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Home , Ambasamudram, Attur, Kallakurichi, Sattur, Sivaganga, Thoothukudi

REVIEW OF RURAL AFFAIRS

Changing Characteristics of Villages in

A Vaidyanathan, R Srinivasan

Illustrating the imaginative use of the Primary Census he spatial aspects of development have been the focus Abstract for Tamil Nadu from the 1991 to 2011 censuses, of wide-ranging research the world over. In , the emphasis has been more on tracking regional disparities this paper separates villages that are chronically T in overall development indicators. Studies of these disparities backward from those that are more developed in terms across towns and villages are relatively rare. Village studies, of demographic and economic characteristics. It also though numerous, have been mostly isolated case studies at makes use of the data to describe changes in spatial the disaggregated level or studies using a sample of villages spread over a vast area. Neither of these two strands has used distributions over time. the demographic data and infrastructure data at the village level/urban ward level provided once in a decade since 1961 by the Director General of Census Operations. The Primary Census Abstract (PCA), published by the Directorate of Census Opera- tions, gives demographic details of every revenue village and urban ward.1 Identifi cation of villages by district and taluk is enabled through serially allotted codes. The Village Directory, published by the Census Directorate, has information on the availability of infrastructure facilities and public utilities in each village and a Town Directory has similar details for every town and .2 These two databases enable not only disaggregated analysis up to the village/urban ward level, but also identifi ca- tion of the outliers—the laggard v illages and those that have been consistently at the higher end of the development ladder. The main aim of this paper is to illustrate the imaginative use of one of the two databases for Tamil Nadu, the PCA, to separate villages that are chronically backward from those that are more developed in terms of demographic and economic characteris- tics and to describe the change in spatial distributions over time. One of the authors earlier carried out a similar exercise for the erstwhile North Arcot District in Tamil Nadu using 1971 and 1981 census data (Vaidyanathan 2013). He has also illus- trated the richness of this database for the state as a whole in another study (Vaidyanathan 2014). In this paper, we use the PCA for all villages from the three censuses between 1991 and 2011. This paper is divided into three parts. Section 1 paints a broad picture of the average Tamil Nadu village and variations in its characteristics over the three censuses. The population size, sex ratio (SR), rate (LR), work participation rate (WPR), the proportions of agriculture and non-agriculture workers and cultivators to total workers (AW/TW and Non- agri/TW) and proportions of agricultural labourers to total ag- ricultural workers (AL/aW) are calculated for each village in every census. The decadal changes in a representative average Tamil Nadu village are discussed in this context. A Vaidyanathan ([email protected]) is a long-standing Section 2 focuses on the comparison between the averages c ontributor to EPW and an Honorary Fellow of the Centre for in the bottom decile (BD) and top decile (TD) of the villages by Development Studies, ; R Srinivasan (seenu242@ the values of each of the above features in 1991 and 2011.3 It gmail.com) teaches econometrics at the University of Madras. highlights differences between the bottom and the top deciles

Economic & Political Weekly EPW december 26, 2015 vol l no 52 65 REVIEW OF RURAL AFFAIRS in the mean value of each of the selected socio-economic indi- The proportion of Scheduled Castes (SCs) and Scheduled cators and their association with other characteristics in dif- Tribes (STs) to total population (%SCST) increased by 0.9 per- ferent years, as well as the quantum of such changes from 1991 centage points in the 1990s and this almost doubled to 1.8 per- to 2011. The focus is on describing distinct patterns of variation, centage points in the 2000s. Correspondingly, the dispersion which might trigger further analysis on exploring the underlying of SCs/STs declined over these two decades. The concentration causes for these changes. of the SC and ST population is increasing in rural Tamil Nadu Section 3 describes the spatial distribution of villages in the and their dispersion has been declining over time. bottom and top deciles of each characteristic across districts The WPR measured as the percentage of total workers to total and taluks in 1991 and 2011. Mapping the spatial concentration population (TW/T Pop) increased from 45.1 to 50.3 and then to of villages in the top and bottom deciles provides the basis for 50.7 in the three censuses. Changes in age, gender and educa- assessing whether and to what extent they are geographically tion need to be examined to understand this trend. The inter- concentrated and whether such geographical concentrations village variability (CV) of the WPR has progressively declined. change over time. The share of agricultural workers in the total workforce (AW/TW) in the state increased marginally during the 1990s 1 Overall Trend through 1991, 2001 and 2011 and declined sharply in the 2000s. The percentage of non- The population of rural Tamil Nadu declined by 1.9 million in agricultural workers (NAW/TW), which gives an idea of the extent 2001 and increased slightly by 2.3 million in 2011. The annual of diversifi cation of employment, declined during the 1990s but population growth rate in rural Tamil Nadu is far less than the increased sharply in the next decade. Because of this, in abso- overall population growth rate of the state because of rapid lute terms, between 1991 and 2001, the number of agricultural urbanisation. A progressive decline in the number of villages workers increased while non-agricultural employment did not over this period could be due to tiny villages being abandoned, show any change. In the subsequent decade, the number of contiguous villages being amalgamated, and, more likely, the agricultural workers declined marginally and that of non-agri- larger villages being reclassifi ed as towns because of urbanisa- cultural workers increased by 1.4 million, which was more tion. The growth in total rural population and a reduction in than the increase in the total number of workers. Unlike the the number of villages are refl ected in a progressive increase WPR, the inter-village variability of NAW/TW is much greater in the average size of villages and a decline in the extent of than that of AW/TW, and both seem to have increased. diversity in size (Table 1). On an average, about one-third of the agricultural workers are Table 1: Salient Socio-economic Characteristics of Tamil Nadu Villages, cultivators and two-thirds are labourers. The share of labourers 1991–2011 fell in 2001, but in 2011 increased to more than what it had been Village Characteristics 1991 2001 2011 Mean CV (%) Mean CV (%) Mean CV (%) in 1991. We fi nd contrasting trends in the dispersions of AW/TW Total population (crore) 3.68 – 3.49 – 3.72 – and AL/TW—the former is increasing, while the latter is declining. Number of villages 15,902 – 15,400 – 15,049 – Table 2 shows the simple correlation coeffi cients between Population/village 2,315 112.5 2,268 96.4 2,474 94.9 different characteristics across villages in 1991 and 2011. Villages Literacy rate 47.1 27.7 58.2 18.3 65.8 13.4 with a higher SR tend, in both periods, to be smaller in size, Sex ratio 981 8.7 992 9.8 993 12.6 Table 2: Correlation between Characteristics of Villages in 1991 and 2011 SR_06 945 26.7 933 24.6 936 25.8 Variable Total Pop Sex Ratio %SCST Literacy TW/T Pop Non-agri/ AL/AW %SCST 24.3 95.2 25.4 92.4 27.2 87.9 Rate TW (TW/Total pop) 45.1 24.2 50.3 20.6 50.7 18.4 Total pop (Non-agri/TW) 32.5 55.0 29.9 71.5 34.8 63.9 1991 1 (AW/TW) 77.5 23.9 70.1 31.2 65.2 34.6 2011 1 (AL/AW) 57.7 43.6 61.2 37.7 68.4 34.1 Sex ratio (AL/TW) 44.7 47.1 42.9 50.4 44.6 50.5 1991 -0.057# 1 (CUL/TW) 32.7 74.7 27.2 78.1 20.6 95.3 2011 -0.016* 1 The LR substantially increased from 47.1 in 1991 to 58.2 in %SCST 1991 -0.176# -0.024# 1 2001 and further to 65.8 in 2011. This was accompanied by a 2011 -0.163# 0.011 1 progressive reduction in inter-village variation (measured by Literacy rate its coeffi cient of variation or CV). Both refl ect the success of 1991 0.207# 0.141# -0.204# 1 public investment in school education and other non-formal 2011 0.082# 0.080# -0.152# 1 literacy programmes. TW/Total pop 1991 -0.101# -0.039# 0.060# -0.231# 1 The average SR shows a progressive though uneven increase 2011 -0.142# -0.073# 0.016* -0.326# 1 over the period. Child sex ratio (SR_06) declined from 946 to Non-Agri/TW 933 during the 1990s and then marginally increased to 936 in 1991 0.331# 0.017* -0.146# 0.390# -0.284# 1 the subsequent decade. The child SR has remained lower than 2011 0.257# 0.019* -0.099# 0.271# -0.360# 1 the SR throughout but does not show a sustained trend. The AL/AW gap between the SR and SR_06 has widened over time. Also 1991 0.113# -0.025# 0.235# 0.149# 0.088# 0.126# 1 noteworthy is the increasing dispersion of the SR and its near 2011 0.049# 0.044# 0.211# 0.097# -0.086# -0.018* 1 # Correlation is significant at the 0.01 level (2-tailed); * correlation is significant at the 0.05 constant nature over the period. level (2-tailed).

