Mul­ti­collinear­ity be­tween dif­fer­ent vari­ables of hu­man devel­op­ment in­dex for bet­ter in­clu­sive growth pol­icy

Economic Challenger - - CONTENTS - − Su­nil Ku­mar, Nim­rata Arora


’The tran­si­tion of In­dian econ­omy from un­der­de­vel­oped to de­vel­op­ing econ­omy traced var­i­ous so­cial eco­nomic prob­lems which have not been con­quered by an in­creased rate of eco­nomic growth. Apart from the in­equal­ity of in­come, var­i­ous other ben­e­fits were not ex­tended to vul­ner­a­ble sec­tions of the so­ci­ety like ad­e­quate ed­u­ca­tion, im­proved health fa­cil­ity and bet­ter em­ploy­ment. Var­i­ous poli­cies have been im­ple­mented by the government to bridge the wide gap be­tween the two groups of so­ci­ety and ini­ti­ated a move to­wards hu­man devel­op­ment from eco­nomic growth. The re­la­tion­ships of life ex­pectancy, ed­u­ca­tion, poverty, and safe water in­dex have been eval­u­ated with HDI. The re­la­tion­ship be­tween HDI and its de­ter­mi­nant vari­ables has been in­ves­ti­gated with the lin­ear mul­ti­ple re­gres­sion model. The ed­u­ca­tion in­dex and safe drink­ing water have been found as the sig­nif­i­cant vari­ables in the de­ter­mi­na­tion of HDI. Th­ese two vari­ables also have the mul­ti­collinear­ity with other vari­ables.

Key Words: Hu­man Devel­op­ment In­dex, In­clu­sive Growth, Mul­ti­collinear­ity, Safe Drink­ing Water. Ab­bre­vi­a­tions: GDP: Gross Domestic Prod­uct, HDI: Hu­man Devel­op­ment In­dex, SHG: Self Help Group, UNDP: United Na­tion Devel­op­ment Pro­gram.


The devel­op­ment of na­tion has been the prime ob­jec­tive of ev­ery econ­omy. Over the last six and half decades the In­dian econ­omy has passed through var­i­ous growth−phases, start­ing from back­ward econ­omy with low growth rate to de­vel­op­ing and sus­tain­able econ­omy. Now, the In­dian econ­omy has en­tered into a dif­fer­ent or­bit en­dorsed as high rate of ex­pan­sion with com­bined ob­jec­tive of in­clu­sive growth. The growth ex­pe­ri­ences of the In­dian econ­omy have been re­mark­able fol­low­ing pos­i­tive trend from the sec­ond five year plan on­wards. By over­com­ing the bane of Bri­tish Government rule, the econ­omy had achieved av­er­age 4.1 per­cent gross domestic prod­uct (GDP) growth rate in the foun­da­tional years that is 1951−1965. With the prob­lem of food cri­sis and de­fen­sive ac­tions the av­er­age growth rate of the econ­omy de­clined a lit­tle in the pe­riod 1965−1975 at 3 per­cent. Af­ter this pe­riod, the In­dian econ­omy at­tained decadal av­er­age growth rate rang­ing from 5.6 per­cent to 8.2 per­cent.

A growth process must yield and en­sure equal ben­e­fi­cial op­por­tu­ni­ties for all . But the as­sump­tion of eco­nomic growth prac­tice, with an in­crease in in­dus­trial growth rate thereby in­creas­ing per capita in­come and ul­ti­mately up­lift­ing stan­dard of liv­ing of the masses at large, had been a fail­ure which em­pha­sized the is­sues of hu­man ca­pa­bil­i­ties. Hu­man ca­pa­bil­i­ties re­fer to ’ well−be­ing’ of the gen­eral masses ( Kindle­berger, 1965). It is a so­cio−eco­nomic is­sue which is not ar­tic­u­lated in eco­nomic growth, for ex­am­ple, in­come dis­par­ity, il­lit­er­acy, un­em­ploy­ment, poverty, poor health fa­cil­ity, scanty liv­ing stan­dard and low life ex­pectancy ( Gasper and Staveren, 2010). Sen (1980)

