GOVERNMENT OF MAHARASHTRA REPORT ON POOLING OF …€¦ · (JULY, 2009 – JUNE, 2010) HOUSEHOLD...

GOVERNMENT OF MAHARASHTRA

REPORT ON POOLING OF CENTRAL AND STATE SAMPLE DATA

66th ROUND OF NATIONAL SAMPLE SURVEY (JULY, 2009 – JUNE, 2010)

HOUSEHOLD CONSUMER EXPENDITURE (TYPE 1 & 2) & EMPLOYMENT & UNEMPLOYMENT

Directorate of Economics and Statistics, Planning Department, Government of Maharashtra,

Mumbai

PREFACE

The Directorate of Economics and Statistics has prepared a report on ‘Household Consumer Expenditure’ and ‘Employment & Unemployment’ based on the data of state, central & pooled (central & state) samples collected in the 66th round (July, 2009 – June, 2010) of National Sample Survey. 2. The report contains important findings of the survey in ‘Executive Summary’ while detailed results are given in ‘Survey Findings’. 3. I hope the results of this survey will be useful to senior officers of the Government involved in policy framing, researchers, economists and academicians. Mumbai Director of Economics and Statistics, September, 2015 Planning Department, Government of Maharashtra

CONTENTS Page CHAPTER-1 Executive Summary 1

CHAPTER-2 Introduction and Background 2

CHAPTER-3 Summary Findings 6

CHAPTER-4 Testing poolability and Methodology for pooling 14

CHAPTER-5 Poolability Test Results 19

Table 5.1(R) & 5.1(U): District wise results of test of MPCE (URP, MRP,

MMRP) for Pooled sample - Run test 19

Table 5.2 (R) & 5.2 (U): District wise test results of persons over worker,

unemployed and out of labour force for PS+SS, CWS and CDS status of

Pooled sample - Chi-square test 21

CHAPTER-6 Pooled Results of schedule 1.0 and 10 and their RSE 23

Table 6.1 (R) & 6.1 (U): District wise estimated number of households and their RSE's for central, state and pooled samples - Type-1 23

Table 6.2 (R) & 6.2 (U): District wise estimated number of persons and their RSE's for Central, State and Pooled sample - Type-1 27 Table 6.3 District wise estimated household size for central, state and pooled sample 29

Table 6.4 (R) & 6.4 (U): District wise estimated sex ratio and their RSE's for Central, State and Pooled sample - Type-1 30

Table 6.5 (R) & 6.5 (U): District wise estimate of MPC (URP) and their RSE's for Central, State and Pooled sample 32

Table 6.6 (R) & 6.6 (U): District wise estimate of MPCE (MRP) and their RSE's for Central, State and Pooled sample 40 Table 6.7 (R) & 6.7 (U): District wise estimated number of households

and their RSE's for central, state and pooled samples - Type-2 48

Table 6.8 (R) & 6.8 (U): District wise estimated number of persons and their RSE's for Central, State and Pooled sample - Type-2 50

Table 6.9 (R) & 6.9 (U): District wise estimated sex ratio and their RSE's for Central, State and Pooled sample - Type-2 52

Table 6.10 (R) & 6.10 (U): District wise estimate of MPCE (MMRP) and their RSE's for Central, State and Pooled sample 54

Table 6.11(R) & 6.11 (U): District wise WPR per 1000(PS+SS) for central, state and pooled samples 62

Table 6.12 (R) & 6.12 (U): District wise LFPR per 1000 for central, state and pooled samples 66

Table 6.13 (R) & 6.13 (U): District wise RSE of estimated WPR per 1000(PS+SS) for central, state and pooled samples 68

Table 6.14 (R) & 6.14 (U): District wise RSE of LFPR for central, state and pooled samples 72

DETAILED TABLES Table (21): Per thousand distribution of persons by usual activity 76

category taking also into consideration the subsidiary economic status of persons categorized 'not working' in the principal status (for pooled samples) Table (34): Per thousand distribution of persons by Current Weekly Activity (for pooled samples) 94

Table (36): Per thousand distribution of persons-Days by Current Daily Activity (for pooled samples) 112

Annexure -1: Sample size for 66th round of each district in the state 130 Annexure -2: Abbreviations used in this Report 131 Annexure -3: Description of Activity status code 132

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Chapter – 1 EXECUTIVE SUMMARY

Findings 1. The average household size at the state level for the rural and urban areas based on the state and central sample are consistent with each other. This in turn gives similar estimate at the state level on the basis of pooled data. The district wise pooled estimates indicate that in rural areas Hingoli, Parbhani, Nashik, Bid have the largest (5.2 each) average household size while Ratnagiri, Raigad have the smallest (3.8) average household size. In urban areas Ratnagiri has smallest (3.5) and Bid, Parbhani have highest (5.7 each) average household size. (Refer table 6.3)

2. As per pooled data, in rural areas Raigad has the highest Monthly per capita expenditure (MPCE) and Nandurbar has lowest MPCE, while in urban areas Mumbai has highest and Washim has lowest MPCE. 3. As per the State sample data, out of the 33 districts, for rural areas, 17 districts have their MPCE below the State average while as per the central sample data this count is 15 districts. 4. For urban areas, all the districts, except four districts viz. Thane, Mumbai, Raigad and Ratnagiri, have their MPCE below the State average as per the State sample data. However, the central sample data shows that except four districts viz. Thane, Mumbai, Raigad and Pune, all other districts have less MPCE compared to the State average. 5. District wise pooled data of sex ratio shows that, in rural area, Chandrapur has highest and Jalgaon has lowest sex ratio while for urban area, Sangli has highest and Latur has lowest sex ratio. 6. As per State sample data, in rural areas, 18 districts and in urban areas 10 districts have the labour participation Rate (LFPR) above state average. While as per central sample data this count is 16 and 8 for rural and urban areas respectively. 7. LFPR for rural areas is comparatively higher than urban areas for both central and state sample. 8. Relative standard error (RSE) for LFPR (ps+ss, cws, cds) is below 1% for rural area. Limitations of the data After pooling of the two samples, the districts Sindhudurg, Hingoli, Parbhani, Akola, Washim, Wardha, Bhandara and Gadchiroli are found to have less number of First Stage Units i.e. FSUs (only 16 villages) in the rural areas while Ratnagiri, Sindhudurg, Nandurbar, Hingoli, Osmanabad, Washim, Bhandara, Gondiya and Gadchiroli districts have less number of FSUs (less than 20 UFS blocks) in the urban areas. These are limiting factors for estimation of district level estimates.

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Chapter – 2

Introduction and Background

Background The National Sample Survey Office (NSSO) conducts nationwide household consumer expenditure surveys at regular intervals as part of its “rounds”, each round normally of a year’s duration. The NSS surveys are conducted through interviews of a random sample of households selected through a scientific design and cover practically the entire geographical area of the country. The household consumer expenditure survey (CES) is generally covered as one of the main subjects of the NSS survey at quinquennial intervals. This provides a series of CES’s. The 66th round survey (July 2009 - June 2010) was the eighth such survey of this quinquennial series, the seventh having been conducted during the 61st round (July 2004 - June 2005). State’s participation in NSS surveys Maharashtra state has been participating in the NSS surveys from 9th round onwards by using the same concepts, definitions and procedures and by adopting the same sample design based on independently drawn sample as that of NSSO called as the State samples. The sample size of the State sample in Maharashtra for rural area is equal to that of Central sample and for urban sample it is one and half times of the Central sample. The sample list of the State sample is drawn and supplied by the NSSO. District wise sample size of 66th round is given in Annexure-1. One of the objectives of states participation in the NSS programme is to provide a mechanism by which sample size will be increased and the pooling of the two sets of data would enable better estimates at lower sub state level, particularly at district level. At the State level, this will result in increased precision of the estimates and at disaggregated level, estimates will be more stable. But the major benefit will be derived in the case of estimates are generated at sub-state level like NSS regions/districts. Emerging need for pooling of Central and State samples The 73rd and 74th constitutional amendment (1992) has brought into existence the democratically elected grassroots institutions of local self governance, with respective delegated functions, both in rural and urban areas. This has enhanced the demand for local level statistics and necessitated requirement of developing basic capabilities at grass root levels to organize such statistics in a harmonious manner. In this context, it is envisioned that the survey resources in overall NSS programme both by Central and State Agencies can be more effectively utilized to generate lower level estimates of key indicators at district level. 13th Finance Commission, in Para 12.99 of its report, noted that “Comparable estimates of district income are extremely relevant for measuring intra-state income disparities. This will enable State Governments to effectively plan policy and programme interventions. They could also be used as a parameter for horizontal distribution of fiscal transfers”. The Commission also recommended for granting finance to State Governments, which

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should be utilized by them for strengthening statistical infrastructure at the district level. These requirements are subsequently brought in institutional framework in the implementation of the 13th Finance Commission. National Statistical Commission’s (NSC) Recommendation The National Statistical Commission in its reports has observed the importance of pooling in the statement:

“The statistical agencies of different State governments have been participating in the NSS programme and canvassing the same questionnaires in matched samples of households in their respective States following identical concepts, definitions and procedures. Results from the central samples and state sample(s) have occasionally been compared. The main purpose of the programme is to pool the two samples and obtain dependable estimates for regions within the States.”

National Statistical Commission (NSC) constituted the committee on pooling of Central and State samples in National Sample Surveys (NSS) etc under the chairmanship of Prof. R. Radhakrishna vide order no. 8(64)/2010-NSC, 30th July, 2010. The terms of reference of the committee are as follows:- • Conditions to be fulfilled for pooling of Central and State Sample NSS data • Methodology for pooling • Time frame by which the exercise needs to be completed by each State • Generating weighting diagrams from the pooled data at sub-state level for the purpose of

consumer price indices (Rural and Urban) including occupation specific indices such as CPIAL, CPIIW etc., from the NSS data on consumer expenditure surveys (quinquennial & thin sample)

Assistance of NSSO (DPD) for processing of NSS State Sample Data Since NSSO develops its own in-house software for processing the Central sample data, in the deliberations of COCSSO held in the recent past, it was recommended that NSSO should assist the States in terms of providing common Data Entry Software, Tabulation Software, Instructions Manual and Training and Hands on Practice to DES personnel. NSSO has already started providing this assistance to States. The harmonization of data processing process is one of the key essences for pooling the different sets of data. The state sample data should be processed using the same set of validation rules as in the case of Central sample data. Accordingly, it is essential that the State sample data is processed, ensuring the use of same data entry layout as in the case of Central sample. If the States are evolving their own data layout, as per their convenience, then the state data should be put in the layout, harmonized of that with the Central data for using the same software developed for Central samples.