66 december 26, 2015 vol l no 52 EPW Economic & Political Weekly REVIEW OF RURAL AFFAIRS and have lower WPRs, but they are more literate and have more low levels. But the WPR in the least literate group (48%) and diversifi ed employment. In these cases, the pattern is more or the proportion of workers in agriculture (92%) was much less the same in both years. But, between the two years, nega- higher compared to what they were (36% and 56%, respectively) tive correlations become weaker and positive associations in the most literate group. In both respects, intra-group varia- stronger. A high SR also went with a lower incidence of SCs/STs bility is higher (more so in the dependence on agriculture) in in 1991, but not in 2011. least literate villages. It is noteworthy that the proportion of Villages with higher literacy tend to be larger in size, have a labourers in the agriculture workforce in the least literate higher SR, and are more diversifi ed in employment. But they group is nearly double but with much less intra-group variabil- have a lower proportion of SCs/STs in their population, and a ity compared to the most literate villages. lower WPR. Barring the WPR, these associations have weak- The trajectories of change in the two groups of villages also ened over time. differ in signifi cant ways. The population in both groups of Villages with a higher incidence of SCs/STs tend to be small- v illages has increased in absolute terms and as a proportion of er, have lower WPRs, and a higher proportion of agricultural the total state population, but the change is more striking in labourers and low-earning non-agricultural workers in the the most literate village group. Intra-group variation remains workforce. A higher incidence of SCs/STs went with a lower SR high in both cases. in 1991, but this association became positive in 2011. All these The overall SR has increased marginally in both groups but associations had weakened in 2011. somewhat more in the top decile. SR_06 has fallen marginally These correlations suggest that the WPR tends to be lower in in both groups. The proportion of SCs/STs remained more or larger, more literate villages and those with higher SRs and a less the same in the bottom decile but increased signifi cantly higher proportion of non-agricultural workers. A higher WPR is in the top decile. Intra-group variability came down in the latter. associated with a higher incidence of SCs/STs. The strength of The WPR rose in both at more or less the same rate and both all these associations has increased since 1991. report progressively greater diversifi cation of employment, but Villages with more diversifi ed employment tend to be larger in the pace was faster in the most literate decile. Among agricul- size and more literate, but with a lower incidence of SCs/STs, tural workers, the share of labourers declined in both, but the lower SR, and lower WPR. All these associations weakened in 2011. change was more pronounced in the top decile. Inter-village vari- A greater dependence of agriculture on wage labour (meas- ability in all these indicators became smaller in both groups. ured by AL/AW) is associated with larger village size and higher LR, but a smaller proportion of SCs/STs. This is the case in both 2.2 Sex Ratio years but the associations have become weaker. In 1991, AL/AW Villages in the lowest decile had an average SR of 873, which tended to be higher in villages with a higher WPR and more was about 10% lower than the state average; had 7% of the diversifi ed employment, and lower in those with higher SRs. t otal rural population; and were about 30% smaller than the But the direction of these associations had reversed by 2011, state average (Table 4, p 68). In villages in the highest decile, even as they remained signifi cant. Table 3: Bottom (BD) and Top Deciles (TD) by Literacy Rate, 1991 and 2011 Village Characteristics 1991 2011 2 Characteristics of Villages in the Bottom and Top Deciles BD TD BD TD Mean CV Mean CV Mean CV Mean CV We have focused on 10 variables from the PCA that give the Total population 20.72 56.6 29.23 39.02 overall socio-economic characteristics of a village—LR, SR, (in lakh) (8.51) (-17.58) SR_06, %SCST, TW/T Pop, Non-agri/TW, AW/TW, AL/AW and Number of villages 1,590 1,590 1,505 1,505 CUL/TW in the censuses of 1991, 2001 and 2011. We have classi- Population/village 1,303 113.0 4,899 137.6 1,942 118.3 2,593 110.6 (639) (5.3) (-2306) (-27) fi ed villages by deciles using six important characteristics— Literacy rate 21.9 38.2 66.3 8.2 50 16.2 79.1 4.4 SR, LR, %SCST, TW/T Pop, Non-agri/TW and AL/AW. We com- (29.1) (-22) (12.8) (-3.8) pare the average of the 10 variables in the bottom decile and Sex ratio 953 11.8 997 13.01 958 12 1,007 32.2 top decile of each of these seven characteristics. (5) (0.2) (10.0) (19.1) SR_06 925 37.3 964 39.1 913 31.5 958 30.5 (-12) (-5.8) (-6.0) (-8.6) 2.1 Literacy Rate %SCST 30.5 113.7 16.5 109.5 30.1 113.5 23.6 94.0 In 1991, villages with the lowest literacy had a population of 2 (-0.4) (-0.2) (7.1) (-15.5) million (6% of the total) and villages with highest literacy, 5.7 TW/Total pop 48.2 26.1 35.8 29.9 55.7 16.3 42.0 25.2 (7.5) (-9.8) (6.2) (-4.7) million (a little under 16% of the state’s population; Table 3). Non-agri/TW 7.8 177.6 44.3 56.8 21.4 95.6 54.5 50.9 On an average, villages in the former category were 40% (13.6) (-82.0) (10.2) (-5.9) smaller than the state average while those at the high end of AW/TW 92.2 15.1 55.7 45.2 78.6 26.1 45.5 63.0 literacy were much larger (more than twice the state average), (-13.6) (11.0) (-10.2) (17.8) with intra-village variability being very high in both groups. AL/AW 45.0 66.8 63.8 40.7 61.9 44.4 74.2 33.8 (16.9) (-22.4) (10.4) (-6.9) The least literate group had signifi cantly lower SRs, both over- AL/TW 41.4 68.3 35.5 63.6 48.7 52.3 33.7 76.0 all (953) and in the 0–6 age group (925). Both are higher than (7.3) (16.0) (-1.8) (12.4) the rates in the most literate group (997 and 925). Intra-group CUL/TW 50.7 57.4 20.2 111.6 29.9 80.0 11.7 158.7 variability in both features is more or less similar at relatively (-20.8) (22.6) (-8.5) (47.1)