iden­ti­fies ba­sic ca­pa­bil­i­ties to achieve well− be­ing for the gen­eral masses. The ca­pa­bil­i­ties to be well−nour­ished and well−shel­tered, to es­cape pre­ma­ture mor­tal­ity, to be ed­u­cated and in good health, and to be able to par­tic­i­pate in so­cial in­ter­ac­tion with­out shame are some ex­am­ples of ba­sic ca­pa­bil­i­ties. Var­i­ous econ­o­mists iden­ti­fied the ca­pa­bil­ity ap­proach in their own way. Alkire ( 2002) fo­cused on ’ca­pa­bil­ity to meet ba­sic needs’, Robeyns (2001) de­fined fun­da­men­tal ca­pa­bil­i­ties and di­vided into ba­sic and non−ba­sic ca­pa­bil­i­ties . To over­come th­ese prob­lems, government in­ter­fered to im­prove the liv­ing stan­dard and so­cio−eco­nomic be­hav­ior of vul­ner­a­ble sec­tions of the so­ci­ety by im­ple­ment­ing var­i­ous poli­cies. The government has made in­ter­fer­ence, firstly, by pro­vid­ing di­rect ben­e­fits for ex­am­ple sub­si­dies, pub­lic distri­bu­tion sys­tem (fair price shops), free ed­u­ca­tion, free vac­ci­na­tion, and var­i­ous poli­cies on em­ploy­ment op­por­tu­ni­ties. Se­condly, by pro­vid­ing as­sis­tance to the de­prived but en­tre­pre­neur­ial sec­tion of the so­ci­ety for ex­am­ple Kisan Credit Card scheme for peas­ants, loans to small scale/ cot­tage in­dus­tries or, self help groups (SHGs) through mi­cro fi­nance and bank­ing in­sti­tu­tions etc. The self re­liance and en­hanc­ing the job op­por­tu­ni­ties are the ma­jor at­tributes of in­clu­sive growth strat­egy as adopted by the government.

Hu­man cap­i­tal is im­pli­cated in the process of growth not merely as a cause but also as an ef­fect of eco­nomic growth and con­trib­utes to eco­nomic devel­op­ment. The re­cip­ro­cal re­la­tion be­tween eco­nomic growth and the growth of hu­man cap­i­tal is likely to be an im­por­tant key to sus­tained eco­nomic growth ( Min­cer, 1995) .

To achieve eco­nomic devel­op­ment, it has to en­sure that all seg­ments of the so­ci­ety be­come part of this growth process; oth­er­wise th­ese so­cio−eco­nomic prob­lems could de­rail the econ­omy from growth (devel­op­ment) track. The term in­clu­sive growth is of­ten used in­ter­change­ably with a suite of other terms like ’broad−based growth’, ’shared−growth’, ’pro−poor growth’, and ’ eq­ui­table growth’ etc. The term in­clu­sive growth is find­ing its way in­creas­ingly in the lex­i­con of government lead­ers, econ­o­mists, plan­ners, and aca­demi­cians not just in In­dia but even in pan−Asia


In­di­ca­tors of Hu­man Devel­op­ment In­dex (HDI) such as lit­er­acy, ed­u­ca­tion, ma­ter­nal and in­fant mor­tal­ity rates, show steady im­prove­ment, but the progress is slow and In­dian econ­omy is still be­hind sev­eral other Asian coun­tries.

HDI is the ag­gre­gate re­sult of the dif­fer­ent vari­ables of so­cial devel­op­ment viz., poverty in­dex, ed­u­ca­tion in­dex, life ex­pectancy in­dex, em­ploy­ment op­por­tu­ni­ties, water re­sources and GDP in­dex etc. It means the per­for­mance of HDI de­pen­dents on the per­for­mance of in­di­vid­ual in­dex of poverty, ed­u­ca­tion, life ex­pectancy, em­ploy­ment op­por­tu­ni­ties, im­proved water re­sources etc. In the present study, the re­la­tion of de­pen­dency has been in­ves­ti­gated be­tween HDI and in­di­vid­ual in­dex per­for­mance of var­i­ous vari­ables.