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For Maharashtra state the data entry software, validation software and tabulation software are developed by Directorate of Economics and Statistics using Oracle, Java and SAS software. For pooling purpose, state data is put in same layouts as that of Central data. Parameters considered for pooling: Considering the smaller sample size at district level following broad parameters were considered for pooling. a)MPCE of FOOD, Non-FOOD, and Total MPCE derived from detail item for URP, MRP and MMRP b) Household size, sex c) Activity status principal, subsidiary, weekly, daily and their intensity Methodology of pooling: Two alternate methods are used in pooling the Central and State sample data. a) Weighting by Matching ratio: Building aggregate estimate of pooled sample in proportion

matching ratio m:n of Central and State sample aggregate estimate where m and n are the allotted sample for Central and State sample separately for rural and urban sector. Building ratio estimate of pooled sample as ratio of aggregate estimates.

b) Weighting by inverse of variance: Ratio estimates are built by weighting the ratio estimate of

Central and State sample in proportion to inverse of variance of ratio of the Central and State sample.

Tables generated 1. Following Tables were generated for testing the poolability of State and Central samples;

a) District wise results of run test of MPCE (URP, MRP, MMRP) for pooled sample of rural and urban sectors.

b) District wise results of chi-square test of persons over worker, unemployed and out of labour force for pooled sample of rural and urban sectors.

2. Following Tables were generated pertaining to the estimation of different parameters and

their RSEs;

a) District wise estimated number of households and their RSEs for Central, State and pooled samples (Matching ratio & Inverse variance methods) for rural and urban sectors for schedule type-I and schedule type-II

b) District wise estimated number of persons and their RSEs for Central, State and pooled samples (Matching ratio & Inverse variance methods) for rural and urban sectors for schedule type-I and schedule type-II

c) District wise estimated sex ratio and their RSEs for Central, State and pooled samples (Matching ratio & Inverse variance methods) for rural and urban sectors for schedule type-I and schedule type-II

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d) District wise estimate of MPCE (URP, MRP, and MMRP) for food, non-food and total for Central, State and pooled samples (Matching ratio & Inverse variance methods) for rural and urban sectors.

e) District wise RSE of estimate of MPCE (URP, MRP, and MMRP) for food, non-food and total for Central, State and pooled samples (Matching ratio & Inverse variance methods) for rural and urban sectors.

f) District wise WPR per 1000(PS+SS) of male, female and total persons for central, state and pooled samples (Matching ratio & Inverse variance methods) for rural and urban sectors.

g) District wise RSE of WPR per 1000(PS+SS) of male, female and total persons for central, state and pooled samples (Matching ratio & Inverse variance methods) for rural and urban sectors.

h) District wise LFPR per 1000(PS+SS, CWS, CDS) for Central, state and pooled samples (Matching ratio & Inverse variance methods) for rural and urban sectors.

i) District wise RSE of LFPR per 1000(PS+SS, CWS, CDS) for central, state and pooled samples (Matching ratio & Inverse variance methods) for rural and urban sectors.

Sample Size of Maharashtra

The sample size of Central and State samples for Maharashtra state is given below; RURAL

Schedule Central Sample State Sample

FSU surveyed

Households surveyed

Persons surveyed

FSU surveyed

Households surveyed

Persons surveyed

1.0 Type I & Type II 504 4015 19112 501 4006 19191

10 504 4017 18715 501 4007 18868

URBAN

Schedule Central Sample State Sample

FSU surveyed

Households surveyed

Persons surveyed

FSU surveyed

Households surveyed

Persons surveyed

1.0 Type I & Type II 502 3980 17117 753 6016 26169

10 502 3988 16760 753 6016 25799

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Chapter – 3

Summary Findings

Run test (one sided) was done over MPCE (URP, MRP, MMRP) for testing the poolability of Central and State sample data for urban and rural. Number of districts for which poolability was rejected by both the above mentioned tests is given below; Table: 3.1

Number of Districts for which Poolability was rejected over MPCE by run test using Z-statistics (one sided)

Type Sector

Rural Urban

URP 4 3

MRP 3 3

MMRP 6 2

Total Districts 33 34

In the above statement run test at 1% critical error the null hypothesis is rejected for 4, 3 and 6 districts in rural areas for URP, MRP and MMRP respectively and for 3, 3 and 2 districts in case of urban areas respectively. Similarly number of districts for which poolability was rejected over LFPR by Chi-Square test is given below; Table: 3.2

Number of Districts for which Poolability was rejected over LFPR by Chi-Square test

Type Sector

Rural Urban

PS + SS 11 00

CWS 13 01

CDS 15 04

Total Districts 33 34

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Divergence between the estimates of Central and State sample: Considering the district as domain of pooling, the divergence is worked out as absolute percentage difference between Central and State sample estimates. The distribution of districts by absolute percentage range of divergence of MPCE (Food, Non-food and total) of Central and State sample in Maharashtra for rural and urban sector and for MPCE (URP, MRP, MMRP) is given in table 3.3 to 3.5 below: Table: 3.3

Distribution of districts by range of percentage divergence of MPCE (URP) of Central and state sample estimates

Item Sector <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total

Districts MPCE: Food Group

Rural 7 7 8 4 4 1 2 33

MPCE: Non Food Group 4 1 5 3 6 2 12 33 MPCE: Total 3 6 6 3 5 3 7 33 MPCE: Food Group

Urban 8 7 7 6 2 3 1 34

MPCE: Non Food Group 5 4 4 5 5 2 9 34 MPCE: Total 9 7 3 3 5 3 4 34 Table: 3.4

Distribution of districts by range of percentage divergence of MPCE (MRP) of Central and state sample estimates


10-15%

15-20%

20-25%

25-30% >30% Total


Rural 7 7 8 4 4 1 2 33


Urban 8 7 7 6 2 3 1 34

MPCE: Non Food Group 6 2 6 4 7 3 6 34 MPCE: Total 4 9 7 4 4 4 2 34 Table: 3.5 Distribution of districts by range of percentage divergence of MPCE (MMRP) of Central and

state sample estimates


10-15%

15-20%

20-25%

25-30% >30% Total


Rural 0 0 0 0 0 0 33 33


Urban 0 0 0 0 0 0 34 34

MPCE: Non Food Group 6 3 7 2 5 3 8 34 MPCE: Total 0 2 2 2 3 1 24 34

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The districts with more than 20 percent divergence in total MPCE (URP) were 15 (45%) out of 33 districts in the rural sector and 12 (35%) out of 34 district in the urban sector. Similarly in total MPCE (MRP) it is 9 (27%) out of 33 districts in the rural sector and 10 (29%) out of 34 district in the urban sector. In case of MPCE (MMRP) it is 26 (79%) in the rural sector and 28 (82%) in the urban sector. The distribution of district by range of RSE of MPCE (URP, MRP, and MMRP) of Central and State sample for rural and urban sector is given in table 3.6 to table 3.11. Table: 3.6

Distribution of districts by range of RSE of MPCE (URP) of central, state and pooled sample of Maharashtra Rural

Item <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total

Districts Central Sample

MPCE: Food Group 27 6 0 0 0 0 0 33 MPCE: Non Food Group 14 12 4 0 3 0 0 33 MPCE: Total 22 8 2 1 0 0 0 33

State Sample MPCE: Food Group 31 2 0 0 0 0 0 33 MPCE: Non Food Group 18 8 5 1 0 1 0 33 MPCE: Total 23 8 1 0 1 0 0 33

Pooled Sample (Matching Ratio) MPCE: Food Group 33 0 0 0 0 0 0 33 MPCE: Non Food Group 20 9 3 1 0 0 0 33 MPCE: Total 29 3 1 0 0 0 0 33

Pooled Sample (Inverse Variance) MPCE: Food Group 33 0 0 0 0 0 0 33 MPCE: Non Food Group 28 3 2 0 0 0 0 33 MPCE: Total 31 2 0 0 0 0 0 33 Table: 3.7

Distribution of districts by range of RSE of MPCE (URP) of central, state and pooled sample of Maharashtra Urban

Item <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total




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Item <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total

Districts Pooled Sample (Matching Ratio)


Pooled Sample (Inverse Variance) MPCE: Food Group 34 0 0 0 0 0 0 34 MPCE: Non Food Group 22 10 2 0 0 0 0 34 MPCE: Total 28 6 0 0 0 0 0 34 Table: 3.8 Distribution of districts by range of RSE of MPCE (MRP) of central, state and pooled sample

of Maharashtra Rural

Item <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total





Pooled Sample (Inverse Variance) MPCE: Food Group 33 0 0 0 0 0 0 33 MPCE: Non Food Group 29 4 0 0 0 0 0 33 MPCE: Total 33 0 0 0 0 0 0 33

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Table: 3.9 Distribution of districts by range of RSE of MPCE (MRP) of central, state and pooled sample

of Maharashtra Urban

Item <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total





Pooled Sample (Inverse Variance) MPCE: Food Group 34 0 0 0 0 0 0 34 MPCE: Non Food Group 23 10 1 0 0 0 0 34 MPCE: Total 30 4 0 0 0 0 0 34 Table: 3.10

Distribution of districts by range of RSE of MPCE (MMRP) of central, state and pooled sample of Maharashtra Rural

Item <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total






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Table: 3.11 Distribution of districts by range of RSE of MPCE (MMRP) of central, state and pooled

sample of Maharashtra Urban

Item <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total






From the above tables which show the distribution of districts by RSE level, it can be seen that in case of URP the pooled estimates of MPCE on food, non-food and total have RSE less than 15% for all districts except for only one district in both rural and urban sector. Also in case of MRP the pooled estimates of MPCE on food, non-food and total have RSE less than 10% for all districts except for one or two districts in urban sector. In case of MMRP, RSE estimates of pooled sample of MPCE on food, nonfood and total MPCE are below 15% for rural and also urban sector. Considering the district as domain of pooling, the divergence is worked out as absolute percentage difference between central and state sample estimates. The distribution of districts by absolute percentage range of divergence of WPR and LFPR (PS+SS, CWS, CDS) of central and state samples in Maharashtra for rural and urban sector is given in table: 3.12 below:

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Table: 3.12 Distribution of districts by range of percentage divergence of WPR and LFPR (PS+SS, CWS

and CDS) of central and state sample estimates

Item <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total

Districts Rural

WPR – PS + SS 14 4 6 2 4 2 1 33 LFPR – PS + SS 14 4 7 1 4 2 1 33 LFPR – CWS 18 4 4 1 3 2 1 33 LFPR – CDS 18 6 3 1 1 2 2 33

Urban WPR – PS + SS 17 3 5 3 5 0 1 34 LFPR – PS + SS 17 5 5 3 3 0 1 34 LFPR – CWS 18 6 4 4 1 0 1 34 LFPR – CDS 18 6 4 4 1 0 1 34 It can be seen from the above table that the divergence level of 7 districts are above 20 % in the rural sector, whereas the divergence level of 6 districts are above 20 % for urban sector. The distribution of districts by range of RSE of WPR and LFPR (PS+SS, CWS, CDS) of central and state sample in Maharashtra for rural and urban sector is given in table: 3.13 & 3.14 below: Table: 3.13

Distribution of districts by range of RSE of WPR and LFPR (PS+SS, CWS and CDS) of Central and State sample of Maharashtra (Rural)

Item <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total



State Sample WPR – PS + SS 21 11 1 0 0 0 0 33 LFPR – PS + SS 21 11 1 0 0 0 0 33 LFPR – CWS 21 11 1 0 0 0 0 33 LFPR – CDS 21 11 1 0 0 0 0 33

Pooled Sample (Matching Ratio Method) WPR – PS + SS 20 13 0 0 0 0 0 33 LFPR – PS + SS 32 1 0 0 0 0 0 33 LFPR – CWS 32 1 0 0 0 0 0 33 LFPR – CDS 32 1 0 0 0 0 0 33

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Item <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total

Districts Pooled Sample (Inverse Variance Method)

WPR – PS + SS 33 0 0 0 0 0 0 33 LFPR – PS + SS 33 0 0 0 0 0 0 33 LFPR – CWS 33 0 0 0 0 0 0 33 LFPR – CDS 33 0 0 0 0 0 0 33 Table: 3.14

Distribution of districts by range of RSE of WPR and LFPR (PS+SS, CWS and CDS) of central and state sample of Maharashtra (Urban)

Item <=5% 5-10%

10-15%

15-20%

20-25%

25-30% >30% Total



State Sample WPR – PS + SS 16 8 5 3 1 0 1 34 LFPR – PS + SS 16 8 5 3 1 0 1 34 LFPR – CWS 16 8 5 3 1 0 1 34 LFPR – CDS 16 8 5 3 1 0 1 34

Pooled Sample (Matching Ratio Method) WPR – PS + SS 34 0 0 0 0 0 0 34 LFPR – PS + SS 4 17 4 4 0 2 3 34 LFPR – CWS 4 17 4 4 0 2 3 34 LFPR – CDS 18 11 2 2 1 0 0 34

Pooled Sample (Inverse Variance Method) WPR – PS + SS 25 6 1 2 0 0 0 34 LFPR – PS + SS 25 6 1 2 0 0 0 34 LFPR – CWS 25 6 1 2 0 0 0 34 LFPR – CDS 25 6 1 2 0 0 0 34

RSE of estimates of WPR and LFPR (PS+SS, CWS, CDS) were found to be within 15 % for central, state sample and pooled estimates in rural sector, whereas in urban sector, RSE of all districts was found to within 25% except one or two districts for central and state sample and within 20% except 2-3 districts for pooled sample.

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Chapter – 4

Testing poolability and Methodology for pooling 1 Testing poolability of central and state sample 1.1 Though the central sample and state sample are drawn independently following identical sampling design with same concepts, definitions and instructions, the state sample unit level data in some cases are not properly validated. There is also expected agency bias in the two sets of data generated by different agencies. As such they cannot be merged for generating pooled estimate without testing that the samples are realized from identical distribution function. Since the parametric distribution of the sample mean is unknown one may adopt nonparametric tests such Run test, Median test, chi-square test etc to test that the samples are coming from identical distribution function. 1.2 Median test 1.2.1 In statistics, the median test is a special case of Pearson's Chi-square test. It tests the null hypothesis that the medians of the populations from which two samples are drawn, are identical. Observations in each sample are assigned to two groups, one consisting of data whose values are higher than the median value in the two groups combined, and the other consisting of data whose values are at the median or below. A Pearson's Chi-square test is then used to determine whether the observed frequencies in each group differ from expected frequencies derived from a distribution combining the two groups. Let m*

be the median of the pooled sample data. Construct 2 X 2 contingency table as below and use chi-square test to test if State sample and Central sample have identical median.

Sample type Number of sample observation Total <= m* > m*

State Sample N11 N12 N1. Central Sample N21 N22 N2. Total N.1 N.2 N..

Observed frequency of each cell Oij= Nij where i= 1 to 2, j= 1 to 2. Expected frequency of each cell Eij= (Ni. * N.j)/N.. where i= 1 to 2, j= 1 to 2.

Value = ∑ ∑ ( Oij − Eij) 2 / Oij with degrees of freedom = (2-1)*(2-1) = 1 The statistical power of this test may sometimes be improved by using a value other than the median to define the groups say quintile classes– that is, by using a value which divides the groups into more nearly equal groups than the median would.

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1.3 Multinomial distribution test or test For discrete data such as status of activity, educational level and categorical variable such as land possessed etc, standard tests of equality of sample proportions of two sets of data based on multinomial distributions, relevant chi-square tests may be used after grouping the attributes/categorical variables into a suitable number of classes so that each class contains adequate number of sample observations. Construct 2 X k contingency table for k classes at the domain where two sets of data are to be pooled as below and use chi-square test if State sample and Central sample have identical distribution.

Sample type Number of sample observation TotalClass - 1 Class - 2 … Class - k-1 Class - k

State Sample N11 N12 … N1k-1 N1k N1. Central Sample N21 N22 … N2k-1 N2k N2. Total N.1 N.2 … N.k-1 N.k N..

Observed frequency of each cell Oij= Nij where i= 1 to 2, j= 1 to k. Expected frequency of each cell Eij= (Ni. * N.j)/N.. where i= 1 to 2, j= 1 to k.

Value = ∑ ∑ ( Oij − Eij)2/Oij with degrees of freedom = (2-1)*(k-1) = k-1

1.4 Wald-Wolfowitz run test 1.4.1 Suppose X and Y are independent random samples with cumulative distribution function (CDF) as Fs(x) and Fc(y). Null Hypothesis to be tested is H0: Fs(x) = Fc(x) for all x against alternative Hypothesis is H1: Fs(x) <= Fc(x) for all x and Fs(x) < Fc(x) for some x. Let x1, x2, ….., xm be iid observation from state sample with distributive function Fs and y1,y2,…..,yn be iid observation from central sample with distributive function Fc. Pool the data and order them with respect to comparable characteristic under consideration say monthly per capita expenditure (MPCE). In the pooled order sequence put “1” for X and “0” for Y. Let U be the total runs observed where 'run' is a sequence of adjacent equal symbols. For example, following sequence: 1111000111001111110000 is divided in six runs, three of them are made out of “1” and the others are made out of “0”. The number of runs U is a random variable whose distribution for large sample can be treated as normal with:

mean : + 1

variance : ( )( ) ( )

16

After normalizing the variable U one may use one sided z-test for testing the Null hypothesis. In extreme case the value of U will be 2 meaning by observed characteristic of all the observation of one sample is less than the other samples. 1.4.2 One of the limitations of this test is when there is a tie between two samples in the observed value. One has to resolve ties in usual manner. However if there is large number of ties which is bound to occur specially for qualitative attributes like education level, activity status etc, this test is not recommended. This test can be well applied for a continuous variable such as MPCE which are less prone to ties. For discrete variable chi-square test is recommended. 2 Methodology for pooling 2.1 Pooling by inverse weight of the variance of the estimates 2.1.1 Aggregate estimate: For any characteristic, consider the state sample [s] in the form of two independent subsample s1 and s2 and the central sample [c] in the form of two independent subsample c1 and c2. Based on this, the respective estimates for state and central can be computed as: t s = ∑ (ts1 + ts2)/2 and t c = ∑(tc1 + tc2)/2 Pooled estimate leading to optimum combination of these two estimates is given by weighing with inverse of the variance of the estimate. Thus the pooled estimate is given by: = ( ) ( )( ) ( ) with ( ) = ( ) ( )( ) ( ) In general and ( ) and ( ) are unknown and can be estimated as ( ) = ∑ ( − ) /4 , ( ) = ∑ ( − ) /4 where ∑l stands for summing over stratum x sub-stratum level variance at the domain of pooling. Thus pooled estimate and estimate of pooled variance is given by = ( ) ( )( ) ( ) = ( ) ( )( ) ( ) 2.1.2 By virtue of weighing the two estimates at the domain level at which two estimates are pooled, the pooled estimate will always lie between the central and state sample estimates. 2.1.3 Estimate of rate: Let rc and rs be the estimate of Rc and Rs ie Y/X based on central and state sample respectively with corresponding estimated mean square error mse(rc) and mse(rs). The pooled estimate and estimate of variance of pooled ratio estimate may be given by: = ( ) ( )( ) ( ) , ( ) = ( ) ( )( ) ( )

17

Where ( ) and ( ) are calculated using estimation procedure of NSS 66th round. Alternatively one can generate the pooled estimate of aggregate by inverse weight of estimate of variance obtained from central and state sample using formula given in para 2.1.1 for the characteristics x as well as y and obtain the pooled estimate of ratio as ratio of pooled estimate of aggregate. This will ensure consistency between pooled estimates of aggregate and the pooled estimate of ratio. 2.1.4 Method laid down in para 2.1.1 and 2.1.2 requires calculation of estimate of variance of the estimates before pooling them. Reliability of estimate of variance should be ascertained with due consideration of sample size. Besides the complex calculations of variances and covariances for each cell of the table, one needs to address the issue of non-additivity of the component estimates with the estimate of marginal total. For e.g. pooled estimate of MPCE of FOOD and NON-FOOD may not add up to MPCE of TOTAL. To obviate this problem one may generate the pooled estimates of components first and then derive the estimate of total as sum of estimates of components. 2.2 Pooling by simple average of the estimates 2.2.1 Many of the States are not fully equipped with complex calculation of estimate of variance especially when cells of the table contains ratio of two characteristics which is usually presented in the NSS reports. When the State’s participation is equal matching of central samples, the simple average of two estimates may be a way of combining the estimates considering central and state samples as independent samples. The pooled estimate will always lie between the estimates based on central and state sample separately. 2.2.2 When the State’s participation is of unequal matching of central samples, the weighted average of two estimates with weights being matching ratio of central and state sample may be a better way of combining the estimates considering central and state samples as independent samples. For any characteristic, consider the state sample [s] in the form of two independent sub-sample s1 and s2 and the central sample[c] in the form of two independent subsample c1 and c2. Let matching ratio of state and central sample be m : n. Based on this, the respective estimates for state and central can be computed as: = ∑ ( + )/ and = ∑ ( + )/ Pooled estimate of these two estimates is given by weighing with matching participation rate m:n. Thus the pooled estimate is given by: = with ( ) = ( ) ( )( ) In general ( ) and ( ) can be estimated as ( ) = ∑ ( − ) /4 , ( ) = ∑ ( − ) /4 and thus = ( ) ( )( ) The pooled estimate will always lie between the estimates based on central and state sample separately.