Economic & Political Weekly EPW december 26, 2015 vol l no 52 67 REVIEW OF RURAL AFFAIRS the SR averaged 1,128 (about 15% higher than the state average) were about 40% smaller than the state average (Table 5). In the and they had 8% of the total population. Villages in this group top decile (predominantly SC/ST villages), which had 4% of the were about 40% smaller than the overall average. Compared to state’s rural population, these villages were smaller than in the the top decile, bottom decile villages were consistently less liter- bottom decile group and much (60%) smaller compared to the ate, had signifi cantly lower SRs and child SRs; slightly higher WPRs; state average. The intra-group variability was very high, it be- and more or less the same degree of diversifi cation. The incidence ing far more pronounced in the top decile category. of SCs/STs in the bottom decile was higher than in the top decile Table 5: Bottom and Top Deciles by Percentage of SCs and STs, 1991 and 2011 in 1991, but signifi cantly lower in 2011. Village Characteristics 1991 2011 BD TD BD TD Table 4: Bottom and Top Deciles by Sex Ratio, 1991 and 2011 Mean CV Mean CV Mean CV Mean CV Village Characteristics 1991 2011 Total population 22.1 16.35 19.02 18.11 BD TD BD TD (-3.08) (1.76) Mean CV Mean CV Mean CV Mean CV Number of villages 1,590 1,590 1,505 1,505 Total population 26.41 22.88 29.18 24.66 Population/village 1,390 235.5 1,028 104.0 1,264 153.7 1,203 99.6 (in lakh) (2.77) (-1.75) (126) (-81.8) (175) (-4.4) Number of villages 1,590 1,590 1,505 1,505 Literacy rate 51.9 31.6 39.5 38.5 66.1 16.1 61.4 21.2 Population/village 1,661 135.5 1,439 110.8 1,939 126.6 1,639 105.4 (14.2) (-15.5) (21.9) (-17.3) (278) (-8.9) (200) (-5.4) Sex ratio 984 13.5 979 11.2 983 14.6 994 10.2 Literacy rate 41.4 37.0 52.8 26.4 61.9 18.3 69.2 13.9 (-1.0) (1.1) (15) (-1.0) (20.5) (-18.7) (16.4) (-12.5) SR_06 940 52.8 967 30.1 936 46.3 935 36.0 Sex ratio 873 8.2 1,128 11.1 878 9.2 1,119 28.6 (-4.0) (-6.5) (-32.0) (5.9) (5) (1.0) (-9) (17.5) %SCST 1.3 69.8 74.5 18.6 1.16 84.8 78.5 15.5 SR_06 804 33.2 1,021 47.3 858 29.7 1,013 38.5 (-0.14) (15.0) (4.0) (-3.1) (54) (-3.5) (-8) (-8.8) TW/Total pop 39.3 33.2 47.1 25.5 49.9 23.4 52.3 18.2 %SCST 22.1 127.8 21.2 116.9 22.1 127.1 25.9 102.9 (10.6) (-9.4) (5.2) (-7.3) (0) (-0.7) (4.7) (-14) Non-agri/TW 25.6 85.8 13.9 124.5 38.5 66.9 25.0 95.1 TW/Total pop 45.5 27.1 43.1 29.5 50.9 22.4 48.0 22.1 (12.9) (-18.9) (11.1) (-29.4) (5.4) (-4.7) (4.9) (-7.4) AW/TW 74.4 29.5 86.1 20.2 61.5 41.9 75.0 31.7 Non-agri/TW 23.1 89.1 22.9 79.7 33.9 67.4 33.9 69.4 (-12.9) (12.4) (-11.1) (11.5) (10.8) (-21.7) (11.0) (-10.3) AL/AW 49.3 57.3 65.3 47.0 60.8 49.0 73.7 38.8 AW/TW 76.9 26.8 77.1 23.7 66.1 35.6 66.1 34.6 (11.5) (-8.3) (8.4) (-8.2) (-10.8) (8.8) (-11) (10.9) AL/TW 36.7 68.8 56.2 51.1 37.4 71.6 55.3 49.7 AL/AW 54.1 52.1 50.4 55.3 60.9 46.0 68.8 37.8 (0.7) (2.8) (-0.9) (-1.4) (6.8) (-6.1) (18.4) (-17.5) CUL/TW 37.7 75.5 29.8 95 24.1 106.1 19.7 121.4 AL/TW 41.6 62.6 38.9 62.7 40.3 62.4 45.5 23.6 (-13.6) (30.6) (-10.1) (26.4) (-1.3) (-0.2) (6.6) (-39.1) CUL/TW 35.3 77.8 38.2 69.0 25.8 95.2 20.6 103.5 The SR in the bottom decile was higher and SR_06 lower com- (-9.5) (17.4) (-17.6) (34.5) pared to the top decile. The intra-group variability of SR was far In the last two decades, there was no signifi cant change in more pronounced in the bottom decile than in the top decile. the SR in either group. The child sr increased in the bottom Predominantly non-SC/ST villages were far more literate, had decile but there was no change in the top decile. Intra-group considerably lower WPR, more diversifi ed employment, and a variability of the SR increased in both; more so in the top decile. lower incidence of agricultural labour than in the decile with a The population of villages in both categories increased margin- predominantly SC/ST population. ally in absolute terms and as a proportion of the total rural popu- Over time, the total population in predominantly non-SC/ST lation. The average size of villages in both categories increased, villages and their average size declined marginally, even as but it was more in the bottom decile than in the top decile. The both show a marginal increase in the predominantly SC/ST variability across villages increased marginally over the period in group. Intra-group variability in this declined steeply in both the bottom decile but increased sharply in the top decile. groups, but more strikingly in the top decile. The proportion of SCs/STs in the population did not change The proportion of SCs/STs in the population has not changed in villages with the lowest SR but increased in those with the much in predominantly non-SC/ST villages, but has risen in highest SR. Intra-group variability in this was high in both the predominantly SC/ST group. Intra-group variability in this groups, but with no signifi cant change over the period. index is much higher and increasing in the former but much The WPR shows an appreciable increase in both categories, smaller and declining in the latter. The LR rose in both groups, and both show an increase of more or less the same extent in though more in the predominantly SC/ST category. Intra-group the degree of diversifi cation. In both groups, the incidence of variability in this declined in both. labourers in the agricultural workforce increased, even as that The WPR shows no signifi cant change in the predominantly of cultivators came down substantially. This change was more non-SC/ST group but shows a progressive rise in the predomi- pronounced among cultivators. nantly SC/ST group. Employment progressively diversifi ed from agriculture in both groups but this shift was proportionately 2.3 Scheduled Castes and Scheduled Tribes more in the predominantly SC/ST group. Much of this diversifi - In 1991, about 6% of the state’s rural population was in the bottom cation in both groups went with a signifi cant decline in the pro- decile (predominantly non-SC/ST) villages; SCs/STs comprised portion of cultivators among all workers. There was no change less than 2% of the population; and villages in this category in the proportion of agricultural labourers in the total workers