In the present study, the in­flu­ence of five pre­dic­tors viz., life ex­pectancy, ed­u­ca­tion, poverty, safe water avail­abil­ity and GDP in­dex have been con­sid­ered to an­a­lyze the de­pen­dency of HDI. The in­di­vid­ual fac­tor per­for­mance also in­flu­ences the other fac­tor, for ex­am­ple im­prove­ment in the poverty in­dex shows that there is im­prove­ment in the eco­nomic con­di­tion of the masses and in­crease in the ac­cess­ing ca­pa­bil­ity of health and san­i­ta­tion fa­cil­i­ties ul­ti­mately in­creases the life ex­pectancy of the peo­ple. Sim­i­lar cor­re­la­tion could be found in cases of other vari­ables also. The sig­nif­i­cant cor­re­la­tion be­tween the pre­dic­tor vari­ables cre­ates the prob­lem of mul­ti­collinear­ity. To eval­u­ate the cor­re­la­tion and re­gres­sion of pre­dic­tor and de­pen­dent vari­ables, mul­ti­ple− re­gres­sion anal­y­sis has been used to an­a­lyze the de­pen­dency of HDI on th­ese pre­dic­tor vari­ables. The sta­tis­ti­cal equa­tion of the lin­ear model of mul­ti­ple−re­gres­sion for four pre­dic­tors (life ex­pectancy in­dex, ed­u­ca­tion in­dex, poverty in­dex and safe water avail­abil­ity in­dex) and one de­pen­dent vari­able (HDI) is as fol­lows:

Y= β0+ β1X1+ β2 X2 + β3 X3 + β4 X4 + β5 X5 + ε

Where Y = Value of de­pen­dent vari­able (HDI)

= a con­stant, the value of Y when all Xi val­ues are zero. = the slope of the re­gres­sion sur­face ( It rep­re­sents the re­gres­sion co­ef­fi­cient as­so­ci­ated with each Xi) X1 = life ex­pectancy in­dex. X2 = ed­u­ca­tion in­dex. X3 = poverty in­dex. X4 = safe drink­ing water in­dex. X5 = GDP in­dex

= an er­ror term, nor­mally dis­trib­uted about a mean of 0.

For the pur­pose of present study ten years data have been col­lected on life ex­pectancy in­dex, ed­u­ca­tion in­dex, poverty in­dex and safe water in­dex start­ing from the year 1998 to 2007. The data have been col­lected from the United Na­tion Devel­op­ment Pro­gram (UNDP) re­ports on Hu­man Devel­op­ment. The data per­tain­ing to In­dian econ­omy have been con­sid­ered for the above said pe­riod. The fol­low­ing vec­tors set the re­la­tion­ship of re­gres­sion equa­tion as dis­cussed above for all four vari­ables with their co­ef­fi­cients.

The above stated vec­tors are rep­re­sent­ing the each equa­tion of mul­ti­ple re­gres­sion model for ten years in­dex val­ues. The val­ues for ß0 will be equal to 1, used to ob­tain the re­gres­sion con­stant. The val­ues for re­main­ing ßi per­tain­ing to four pre­dic­tor vari­ables and con­tain scores (co­ef­fi­cients) for th­ese sub­jects. The log val­ues of HDI and pre­dic­tor vari­ables have been con­sid­ered to gen­er­al­ize the ac­tual val­ues.


The re­sults on mul­ti­ple−re­gres­sion have been pre­sented in the fol­low­ing ta­bles. Ta­ble 1 shows the cor­re­la­tion be­tween the HDI and pre­dic­tor vari­ables. Ta­ble 2 re­veals the pre­dic­tor vari­ables those which have been ei­ther en­tered or re­moved for the anal­y­sis. Ta­ble 1 states the model sum­mary with the help of resid­ual sum square. Ta­ble 2 demon­strates the co­ef­fi­cients and collinear­ity statis­tics, and Ta­ble 3 shows the collinear­ity di­ag­nos­tic.

Ta­ble 1 states the model sum­mary. The value of R−Square for ed­u­ca­tion in­dex is 0.845 and for safe water avail­abil­ity in­dex is 0.941. Sim­i­larly, R−Square of vari­ables LI, PI, and GI is 0.128, 0.112, and 0.903, re­spec­tively. The value of Ad­justed R−square shows the per­cent of vari­a­tion. It shows that 81.9 per­cent vari­a­tion has been ex­plained by the ed­u­ca­tion in­dex and 91.7 per­cent vari­a­tion has been ex­plained by the both ed­u­ca­tion in­dex and safe water avail­abil­ity in­dex. All the vari­ables are sta­tis­ti­cally sig­nif­i­cant. The value of R−square is close to 1 which states the ro­bust­ness of the model.

