CHAPTER IV CAUSALITY AND CONVERGENCE OF RURAL INFRASTRUCTURE AND RURAL DEVELOPMENT ACROSS DISTRICTS IN ASSAM

CHAPTER IV CAUSALITY AND CONVERGENCE OF RURAL INFRASTRUCTURE AND RURAL DEVELOPMENT ACROSS DISTRICTS IN ASSAM IV.1 Having explored and depicted the status of development and infrastructure in rural Assam across districts and over time, the background is now set up for proving whether there is a link between level of rural development and the state of rural infrastructure in the state. The present chapter is an attempt for such an exercise. IV.2 Interconnection between Rural Infrastructure and Rural Development At priori, it can be argued that improvement in rural infrastructure facilities influences rural development positively. At the same time, rural infrastructure provision may also be influenced by rural development achieved in both current and past periods. This mutually reinforcing nature of relationship between rural infrastructure and rural development gives scope of formulating a simultaneous equation model as described in the next section. The regression analysis on the simultaneous equation model may be of use in establishing the inter-relation between these two areas. Another question pertinent in the dynamics of rural infrastructure and rural development inter-dependence is whether there is a tendency towards convergence 1 in both these two aspects. Hence, a section in this chapter has also 1 In Economics, the idea of convergence indicates to the perception that the per capita income of the poorer economies will tend to grow at faster rates than that in the richer economies as result of which all 86

been devoted to exploring the signs and significance of convergence or otherwise in rural infrastructure improvement and overall rural development. IV.2.1 Formulation of Simultaneous Equation Model In context of the present study, indices of rural development and rural infrastructure have been formulated following broadly the principles outlined in the UNDP Human Development Report, 2010 (UNDP 2010) for construction of the Human Development Index. For this purpose, districts are given scores for any attainment out of the scale of difference between the maximum attainment and the minimum attainment among the districts recorded in the reference period of 2001 to 2011. However, attainment indicators have to be changed because of non-availability of comparable data for the two time points of the present exercise. For instance, in the rural development index, instead of life expectancy rural sex-ratio in 0-6 age group has been taken as the health indicator and rural literacy rate has been taken as the indicator of educational attainment. As per UNDP methodology, log value of per capita agricultural district domestic product at constant prices of a district rather than the per capita agricultural district domestic product itself has been taken as the indicator of standard of living. Component indices have been compiled to a rural development index by taking their geometric mean (refer annexure IV.A for technical notes). As for rural infrastructure, the focus of the present exercise was on rural roads, rural economies would ultimately converge in terms of per capita income. Such convergence may be of two types. While σ-convergence refers to the countries converging to the same rate of growth, β- Convergence refers to countries converging to their own steady state long run growth rate. 87

electricity supply and rural tele-connectivity the critical non-specific components of infrastructure. However, the final index have to be based on only roads as reliable and comparable data on the other two components could not be obtained for both the time points. The process of construction of the rural road-cum-infrastructure index has been elaborated in Chapter III (Section III.3.1). To investigate the inter-relationship between rural infrastructure and rural development, the following simultaneous equation model has been formulated. Y 1i = F(X 1i, X 0i, Y 0i )...(1) X 1i = ψ(y 1i, Y 0i, X 0i )...(2) Where Y 0i and Y 1i are rural development indices for the i-th district at the starting and the end time points respectively and X 0i and X 1i respectively are the corresponding rural infrastructure indices. The rational for including the lagged dependent variable as regressors arises from the fact that a district which was relatively more developed in either rural infrastructure or rural development status can be expected to retain the higher value of the respective dependent variables. Since the dependent variables are bounded in the range 0 to 1, a linear specification of the equations (1) and (2) will not be appropriate. Hence, the following Logistic functional forms have been adopted: 88