68 december 26, 2015 vol l no 52 EPW Economic & Political Weekly REVIEW OF RURAL AFFAIRS in both SC/ST and non-SC/ST villages but their share in the total where diversifi cation is also accompanied by a big increase in agricultural workforce showed a signifi cant increase in both cate- labourers as a proportion of total agricultural workforce. gories. This shift was more in the predominantly SC/ST group. Employment in the bottom decile has been far more diversifi ed than in the top decile. The non-agriculture labourers to total 2.4 Workforce Participation workers increased from 41.7% to 58.9% in the bottom decile In 1991, villages in the LD were larger than the average for the and only increased from 12.6% to 18.8% in the TD in 20 years. state, reported an average WPR of 58%, and comprised 11% of The decline in dispersions of this variable in both deciles shows the total rural population (Table 6). Villages in the top decile the widespread change in each decile. The decline in agricultural were much smaller in size (population about 63% compared to workers was mostly due to a sharper decline in cultivators. the state average). They accounted for 8% of the total rural population and an average WPR of 64%. 2.5 Extent of Employment Diversification Table 6: Bottom and Top Deciles by Total Workers to Total Population, Compared to villages with the least diversifi ed employment 1991 and 2011 (lowest proportion of workers in non-agricultural activities Village Characteristics 1991 2011 BD TD BD TD and the highest in agriculture measured by the Non-agri/TW Mean CV Mean CV Mean CV Mean CV ratio; Table 7), villages with the most diversifi ed employment Total population 40.52 23.41 39.6 21.08 (in lakh) (-0.92) (-2.33) cover a much larger population, are much larger in size, sig- Number of village 1,590 1,590 1,505 1,505 nifi cantly more literate, and have a larger proportion of SCs/ Population/village 2,548 176.6 1,472 101.7 2,598 115.2 1,401 103.3 STs, higher SR and markedly lower WPRs. There are signifi cant (50) (-61.4) (-71) (1.6) differences between the two groups in the magnitude of Literacy rate 59.3 26.2 41.5 33.5 73.9 12.4 61.6 16.7 (14.6) (-13.8) (20.1) (-16.8) changes in all these aspects over the last two decades. Sex ratio 991 13.5 982 10.8 1,005 31.7 986 12.2 Table 7: Bottom and Top Deciles in Extent of Employment Diversification (14) (18.2) (4) (1.4) Village Characteristics 1991 2011 SR_06 962 34.2 929 41.1 953 31.5 929 36.2 BD TD BD TD (-9) (-2.7) (0) (-4.9) Mean CV Mean CV Mean CV Mean CV %SCST 17.1 146.5 26.3 103 22.7 103.2 29.1 94.3 Total population 13.13 69.12 18.42 54.21 (5.6) (-43.3) (2.8) (-8.7) (5.29) (-14.91) TW/Total pop 28.9 13.2 63.9 6.9 35.8 12.2 66.0 7.6 Number of villages 1,590 1,590 1,505 1,505 (6.9) (-1.0) (2.1) (0.7) Population/village 826 98.2 4,347 109.7 1,234 100.8 3,602 99.4 Non-agri/TW 41.7 62.1 12.6 108.6 58.9 47.2 18.8 93.6 (408) (2.6) (-745) (-10.3) (17.2) (-14.9) (6.2) (-15.0) Literacy rate 31.6 48.5 57.3 23.0 59.1 21.1 72.1 12.9 AW/TW 58.3 14.5 87.4 15.6 41.1 67.6 81.2 23.7 (27.5) (-27.4) (14.8) (-10.1) (-17.2) (53.1) (-6.2) (8.1) Sex ratio 969 13.8 976 12.3 984 12.7 998 10.2 AL/AW 56.0 54.2 55.2 51.4 69.8 37.8 59.1 48.7 (15) (-1.1) (22) (-2.1) (13.8) (-16.4) (3.9) (-2.7) SR_06 953 41.7 948 24.1 924 37.0 957 25.3 AL/TW 32.6 73.1 48.2 54.3 28.7 84.5 47.9 54.6 (-3.9) (11.4) (-0.3) (0.3) (-29) (-4.7) (9) (1.2) CUL/TW 25.6 117.4 39.2 70.3 12.4 164.8 33.2 78.8 %SCST 33.7 99.3 17.7 114.1 36.4 89.4 22.5 105.4 (-13.2) (47.4) (-6.0) (8.5) (2.7) (-9.9) (4.8) (-8.7) TW/Total population 52.0 24.2 38.5 28.5 57.8 17.8 44.0 21.4 The WPR in villages of the bottom decile at 29% was much (5.8) (-6.4) (5.5) (-7.1) lower than in the top decile where it was nearly 64%. The pop- Non-agri/TW 1.7 57.7 60.3 27.7 5.5 43.0 79.6 12.4 ulation of the former was more literate (59% against 41% in the (3.8) (-14.7) (19.3) (-15.3) AW/TW 98.3 1.0 39.7 42.2 94.5 2.5 20.4 48.5 top decile) and had slightly higher overall and child srs, but a (-3.8) (1.5) (-19.3) (6.3) signifi cantly smaller proportion of SCs/STs (17% against 26% in AL/AW 43.7 72.9 63.2 40.6 59.1 54.1 67.1 36.1 the top decile). Their employment was far more diversifi ed (15.4) (-18.8) (3.9) (-4.5) AL/TW 42.9 73.2 25.1 55.5 55.9 54.7 13.7 61.1 with 42% workers in non-agricultural activities compared to (13.0) (-18.5) (-11.4) (5.6) 12% to 13% in the top decile, and their agricultural workforce CUL/TW 55.4 56.8 14.6 78.0 38.6 79.7 6.7 75.8 had a higher proportion of labourers. (-16.5) (22.9) (-7.9) (-2.2) There are signifi cant differences between the two groups in The total population in the most diversifi ed group in 2011 was changes over the last two decades. There was little change in about 20% smaller than in 1991, and the average size of villages in the total population in the two groups or in the average size of this group came down by about 16%. This probably refl ects some their villages. In the social indicators, overall srs as well as the larger villages in this group graduating to urban status. In the least proportion of SCs/STs increased in both groups but the increase diversifi ed group, by contrast, the total population increased by was more pronounced in the bottom decile. nearly 40% and the average village size by nearly 60%. The WPR and the extent of diversifi cation in employment The WPR has increased signifi cantly in both groups, somewhat have increased in both groups but the changes are more strik- more in the least diversifi ed category. The proportion of workers ing in the bottom decile. The decline in the share of agricul- in non-agricultural activities increased in both—from 60% to ture in the working population is shared by both cultivators nearly 80% in the most diversifi ed group, and from less than 2% to and agricultural labourers. In both deciles, the decline in the 5.5% in the least diversifi ed group. In absolute terms as well, the share of cultivators is more pronounced than that of labourers. number of non-agricultural workers increased in both groups, but The extent of decline is more pronounced in the bottom decile the increase in the most diversifi ed group (from 16 to 19 million)