Ta­ble 2 re­veals the stan­dard­ized co­ef­fi­cients of beta val­ues. It also shows the collinear­ity statis­tics as tol­er­ance and vari­ance in­flated fac­tor (VIF) . The co­ef­fi­cient of ed­u­ca­tion in­dex and safe drink­ing water in­dex are sig­nif­i­cant at 0.01 and 0.05 level. Tol­er­ance shows the per­cent of the vari­ance in a given pre­dic­tor that can­not be ex­plained by other pre­dic­tors. The small value of tol­er­ance shows that vari­ance of a given pre­dic­tor is ex­plained by other pre­dic­tors, and large value shows that vari­ance is ex­plained by the vari­able it­self. The val­ues of co­ef­fi­cients are sig­nif­i­cant. The ed­u­ca­tion in­dex co­ef­fi­cient is sig­nif­i­cant at the 0.01 level and safe water avail­abil­ity in­dex co­ef­fi­cient is sig­nif­i­cant at the 0.05 level. The tol­er­ance val­ues are close to ’1’ it means very less per­cent­age of vari­ance of ed­u­ca­tion and safe water avail­abil­ity in­dex is shown by other pre­dic­tors. This is the rea­son of se­lect­ing th­ese two pre­dic­tors in the model.

The co­ef­fi­cient of all the vari­ables is not sig­nif­i­cant which shows that th­ese vari­ables play a less im­por­tant role in the de­ter­mi­na­tion of HDI as com­pared to ed­u­ca­tion in­dex and safe water avail­abil­ity. The collinear­ity statis­tics tol­er­ance shows that around 30 to 85 per­cent of the

in­for­ma­tion is ex­plained by the ed­u­ca­tion in­dex and safe water avail­abil­ity in­dex as tol­er­ance score ranges from 0.142 to 0.708. The least value of tol­er­ance of GDP in­dex leads to in­flated value of vari­ance of poverty in­dex and shows the prob­lem­atic sit­u­a­tion of collinear­ity.

Ta­ble 3 re­veals the di­ag­nos­tics for the mul­ti­ple cor­re­lated vari­ables. It shows that ei­gen­value of the vari­ables ed­u­ca­tion in­dex and avail­abil­ity of safe water is around one and con­di­tion in­dex is be­low 5 which states that th­ese two vari­ables are least in­flu­enced by each other. From the above dis­cus­sion it can be con­cluded that ed­u­ca­tion in­dex is the most im­por­tant pre­dic­tor of HDI. It shows that an in­crease in ed­u­ca­tion among the gen­eral masses in­creases the aware­ness of health, ca­reer, bet­ter em­ploy­ment op­por­tu­ni­ties, and ex­pec­ta­tion of good liv­ing con­di­tions that re­sult into the im­prove­ment in poverty sit­u­a­tion. The in­creas­ing aware­ness about health among the gen­eral masses, the ac­ces­si­bil­ity of safe drink­ing water is also a pre­dic­tor of im­proved hu­man devel­op­ment in­dex. The re­sults also in­di­cate that the safe drink­ing water en­sures the good health of the gen­eral masses. As an im­pli­ca­tion, government should take ef­fec­tive mea­sures to en­sure suc­cess­ful ed­u­ca­tion sys­tem and avail­abil­ity of safe drink­ing water.


It has been ob­served that the ed­u­ca­tion in­dex also rep­re­sents other in­dexes which mean that HDI could be im­proved with the im­prove­ment in the ed­u­ca­tion in­dex. Aware­ness about health, in­creased pro­duc­tion, aris­ing is­sues of ex­ter­nal­i­ties and eco­nomic growth are some of the ben­e­fits of ed­u­cat­ing masses of pop­u­la­tion ( Nichloas, 1987). Broadly hu­man cap­i­tal is re­lated with knowl­edge and skills em­bod­ied in hu­mans that are ac­quired through school­ing, train­ing and ex­pe­ri­ence are use­ful in the pro­duc­tion of goods, ser­vices and fur­ther knowl­edge. Plau­si­bly ed­u­ca­tion is key fac­tor to hu­man cap­i­tal and also sup­ple­mented by health con­di­tions (Shekhar, 2006).