= = ( )...(3) ( )...(4) where, α i and γ i s are the parameters to be estimated and u i and v i are the disturbances. Applying logit transformation, equations (3) and (4) can be linearised in parameters. Carrying out the transformation, we get the following two equations: =log = + +! + " +#...(5) $ =log % % =& +& +&! +& " +'...(6) After the transformation, the model does not strictly remain a simultaneous equation model and hence can be estimated by OLS. However, as Z 1i has been constructed entirely on the value of the original dependent variable Y 1i and W 1i has been constructed on the value of the other original dependent variable X 1i, the inherent simultaneity in equations (5) and (6) cannot be ruled out. Therefore the equations have been estimated by both OLS and 2SLS methods but the results of both the methods have been found similar. IV.2.2 Formulation of Convergence Model In order to investigate whether convergence is taking place in both rural infrastructure improvement and rural development process in Assam, the following two equations have been formulated as done by Young et al (2008): 89

log % % =( +( )*+( )+,...(7) log =(!+( " )*+( )+-...(8) where, β i s are the parameters to be estimated and µ i and ε i are the disturbances. The sign and significance of the estimated coefficients of the explanatory variables will give idea whether β-convergence is taking place. If the estimated coefficient is negative and significant, β-convergence is said to take place. On the other hand, positive and significant estimated coefficient would suggest divergence instead of convergence to take place. However, insignificant coefficient of either sign would suggest neither convergence nor divergence. IV.3 Status of Rural Infrastructure and Rural Development in Assam IV.3.1 Status of Rural Infrastructure Table 4.1 presents the availability of rural infrastructure as indicated by the overall infrastructure index across districts of Assam. The road index and the electricity index have been taken from chapter III (sections III.3.1 & III.3.2). The Overall infrastructure index has been calculated using the following formula:.'/01)) 345/6= 78*15345/6 :)/;<0=;=<> 345/6 Inter-district variations in rural infrastructure facility across districts in Assam can be easily observed from the table below. As per the overall infrastructure index, rural infrastructure facilities have been found the highest in Jorhat followed by Kamrup, Nagaon and Golaghat districts. The district of Kokrajhar has been found at the 90

bottom in terms of rural infrastructure availability. The status of rural infrastructure in the Barak valley districts is also not encouraging. Table 4.1: Indices of Rural Infrastructure across Districts of Assam District Road Index Electricity Index Overall Index Dhubri 0.071 0.834 0.243 Kokrajhar 0.087 0.368 0.179 Bongaigaon 0.139 0.873 0.348 Goalpara 0.228 0.920 0.458 Barpeta 0.059 0.848 0.224 Nalbari 0.107 0.887 0.308 Kamrup 0.338 0.792 0.517 Darrang 0.038 0.949 0.190 Sonitpur 0.223 0.700 0.395 Lakhimpur 0.164 0.752 0.351 Dhemaji 0.300 0.379 0.337 Morigaon 0.287 0.671 0.439 Nagaon 0.286 0.848 0.492 Golaghat 0.251 0.943 0.487 Jorhat 0.427 0.982 0.648 Sibsagar 0.359 0.307 0.332 Dibrugarh 0.213 0.506 0.328 Tinsukia 0.136 0.973 0.364 Karbi Anglong 0.420 0.536 0.474 N. C. Hills 0.463 0.239 0.333 Karimganj 0.066 0.505 0.183 Hailakandi 0.084 0.932 0.280 Cachar 0.043 0.835 0.189 Source: Basic data taken from Statistical Hand Book Assam, 2011, Economic Survey, Assam, 2011 IV.3.2 Status of Rural Development The current status of rural development especially in terms of health, education and living standard attained by different districts of Assam can be observed in the table below: 91

Table 4.2: District-wise status of Rural Development in Assam Districts Index of Rural Child Sex Ratio Rural Literacy Index Rural Income Index Overall Rural Development Index Dhubri 0.779 0.341 0.141 0.334 Kokrajhar 0.559 0.568 0.351 0.481 Bongaigaon 0.824 0.632 0.354 0.569 Goalpara 0.588 0.625 0.310 0.485 Barpeta 0.603 0.506 0.183 0.382 Nalbari 0.779 0.923 0.141 0.466 Kamrup 0.735 0.728 0.160 0.441 Darrang 0.397 0.550 0.001 0.051 Sonitpur 0.647 0.644 0.472 0.582 Lakhimpur 0.676 0.896 0.625 0.724 Dhemaji 0.456 0.643 0.560 0.547 Morigaon 0.559 0.645 0.357 0.505 Nagaon 0.647 0.733 0.345 0.547 Golaghat 0.706 0.879 0.540 0.695 Jorhat 0.779 0.999 0.544 0.751 Sibsagar 0.647 0.970 0.538 0.696 Dibrugarh 0.691 0.777 0.636 0.699 Tinsukia 0.999 0.597 0.537 0.684 Karbi Anglong 0.001 0.733 0.681 0.079 N. C. Hills 0.485 0.779 0.753 0.658 Karimganj 0.662 0.917 0.370 0.608 Hailakandi 0.485 0.794 0.288 0.481 Cachar 0.618 0.915 0.319 0.565 Source: Basic data have been taken from Statistical Handbook Assam, 2011, Economic Survey Assam, 2011 & Office of the Census of India The health indicator measured by under-6 rural sex ratio is found the highest in Tinsukia district while the district of Karbi Anglong comes last in this regard. The educational attainment measured by the rural literacy index is the highest in Jorhat while N C Hills tops the list in terms of achievement in standard of living as shown by the rural income index calculated from per capita agricultural district domestic product. Dhubri and Darrang lag behind the other districts in these two attainments respectively. The overall rural development index is found to be the highest in 92