Economic & Political Weekly EPW december 26, 2015 vol l no 52 69 REVIEW OF RURAL AFFAIRS was much larger than in the least diversifi ed group where its their population, a lower WPR, a lower degree of diversifi cation growth was much smaller (from 0.11 million to 0.59 million). in employment, and a very low incidence of wage labour in The diversifi cation process has resulted in a reduction in the agriculture. proportion of workers dependent on agriculture in both groups. There have been signifi cant changes in this pattern in the But this was far more marked in the most diversifi ed group com- last two decades. In both years, the total population of villages pared to the least diversifi ed group, where close to 95% of work- in the lowest decile of AL/AW as well as the average size of ers are still employed in agriculture. It is also noteworthy that v illages was smaller compared to the group with the highest while there was a sharp reduction in the number of agricultural incidence of wage labour. The difference has however nar- workers (from 11 million to 5 million) in the most diversifi ed rowed because the population in the lowest decile has in- villages, there was a signifi cant increase (from 6.7 million to creased while it has declined in the top decile. The literacy rate more than 10 million) in the least diversifi ed group. The compo- has increased in both groups but at a faster rate in the bottom sition of the agricultural workforce also changed, with the pro- decile and the gap has now disappeared. The WPR has increased portion of labourers among them recording an increase in both, in both at more or less the same rate. though more strikingly in the least diversifi ed group. Changes in other indicators, however, show marked differ- Among the social indicators, there was a signifi cant increase ences. The extent of employment diversifi cation recorded a in literacy in both groups but narrowing differences between steep increase in the bottom decile (the group with the least the two, and a modest increase in SR (slightly more in the least incidence of AL/AW) while it declined substantially in the diversifi ed group). The proportion of SCs/STs in the population group with the highest incidence of AL/AW. The steep reduc- increased in both groups, it being more pronounced in the tion in the share of the SCs/STs in population (from close to most diversifi ed group. 25% to less than 2%) in the bottom decile group contrasts with a sizeable increase in the top decile. Particularly striking is the 2.6 Incidence of Wage Labour in Agriculture phenomenal rise in AL/AW (from less than 9% to more than Agricultural workers comprise cultivators and those that work 60%) in the bottom decile compared to the increase from 91% for them as wage labour. The latter as a proportion of all agri- to 96% in the top decile. cultural workers ranged in 1991 from less than 9% in villages While the discussion highlights diverse changes in charac- of the lowest decile to more than 97% in the top decile (Table 8), teristics of the bottom and top deciles by different socio- highlighting one signifi cant aspect of the agrarian structure. economic indicators, it also gives an indication of changes in Compared to villages in the top decile (with the highest incidence disparities bet ween these two groups in particular indicators of wage labour), those with the lowest incidence of wage labour and associated changes in other indicators. The disparity had a larger population and were smaller on an average, had a between the bottom and top deciles has narrowed, albeit in signifi cantly lower literacy rate, and a marginally higher SR. varying degrees, in all indicators. The decline is most pro- On the other hand, they had a smaller proportion of SCs/STs in nounced in literacy rates and least in sex ratios. SCs/STs and all Table 8: Bottom and Top Deciles by AL/AW, 1991 and 2011 economic indicators show a mixed pattern with reduced dis- Village Characteristics 1991 2011 parities and marginal changes in a majority of cases. A widen- BD TD BD TD Mean CV Mean CV Mean CV Mean CV ing inter-decile disparity is also seen in economic indicators (es- Total population 17.82 25.93 20.70 19.50 pecially the WPR and Non-agri/TW). (2.88) (-5.8) Number of villages 1,590 1,590 1,505 1,505 3 Spatial Distribution of Villages in Select Indicators Population/village 1,121 108.3 1,631 144.4 1,373 117.5 1,295 96.7 (252) (9.2) (-336) (-48.7) In every census, each village is given a code number, sometimes Literacy rate 41.3 37.4 49.0 29.3 64.0 17.7 66.1 16.2 a continuous code for villages in each taluk and at other times in (-22.7) (-19.7) (17.1) (-13.1) each district. In 2011, each village in the country was given a Sex ratio 991 11.4 981 12.9 980 13.2 998 11.5 unique code. The increasing number of districts and taluks are (-11) (1.8) (17) (-1.4) accommodated by rearranging villages and towns, changing the SR_06 965 44.3 958 32.8 934 40.5 946 33.2 (-31) (-3.8) (-12) (0.4) state and district codes in every census. Therefore, generating %SCST 24.5 113.3 36.9 76.6 24.8 118.1 43.1 69.8 matching codes across the three censuses for each village and (0.3) (4.8) (6.2) (-6.8) mapping changes at the village level is diffi cult. The subsequent TW/Total pop 43.8 31.6 45.1 27.1 51.7 23.2 51.8 19.8 discussion focuses on changes at the taluk and district levels. (7.9) (-8.4) (6.7) (-7.3) Though extensive changes in boundaries have taken place Non-agri/TW 16.1 114.3 26.2 89.7 29.6 97.0 23.8 75.3 (13.5) (-17.3) (-2.4) (-14.4) at these levels, it is possible to reclassify the 2011 village-level AW/TW 83.9 22 73.8 31.8 70.4 40.8 76.2 23.5 data corresponding to the taluks and districts as classifi ed in (-13.5) (18.8) (2.4) (-8.3) 1991. Thus, 15,901 villages spread over 31 districts and 275 AL/AW 8.7 69.5 90.8 18.3 21.4 54.0 96.4 2.1 taluks in 2011 were mapped on 20 districts and 167 taluks listed (12.7) (-15.5) (5.6) (-16.2) in the 1991 Census. This section is based on a regrouping of the AL/TW 7.3 74.9 67.0 33.5 15.0 65.1 73.4 24.2 (7.7) (-9.8) (6.8) (-9.3) village-level data on the above basis and focusing on districts CUL/TW 76.6 23.9 6.8 59.4 55.4 46.9 2.8 57.8 and taluks with the largest number of villages in each decile. (-21.2) (23) (-4) (-1.6) We have listed the top 10 taluks in each decile. The distribution of