18

2.3 Summing up: For those characteristics which are known to be distributed as Normal, poolability of the two sets of central and state data may be tested by standard parametric tests such as Z-test. For those characteristics for which transformation makes them Normal, such methodology may be adopted. In most of the situations where the distribution is non-normal and unknown, the two sets of data may be tested through various non-parametric tests such as those laid down in para 1 of above. For discrete data, Standard tests of equality of proportions based on binomial distribution may be used and for multinomial distributions relevant chi-square tests may be used.

19

CHAPTER-5 Poolability Test Results

Poolability test were undertaken and the test results are given below; Table 5.1(R): District wise results of Run test of MPCE (URP, MRP, MMRP) for Pooled sample

Sector:Rural (Schedule 1.0 Type-1 and Type -II)

Z0.01 = -2.33 [one sided test] reject if z-value < Z0.01

District code

District Name MPCE-URP MPCE-MRP MPCE-MMRP Z-Value ACCEPT Z-Value ACCEPT Z-value Accept

1 Nandurbar -1.3 Y -0.75 Y -3.039 N 2 Dhule -2.03 Y 1.2 Y -4.920 N 3 Jalgaon -0.85 Y -2.19 Y -1.742 Y 4 Buldhana 0.13 Y 0.46 Y -0.250 Y 5 Akola -2.66 N -2.17 Y -0.532 Y 6 Washim 1.6 Y -1.03 Y -2.485 N 7 Amravati -0.19 Y 1.49 Y 0.501 Y 8 Wardha 0.45 Y 0.11 Y -0.177 Y 9 Nagpur 0.14 Y 1.17 Y -0.579 Y 10 Bhandara -3.37 N -3.66 N -2.405 N 11 Gondia 0.22 Y -0.22 Y -1.013 Y 12 Gadchiroli -4.26 N -4.13 N -2.307 Y 13 Chandrapur -0.14 Y -2.23 Y -2.750 N 14 Yavatmal -0.06 Y -0.16 Y -1.509 Y 15 Nanded -1.9 Y 1.7 Y -2.016 Y 16 Hingoli -3.02 N -3.48 N 0.000 Y 17 Parbhani -0.18 Y -1.34 Y -1.242 Y 18 Jalna 1.01 Y -2.01 Y 0.217 Y 19 Aurangabad 0.5 Y 0.2 Y 0.314 Y 20 Nashik 1.04 Y 0.44 Y -2.781 N 21 Thane -1.63 Y 1.6 Y -2.146 Y 24 Raigad -1.83 Y 0.07 Y 1.588 Y 25 Pune 0.36 Y -0.6 Y -0.563 Y 26 Ahmednagar -1.07 Y -1.64 Y -1.484 Y 27 Beed -0.81 Y -1.6 Y 0.313 Y 28 Latur -0.44 Y 1.08 Y -0.250 Y 29 Osmanabad -1.16 Y -1.43 Y -0.868 Y 30 Solapur 1.12 Y -2.26 Y -0.920 Y 31 Satara -1.07 Y -2.31 Y 0.224 Y 32 Ratnagiri -0.75 Y -2.11 Y 1.127 Y 33 Sindhudurg 0.8 Y -0.29 Y 1.420 Y 34 Kolhapur -0.26 Y -2.29 Y -0.767 Y 35 Sangli -1.3 Y -0.75 Y -1.177 Y

20

Table 5.1(U): District wise results of Run test of MPCE (URP, MRP, MMRP) for Pooled sample

Sector:Urban (Schedule 1.0 Type-1 and Type -II)

Z0.01 = -2.33 [one sided test] reject if z-value < Z0.01

District code

District Name MPCE-URP MPCE-MRP MPCE-MMRP Z-Value ACCEPT Z-Value ACCEPT Z-value Accept

1 Nandurbar -1.95 Y -0.86 Y -0.385 Y 2 Dhule -0.01 Y 1.34 Y -0.297 Y 3 Jalgaon -1.47 Y -0.53 Y -0.230 Y 4 Buldhana 1.19 Y -1.65 Y 0.311 Y 5 Akola -1.62 Y -0.23 Y -0.959 Y 6 Washim 0.77 Y 1.56 Y -0.616 Y 7 Amravati -1.74 Y -1.27 Y -0.705 Y 8 Wardha -0.96 Y -0.04 Y -2.611 N 9 Nagpur 0.13 Y -0.22 Y -0.250 Y 10 Bhandara -2.47 N -2.39 N 0.077 Y 11 Gondia -0.33 Y -1.57 Y -1.120 Y 12 Gadchiroli 0.31 Y 0.87 Y -0.848 Y 13 Chandrapur 0.53 Y 0.19 Y -1.620 Y 14 Yavatmal 0.53 Y 0.84 Y 0.033 Y 15 Nanded -0.79 Y 0.98 Y -2.446 N 16 Hingoli -0.62 Y -1.59 Y 1.926 Y 17 Parbhani 1.63 Y 1.55 Y 0.417 Y 18 Jalna -0.79 Y 1.08 Y -0.132 Y 19 Aurangabad -2.1 Y -2.81 N 0.171 Y 20 Nashik -1.47 Y 0.14 Y -2.034 Y 21 Thane -0.8 Y 0.35 Y -0.699 Y 22 Mumbai 0.15 Y 0.46 Y -0.606 Y 24 Raigad 0.58 Y -0.52 Y -1.726 Y 25 Pune -1.28 Y 1.66 Y -1.780 Y 26 Ahmednagar -2.41 N -2.21 Y 0.000 Y 27 Beed -0.79 Y 1.63 Y -2.281 Y 28 Latur -0.3 Y 0.72 Y 0.364 Y 29 Osmanabad 0.08 Y -0.08 Y -0.154 Y 30 Solapur -1.12 Y 1.58 Y -1.353 Y 31 Satara -3.27 N -3.43 N -0.793 Y 32 Ratnagiri 0.31 Y -1.36 Y 0.308 Y 33 Sindhudurg 1 Y 1.5 Y -0.385 Y 34 Kolhapur 0.43 Y 1.55 Y 0.535 Y 35 Sangli -0.63 Y 0.51 Y -0.463 Y

21

Table 5.2(R): District wise Chi-Square test results of persons over worker, unemployed and out of labour force for PS+SS, CWS and CDS status of Pooled sample

Sector: Rural (Schedule 10) χ2.01 = 9.21 df = 2 [one sided test] reject if χ2-value > χ2.01

District Code District Name

PS+SS CWS CDS χ2 value ACCEPT χ2 value ACCEPT χ2 value ACCEPT

1 Nandurbar 1.68 Y 21.75 N 35.39 N 2 Dhule 5.09 Y 10.62 N 15.98 N 3 Jalgaon 12.28 N 25.40 N 74.61 N 4 Buldhana 1.29 Y 1.58 Y 15.33 N 5 Akola 6.66 Y 7.21 Y 18.71 N 6 Washim 16.17 N 19.41 N 22.00 N 7 Amravati 11.06 N 10.28 N 43.75 N 8 Wardha 0.28 Y 0.03 Y 0.85 Y 9 Nagpur 5.89 Y 5.64 Y 10.82 N

10 Bhandara 8.80 Y 0.12 Y 3.30 Y 11 Gondia 9.41 N 3.50 Y 13.86 N 12 Gadchiroli 3.18 Y 1.36 Y 2.67 Y 13 Chandrapur 9.88 N 3.12 Y 5.25 Y 14 Yavatmal 3.04 Y 1.22 Y 53.22 N 15 Nanded 3.65 Y 2.29 Y 1.70 Y 16 Hingoli 0.30 Y 0.04 Y 2.38 Y 17 Parbhani 9.01 Y 9.60 N 22.73 N 18 Jalna 7.09 Y 3.53 Y 11.66 N 19 Aurangabad 16.92 N 12.78 N 14.69 N 20 Nashik 5.58 Y 3.61 Y 6.58 Y 21 Thane 9.28 N 1.88 Y 6.58 Y 24 Raigad 6.58 Y 3.07 Y 1.03 Y 25 Pune 5.59 Y 23.41 N 28.41 N 26 Ahmednagar 12.83 N 5.44 Y 31.18 N 27 Beed 6.92 Y 5.92 Y 18.38 N 28 Latur 0.72 Y 0.75 Y 3.19 Y 29 Osmanabad 18.27 N 17.85 N 23.87 N 30 Solapur 0.92 Y 0.13 Y 10.80 N 31 Satara 1.56 Y 16.42 N 13.00 N 32 Ratnagiri 22.94 N 23.58 N 16.59 N 33 Sindhudurg 14.70 N 12.27 N 16.69 N 34 Kolhapur 2.56 Y 11.06 N 5.68 Y 35 Sangli 3.08 Y 7.23 Y 4.50 Y

