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It observes that NREGA can have significant favourable multiplier impacts on a village economy, and it can lead to sustainable and labour intensive growth of the village / region. It can also contribute towards women s empowerment, and lead towards pro- poor growth. Z #Approach of the study The study involves construction of a Social Accounting Matrix (SAM) for Nana Kotda village in North Gujarat to understand the village economy. It uses multiplier analysis to assess of the impact of NREGA works, including those that address unpaid work, on household production, incomes and employment as well as on the village economy. The NREGS works are treated as external shocks in the analysis. ZMA$ Three major sources of Data  Comprehensive information on the economy of Nana Kotda through an in-depth census survey, Complete statistics on the working of National Rural Employment Guarantee Scheme (NREGS) in the village The time use data to estimate the time spent on unpaid SNA and non-SNA work $<1%!/Two observations on Employment Trends in India 0.$( Economic growth has failed to generate adequate size and quality of employment in the Indian economy. The neo-liberal paradigm does not have a built-in mechanism to ensure full employment / labour intensive growth. Huge burden of unpaid work (SNA and non-SNA) exists along with un/underemployment in the labour market. There is a need to shift unpaid work in the public domain. NREGA can ensure short term employment at the bottom as well as medium / long term labour intensive growth. 0PP&"Nana Kotda Village -1$LA backward village in Sabarkantha district, a district selected for NREGA in the first year. Main occupation: agriculture 91% population depend, fully or partly on agriculture and allied activities 404 Households  94 % belong to SC/ST/OBC 17% BPL  But unstable incomes for majority HHs  indebtedness and vulnerability. 50% adult women and one fourth of men are illiterate. Poor health and high human poverty. $Z'#Nana Kotda Village -2$ Gaps in basic services and infrastructure Poor education and health facilities Lack of dependable drinking water, sanitation, street lights in poorer localities. 8($Nana Kotda Village -3$ Agriculture: 70% rainfed  mostly single Unviable agriculture in 3 years out of every 5 years. Low production of animal husbandry / diary Rs 285/- per member per year. Low consumption expenditure  high indebtedness: 48% have average debt of Rs 33667 for consumption from private sources. 9% have taken loans for productive assets 0PTPT)%LNana Kotda Village  Employment Scene '%$( 78.38 WPR for men and 64.52 WPR for women: 132 days of average employment. 