70 december 26, 2015 vol l no 52 EPW Economic & Political Weekly REVIEW OF RURAL AFFAIRS all villages in each decile over all the districts and taluks is individually and to a limited extent in their combinations. given in Appendices 1 and 2 (pp 72-73). However a more disaggregated look at these aspects at the taluk level of these districts shows a more complex picture. 3.1 District Concentration We analyse the concentration of villages in the bottom and top 3.2 Changes at the Taluk Level deciles in each selected characteristic in different districts. It We focus on 10 taluks in each of the high-concentration dis- so happens that the bulk (two-thirds to three-fourths) of tricts that had the largest number of villages in the bottom and v illages in both the lowest and highest deciles of all indicators top deciles of different characteristic in 1991 and 2011 and the are concentrated in fi ve to seven districts in both periods, changes that have occurred in them (Appendix 2). It turns out more or less in the same degree. In all indicators, the villages that the taluks that fi gure in these two deciles are seldom the in the two deciles are identical (Appendix 1). same across indicators and for the same indicator in the two The number of villages in the high-concentration districts years. Among those that fi gure in both periods, only four fi gure declined between 1991 and 2011 in both deciles of all indica- under more than one indicator—Harur and in Dharma- tors, barring the top decile of literacy and employment diversi- puri; Kattankulathur in Chengalpet; and in South fi cation. This implies that a sizeable number of villages in the Arcot, all of them in the worst-placed group. These villages can high-concentration districts in the bottom decile improved be considered among the worst-placed in several key aspects. their position and moved to higher deciles and that an increas- Three of them also fi gure in the best-placed category of some, ing number are moving into these categories from other dis- much fewer, indicators. tricts. The decline in the number of villages in high-concentra- A second striking feature is that between 1991 and 2011, tion districts in the top deciles means that improvements are unlike at the district level, there were huge changes in the taluks being more widely diffused among other districts. On the other falling under both deciles and in all indicators. Overall, only half hand, the increase in the number of villages in the top deciles fi gure in both years; the other half gave place to new entrants in of the high-concentration districts in literacy and diversifi ed 2011. The proportion of new entrants was higher at 60% in the employment means that improvements in these respects are best-placed group than in worst-off group (40%), and markedly more concentrated in the better-off d istricts. higher in economic than in social indicators. New entrants are Within the high-concentration group, there are considerable the largest in , followed by South Arcot and Chengalpet. differences in both the direction and extent of change. In both New entrants in the worst-off group are largest in WPR and deciles and all categories, the number of villages in the high- ALW/AW and relatively few in NAW and literacy. This could be concentration districts has (with some signifi cant exceptions) because a relative deterioration in these aspects has pushed declined in varying degrees. This decline in districts that are some taluks into the lowest decile. New entrants in the best- worst placed in different indicators (including high SC/ST placed taluks, which are found in all indicators but is largest in and high AL/AW) points to a shift of villages to higher deciles, AL/AW, SR and WPR and least in NAW/AW, indicate that im- again in varying degrees. The decline in the number of villages provements in these aspects in the high-concentration districts that are best placed in different indicators (including low SC/ST are being more widely diffused across their taluks. and low AL/AW), however, indicates some have moved to lower The factors underlying these differences in new entrants deciles. Some districts show contrary trends in both groups. across indicators and districts and their signifi cance are an im- For instance, South Arcot shows an increase in the number of portant and worthwhile area for future research. Also worth- villages with low employment diversifi cation, high AL/AW, while is exploring the shifts in the position of taluks in other and high SR; Chengalpet in the low SC/ST group has high NAW districts in various indicators. In most of these districts, the and low AL/AW; and Thanjavur has low SC/ST, low WPR, number of village in the bottom decile of sr and literacy rate and high SR. are in the top decile by %SCST. The picture is similar in eco- Another notable feature is that the same districts fi gure in nomic indicators but with some signifi cant differences. The both deciles of multiple indicators. Thus South Arcot and Chen- total number of villages in the bottom decile of WPR shows a galpet fi gure among the worst as well as best-placed districts in slight increase, suggesting the position has worsened in more fi ve of the six indicators. Thanjavur fi gures in the b ottom decile villages. This tendency is very marked in Thanjavur and to a of three indicators and four indicators in the top decile. Salem smaller extent in North Arcot. But in all others there is im- fi gures among the best-placed districts in four i ndicators. That provement. The reduction in Non-agri/TW indicates that the these districts contain clusters of villagers that are worst- diversifi cation of employment has spread to more villages, placed as well as those that are best-placed in the select socio- largely refl ecting the striking improvement in Chengalpet. In economic indicators points to the coexistence of extremes all others, a sizeable number have moved to groups with a lower within them. It would be interesting to track whether this con- degree of diversifi cation. The decline in the number of villages trast has become sharper or weaker over time. with the lowest dependence of agriculture on wage labour sug- The data suggest that districts where the worst-placed and gests a signifi cant increase overall, practically in all districts of best-placed villages are concentrated have remained largely the group. Also noteworthy is that the same districts fi gure in the same over the last two decades. Districts other than those both deciles of more than one indicator. Thus South Arcot and cited above have become more important in some indicators Chengalpet are in the bottom decile of four out of six indicators

Economic & Political Weekly EPW december 26, 2015 vol l no 52 71 REVIEW OF RURAL AFFAIRS and fi ve out of six indicators in the top decile. and districts in the top deciles means that improvements are being Thanjavur are in four of six indicators in both deciles. Pudukottai more widely diffused among other districts. But the increase in fi gures in the bottom decile in three of six indicators. the number of villages in the high-concentration districts It is clear that both the worst-placed and best-placed regions means the highest literacy and most diversifi ed employment are concentrated in the same districts. At the same time, it means are being concentrated in better-off districts. highlights the coexistence of extremes in a few districts. Within the high-concentration group, there are considerable It can be seen that the bulk (two-thirds to three-fourths) of differences in both the direction and extent of change. In both villages in both the lowest and highest deciles of all indicators deciles and all categories, the number of villages has declined are concentrated in fi ve to seven districts in both periods, in the bottom deciles of all indicators, except SCs/STs and AL/ more or less in the same degree. In all indicators, the villages AW. This points to a move to higher deciles. In the top deciles in the two deciles are identical. of these indicators, it indicates a shift to lower deciles. The The number of villages in the high-concentration districts d ecline in numbers with the highest (lowest) concentrations of declined between 1991 and 2011 in both deciles of indicators SC/ST and of AL/AW means that the proportion of this group in except in the top decile of literacy and employment diversifi ca- the population of some villages has come down (increased) to tion. This implies that a sizeable number of villages in the high- the extent that they have moved to a lower (higher) decile. concentration districts in the bottom decile improved their There are, however, several individual exceptions, notably p osition and moved to higher deciles and that an increasing S alem in LR, Thanjavur in WPR, South Arcot and Pudukottai in number are moving into these categories from other districts. NAW/TW in the bottom decile; and South Arcot, Chengalpet The decline in number of villages in high-concentration and Thanjavur in the top decile of three of four indicators.