Barro and Martin (1995) es­ti­mated a log lin­ear re­la­tion­ship be­tween years of ed­u­ca­tion and an­nual wage in­come. They sug­gest that an ad­di­tional year of school­ing in­creases wages at the in­di­vid­ual level by around 6.5 per cent in Euro­pean Union . The pos­i­tive role of the state in ed­u­ca­tion can over­come prob­lems as­so­ci­ated with hu­man well−be­ing, both, eco­nomic and so­cial. The ed­u­ca­tion should not just be left

ei­ther to the whims of mar­ket mech­a­nism rather State should in­ter­fere to in­crease hu­man ca­pa­bil­i­ties (Deitz and Cypher, 2009). How­ever, there are num­ber of pol­icy mea­sures which al­ready have been un­der­taken by the government to en­sure bet­ter ed­u­ca­tion in­dex, for ex­am­ple, Sarva Shik­sha Ab­hiyan, free ele­men­tary ed­u­ca­tion, and schol­ar­ships for fe­male child etc. Be­sides in­creas­ing the num­ber of pri­mary school en­rol­ment, government should for­mu­late the poli­cies which could sus­tain the pri­mary school en­rol­ment per­cent­age and be help­ful for in­creas­ing the per­cent­age of sec­ondary and higher ed­u­ca­tion (Ti­lak, 2007).

Safe drink­ing water avail­abil­ity in­dex is the sec­ond most im­por­tant pre­dic­tor vari­able for HDI. It is an im­por­tant vari­able be­cause it has not been pre­sented by other pre­dic­tor vari­ables. In sim­ple words, it has no sig­nif­i­cant cor­re­la­tion with other vari­ables. Tadaro ( 1998) has es­ti­mated that more than one bil­lion peo­ple world− wide have no ac­cess to clean water and an ad­di­tional one bil­lion live in ar­eas with chronic water short­ages. And many of the poor col­lect drink­ing water from rivers and canals that are pol­luted with hu­man exc­reta and chem­i­cal which is con­tribut­ing to the spread of dis­eases.

The in­creased life ex­pectancy might not en­sure the avail­abil­ity of safe drink­ing water rather safe drink­ing water avail­abil­ity may en­sure the bet­ter life ex­pectancy.

The water qual­ity mon­i­tor­ing is now be­ing con­sid­ered as an im­por­tant part of the government pro­gram. Since the year 2000, water qual­ity mon­i­tor­ing has been ac­corded a high pri­or­ity and in­sti­tu­tional mech­a­nisms have been devel­oped at na­tional, state, district, block and pan­chayat lev­els. The government has also out­lined req­ui­site mech­a­nisms to mon­i­tor the qual­ity of drink­ing water and de­vise ef­fec­tive In­for­ma­tion, Ed­u­ca­tion and Com­mu­ni­ca­tion (IEC) in­ter­ven­tions to dis­sem­i­nate in­for­ma­tion and ed­u­cate peo­ple on health and hy­giene. The Government of In­dia launched the Na­tional Ru­ral Drink­ing Water Qual­ity Mon­i­tor­ing and Sur­veil­lance Pro­gram in Fe­bru­ary 2006. This en­vis­ages in­sti­tu­tion­al­iza­tion of com­mu­nity par­tic­i­pa­tion for mon­i­tor­ing and sur­veil­lance of drink­ing water sources at the grass­root lev­els by Gram Pan­chay­ats and Vil­lage Water and San­i­ta­tion Com­mit­tees, fol­lowed by check­ing the pos­i­tively tested sam­ples at the district and state level lab­o­ra­to­ries. One ma­jor prob­lem when it comes to ad­dress­ing the prob­lems re­lated to water is that the pro­vi­sions for water are dis­trib­uted across var­i­ous min­istries and in­sti­tu­tions. With sev­eral in­sti­tu­tions in­volved in water sup­ply, in­ter−sec­toral co­or­di­na­tion be­comes crit­i­cal for the success of the pro­gram.

The trends of government bud­get on health and fam­ily wel­fare has a sig­nif­i­cant role in the im­prove­ment of var­i­ous pre­dic­tor vari­ables of HDI. As an im­pli­ca­tion to the government and pol­icy maker, it is sug­ges­tive that the ed­u­ca­tion per­cent­age should be in­creased by im­ple­ment­ing more fea­si­ble poli­cies. The ini­tia­tive taken for avail­abil­ity of safe drink­ing water should be con­tin­ued. The em­ploy­ment op­por­tu­ni­ties gen­er­ated un­der the so­cial ser­vices are not only solv­ing the prob­lem of un­em­ploy­ment rather th­ese are also help­ful to in­crease the stan­dard of liv­ing be­cause the ma­jor aims of th­ese em­ploy­ment op­por­tu­ni­ties are de­vel­op­ing hy­giene con­di­tions around the liv­ing ar­eas and self−devel­op­ment of the vul­ner­a­ble sec­tions of the so­ci­ety.