61.36% hired and 38.74 family lab 300 persons commute to nearby villages for manual work. High underemployment and unemployment and people want work / more work. ,*&&Burden of Unpaid SNA and non SNA work '%$(DFetching water, collecting fuel wood and fodder, collecting other free goods take up to 20% of the productive time of workers  men and women. Making dung cakes / animal grazing and other subsistence work. Unpaid non-SNA care and other activities It is feasible to reduce unpaid work of women and poor and release 350 women and 50 men for productive work in the labour market to raise their income and employment. TZZ@ZZZ+'NREGA in Nana Kotda -1  6 works in the first year  all check dam desilting. No work has been taken up thereafter. 238 persons (127 women and 111 men) from 161 households participated. 9812 person days, Rs. 5.86 lakh wage income. Wage rate between Rs 50  Rs 74. Average days of work for participant household : 53 days. For the village 14 days per year instead of 100 days. eZe,(NREGA in Nana Kotda -2$ The poorest participated the least in NREGA (2.48 %) The landless / MF participated the least No job guarantee, no unemployment allowance. No other entitlements. 66q-)NREGA in Nana Kotda -3$ 80% households want to work on NREGA if work is available. Many could not work on NREGA because (1) no information, (2) limited work distributed to a few (3) children at home, (4) no guarantee so have to migrate..Multiplier analysis using SAM  Definition: SAM is an organised matrix representation of all transactions and transfers between different production activities, factors of production and institutions ( Households, corporate sector, government) within the economy. NREG works undertaken in the village have multiplier effect on the output, income and employment of village economy. Multipliers measures the response of the economy to a change in the demand of a sector   )Output, Income and Employment Multipliers** * The output multiplier for a sector is defined as the total value of production by all the sectors of the economy due to change in one unit of final demand for that sector. The income or value added multipliers gives an estimates of the direct and indirect income changes resulting from the one unit change in output. The employment multiplier gives an estimate of the direct and indirect employment generated in the economy by one unit change in output for that sector. @Increased output & Income of HH- construction of six check dams  A?  $Impact of NREGS on Output and Income%%$      -Impact of NREGS works on employment continued..  (Output, Income and HH Income multipliers))    Values of Multiplier $Dynamission of Multiplier Coefficient Value will increase with larger NREGA with favourable distribution of income to the poor. Value will increase with expansion in local production.  %Multiplier underestimates the Impact &$$aImpact of check dam de silting: area under irrigation increased yields of cotton / castor increased new crops added. Cost of power in drawing water reduced. Farmers shifted to more productive / remunerative / labour intensive crops. More consumption of local crops multiplier coefficients increased. Needed large scale NREGA works - simulationT!PPPP,Pb!Going Beyond Multiplier Analysis ""(Q Health and Nutrition Education Improved access of women to productive work L"-PNREGA and Pro-Poor Development$Agricultural growth  increased productivity and incomes in agriculture. Animal husbandry development diversification of primary sector. Increased trading  non farmer sector possibilities. Labour intensive development. & Recommendations$Long term view: Systematic Planning: (1) perspective plan, (2) convergence, (3) multilevel planning. NREGA should address unpaid work for gender empowerment and poverty reduction. 60:40 ratio 100 days limit may be extended / removed. Large scale dissemination and social audit.  Z/+  THANK YOU !B 0*   0` 33` Sf3f` 33g` f` www3PP` ZXdbmo` \ғ3y`Ӣ` 3f3ff` 3f3FKf` hk]wwwfܹ` ff>>\`Y{ff` R>&- {p_/̴>?" dd@,|?" dd@   " @ ` n?" dd@   @@``PR    @ ` ` p>> LD(    6Ê  `}  T Click to edit Master title style! !  0Ɗ  `  RClick to edit Master text styles Second level Third level Fourth level Fifth level!     S  0l͊ ^ `  X*  0Ҋ ^   Z*  0p׊ ^ `  Z*  c \A .@logo4S`T4S`T"7  <A ??"P ` H  0޽h ? 3380___PPT10.w; G Default Design} 0  $(  r  S H> H r  S H `   H H  0޽h ? 33___PPT10i.w G+D=' = @B +0  0 0(  x  c $]H `}  H x  c $`^H ` H H  0޽h ? 3380___PPT10.NG0  0 0(  x  c $iH `}  H x  c $jH ` H H  0޽h ? 3380___PPT10.]0  0 0(  x  c ${H `}  H x  c ${H ` H H  0޽h ? 3380___PPT10.j7_0  0  0(  x  c $HH `}  H x  c $ H ` H H  0޽h ? 3380___PPT10. ,0  0 00(  x  c $H `}  H x  c $|H ` H H  0޽h ? 3380___PPT10.'0  0 @0(  x  c $ԧH`0  H x  c $H@ ` H H  0޽h ? 3380___PPT10. 0  0 P0(  x  c $H `}  H x  c $H ` H H  0޽h ? 3380___PPT10.@ 70  0 `0(  x  c $H `}  H x  c $H0 ` H H  0޽h ? 3380___PPT10.z0  0 p0(  x  c $  `}   x  c $ `  H  0޽h ? 3380___PPT10.`0  0 0(  x  c $ `}   x  c $ `0  H  0޽h ? 3380___PPT10.T0  0 0(  x  c $,6 `   x  c $70  H  0޽h ? 3380___PPT10.nX0  0 0(  x  c $E `   x  c $F0 `0  H  0޽h ? 3380___PPT10.`I0  0 0(  x  c $|U `}   x  c $$V0   H  0޽h ? 3380___PPT10.S  0 0r(    Hh `@     Bh   H  0޽h ? 33___PPT10i.Ь+D=' = @B +r  0 @r(    H4v      B w `0  H  0޽h ? 3380___PPT10. b=J  0 IIP_d1I(    H 0@   LB  c $D@H8 p} dp@}  H ? } ^1.17( "   @`  H ? } ^1.97( "   @`   HИ ? } `167.90( "   @`   Hر ?  } bTotal * "   @`   Hܻ ?%   ^1.48( "   @`   H0ƹ ?%   ^0.07( "   @`   H ? %   ^4.72( "   @`  Hڹ ?%   h All other HH*   "   @`  H ?y %  ^0.06( "   @`  H  ?y %  ^0.01( "   @`  Hp ? y %  _21.71( "   @`  H ?y  %  dServices*  "   @`  H ? y  ^0.99( "   @`  HT ? y  ^0.47( "   @`  HX  ? y  _47.45( "   @`  H* ?  y  bLabour* "   @`  H% ?!   ^1.40( "   @`  H,> ?!   ^0.20( "   @`  H0H ? !   _14.23( "   @`  HXB ?!   | Self employed in non agriculture*!  "   @`  H(\ ?u !  ^1.60( "   @`  Hf ?u !  ^0.33( "   @`  HTV ? u !  _20.57( "   @`  Hk ?u  !  h Large Farmer*   "   @`  Hă ? u  ^1.61( "   @`   Hȍ ? u  ^0.33( "   @` ! H ? u  _20.43( "   @` " HС ?  