Notes town; and even the distance to the nearest References 1 The demographic details include population, school, medical facility, etc. Vaidyanathan, A (2013): “Socio Economic Charac- segregated by sex, literacy, age group 0–6 3 We have excluded the 2001 Census in the subse- teristics of Villages in North Arcot: An Explor- years, SC and ST, workers classifi ed by indus- quent sections focusing on changes in the char- atory Study,” India’s Evolving Economy: Puz- trial origin and by duration of employment as acteristics of villages falling in the bottom and zles and Perspectives, New Delihi: Academic main, marginal, and seeking employment. top deciles of selected characteristics partly be- Foundation. 2 The VD gives data on availability or non- cause of limitations of space, and also because, — (2014): “Socio Economic Characteristics of availability of schools, medical facilities, post with a few exceptions, there are no discontinui- Tamil Nadu Villages,” Development Narratives: offi ce, banks, roads, drinking water, electricity, ties in the trend. The basic tabulations relating to The Political , V K Natraj types of agricultural land, extent of irrigation these two deciles, as well as village-specifi c data and A Vaidyanathan (eds), New : Academic facilities in a village; distance to the nearest in these groups, are available with the authors. Foundation.

Appendix 1: Distribution of Villages in BD and TD across Districts in 1991 and 2011 Bottom Decile Top Decile Bottom Decile Top Decile District 1991 2011 District 1991 2011 District 1991 2011 District 1991 2011 Characteristic: Literacy rate 215 428 South Arcot (RD) 128 196 South Arcot (RD) 375 324 Thanjavur (RD) 342 466 Sambuvarayar (RD) Dharmapuri (RD) 323 314 Chidambaranar 153 140 Pudukottai 156 85 Dharmapuri (RD) 126 89 MGR Chengai (RD) 159 137 MGR Chengai (RD) 147 129 North Arcot 91 101 (RD) 125 70 Salem 159 198 115 99 112 68 Tiruvannamalai 127 109 Tiruchirappalli (RD) 103 88 108 48 Sambuvarayar (RD) Periyar 99 140 South Arcot (RD) 94 124 Tiruvannamalai Total 1,143 1,082 Total 954 1,046 Sambuvarayar (RD) 72 113 Characteristic: Sex ratio Total 1,039 1,057 Total 1,099 981 Dharmapuri (RD) 234 203 South Arcot (RD) 303 319 Characteristic: Non-agri/TW South Arcot (RD) 232 209 MGR Chengai (RD) 385 306 South Arcot (RD) 309 344 MGR Chengai (RD) 245 357 MGR Chengai (RD) 158 135 Thanjavur (RD) 205 214 Dharmapuri (RD) 241 149 Salem 161 112 Tiruvannamalai 152 148 Salem 157 157 MGR Chengai (RD) 140 52 North Arcot 148 199 Sambuvarayar (RD) Pudukottai 129 191 Tirunelveli 128 98 Pudukottai 123 122 Tiruvannamalai 121 108 Kamarajar 83 125 Thanjavur (RD) 108 129 Sambuvarayar(RD) Total 1,007 946 Total 1,050 996 Salem 115 89 Characteristic: %SCST Thanjavur (RD) 87 151 Dharmapuri (RD) 288 315 Pasumpon 200 94 Total 1,142 1,084 Total 765 891 Salem 288 224 Chidambaranar 187 99 Characteristic: AL/AW South Arcot (RD) 223 231 Tirunelveli 172 78 Dharmapuri (RD) 228 203 Thanjavur (RD) 376 334 MGR Chengai (RD) 181 151 Pudukottai 149 144 Pudukottai 220 122 MGR Chengai (RD) 323 244 Thanjavur (RD) 105 73 MGR Chengai (RD) 136 147 South Arcot (RD) 219 209 South Arcot (RD) 217 296 Thanjavur (RD) 132 337 152 423 Madurai 151 119 South Arcot (RD) 108 98 Pasumpon 125 47 Ramanathapuram 100 46 Tiruvannamalai Total 1,085 994 Total 1,184 1,043 Sambuvarayar (RD) 121 148 Characteristic: TW/total pop MGR Chengai (RD) 102 135 South Arcot (RD) 294 169 Salem 195 202 Thanjavur (RD) 39 129 MGR Chengai (RD) 283 274 Kamarajar 134 55 Total 1,206 1,416 Total 1,067 993

72 december 26, 2015 vol l no 52 EPW Economic & Political Weekly REVIEW OF RURAL AFFAIRS