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from a Gen­der Per­spec­tive, Ox­ford Univer­sity Press, New Delhi. 4. Sen, Amartya (1980), Equal­ity of what? In The Tan­ner Lec­ture on Hu­man Val­ues, edited by S. McMur­rin. Cam­bridge: Cam­bridge Univer­sity Press. 5. Alkire, Sabina (2002), Valu­ing free­dom: Sen’s ca­pa­bil­ity ap­proach and poverty re­duc­tion. Ox­ford Univer­sity Press, Ox­ford. 6. Robeyns, In­grid (2001), Un­der­stand­ing Sen’s ca­pa­bil­ity ap­proach. Avail­able from http://­ 7. Min­cer, Ja­cob (1995), Eco­nomic Devel­op­ment, Growth of Hu­man Cap­i­tal and the Dy­nam­ices of the Wage Struc­ture, Jour­nal of Eco­nomic Growth, Vol. 1, pp. 29− 48. 8. Eleventh Five Year Plan (2007−12), In­clu­sive Growth, Plan­ning Com­mis­sion, Government of In­dia, Vol. 1, 2008. 9. Stevens, James P. ( 2009), Ap­plied Mul­ti­vari­ate Statis­tics for the So­cial Sciences, Tay­lor & Fran­cis, USA, pp. 63− 93 10. Mul­ti­ple re­gres­sion is used as a de­scrip­tive tool in three types of sit­u­a­tions. First, it is of­ten used to de­velop a self−weight­ing es­ti­mates equa­tion by which to pre­dict val­ues for a cri­te­rion vari­ables from the pre­dic­tor vari­ables. Sec­ond is used for con­trol­ling for con­found­ing vari­ables to bet­ter eval­u­ate the con­tri­bu­tion of other vari­ables. The third type re­ferred to de­scribe an en­tire struc­ture of link­ages that have been ad­vanced from ca­sual the­ory. 11. The vari­ance in­fla­tion fac­tor (VFI) for a pre­dic­tor in­di­cates whether there is a strong lin­ear as­so­ci­a­tion be­tween it and all the re­main­ing pre­dic­tors. My­ers (1990) of­fered the fol­low­ing sug­ges­tion: "Though no rule of thumb on num­ber­i­cal val­ues is fool­proof, it is gen­er­ally be­lieved that if any VIF value ex­ceeds 10, there is rea­son for at least some con­cern; then one should con­sider an alternative to least squares es­ti­ma­tion to com­bat the prob­lem". 12. Barr, Ni­cholas (1987), The Eco­nom­ics of the Wel­fare State, Wei­den­feld and Ni­col­son, (Lon­dan), pp. 288−293. 13. Ku­mar, C. Shekhar (2006), Hu­man Cap­i­tal and Growth Em­pir­ics, The Jour­nal of De­vel­op­ing Ar­eas, Vol. 40, No. 1, pp. 153− 179. 14. Barro and Sala−I−Martin (1995), Tech­no­log­i­cal Dif­fu­sion, Con­ver­gences and Growth, NBER Work­ing Pa­per, 5151. 15. Di­etz, James L. and Cypher, James M. ( 2009), The Process of Eco­nomic Devel­op­ment, Rout­ledge (USA), pp. 391− 415. 16. Ti­lak, Jand­hyala B. G. ( 2007), Post− ele­men­tary Ed­u­ca­tion, Poverty and Devel­op­ment in In­dia, In­ter­na­tional Jour­nal of Ed­u­ca­tional Devel­op­ment, Vol.27, is­sue 4, pp. 435−445. 17. Tadaro, Michael P. (1998), Eco­nomic Devel­op­ment, Ad­di­son Wes­ley Long­man (USA), p.365. 18. Chandra­iah, C. Ramesh (2001), Drink­ing Water as a Fun­da­men­tal Right, Eco­nomic and Po­lit­i­cal Weekly, Vol. 36, No.8, pp. 619− 621. 19. Rober J. Tata and Ron­ald R. Schnltz (1988), World Vari­a­tion in Hu­man Wel­fare: A New In­dex of Devel­op­ment Sta­tus, An­nals of the As­so­ci­a­tion of Amer­ica Ge­og­ra­phers, Vol. 78, No.4, pp.580−593.

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