u  h Small Farmer*   "   @` # H ?   ^1.44( "   @` $ Hص ?   ^0.56( "   @` % H< ?    _38.79( "   @` & Hɿ ?   kMarginal Farmer* "   @` ' H`ӿ ?q  bGrowth* "   @` ( HͿ ?q  e Increased*   "   @` ) H ? q  `Base* "   @` * H ?q   e HH Income*   "   @` + HX ?$q R   @` , H ?$q R   @` - H  ? $q R   @` . H ?$ q R   @` / H  ?x$ ^2.22( "   @` 0 H8* ?x$ ^4.52( "   @` 1 H<4 ? x$ `188.61( "   @` 2 H> ?x $ bTotal * "   @` 3 HDH ?x ^4.53( "   @` 4 HB ?x ^1.67( "   @` 5 H[ ? x _36.88( "   @` 6 Hhf ? x }!Self- employed in non agriculture*" !"   @` 7 HDp ?  ^1.32( "   @` 8 Hy ?  ^0.25( "   @` 9 H ?  _19.27( "   @` : H~ ?   h Construction*   "   @` ; H ?t  ^1.78( "   @` < H ?t  ^0.53( "   @` = Ht ? t  _29.90( "   @` > H ?t  lAnimal husbandry* "   @` ? H ?t ^1.70( "   @` @ H ?t ^1.75( "   @` A Ht ? t `102.56( "   @` B H ? t g Agriculture*   "   @` C HT ? cpercent* "   @` D H ? dRs lakhs*  "   @` E H  ?  dRs lakhs*  "   @` F H  ?  ]* "   @` G HL  ?p bGrowth* "   @` H H`  ?p e Increased*   "   @` I H  ? p `Base* "   @` J HP.  ?p  bOutput* "   @`fB K 61 ?fB L 61 ? p }fB M 61 ?p}fB N 61 ?p}fB O 61 ?fB P 61 ?ttfB Q 61 ?  fB R 61 ?fB S 61 ?xxfB T 61 ?$$fB U 61 ?qqfB V 61 ?  fB W 61 ?  fB X 61 ?u u fB Y 61 ?! ! fB Z 61 ?  fB [ 61 ?y y fB \ 61 ?% % fB ] 61 ?  lB ^ <1 ?pplB _ <1 ?p}lB ` <1 ?p}lB a <1 ?}}H  0޽h ? 3380___PPT10.X  0 og` (  LB  c $D` r  S <  `     <`= `"`: Increased output generated- 4.52 lakhs. In absolute terms increase is maximum in Agriculture (1.75) lakhs. followed by self-employed in non-agriculture (1.67) lakhs. However growth rate is maximum in self employed in non agriculture. Income of all the households increases by 1.97 lakhs with a growth rate of 1.17 percent. In absolute terms increase in income is maximum for marginal farmers followed by labour households, but in percentage terms the growth is highest for large and small farmers.n(~DYH  0޽h ? 3380___PPT10.:D  0 p!# D(     6T  pL W#Impact of NREGS works on employment$$LB  c $D@F  0     `@    <0Y ?u0  a994,(# @`   <`h ?u  a168,(# @`   <q ?   a826,(# @`   <4{ ?B   b9812,(# @`   <u ?B  b5492,(# @`   <, ?  b4320,(# @`   <| ?  rNREGS Works undertaken* # @`   <̣ ?u0 aTotal* # @`   < ?u bFemale* # @`   <Է ?  `Male* # @`   <8 ?B   aTotal* # @`   <T ?B  bFemale* # @`   < ? `Male* # @`   < ? ]* # @`   < ? 0 !Indirect Employment (person days)," !# @`   < ?   }Direct Employment (person days),  # @`   <D ?  _, # @`ZB   s *1 ?0ZB   s *1 ?  ZB   s *1 ?  ZB   s *1 ?0ZB   s *1 ? ZB   s *1 ?B B ZB   s *1 ? ZB   s *1 ?uu `B   01 ? 0 `B !  01 ?  `B "  01 ?0 0 `B #  01 ? 0 H  0޽h ? 3380___PPT10.0S-  0 $(  $ $ Z\  c"$` @   LB $ c $Dpp $ 0 "`pz =yDirect employment generated is 9812 person days for 238 men & women form 161 households. Indirect employment generated is 994 person days (826 man days and 168 women days). Low value of multipliers: 50% of the goods comes from outside the village. Multipliers underestimates the impact: SAM is a static model assuming that change in technology or productivity is not rapid. Y 2 2T 2 2K 2 2 23&Y8XH $ 0޽h ? 