Jorhat and lowest in Darrang district. A comparison of the districts can be made in terms of the rural infrastructure and rural development index values which are depicted in the following figure: Figure 4.1: 1: Rural Infrastructu Infrastructure re and Rural Development Index Values across Districts of Assam, 2011 Rural Infrastructure Index Rural Development Index 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Source: Table 4.1 and Table 4. 2 The figure represents almost a positive linkage between rural infrastructure and rural development. However, Darrang and Karbi Anglong depict a different picture where rural infrastructure levels are higher than their achievements in rural development. The upper Assam districts indicate to have better rural infrastructure facilities and rural development standards than most of the lower Assam districts. While N C Hills has been found to attain very high level of rural development, the position of Karbi Anglong, the other hill district, has been found very discouraging disco in this regard. But both the hill districts are having significant rural infrastructure 93

facilities. The Barak Valley districts possess more or less comparable infrastructure and development standards in their rural areas. IV.4 Inter-dependence between Rural Infrastructure and Rural Development In order to examine the rural infrastructure-rural development inter-relationship, both OLS and 2SLS regressions have been estimated on the equations constructed as mentioned in section II above. However, results of both types of regression have been found the same. The results of the regressions have been presented in the tables below: Table 4.3: Results of Regression of Current Development Index Variable/Items Estimated Coefficients/Values Lagged Development 1.102** Index (Y 0i ) (1.778) Current Infrastructure 0.799 Index (X 1i ) (0.877) Lagged Infrastructure -1.880* Index (X 0i ) (-1.682) Constant -0.357 (-1.361) R 2 0.253 F (3, 19) 2.146* Note: Values in brackets represent t values. *, ** & *** represent significance at 10%, 5% and 1% level respectively. The current rural infrastructure has not been found to have any significant influence on current rural development (The result is not much convincing because of limitation of data used). However, the current rural development process is found to be positively and significantly influenced by lagged rural development. Thus, the districts with higher rural development attainments in the earlier periods have 94

experienced higher rural development status in the current period. However, a negative relationship is found between current rural development and lagged rural infrastructure which suggests that the districts deficient in rural infrastructure facilities in the earlier periods have succeeded in improving their rural development status in the present period. Table 4.4: Results of Regression of Current Infrastructure Index Variable/Items Estimated Coefficients/Values Lagged Infrastructure 2.286** Index (X 0i ) (3.039) Current Development 0.632* Index (Y 1i ) (1.493) Lagged Development 0.336 Index (Y 0i ) (0.646) Constant -1.546*** (-6.341) R 2 0.494 F (3, 19) 6.185** Note: Values in brackets represent t values. *, ** & *** represent significance at 10%, 5% and 1% level respectively. The current improvement in rural infrastructure across districts in Assam is positively and significantly influenced by both the rural infrastructure in the earlier periods and the current rural development process. Therefore, the districts with higher rural development attainments in the present period and higher levels of rural infrastructure in the earlier periods are found to possess better provisions of rural infrastructure in the current period. Here no significant relationship is found between current provision of rural infrastructure and rural development attained in the past. Thus current improvement in rural infrastructure of the districts of Assam is not 95

found to significantly influence upon current rural development process though it is positively influenced by the current rural development process. Moreover, rural development and rural infrastructure in the present period are positively depended upon their past achievements. To state more specifically, districts which are already developed rural areas have improved more in their rural development achievements and districts with already developed rural infrastructure in the past have added more to their rural infrastructure provision indicating divergence to take place in both the rural infrastructure and rural development process. Though significant negative dependence is found between current rural development and lagged rural infrastructure, no such significant dependence is found between current rural infrastructure and lagged rural development. To examine the presence or absence of convergence more formally, a regression analysis is done on the equations constructed as described in section II. The regression results are shown below: The negative and highly significant coefficients of the explanatory variables in both the tables above indicate occurrence of strong β-convergence in both the rural development process and the process of rural infrastructure improvement among the districts of Assam. It is a good sign for the state economy as the less developed districts have succeeded in improving their pace of rural development and adding more rural infrastructure facilities over time. It would help minimising the gap between the districts in terms of rural development and rural infrastructure provision in due course of time. 96