22

Table 5.2(U): District wise Chi-Square test results of persons over worker, unemployed and out of labour force for PS+SS, CWS and CDS of Pooled sample

Sector: Urban (Schedule 10) χ2.01 = 9.21 df = 2 [one sided test] reject if χ2-value > χ2.01

District Code District Name PS+SS CWS CDS

χ2 value Accept χ2 value Accept χ2 value Accept 1 Nandurbar 6.87 Y 5.58 Y 1.84 Y 2 Dhule 0.25 Y 5.28 Y 12.41 N 3 Jalgaon 1.87 Y 2.22 Y 8.54 Y 4 Buldhana 0.09 Y 2.06 Y 5.38 Y 5 Akola 5.27 Y 3.37 Y 5.80 Y 6 Washim 0.32 Y 4.13 Y 11.17 N 7 Amravati 1.00 Y 2.39 Y 4.10 Y 8 Wardha 6.41 Y 4.61 Y 10.35 N 9 Nagpur 0.09 Y 4.56 Y 6.25 Y

10 Bhandara 8.73 Y 8.59 Y 16.58 N 11 Gondia 0.35 Y 1.15 Y 3.84 Y 12 Gadchiroli 0.01 Y 0.42 Y 0.57 Y 13 Chandrapur 1.26 Y 0.43 Y 0.98 Y 14 Yavatmal 0.52 Y 0.97 Y 5.30 Y 15 Nanded 1.29 Y 0.39 Y 0.36 Y 16 Hingoli 1.17 Y 0.74 Y 0.12 Y 17 Parbhani 4.58 Y 5.81 Y 20.06 N 18 Jalna 5.63 Y 5.35 Y 9.49 N 19 Aurangabad 1.06 Y 2.55 Y 7.24 Y 20 Nashik 4.14 Y 3.84 Y 0.93 Y 21 Thane 0.41 Y 0.15 Y 0.43 Y 22 Mumbai 9.02 Y 14.59 N 20.30 N 24 Raigad 1.41 Y 1.91 Y 5.04 Y 25 Pune 6.61 Y 4.20 Y 1.86 Y 26 Ahmednagar 6.12 Y 4.73 Y 11.06 N 27 Beed 2.38 Y 0.18 Y 8.55 Y 28 Latur 0.47 Y 0.57 Y 3.21 Y 29 Osmanabad 7.38 Y 7.38 Y 12.54 N 30 Solapur 4.16 Y 1.42 Y 17.51 N 31 Satara 6.45 Y 9.15 Y 6.08 Y 32 Ratnagiri 0.63 Y 0.63 Y 2.21 Y 33 Sindhudurg 0.29 Y 0.68 Y 1.71 Y 34 Kolhapur 2.48 Y 2.92 Y 3.20 Y 35 Sangli 0.08 Y 0.08 Y 0.39 Y

23

CHAPTER – 6 POOLED RESULTS OF MPCE, WPR AND LFPR

Table 6.1(R): District wise estimated number of households and their RSE's for central, state and pooled samples

Sector: Rural (Schedule 1.0 Type-1)


Estimated no. of Households RSE Sample Households

Central State Pooled (MR)

Pooled (IV) Central State Pooled

(MR) Pooled

(IV) Central State Pooled

1 Nandurbar 243432 236083 239758 237671 7.54 4.08 8.65 7.18 96 96 192 2 Dhule 300289 283212 291751 290918 2.24 2.15 3.11 3.11 96 96 192 3 Jalgaon 644622 514847 579735 576470 5.47 6.51 8.39 8.43 192 175 367 4 Buldhana 404892 434719 419806 429145 1.54 0.69 1.64 1.25 128 128 256 5 Akola 208118 239657 223888 211290 1.14 2.95 3.33 2.12 64 64 128 6 Washim 195425 202189 198807 195902 1.08 3.8 4.01 2.08 64 64 128 7 Amravati 341244 409388 375316 401035 1.88 0.59 1.83 1.12 128 128 256 8 Wardha 192898 217169 205034 214386 4.82 1.54 4.82 2.94 64 64 128 9 Nagpur 303769 310751 307260 310739 5.22 0.22 5.17 0.43 96 96 192 10 Bhandara 223883 205366 214625 219305 1.99 3.78 4.17 3.52 64 64 128 11 Gondiya 252060 236742 244401 239048 0.54 0.24 0.60 0.44 96 96 192 12 Gadchiroli 211708 207812 209760 208737 3.14 1.79 3.63 3.11 64 64 128 13 Chandrapur 456887 341839 399363 454022 0.5 4.18 3.62 0.99 96 96 192 14 Yavatmal 479459 491365 485412 481990 2.01 3.78 4.32 3.56 160 160 320 15 Nanded 377730 452382 415056 384281 1.48 3.99 4.56 2.79 160 160 320 16 Hingoli 174199 198231 186215 174484 0.93 7.48 8.01 1.85 64 64 128 17 Parbhani 220795 208950 214873 216769 3.01 4.44 5.31 4.99 64 64 128 18 Jalna 312085 280207 296146 300435 2.09 3.07 3.65 3.47 96 96 192 19 Aurangabad 483792 326061 404927 341964 4.04 2.01 5.09 3.63 128 128 256 20 Nashik 492691 604438 548565 562850 3.4 2.13 3.85 3.63 192 184 376 21 Thane 505531 616635 561083 521149 1.36 2.75 3.26 2.44 157 160 317 24 Raigad 367530 436697 402114 399377 1.88 1.71 2.53 2.54 119 128 247 25 Pune 665888 654224 660056 657366 2.1 1.3 2.48 2.21 189 192 381

24


Estimated no. of Households RSE Sample Households



(MR) Pooled


26 Ahmednagar 734372 668775 701574 701056 0.46 0.5 0.67 0.67 191 192 383 27 Bid 441635 400220 420928 402966 3.1 0.91 3.37 1.75 128 128 256 28 Latur 334835 365862 350349 339751 0.83 1.75 1.99 1.50 128 128 256 29 Osmanabad 271854 270669 271262 271750 0.91 2.94 3.08 1.74 96 96 192 30 Solapur 565709 568969 567339 566359 1.03 2.06 2.31 1.85 192 192 384 31 Satara 547633 524040 535837 546802 0.49 2.68 2.67 0.96 159 160 319 32 Ratnagiri 349723 350562 350143 350502 2.3 0.64 2.38 1.23 128 128 256 33 Sindhudurg 175413 163704 169559 171368 0.53 0.79 0.94 0.88 64 63 127 34 Kolhapur 528442 585920 557181 529213 0.33 2.54 2.69 0.65 192 192 384 35 Sangli 420151 472635 446393 447816 1.21 1.02 1.57 1.57 160 160 320

Maharashtra 12428697 12480320 12454509 12453109 0.49 0.51 0.70 0.70 4015 4006 8021

MR- Matching Ratio method IV-Inverse Variance method

25

Table 6.1(U): District wise estimated number of households and their RSE's for central, state and pooled samples

Sector: Urban (Schedule 1.0 Type-1)

District Code District

Estimated no. of Households RSE of Estimated Households Sample Households



(MR) Pooled


1 Nandurbar 45824 25226 33465 25227 0.11 12.27 0.38 0.23 32 63 95 2 Dhule 79794 75914 77466 75945 1.28 13.53 0.26 2.54 63 96 159 3 Jalgaon 193785 158582 172663 166947 6.38 9.35 0.17 10.58 96 160 256 4 Buldhana 86327 82943 84297 82945 0.22 9.44 0.25 0.45 64 96 160 5 Akola 73547 129718 107250 83006 9.12 7.24 0.23 11.70 64 96 160 6 Washim 23664 36958 31640 30936 4.19 7.18 0.41 7.40 32 64 96 7 Amravati 194019 165682 177017 170156 4.59 9.04 0.17 8.19 96 160 256 8 Wardha 63373 61335 62150 61756 2.54 4.82 0.29 4.50 64 96 160 9 Nagpur 627487 537668 573596 617189 1.22 0.38 0.09 0.72 253 376 629 10 Bhandara 40449 23283 30149 38081 5.22 1.2 0.40 2.37 32 64 96 11 Gondiya 48399 27923 36113 41832 4.00 1.58 0.37 3.02 32 64 96 12 Gadchiroli 25166 13652 18258 14424 2.71 5.49 0.52 4.96 32 64 96 13 Chandrapur 146991 138192 141712 140235 6.23 10.65 0.19 10.76 64 96 160 14 Yavatmal 102729 118964 112470 114809 3.34 6.59 0.22 5.97 64 96 160 15 Nanded 153984 102229 122931 110001 5.34 8.44 0.20 9.15 64 96 160 16 Hingoli 37188 36281 36644 36984 18.04 9.5 0.38 16.81 32 64 96 17 Parbhani 77147 70094 72915 71318 2.2 4.37 0.27 3.94 64 95 159 18 Jalna 35446 98170 73080 35903 16.9 4.01 0.28 7.89 64 96 160 19 Aurangabad 308445 234549 264107 237516 3.38 12.58 0.14 6.55 96 160 256 20 Nashik 312454 330067 323022 327751 1.41 3.83 0.13 2.64 192 320 512 21 Thane 1877616 1764047 1809475 1799582 2.42 3.37 0.05 3.93 564 864 1428 22 Mumbai 2704835 3061751 2918985 2713309 9.83 1.74 0.04 3.42 766 908 1674 24 Raigad 200809 167954 181096 175445 8.78 13.51 0.17 14.76 64 96 160 25 Pune 1211471 1378905 1311931 1319287 2.29 3.51 0.06 3.85 415 638 1053 26 Ahmednagar 170264 197360 186522 171928 15.09 4.48 0.17 8.59 96 160 256

26


Estimated no. of Households RSE of Estimated Households Sample Households



(MR) Pooled


27 Bid 59002 84609 74366 75065 5.46 10.15 0.27 9.74 64 96 160 28 Latur 81675 131346 111478 111428 3.11 6.11 0.22 5.67 64 96 160 29 Osmanabad 35091 40996 38634 40531 2.3 9.19 0.37 4.46 32 64 96 30 Solapur 255333 223264 236092 227536 3.39 7.56 0.15 6.20 128 192 320 31 Satara 119033 95523 104927 98331 14.65 31.92 0.22 26.70 64 96 160 32 Ratnagiri 34965 67264 54344 44035 21.2 25.48 0.32 34.32 32 64 96 33 Sindhudurg 19415 13448 15835 18196 8.99 3.16 0.56 6.01 32 64 96 34 Kolhapur 169974 238820 211282 238780 0.14 8.34 0.16 0.28 95 160 255 35 Sangli 124596 136857 131953 133668 5.07 9.39 0.20 8.93 64 96 160