3380___PPT10. s>g}  0 ||(g|(  ( ( Bh  0   {F P`h ( P`h ( B ?`h a1.057*("   @` ( B2 ? h a1.089*("   @` ( B? ?  h a1.463*("   @`  ( B8: ? h jOther services* "   @`  ( <B ?h `24,("   @`  ( B[ ?6` a0.983*("   @`  ( BDV ? 6 a1.013*("   @`  ( B`o ? 6  `1.43*("   @` ( Bi ?6  e Transport*   "   @` ( < ?6 `23,("   @` ( B ?`6 a0.721*("   @` ( B` ? 6 a0.744*("   @` ( B ?  6 a2.085*("   @` ( B ? 6 dPDS Shop*  "   @` ( <\ ?6 `22,("   @` ( B ?` a0.321*("   @` ( B ?  a0.331*("   @` ( B ?   a1.278*("   @` ( B( ?  dPan shop*  "   @` ( < ? `21,("   @` ( B ?k ` a0.347*("   @` ( B ? k  a0.358*("   @` ( B ? k  a1.157*("   @` ( B ?k  f Cloth Shop*   "   @` ( <p ?k  `20,("   @` ( B# ? `k  `0.48*("   @`  ( B, ? k  a0.494*("   @` !( B6 ? k  `1.21*("   @` "( BH1 ? k  e Carpenter*   "   @` #( <J ? k  `19,("   @` $( BT ?9 `  a1.042*("   @` %( B^ ? 9   a1.074*("   @` &( Bi ? 9  a1.456*("   @` '( Bhc ?9  bBarber* "   @` (( <| ?9   `18,("   @` )( B ? `9  a0.743*("   @` *( Bd ? 9  a0.765*("   @` +( B ? 9  a1.742*("   @` ,( B ? 9  tFruit & Vegetable vendor* "   @` -( <خ ? 9  `17,("   @` .( Bp ? `  a0.358*("   @` /( Bt ?    a0.369*("   @` 0( B ?   a1.157*("   @` 1( B ?  i Bangle vendor*  "   @` 2( <H ?   `16,("   @` 3( BL ?n `  a0.073*("   @` 4( B( ? n   a1.002*("   @` 5( B( ? n   a1.063*("   @` 6( B ?n   e Education*   "   @` 7( < ?n   `15,("   @` 8( Bd ? `n  a0.398*("   @` 9( B8 ? n  a0.413*("   @` :( B82 ? n  a1.217*("   @` ;( B`, ? n  h Construction*   "   @` <( <E ? n  `14,("   @` =( BO ?< `  a0.152*("   @` >( BY ? <   a0.158*("   @` ?( Bc ? <  a1.966*("   @` @( B^ ?<  jCotton Ginning* "   @` A( < x ?<   `13,("   @` B( B ?`<  a1.074*("   @` C( B ? <  a1.108*("   @` D( B@ ?  <  a1.936*("   @` E( Bh ? <  lAnimal husbandry* "   @` F( <` ?<  `12,("   @` G( B ? ` a1.116*("   @` H( B ?  a1.151*("   @` I( BԴ ?   a1.576*("   @` J( B ?   g Other crops*   "   @` K( < ?  `11,("   @` L( B ?q`  a0.208*("   @` M( B< ? q  a0.215*("   @` N( B ? q  a1.144*("   @` O( B ?q  oFruits & Vegetables* "   @` P( < ?q  `10,("   @` Q( B ?`q a0.038*("   @` R( B$ ? q a0.039*("   @` S( B. ?  q a1.024*("   @` T( B: ? q bCotton* "   @` U( < ?q _9,("   @` V( BO ??` a1.241*("   @` W( BX ? ? a1.281*("   @` X( Ba ? ?  a1.636*("   @` Y( Bk ??  e Groundnut*   "   @` Z( <t1 ?? _8,("   @` [( B$4 ?`? a1.207*("   @` \( B ? ? a1.246*("   @` ]( B ?  ? a1.666*("   @` ^( B` ? ? bCastor* "   @` _( << ?? _7,("   @` `( B ? ` `0.41*("   @` a( B@ ?  a0.423*("   @` b( BD ?   a1.219*("   @` c( B, ?   bPulses* "   @` d( < ?  _6,("   @` e( Bt ?t`  a0.197*("   @` f( B ? t  a0.204*("   @` g( B ? t  a1.165*("   @` h( B ?t  yTur* "   @` i( <  ?t  _5,("   @` j( Bt ?`t a1.147*("   @` k( B  ? t a1.185*("   @` l( B% ?  t a1.805*("   @` m( Bd/ ? t aMaize* "   @` n( <0) ?t _4,("   @` o( B\I ?B` a0.434*("   @` p( BC ? B a0.448*("   @` q( B] ? B  a1.291*("   @` r( BXg ?B  aBajra* "   @` s( <= ?B _3,("   @` t( B0a ?