level of inter-state variations in socio-economicinfrastructure during 2001-02. Multiple regression analysis has also been carried out toanalyse the joint effect of these individually significant determinants of infrastructuraldevelopment during 2001-02. The results have been given in table 7.Table 7. Res ults of Multiple (Step-Wise) Regression Analysis with Composite Indices ofInfrastructural Development as Dependent Variable (2001-02)Constant PMNSDP PCPED R 22FR (D.f.= 1,13)0.6172*32.260.3858 0.7128* 0.6907(5.680)(1, 13)0.4587*-0.57130.4569** 0.8004* 0.767224.07(4.064) (2.306)(2, 12)Note: 1. *significant at 1 percent level of significance, ** significant at 5 percent level of significance2. R 2 2denotes coefficient of determination and R denotes adjusted coefficient of determination
Infrastructural Development in India: Pre and Post Reform … 23The results show that during 2001-02, level of industrialisation, as measuredby PMNSDP, explained about 71 per cent of infrastructural variations across states.Inclusion of per capita public expenditure on development (PCPED) into the modelfurther raised the explanatory power of the model to 0.8004. The regression coefficientof per capita public expenditure on development (PCPED) is found to be significantlypositive. The inclusion of URBP into the regression model, however, reduced the valueof adjusted R 2 and therefore the variable URBP has been dropped from the regressionmodel.To sum up, the level of industrialisation and per capita public expenditure ondevelopment accounted for about 80 per cent of the observed variations in socioeconomicinfrastructure across states during the year 2001-02.7. SUMM<strong>IN</strong>G UPThe infrastructural disparities across 15 major states of India reduced duringthe decade of 1980s whereas the decade of 1990s witnessed increased disparities acrossstates in terms of socio-economic infrastructure. In other words, the infrastructuraldisparities across states increased during the post-reform period. This has beenindicated by the rise in the value of inequality measures of composite indices ofinfrastructural development during the post-reform period.The study highlights that the relative position of the states in terms of socioeconomicinfrastructure also stood, more or less, frozen at all three reference points, atleast at the upper and the lower level if not at the middle level. Punjab continued tooccupy the top most position in terms of infrastructural development throughout thestudy period followed by Kerala and Maharashtra. Further, infrastructural disparitiesare found to be highest within the less developed states as compared to the highlydeveloped and moderately developed states.The level of industrial development and per capita public expenditure ondevelopment emerged to be the significant explanatory variables for inter-statedisparities in socio-economic infrastructure. These variables, together, explained 80.04per cent of the observed variations in infrastructure during the year 2001-02.It is, thus, clear that in order to sort out the problem of inter-state disparities ininfrastructure, industrialization process of the backward states should be given dueconsideration. Public expenditure can also play a significant role in providing therequisite finance for this purpose which can finally help the lagging states to moveupward in terms of development.In the wake of negative employment elasticity in agriculture in India, thedevelopment of non-primary sectors becomes all the more important and theinfrastructure sector is the most promising sector amongst all other non-primarysectors. Deep inter-linkage between infrastructure and aggregate development alsolends credentials to the policy of developing socio-economic infrastructure in thelagging states of India.
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