Maharashtra 9740294 10069569 9937859 9782609 3.08 1.22 0.02 2.27 3980 6016 9996

27

Table 6.2(R): District wise estimated number of persons and their RSE's for central, state and pooled samples



Estimated no. of persons (00) RSE of Estimated persons



(MR) Pooled (IV)

1 Nandurbar 13534 10762 12148 11680 6.65 5.88 9.06 8.872 Dhule 14188 13393 13791 13593 3.18 1.95 3.78 3.333 Jalgaon 25181 22414 23797 25160 0.31 4.05 3.82 0.624 Buldhana 18543 21905 20224 21798 5.22 0.8 4.86 1.595 Akola 9494 11745 10620 11575 5.66 1.31 5.27 2.566 Washim 8138 9664 8901 8655 2.88 3.38 4.51 4.397 Amravati 15413 18999 17206 17180 6.44 5.3 8.22 8.238 Wardha 7356 9182 8269 8472 8.41 5.38 9.57 9.119 Nagpur 13309 13293 13301 13302 5.26 6.07 8.03 7.95

10 Bhandara 10905 9552 10228 10616 2.74 6 6.32 4.9911 Gondia 9925 11172 10548 10019 0.75 2.32 2.56 1.4212 Gadchiroli 9507 8822 9165 9501 0.52 5.98 5.78 1.0413 Chandrapur 18166 14813 16489 18141 0.4 5.72 5.16 0.8114 Yavatmal 19589 23617 21603 20439 2.39 3.83 4.71 4.0715 Nanded 19172 21776 20474 19890 1.15 1.64 2.04 1.8816 Hingoli 9883 9444 9664 9581 4.96 3.5 6.12 5.7217 Parbhani 11097 11294 11196 11164 3.93 5.36 6.66 6.3418 Jalna 13191 13584 13387 13552 5.32 1.53 5.46 2.9419 Aurangabad 21516 14571 18043 14757 8.61 2.11 10.4 4.1120 Nashik 26943 30198 28571 28543 3.41 3.09 4.58 4.5921 Thane 25464 26709 26087 25490 0.59 3.89 4.02 1.1624 Raigad 14415 16209 15312 15346 4.17 3.57 5.45 5.4325 Pune 31064 29429 30247 30627 1.08 1.89 2.15 1.8826 Ahmednagar 35533 31510 33522 35060 0.64 1.96 1.96 1.2127 Bid 20845 22899 21872 21652 1.92 2.17 2.91 2.8828 Latur 16532 18019 17276 18018 7.73 0.23 7.4 0.4629 Osmanabad 12592 13396 12994 12988 1.57 1.5 2.17 2.1730 Solapur 26525 24335 25430 24556 3.49 1.28 3.84 2.431 Satara 24807 22239 23523 22870 6.52 4.15 7.92 7.0232 Ratnagiri 13822 12869 13345 12998 10.29 4.37 11.46 8.0433 Sindhudurg 7674 6729 7201 7674 0.07 5.15 4.82 0.1534 Kolhapur 23105 27312 25208 24516 3.2 3.81 5.06 4.9135 Sangli 17836 20550 19193 19175 2.4 2.11 3.18 3.18

Maharashtra 565262 572405 568834 569546 0.76 0.61 0.97 0.95

28

Table 6.2 (U): District wise estimated number of persons and their RSE's for central, state and pooled sample



Estimated no.of persons (00) RSE of Estimated persons



(MR) Pooled

(IV)

1 Nandurbar 1893 1457 1631 1468 3.65 0.78 0.18 1.522 Dhule 3657 3703 3685 3703 19.72 1.62 0.12 3.243 Jalgaon 9492 7925 8552 8364 7.7 5.75 0.08 9.254 Buldhana 4730 3620 4064 3632 11.84 1.57 0.11 3.115 Akola 3293 5972 4900 4026 7.4 6.65 0.11 10.326 Washim 1258 2007 1707 1562 6.3 4.78 0.18 7.837 Amravati 8158 6967 7443 8081 0.46 2.03 0.08 0.898 Wardha 2865 2534 2666 2566 2.27 0.85 0.14 1.599 Nagpur 28293 21777 24383 21959 6.13 1.35 0.05 2.6410 Bhandara 1565 940 1190 1073 6.19 5.37 0.2 8.3411 Gondiya 2171 1189 1582 2161 0.3 5.3 0.18 0.612 Gadchiroli 1033 522 727 551 3.96 1.9 0.26 3.513 Chandrapur 6930 5567 6112 5583 12.47 1.7 0.09 3.3614 Yavatmal 5359 4704 4966 4865 8.43 5.49 0.1 9.2115 Nanded 8441 5685 6787 7940 3.58 11.26 0.09 6.8816 Hingoli 1770 2068 1949 1786 5.12 18.29 0.16 9.8617 Parbhani 4280 4073 4156 4183 2.41 2.7 0.11 3.618 Jalna 1854 4833 3641 1935 5.27 12.13 0.12 9.9619 Aurangabad 15134 10297 12232 10409 14.17 3.2 0.06 6.2620 Nashik 14230 16254 15444 15117 1.71 1.69 0.06 2.4121 Thane 72834 73663 73331 73192 1.67 1.9 0.03 2.5122 Mumbai 103564 120616 113795 103599 0.35 6.6 0.02 0.6924 Raigad 7177 7412 7318 7402 12.24 2.46 0.08 4.8325 Pune 45246 52749 49748 50423 3.16 1.82 0.03 3.1526 Ahmednagar 7035 9838 8717 7052 1.96 18.34 0.08 3.9127 Bid 2894 5163 4255 4942 14.4 2.65 0.11 5.2728 Latur 3764 6476 5391 6446 3.64 0.22 0.1 0.4529 Osmanabad 1759 2261 2060 2174 2.26 0.8 0.16 1.5230 Solapur 13569 10374 11652 10872 5.97 3.36 0.07 5.8831 Satara 3752 3834 3801 3811 24.64 14.85 0.12 25.4432 Ratnagiri 1285 2344 1920 1595 23.21 19.81 0.17 31.4833 Sindhudurg 802 467 601 579 4.99 6.08 0.29 834 Kolhapur 8117 9862 9164 9002 9.85 8 0.08 12.4735 Sangli 5491 5179 5304 5427 3.75 7.86 0.1 6.77

Maharashtra 403693 422333 414877 407251 1.02 2.02 0.01 1.83

29

Table 6.3: District wise estimated household size for central, state and pooled sample (Schedule 1.0, Type-1)

District Code

District Name



(MR) Pooled

(IV) Rural Urban

1 Nandurbar 5.6 4.6 5.1 4.9 4.1 5.8 4.9 5.82 Dhule 4.7 4.7 4.7 4.7 4.6 4.9 4.8 4.93 Jalgaon 3.9 4.4 4.1 4.4 4.9 5.0 5.0 5.04 Buldhana 4.6 5.0 4.8 5.1 5.5 4.4 4.8 4.45 Akola 4.6 4.9 4.7 5.5 4.5 4.6 4.6 4.96 Washim 4.2 4.8 4.5 4.4 5.3 5.4 5.4 5.07 Amravati 4.5 4.6 4.6 4.3 4.2 4.2 4.2 4.78 Wardha 3.8 4.2 4.0 4.0 4.5 4.1 4.3 4.29 Nagpur 4.4 4.3 4.3 4.3 4.5 4.1 4.3 3.610 Bhandara 4.9 4.7 4.8 4.8 3.9 4.0 3.9 2.811 Gondiya 3.9 4.7 4.3 4.2 4.5 4.3 4.4 5.212 Gadchiroli 4.5 4.2 4.4 4.6 4.1 3.8 4.0 3.813 Chandrapur 4.0 4.3 4.1 4.0 4.7 4.0 4.3 4.014 Yavatmal 4.1 4.8 4.5 4.2 5.2 4.0 4.4 4.215 Nanded 5.1 4.8 4.9 5.2 5.5 5.6 5.5 7.216 Hingoli 5.7 4.8 5.2 5.5 4.8 5.7 5.3 4.817 Parbhani 5.0 5.4 5.2 5.2 5.5 5.8 5.7 5.918 Jalna 4.2 4.8 4.5 4.5 5.2 4.9 5.0 5.419 Aurangabad 4.4 4.5 4.5 4.3 4.9 4.4 4.6 4.420 Nashik 5.5 5.0 5.2 5.1 4.6 4.9 4.8 4.621 Thane 5.0 4.3 4.6 4.9 3.9 4.2 4.1 4.122 Mumbai --- --- --- --- 3.8 3.9 3.9 3.824 Raigad 3.9 3.7 3.8 3.8 3.6 4.4 4.0 4.225 Pune 4.7 4.5 4.6 4.7 3.7 3.8 3.8 3.826 Ahmednagar 4.8 4.7 4.8 5.0 4.1 5.0 4.7 4.127 Bid 4.7 5.7 5.2 5.4 4.9 6.1 5.7 6.628 Latur 4.9 4.9 4.9 5.3 4.6 4.9 4.8 5.829 Osmanabad 4.6 4.9 4.8 4.8 5.0 5.5 5.3 5.430 Solapur 4.7 4.3 4.5 4.3 5.3 4.6 4.9 4.831 Satara 4.5 4.2 4.4 4.2 3.2 4.0 3.6 3.932 Ratnagiri 4.0 3.7 3.8 3.7 3.7 3.5 3.5 3.633 Sindhudurg 4.4 4.1 4.2 4.5 4.1 3.5 3.8 3.234 Kolhapur 4.4 4.7 4.5 4.6 4.8 4.1 4.3 3.835 Sangali 4.2 4.3 4.3 4.3 4.4 3.8 4.0 4.1

Maharashtra 4.5 4.6 4.6 4.6 4.1 4.2 4.2 4.2

30

Table 6.4(R): District wise estimated sex ratio and their RSE's for central, state and pooled sample