`B a0.922*("   @` u( B ? B a0.953*("   @` v( B ?  B a1.671*("   @` w( BT ? B aJowar* "   @` x( <8 ?B _2,("   @` y( Bxt ?` a1.189*("   @` z( B ?  a1.228*("   @` {( B ?   a1.793*("   @` |( B ?  aWheat* "   @` }( <( ? _1,("   @` ~( Bp ?P` qHH Income Multipliers* "   @` ( B\ ? P nIncome Multipliers* "   @` ( B ? P  nOutput Multipliers* "   @` ( B ?P  bSector* "   @` ( < ?P {Sr No* "   @`ZB ( s *1 ?`ZB ( s *1 ?PhZB ( s *1 ? P hZB ( s *1 ? P hZB ( s *1 ?PhZB ( s *1 ?`ZB ( s *1 ?B`BZB ( s *1 ?`ZB ( s *1 ?t`tZB ( s *1 ? ` ZB ( s *1 ?`ZB ( s *1 ??`?ZB ( s *1 ?`ZB ( s *1 ?q`qZB ( s *1 ? ` ZB ( s *1 ?`ZB ( s *1 ?< `< ZB ( s *1 ? ` ZB ( s *1 ?n `n ZB ( s *1 ? ` ZB ( s *1 ? ` ZB ( s *1 ?9 `9 ZB ( s *1 ? ` ZB ( s *1 ?k `k ZB ( s *1 ?`ZB ( s *1 ?`ZB ( s *1 ?6`6ZB ( s *1 ?``B ( 01 ?P`P`B ( 01 ?Ph`B ( 01 ?`P`h`B ( 01 ?h`hH ( 0޽h ? 3380___PPT10. 8  0 77PR,7(  ,K7F `C , `C , BЮA?W C `7.92*("   @` , B( ?`W C hOther services( "   @` , B( ?W  `2.96*("   @` , B* ?` W  c Transport(   "   @`  , B3 ?W p  `3.53*("   @`  , BHP ?`pW  bPDS Shop(  "   @`  , BW ?W p `1.87*("   @`  , B a ?` W p bPan shop(  "   @`  , Bj ?W   `0.58*("   @` , B(u ?` W  d Cloth Shop(   "   @` , B~ ?W o   `5.34*("   @` , Bx ?`o W  c Carpenter(   "   @` , Bty ?W o  a12.50*("   @` , B ?` W o  `Barber( "   @` , B ?W 8   `7.27*("   @` , B ?`8 W  rFruit & Vegetable vendor( "   @` , B ?W 8  `3.95*("   @` , B ?` W 8  g Bangle vendor(  "   @` , B ?W    `5.60*("   @` , B\ ?` W  c Education(   "   @` , B ?W e   `1.98*("   @` , B ?`e W   f Construction(   "   @` , B ?W e  `2.86*("   @` , B(?`W e  hCotton Ginning( "   @` , B ?W . `1.69*("   @` , B?`.W  jAnimal husbandry( "   @` , B?W . `1.22*("   @`  , B4)?`W . e Other crops(   "   @` !, B2?W  `2.98*("   @` ", BH-?`W  mFruits & Vegetables( "   @` #, BF?W \ `1.81*("   @` $, BdP?`\W  `Cotton( "   @` %, BhZ?W \ `1.99*("   @` &, Bd?`W \ c Groundnut(   "   @` ', Bt?W % `2.08*("   @` (, B~?`%W  `Castor( "   @` ), B?W % `2.44*("   @` *, B?`W % `Pulses( "   @` +, Bc?W  `8.84*("   @` ,, B ?`W  wTur( "   @` -, BD?W R `4.79*("   @` ., B?`RW  _Maize( "   @` /, B?W R `1.83*("   @` 0, B\l?`W R _Bajra( "   @` 1, B?W  `8.02*("   @` 2, B?`W  _Jowar( "   @` 3, B`?W  `2.63*("   @` 4, BX?`W  _Wheat( "   @` 5, B?` v Employment Multiplier.(#   @``B 6, 01 ?`ZB 7, s *1 ?`ZB 8, s *1 ?`ZB 9, s *1 ?W W CZB :, s *1 ?`ZB ;, s *1 ?`RRZB <, s *1 ?`ZB =, s *1 ?`ZB >, s *1 ?`%%ZB ?, s *1 ?`ZB @, s *1 ?`\\ZB A, s *1 ?`ZB B, s *1 ?`ZB C, s *1 ?`..ZB D, s *1 ?`ZB E, s *1 ?`e e ZB F, s *1 ?`  ZB G, s *1 ?`  ZB H, s *1 ?`8 8 ZB I, s *1 ?`  ZB J, s *1 ?`o o ZB K, s *1 ?`  ZB L, s *1 ?`  ZB M, s *1 ?`ppZB N, s *1 ?`  ZB O, s *1 ?``B P, 01 ?``C`B Q, 01 ?C`B R, 01 ?`CCH , 0޽h ? 3380___PPT10.:0  0 x0(  xx x c $L  `}   x x c $$  0   H x 0޽h ? 3380___PPT10.w0  0 |0(  |x | c $ `}   x | c $ `  H | 0޽h ? 3380___PPT10.`X0  0 0(  x  c $d& `}   x  c $<'  `  H  0޽h ? 