Appendix 2: Taluk Concentrations Appendix2D: Distribution of Villages in BD and TD by WPR across Taluks Appendix 2A: Distribution of Villages in BD and TD by LR across Taluks Sl Taluks Bottom Decile TW BD TW BD Taluks Top Decile TW BD TW BD Sl Taluks Bottom Decile LR BD TW BD Taluks Top Decile LR TD LR TD No 91 11 91 11 No 91 11 91 11 1 Chengai MGR Kantaankolathur 65 67 Dharmapuri Harur 67 35 1 South Arcot Kallakurichi 111 108 Chengai MGR Kantaankolathur 40 2 Pudukottai Avudaiyar Kovil 47 Anna 59 56 2 South Arcot Thiruvennainallur 76 56 Chidambaranar 3 Chengai MGR Sriperumbudur 37 49 Kamarajar 39 41 Aruppukottai 44 3 Dharmapuri Hosur 69 65 Tiruchirappalli Lalgudi 37 46 4 South Arcot Thiruvennainallur 34 Coimbatore 44 4 Dharmapuri Harur 65 59 Thanjadvur Nannilam 37 63 5 South Arcot Kallakurichi 33 Tiruchirappalli 41 5 Tiruvannamalai Tirunelveli 32 6 South Arcot Villupuram 32 Madurai Tirumangalam 39 Sambuvarayar 57 55 7 Pudukottai Thirumayam 32 Kamarajar Virudhunagar 36 6 South Arcot Tirukoilu 54 56 Chidambaranar Thoothukudi 8 South Arcot Gingee 31 Salem 33 30 9 Pudukottai Alangudi 29 Chidambaranar Thoothukudi 31 7 Dharmapuri Denkanikotta 42 47 Tiruchirappalli Trichirapalli 30 10 South Arcot Tirukoilu 29 South Arcot Kallakurichi 30 31 8 Dharmapuri 41 42 Tirunelveli Nanguneri 29 11 North Arcot Ambedkar Walajpet 29 Salem 40 9 Salem 36 45 Thanjavur 29 45 12 Thanjavur Kummbakonam 39 Chidambaranar Thoothukudi 10 Dharmapuri Pallakodu 35 44 Thanjavur Kudavasal 29 40 Vilathikulam 37 South Arcot Kattumannarkoil 31 13 Thanjavur Mayiladuturai 35 Periyar Erode 40 11 Thanjavur Mayiladuturai 37 14 Thanjavur Tiruvidaimarudur 37 South Arcot Gingee 56 12 South Arcot 34 15 Thanjavur Pattukottai 47 Salem 36 13 Thanjavur 32 16 Thanjavur Nannilam 35 Tiruvannamalai Sambuvarayar 14 Thanjaur Thiruvaiyaru 32 33 17 Thanjavur Papanasam 35 Tiruvannamalai Sambuvarayar Appendix 2B: Distribution of Villages in BD and TD by SR across Taluks 31 Sl Taluks Bottom Decile SR BD SR BD Taluks Top Decile SR TD SR TD 18 Pudukottai Arantangi 34 No 91 11 91 11 1 Dharmapuri Harur 89 54 Pasumpon Sivagangai Appendix 2E: Distribution of Villages in BD and TD by AL/AW across Taluks Tiruppattur 57 Sl Taluks Bottom Decile ALAW ALAW Taluks Top Decile ALAW ALAW 2 Dharmapuri Uttangarai 75 68 Pudukottai Thirumayam 55 No BD 91 BD 11 TD 91 TD 11 3 Salem Salem 71 41 Pasumpon Sivagangai 1 Dharmapuri Hosur 78 Madurai Madurai North 59 31 54 33 2 Pudukottai Avudaiyar Kovil 74 Chengai MGR Kantaankolathur 50 4 Salem 64 54 Tirunelveli Nanguneri 46 3 Ramanathapuram 60 Chengai MGR 47 5 Salem Sankari 57 Chidambaranar Thoothukudi 4 Kamarajar Virudhunagar Tiruchuli 47 Chengai MGR Ponneri 46 5 South Arcot Kallakurichi 46 Chengai MGR Sriperumbudur 44 Vilathikulam 45 33 6 Dharmapuri Harur 42 34 South Arcot Kattumannarkoil 42 47 6 Chengai MGR Pudukottai Avudiayar Kovil 42 7 Pudukottai Kulattur 41 South Arcot Chidambaram 42 49 Kantaankolathur 48 33 8 South Arcot Thiruvennainallur 40 Thanjavur Thiruvarur 34 45 7 Dharmapuri Hossur 36 34 Kamarajar Virudhunagar 9 Pasumpon Sivagangai Sivaganga 36 Chengai MGR Kancheepuram 33 28 Aruppukottai 37 10 Dharmapuri Uttangarai 35 66 Thanjavur Nannilam 33 49 8 Salem 35 Ramanathapuram Tiruvadanai 34 11 Pasumpon Sivagangai Chengai MGR Maduranthagam 34 9 Tiruvannamalai Pasumpon Sivagangai Devaikkottai Sambuvarayar Chengam 29 Devaikkottai 34 12 South Arcot Gingee 41 Thanjavur Papanasam 32 10 South Arcot Kallakurichi 29 43 Chidmabaranar Thoothukudi 13 Ramanathapuram Chidmabaranar Thoothukudi Kovilpatti 32 38 Vilathikulam 29 11 Dharmapuri Pallakodu 45 Thanjavur Patuukkottai 90 14 Pudukottai THirumayam 38 Madurai Tirumangalam 29 12 Dharmapuri Denkanikotta 34 Pudukottai Arantangi 57 15 Pudukottai Arantangi 47 13 Thanjavur Orathanadu 47 16 Tiruvannamalai Sambuvarayar 14 Thanjavur 34 Cheyyar 43 15 Chengai MGR Kancheepuram 26 17 Tiruvannamalai Sambuvarayar Tiruvannamalai 40 16 Tiruchirappalli Lalgudi 24 18 Dharmapuri Krishnagiri 38 17 Pudukottai Alangudi 24 19 Tiruvannamalai Sambuvaryar Polur 35 18 Thanjavur Mayiladuturai 23 20 Thanjavur Pattikkottai 35 Appendix 2C: Distribution of Villages in BD and TD by %SCST across Taluks 21 Chengai MGR Kantaankolathur 34 Sl Taluks Bottom Decile SCST SCST Taluks Top Decile SCST SCST Appendix 2F: Distribution of Villages in BD and TD by Non-agri/ No BD 91 BD 11 TD 91 TD 11 TW across Taluks 1 Dharmapuri Uttangarai 66 66 Dharmapuri Harur 68 59 Sl Taluks Bottom Decile Non-agri/ Non-agri/ Taluks Top Decile Non-agri/ Non-agri/ 2 Tiruvannamalai Sambuvarayar Chengai MGR Kantaankolathur 66 35 No TW BD 91 TW BD 11 TW BD 91 TW BD 11 Tiruvannamalai 51 40 1 South Arcot Kallakurichi 71 78 Chengai MGR Sriperumbudur 35 93 3 Dharmapuri Harur 48 34 South Arcot Kallakurichi 66 61 2 Pudukottai Arantangi 55 Chengai MGR Kantaankolathur 70 88 4 Chengai MGR Kantaankolathur 47 34 Chengai MGR Sriperumbudur 62 3 South Arcot Gingee 35 53 Kamarajar Virudhunagar Sattur 56 5 South Arcot Gingee 47 41 Salem Yercaud 60 57 4 Pudukottai Avudaiyar Kovil 61 51 North Arcot Ambedkar 54 6 Dharmapuri Krishnagiri 43 38 Chengai MGR Maduranthagam 59 58 5 South Arcot Tittagudi 49 North Arcot Ambedkar 43 7 Tiruvannamalai Sambuvarayar 42 43 South Arcot Kattumannarkoil 44 37 6 Dharmapuri Harur 83 40 Salem Yercaud 36 38 Cheyyar 7 South Arcot Thiruvennainallur 47 35 Chengai MGR Ponneri 35 8 Pudukottai Arantangi 39 46 Chengai MGR Kancheepuram 39 42 8 Dharmapuri Uttangari 43 34 Chenagi MGR 35 34 9 Thanjavur Peravurani 34 South Arcot 39 9 Tiruvannamalai Sambuvarayar Polur 33 Chenagi MGR Tiruvallur 30 10 Salem Salem 31 Tiruvannamalai Sambuvarayar 10 Dharmapuri Hosur 37 30 North Arcot Ambedkar 30 30 Chengam 37 11 Kamarajar Tiruchuli 51 Salem Salem 45 12 Tiruvannamalai Periyar Perundurai 41 11 Thanjavur 35 Thanjavur Thiruvarur 40 Sambuvarayar Chengam 40 12 Tiruvannamalai South Arcot Chidambaram 36 13 Dharmapuri Krishnagiri 33 Tirunelveli Ambasamudram 40 Sambuvarayar Polur 36 14 North Arcot Ambedkar 34 13 Chengai MGR Cheyyur 36 15 Chengai MGR Kancheepuram 30

Economic & Political Weekly EPW december 26, 2015 vol l no 52 73