Table 4.5: Convergence in Development Process Variable/ Estimated Items Coefficients/Values Lagged Development Index (Y 0i ) -0.747** (-2.792) Constant -0.244** (-2.090) Table 4.6: Convergence in Infrastructure Progress Variable/ Estimated Items Coefficients/Values Lagged Infrastructure Index (X 0i ) -0.692* (-.4.827) Constant -0.503** (-3.402) R 2 0.271 R 2 0.526 F (1, 21) 7.793* F (1, 21) 23.297* Note: Values in brackets represent t values *, ** & *** represent significance at 10%,5% and 1% level respectively Note: Values in brackets represent t Values *, ** & *** represent significance at 10%, 5% and 1% level respectively IV.5 Conclusion There is considerable difference in rural development attainment and status of rural infrastructure across districts in Assam. Further, there is a distinct but less than perfect correspondence between status of rural infrastructure and the level of rural development attainment. While rural development has been found to positively influence rural infrastructure provision, no such relation has been found in the other way round. Thus, while higher rural development creates more rural infrastructures, improved rural infrastructure has not found to have significant impact assisting the rural development process across districts of Assam. In case of both rural development and state of rural infrastructure across districts there is evidence of convergent tendency. However in view of wide disparities in 97

both rural development attainments and the state of rural infrastructure among districts, natural convergence may require a fairly long time. Hence state interventions are warranted to help relatively backward regions within the state to break the nexus of low rural development attainment and poor state of rural infrastructure. In view of the positive influence of rural infrastructure on rural development process, a case for intervention through provision of rural infrastructure can be made. The case arises from the public good element inherent in most of the basic infrastructure facilities, which makes market provision of such facilities not only very uncertain but indeed very unlikely in backward areas. Having explored the infrastructure-development inter-relationship in the rural areas across districts of Assam on the basis of available secondary data in this chapter, the relationship between the two has been re-examined on the basis of collected primary data in the subsequent chapters. Apart from examining the impact of rural infrastructure on rural development, attempts have also been made to find out the role played by some village level institutions especially the gaon panchayats in improving status of rural infrastructure provision and accelerating the pace of development of the rural areas of Assam. Before going to that exercise, the next chapter has been designed to incorporate a brief outline of the structure of local governments in the state along with a few related issues with such self-governing bodies in the rural areas of the state. 98

ANNEXURE IV.A TECHNICAL NOTES INDEX CONSTRUCTION Index of Rural Development The index of rural development has been constructed as a composite index of three dimension indices under 6 age rural sex ratio index, rural literacy index and rural income index. For this, district-wise data on under 6 age rural sex ratio and rural literacy at the two reference periods of 2001 and 2011 have been taken. To construct the rural income index, per capita agricultural district domestic product has been used as a proxy of rural income since district-wise income data are not found available in rural-urban break-up. Moreover, agriculture is the primary source of income of most of the rural people. Following the UNDP (2010) methodology, log value of per capita district domestic product has been taken instead of per capita district domestic product itself. The dimension indices measure district-wise attainment of the three basic dimensions of rural development namely a good attitude towards girl child, knowledge and a decent standard of living. In the first step, dimension indices have been calculated by taking the actual maximum and minimum attainments among the districts in the respective dimensions in the reference period of 2001 and 2011. The maximum and minimum values in the three dimensions in the reference period are as follows: 99