3380___PPT10.g0  0 0(  x  c $02 `}   x  c $3` `  H  0޽h ? 3380___PPT10.K0  0 0(  x  c $E `}   x  c $lF `  H  0޽h ? 3380___PPT10.mCE$  0 $(  r  S  A `}  A r  S A ` A H  0޽h ? 3380___PPT10.b 0 b ba(  ` `: # #"znfffffffffffffffffofffffRP`   BT?J`: N+27.30,(b B   BZ?J: L2526,(b B   B:?{ : L1984,(b B   BDb?{ : c No completed per district* b B   <i?J` O+ 30.07,(b B   <n?J L5472,(b B    <Hr?{  L4207,(b B    <v?{  c No of works per district* b B    <x?Jo` M- 2.1,(b B    <L}?oJ M46.16,(b B    <<?{ o M47.14,(b B   <t?o{  U % completed* b B   <X?J`o P+ 110.06, (b B   <܎?Jo N833474,(b B   <?{ o N396782,(b B   <?{ o S Completed* b B   <X?J=` O+118.57,(b B   <?=J N972234,(b B   <<?{ = N444806,(b B   <8?={  Q Ongoing*  b B   <?J `= P+ 114.56, (b B   <? J= O1805708,(b B   <?{ = N841588,(b B   <? { = R Works: Total*  b B   <?J `  P+34.25.(b B   <? J  P592.26.(b B   <?{   P441.17.(b B   <? {  m%Funds used per district (In millions),& %b B   < ?Jr `  N+12.01,(b B    <?r J  M81.86,(b B  ! <?{ r   M73.08,(b B  " <L?r {  U% of funds used* b B  # <?J `r  O+ 81.32,(b B  $ <? Jr  Q 159987.75, ( b B  % <?{ r  P88233.55, (b B  & <? { r  ^Funds used (In millions)* b B  ' <?J@ `  O+ 61.88,(b B  ( <@?@ J  Q 195447.24, ( b B  ) <D?{ @   Q 120735.55, ( b B  * <?@ {  bFunds Allotted (In millions)* b B  + <?J `@  P- 3.66.(b B  , <? J@  N4.35.(b B  - <?{ @  N4.52.(b B  . <? { @  n&Person days per district (In millions),' &b B  / <?J `  O+ 13.38,(b B  0 <h? J  M43.30,(b B  1 <p&?{    M38.19,(b B  2 <)? {  Q % Others*  b B  3 <@.?Ju `  O+ 80.05,(b B  4 <2?u J  N622.25,(b B  5 <L7?{ u   N345.60,(b B  6 <<?u {   ] Others (In millions)* b B  7 <??J`u  O- 19.68,(b B  8 <C?Ju  M29.27,(b B  9 <H?{ u  M36.45,(b B  : <$M?{ u  M % ST* b B  ; <tQ?JC` O+ 27.53,(b B  < <V?CJ N420.70,(b B  = < [?{ C N329.88,(b B  > < `?C{  Y ST (In millions)* b B  ? <xd?J`C N+ 8.14,(b B  @ <h?JC M27.42,(b B  A <pm?{ C M25.36,(b B  B <q?{ C M % SC* b B  C < v?J` O+ 71.73,(b B  D <Xz?J N394.11,(b B  E <;?{  N229.50,(b B  F <8?{  Y SC (In millions)* b B  G <D?Jx` N+ 4.58,(b B  H <P?xJ M42.51,(b B  I <?{ x M40.65,(b B  J <?x{  P % women*  b B  K <P?J`x O+ 66.05,(b B  L <?Jx N610.90,(b B  M <?{ x N367.90,(b B  N <?{ x \ Women (In millions)* b B  O <?JF` P- 1.56.(b B  P <(?FJ O42.38.(b B  Q <?{ F O43.05.(b B  R <$?F{  ZPerson days per HH, b B  S <?J`F O+ 58.78,(b B  T <?JF O1437.07,(b B  U <?{ F N905.06,(b B  V <?{ F _Person days (In millions)* b B  W <0?J` O-2.23.(b B  X <?J P102755.(b B  Y <?{  P105100.(b B  Z <(?{  eHH provided work per district, b B  [ <T?J{` Q+ 61.32.(b B  \ <T?{J O33.91.(b B  ] <?{ { O21.02.(b B  ^ <$?{{  dHH provided work (In millions)* b B  _ <?J`{ Q+ 61.35.(b B  ` <?J{ O34.19.(b B  a <?{ { O21.19.(b B  b <H?{ { dHH demanded work (In millions)* b B  c <?JI` O+ 65.00,(b B  d < ?IJ K330,(b B  e <?{ I K200,(b B  f <?I{  UNo of Districts* b B  g <8?J`I R% Change. 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