Sex Ratio RSE of Sex Ratio



(MR) Pooled

(IV)


10 Bhandara 869 776 822 826 7.65 9.24 5.94 5.9011 Gondiya 931 917 924 921 1.39 0.87 0.82 0.7412 Gadchiroli 719 1013 866 719 0.35 8.87 5.19 0.3413 Chandrapur 1055 1160 1108 1156 10.00 1.85 4.86 1.8214 Yavatmal 881 803 842 804 4.71 0.62 2.48 0.6215 Nanded 784 834 809 802 3.28 4.16 2.67 2.5716 Hingoli 1001 855 928 923 4.23 4.58 3.11 3.1217 Parbhani 844 1135 989 1064 6.48 2.73 3.17 2.5318 Jalna 912 825 868 826 6.46 0.72 3.41 0.7219 Aurangabad 931 967 949 965 7.67 1.44 3.83 1.4220 Nashik 943 1018 980 948 0.71 2.33 1.25 0.6721 Thane 1070 891 981 1044 1.16 3.37 1.66 1.1024 Raigad 1056 1089 1073 1074 2.09 1.84 1.39 1.3825 Pune 880 901 890 887 2.06 2.94 1.80 1.6926 Ahmednagar 926 830 878 901 2.26 4.28 2.35 2.0027 Bid 866 1055 960 1047 3.92 0.65 1.80 0.6428 Latur 983 894 938 897 9.03 1.93 4.82 1.8929 Osmanabad 952 745 848 952 0.09 2.30 1.01 0.1030 Solapur 1065 899 982 922 3.17 1.48 1.85 1.3531 Satara 1019 922 970 986 5.23 8.18 4.76 4.4132 Ratnagiri 1013 1180 1097 1174 10.16 1.66 4.77 1.6333 Sindhudurg 1058 1009 1033 1056 1.35 7.81 3.88 1.3334 Kolhapur 925 930 928 926 2.08 5.89 3.13 1.9635 Sangli 917 1000 958 971 4.82 3.26 2.86 2.70

Maharashtra 938 940 939 939 0.88 0.81 0.60 0.59

31

Table 6.4(U): District wise estimated sex ratio and their RSE's for central, state and pooled sample






(MR) Pooled

(IV)


10 Bhandara 1226 929 1048 1140 4.49 9.26 2.20 4.0711 Gondiya 1142 868 978 1003 3.12 4.05 2.28 2.4912 Gadchiroli 1194 985 1069 1068 2.08 2.04 2.19 1.4713 Chandrapur 846 886 870 886 15.29 0.57 2.45 0.5814 Yavatmal 992 885 928 957 3.81 6.08 2.35 3.2315 Nanded 884 879 881 884 2.88 11.11 2.43 2.7916 Hingoli 882 1077 999 894 6.04 19.15 2.30 5.7617 Parbhani 804 962 899 917 4.15 2.20 2.42 1.9518 Jalna 1003 841 906 1000 1.70 15.18 2.38 1.6919 Aurangabad 951 895 917 899 13.13 3.80 2.37 3.6520 Nashik 1033 925 968 1020 0.58 1.78 2.31 0.5521 Thane 864 874 870 870 2.17 1.92 2.45 1.4422 Mumbai 856 963 920 860 0.77 3.94 2.39 0.7624 Raigad 1057 748 871 758 9.03 2.30 2.40 2.2425 Pune 887 900 895 898 4.01 1.98 2.41 1.7826 Ahmednagar 914 972 949 915 1.20 17.83 2.35 1.2027 Bid 981 872 915 896 11.72 7.00 2.37 6.0228 Latur 806 884 852 850 5.27 4.20 2.48 3.2929 Osmanabad 925 875 895 878 5.83 1.54 2.40 1.4930 Solapur 888 1053 987 953 6.12 6.36 2.31 4.4231 Satara 1165 975 1051 1020 22.61 15.17 2.21 12.6432 Ratnagiri 959 1080 1031 1028 27.28 20.94 2.26 16.6433 Sindhudurg 1001 973 984 980 2.49 1.51 2.30 1.2934 Kolhapur 916 868 887 889 14.09 12.90 2.41 9.5235 Sangli 1126 1110 1116 1121 4.01 6.17 2.16 3.36

Maharashtra 904 926 917 913 1.12 1.36 2.38 0.87

32

Table 6.5(R): District wise Estimate of MPCE (URP) and their RSE's for central, state and pooled sample Sector: Rural (Schedule 1.0 Type-1)


Estimate of MPCE (URP) RSE of Estimated MPCE (URP)

Central State Pooled (MR) Pooled (IV) Central State Pooled

(MR) Pooled

(IV)

1 Nandurbar Food 419.39 352.84 386.12 383.07 4.09 4.43 3.01 3.02 Non-Food 333.36 261.19 297.27 268.96 9.52 4.22 5.65 3.87 Total 752.75 614.03 683.39 645.17 6.47 4.27 4.05 3.58

2 Dhule Food 506.36 380.12 443.24 400.64 3.33 1.95 2.08 1.70 Non-Food 350.49 298.02 324.26 306.87 3.34 1.77 1.98 1.57 Total 856.85 678.14 767.50 778.55 0.60 0.86 0.51 0.50

3 Jalgaon Food 542.94 441.78 492.36 457.08 2.85 1.48 1.70 1.32 Non-Food 596.49 395.40 495.94 396.09 13.21 1.17 7.96 1.17 Total 1139.43 837.18 988.30 841.28 8.15 1.30 4.73 1.29

4 Buldhana Food 468.74 413.79 441.27 451.73 1.72 2.90 1.64 1.48 Non-Food 394.59 309.93 352.26 388.77 2.50 11.73 5.35 2.45 Total 863.33 723.72 793.53 848.27 1.95 6.68 3.23 1.87

5 Akola Food 564.12 419.06 491.59 419.06 2.43 0.00 1.39 0.00 Non-Food 451.40 313.85 382.63 352.97 6.77 6.13 4.72 4.61 Total 1015.52 732.91 874.22 777.96 4.36 2.63 2.76 2.27

6 Washim Food 521.18 455.87 488.52 514.89 2.60 9.09 4.46 2.50 Non-Food 389.21 674.82 532.02 402.94 11.23 28.82 18.73 10.58 Total 910.39 1130.70 1020.54 922.63 6.29 20.87 11.89 6.03

7 Amravati Food 397.93 400.87 399.40 400.81 9.72 1.48 4.90 1.46 Non-Food 516.43 400.86 458.65 403.64 22.42 4.54 12.78 4.45 Total 914.36 801.73 858.05 804.41 16.88 3.00 9.10 2.96

8 Wardha Food 501.80 455.00 478.40 484.79 4.15 6.05 3.61 3.42 Non-Food 553.92 341.16 447.54 356.01 7.13 3.17 4.57 2.93 Total 1055.72 796.16 925.94 814.72 5.71 2.10 3.38 1.98

33




(MR) Pooled

(IV)

9 Nagpur Food 542.55 493.56 518.06 494.15 5.62 0.68 2.96 0.68 Non-Food 509.56 448.43 479.00 451.31 3.66 0.92 2.00 0.90 Total 1052.11 941.99 997.05 944.89 1.50 0.28 0.80 0.27

10 Bhandara Food 408.05 496.67 452.36 452.05 4.00 3.31 2.56 2.56 Non-Food 280.29 523.33 401.81 282.85 1.77 9.20 6.02 1.75 Total 688.33 1020.00 854.17 720.88 3.09 6.33 3.98 2.81

11 Gondiya Food 388.92 454.12 421.52 420.52 1.45 1.28 0.96 0.96 Non-Food 346.73 358.07 352.40 356.22 3.30 1.41 1.77 1.30 Total 735.65 812.19 773.92 752.65 0.79 1.34 0.80 0.68

12 Gadchiroli Food 405.37 572.47 488.92 420.18 1.17 2.67 1.64 1.08 Non-Food 241.54 403.49 322.52 364.60 9.60 3.23 4.12 3.12 Total 646.91 975.96 811.44 809.35 4.32 2.90 2.45 2.46

13 Chandrapur Food 489.88 496.15 493.02 495.03 8.17 3.76 4.48 3.42 Non-Food 386.89 365.20 376.05 365.33 20.19 1.61 10.41 1.61 Total 876.77 861.36 869.06 861.54 13.47 1.49 6.83 1.48

14 Yavatmal Food 434.47 406.23 420.35 430.40 1.90 4.96 2.59 1.78 Non-Food 407.92 350.41 379.17 387.36 5.14 8.02 4.62 4.34 Total 842.39 756.64 799.52 835.27 1.72 6.38 3.15 1.67

15 Nanded Food 422.47 514.54 468.51 457.53 3.25 3.40 2.38 2.36 Non-Food 333.75 540.79 437.27 399.37 10.07 9.13 6.83 6.96 Total 756.22 1055.32 905.77 856.52 6.26 6.32 4.51 4.51

16 Hingoli Food 375.14 504.52 439.83 502.12 4.92 0.50 2.12 0.50 Non-Food 230.03 433.74 331.88 371.83 8.95 3.14 3.72 3.05 Total 605.17 938.26 771.71 913.48 6.45 1.18 2.63 1.17

17 Parbhani Food 430.56 517.64 474.10 460.04 0.73 0.85 0.57 0.56 Non-Food 313.69 474.44 394.06 313.98 0.67 10.47 6.31 0.67 Total 744.25 992.08 868.16 747.54 0.71 4.56 2.62 0.70

18 Jalna Food 516.79 554.20 535.50 539.57 6.01 4.49 3.71 3.60 Non-Food 454.78 515.02 484.90 470.70 7.19 10.59 6.56 5.96 Total 971.57 1069.22 1020.39 1009.82 6.56 7.43 4.99 4.92

34




(MR) Pooled

(IV)

19 Aurangabad Food 587.44 558.15 572.80 576.11 2.92 3.87 2.41 2.33 Non-Food 578.76 405.83 492.30 474.39 3.29 3.80 2.49 2.53 Total 1166.21 963.98 1065.09 1165.46 0.16 3.23 1.47 0.16

20 Nashik Food 557.88 476.49 517.18 485.47 2.01 0.83 1.15 0.77 Non-Food 569.94 447.80 508.87 450.68 7.20 1.42 4.08 1.40 Total 1127.82 924.29 1026.06 929.94 3.76 0.78 2.10 0.76