Dimension Maximum Value Minimum Value 1. Under 6 age Rural Sex Ratio 982 914 (Tinsukia, 2011) (Karbi Anglong, 2011) 2. Rural Literacy 81.36 43.62 (Jorhat, 2011) (Dhubri, 2001) 3. Agricultural DDP Per Capita (in Rs.) 13103 2251 (N C Hills, 2001) (Darrang, 2007) After deriving the maximum and minimum values, dimension indices have been calculated using the following equation:?=@/4a=*4 345/6= BCDEFG HFGE IJKEK HFGE IFLKEK HFGE IJKEK HFGE.(1) The values of the dimension indices so calculated would be within the range 0 1. To make the values conformable for further calculations, the 0 s and 1 s have been replaced by 0.001 and 0.999 respectively. Then the geometric mean of the three dimension indices of each district has been derived which has been considered as the final rural development index of the respective districts. For instance, the actual values of the dimensions in the district of Dhubri in 2011 are: Dimension Actual Value 1. Under 6 age Rural Sex Ratio 967 2. Rural Literacy 56.49 3. Agricultural DDP Per Capita (Lakh Rs.) 2882 100

Using equation (1), Rural under 6 age Sex Ratio Index= Z[\Z] Z^!Z] =0.779 Rural Literacy Index= f[.]z]".[! ^."[]".[! =0.341 Rural Income Index= klm(!^^!)klm (!!f) klm("")klm (!!f) =0.141 8#01)?/'/)*n@/4< 345/6=o/*@/<0=; p/14 *q <h/?=@/4a=*4 345=;/A = 0.779 0.341 0.141 = 0.334 Index of Rural Infrastructure The rural infrastructure index has also been calculated as a composite index of two dimension indices of rural road index and rural electricity index. The dimension indices measure availability of rural road connectivity and status of rural electricity supply, the two basic components of infrastructure services in the rural areas across districts in Assam. The rural road index is consisted of two indicators of rural roads per lakh of rural population and rural roads per hundred square kilometer of rural geographical area of each district. Rural roads per lakh of rural population may overstate the rural road availability in the thinly populated districts whereas rural road per hundred square kilometer of rural geographical area may understate the rural road availability in the thickly populated districts. Therefore the two indicators have been taken to get a more reliable index of rural road availability. The rural electricity index has been constructed from data on percentage of villages electrified across districts in Assam. Initially, the observed maximum and minimum values regarding rural roads per lakh of rural population and rural roads per hundred square kilometer of rural 101

geographical area have been found out among the districts in the two reference periods of 2004 and 2011. Then the dimension indices of rural roads per lakh of rural population and rural roads per hundred square kilometer of rural geographical area have been constructed by applying equation (1) mentioned above. The geometric mean of these two dimension indices has been taken as the final rural road index. The 0 and 1 values in the indices have been replaced by 0.001 and 0.999 respectively to make them conformable for calculation of the road index using geometric mean. The maximum and minimum values regarding villages electrified have also been derived in the two reference periods and equation (1) has been applied to arrive at the rural electricity index. 0 and 1 s have again been replaced by 0.001 and 0.999 respectively. The maximum and minimum values of the corresponding dimensions in the reference periods are: Dimension Maximum Value Minimum Value 1. Rural Roads per Lakh of 930 46 Rural Population (in km) (N C Hills, 2011) (Dhubri, 2004) 2. Rural Roads per Hundred sq km 61.79 14.46 of Rural Geographical Area (in km) (Jorhat, 2011) (Dhemaji, 2004) 3. Percentage of Electrified Villages 99 28 (Nalbari, 2004) (Dhemaji, 2004) The geometric mean of rural road index and rural electricity index has been considered as the final rural infrastructure index. For instance, the actual values of the dimensions in the district of Goalpara in 2011 are: 102

Dimension Actual Value 1. Rural Roads per Lakh of Rural Population (in km) 113 2. Rural Roads per Hundred sq km of Rural Geographical Area(in km) 47.16 3. Percentage of Electrified Villages 93 Using equation (1), 345/6 *q 8#01) 8*15A n/0 t1uh *q 8#01) v*n#)1<=*4= 113 46 930 46 =0.076 345/6 *q 8#01) 8*15A n/0 00 Ay u@ *q 8#01) o/*+01nh=;1) z0/1= 47.16 14.46 61.79 14.46 =0.691 8#01) 8*15 345/6=o/*@/<0=; p/14 *q <h/ 1{*'/ < *?=@/4A=*4 345=;/A = 0.076 0.691 8#01) :)/;<0=;=<> 345/6= 93 28 99 28 =0.920 8#01) 34q01A<0#;<#0/ 345/6 =o/*@/<0=; p/14 *q 345=;/A *q 8#01) 8*15 145 8#01) :)/;<0=;=<> =7 0.076 0.691 0.920 = 0.458 103