21 Thane Food 514.50 557.05 535.77 535.13 2.83 2.69 1.95 1.95 Non-Food 637.60 517.72 577.66 636.67 0.79 10.98 4.94 0.79 Total 1152.10 1074.77 1113.44 1148.64 1.34 6.64 3.28 1.32

24 Raigad Food 640.55 626.12 633.34 626.76 6.55 1.45 3.39 1.41 Non-Food 845.75 673.59 759.67 738.10 20.10 19.54 14.15 14.10 Total 1486.31 1299.71 1393.01 1356.50 14.26 10.79 9.12 8.62

25 Pune Food 533.39 582.90 558.15 578.30 6.22 1.82 3.12 1.75 Non-Food 556.82 575.93 566.37 574.89 13.21 3.06 6.68 2.99 Total 1090.21 1158.83 1124.52 1158.48 9.79 0.66 4.76 0.65

26 Ahmednagar Food 557.97 483.20 520.58 484.52 2.85 0.44 1.54 0.44 Non-Food 491.43 470.32 480.87 489.96 0.92 3.52 1.79 0.89 Total 1049.39 953.52 1001.46 1023.38 1.09 1.96 1.09 0.95

27 Bid Food 609.25 586.66 597.95 590.37 2.94 1.35 1.64 1.23 Non-Food 584.15 576.71 580.43 582.55 3.36 6.50 3.64 2.98 Total 1193.39 1163.37 1178.38 1193.33 0.18 3.89 1.92 0.18

28 Latur Food 488.91 581.71 535.31 523.80 4.20 4.55 3.13 3.10 Non-Food 464.79 587.75 526.27 474.22 2.72 7.46 4.34 2.56 Total 953.70 1169.46 1061.58 993.00 3.48 6.01 3.66 3.02

29 Osmanabad Food 539.06 481.74 510.40 504.43 2.03 1.84 1.38 1.36 Non-Food 580.57 388.58 484.58 464.62 4.30 5.20 3.32 3.38 Total 1119.64 870.32 994.98 969.05 3.21 3.34 2.32 2.33

30 Solapur Food 546.80 560.63 553.72 559.08 1.76 0.61 0.92 0.58 Non-Food 730.65 416.45 573.55 419.85 4.97 0.91 3.18 0.90 Total 1277.45 977.09 1127.27 983.95 3.15 0.63 1.81 0.62

35




(MR) Pooled

(IV)

31 Satara Food 544.27 612.82 578.55 545.48 0.47 3.12 1.67 0.47 Non-Food 583.93 686.14 635.04 611.34 8.27 11.63 7.34 6.76 Total 1128.20 1298.96 1213.58 1163.98 4.51 7.61 4.58 3.89

32 Ratnagiri Food 534.54 541.64 538.09 538.45 0.76 0.67 0.51 0.50 Non-Food 464.86 559.42 512.14 493.35 1.83 2.31 1.51 1.44 Total 999.41 1101.05 1050.23 1033.45 1.00 1.28 0.82 0.79

33 Sindhudurg Food 519.94 582.93 551.43 520.65 0.45 3.77 2.00 0.45 Non-Food 356.01 543.92 449.97 531.28 6.24 1.10 2.56 1.08 Total 875.95 1126.85 1001.40 985.34 2.80 2.48 1.86 1.87

34 Kolhapur Food 553.32 610.85 582.08 578.01 1.24 1.30 0.90 0.90 Non-Food 441.41 488.89 465.15 462.87 5.99 5.96 4.23 4.23 Total 994.73 1099.74 1047.23 1040.50 2.99 3.08 2.15 2.15

35 Sangali Food 572.96 614.34 593.65 587.05 2.19 2.84 1.81 1.73 Non-Food 493.32 416.21 454.77 426.37 7.73 3.57 4.50 3.25 Total 1066.28 1030.55 1048.42 1040.91 4.37 2.89 2.64 2.41

27 Maharashtra Food 515.16 514.43 514.79 514.67 0.72 0.51 0.44 0.41 Non-Food 495.77 466.37 481.07 479.00 1.82 1.68 1.24 1.23 Total 1010.93 980.80 995.87 993.09 1.16 1.00 0.77 0.76

36

Table 6.5(U): District wise Estimate of MPCE (URP) and their RSE's for central, state and pooled sample





(MR) Pooled

(IV)










37




(MR) Pooled

(IV)











38




(MR) Pooled

(IV)



22 Mumbai Food 1030.95 1051.13 1043.06 1045.48 4.67 2.86 2.53 2.44 Non-Food 1811.51 1827.97 1821.38 1820.57 11.05 9.89 7.40 7.37 Total 2842.46 2879.10 2864.44 2863.74 8.74 7.33 0.74 5.61








39




(MR) Pooled

(IV)





35 Sangli Food 591.84 741.40 681.58 739.49 2.45 0.22 0.86 0.22 Non-Food 1050.29 853.43 932.17 923.62 6.80 6.23 4.60 4.62 Total 1642.13 1594.83 1613.75 1607.33 5.24 3.23 1.00 2.75

Maharashtra Food 826.75 811.08 817.35 812.73 1.67 0.58 0.76 0.55 Non-Food 1405.23 1245.94 1309.65 1301.31 4.23 3.48 2.69 2.69 Total 2231.98 2057.02 2127.01 2109.23 3.26 2.31 0.89 1.89

40

Table 6.6(R): District wise Estimate of MPCE (MRP) and their RSE's for central, state and pooled sample


District code District

Estimate of MPCE (MRP) RSE of Estimated MPCE (MRP)

Central State Pooling (MR)

Pooling (IV) Central State Pooling

(MR) Pooling (IV)










41





(MR) Pooling (IV)











42





(MR) Pooling (IV)











43





(MR) Pooling (IV)






44

Table 6.6(U): District wise Estimate of MPCE (MRP) and their RSE's for central, state and pooled sample


District code District Type




(MR) Pooling (IV)










45





(MR) Pooling (IV)











46





(MR) Pooling (IV)











47





(MR) Pooling (IV)







48

Table 6.7(R): District wise Estimated no. of households and their RSE's for central, state and pooled sample



Estimated no. of households RSE of estimated households


(MR) Pooled

(IV)



Maharashtra 12426147 12491809 12458978 12458616 0.48 0.48 0.68 0.68

49

Table 6.7(U): District wise estimated no. of households and their RSE's for central, state and pooled sample



Estimated no. of households RSE of estimated households



(MR) Pooled

(IV)



Maharashtra 9727857 10080724 9939577 9772209 1.22 3.11 0.02 2.28

50

Table 6.8 (R): District wise estimated number of persons and their RSE's for central, state and pooled sample






(MR) Pooled

(IV)



Maharashtra 554385 564507 559446 559985 0.79 0.7 1.06 1.05

51

Table 6.8 (U): District wise estimated number of persons and their RSE's for central, state and pooled sample






(MR) Pooled

(IV)



Maharashtra 406068 421023 415041 408937 1.00 1.99 0.01 1.79

52

Table 6.9 (R): District wise estimated sex ratio and their RSE's for central, state and pooled sample





(MR) Pooled

(IV)

1 Nandurbar 914 930 922 928 7.42 2.5 3.89 2.372 Dhule 976 1017 996 1006 3.8 2.22 2.18 1.923 Jalgaon 927 1045 986 927 0.17 3.56 1.89 0.154 Buldhana 838 892 865 882 8.73 3.86 4.67 3.535 Akola 874 843 858 856 5.82 5.24 3.93 3.96 Washim 802 1350 1076 930 5.7 6.13 4.39 4.37 Amravati 909 965 937 961 5.72 1.6 2.9 1.548 Wardha 1205 866 1036 945 6.17 4.71 4.09 3.799 Nagpur 910 949 929 938 5.29 3.22 3.07 2.7510 Bhandara 933 1039 986 953 2.91 5.39 3.16 2.5611 Gondiya 867 922 894 905 4.67 2.93 2.72 2.4812 Gadchiroli 1267 785 1026 933 7.61 8.19 5.65 5.7313 Chandrapur 1178 924 1051 1101 6.08 11.74 6.18 5.4314 Yavatmal 867 925 896 910 3.51 1.92 1.97 1.6815 Nanded 1008 1071 1039 1040 2.64 2.41 1.79 1.7816 Hingoli 849 1020 934 866 4.88 12.1 6.97 4.5417 Parbhani 1022 910 966 910 14.58 0.32 7.71 0.3118 Jalna 936 986 961 943 4.48 10.4 5.77 4.1119 Aurangabad 852 882 867 854 2.88 10.42 5.49 2.7720 Nashik 939 995 967 952 1.29 2.17 1.28 1.1121 Thane 961 1041 1001 967 0.84 2.72 1.47 0.824 Raigad 1219 847 1033 916 3.14 2.15 2.05 1.825 Pune 922 891 907 893 5.07 1.09 2.63 1.0726 Ahmednagar 1061 879 970 886 1.56 0.37 0.87 0.3727 Bid 943 905 924 910 2.92 1.24 1.61 1.1528 Latur 1099 919 1009 1074 1.04 3.1 1.52 0.9929 Osmanabad 886 936 911 888 1.85 8.34 4.38 1.830 Solapur 925 969 947 933 1.37 2.78 1.57 1.2331 Satara 933 930 932 931 1.26 0.66 0.71 0.5932 Ratnagiri 1338 938 1138 986 8.31 4.38 5.21 3.9133 Sindhudurg 1033 960 997 972 2.83 1.29 1.59 1.1834 Kolhapur 952 967 960 952 0.34 3.93 1.99 0.3535 Sangli 1126 885 1006 945 7.19 5.27 4.65 4.27

Maharashtra 971 947 959 958 0.77 0.76 0.54 0.54

53

Table 6.9 (U): District wise estimated sex ratio and their RSE's for central, state and pooled sample






(MR) Pooled

(IV)



Maharashtra 892 862 874 887 1.08 2.42 2.44 0.98

54

Table 6.10(R): District wise Estimate of MPCE (MMRP) and their RSE's for central, state and pooled sample



Estimate of MPCE (MMRP) RSE of Estimated MPCE (MMRP)

Central State Pooled (MR) Pooled (IV) Central State Pooled (MR)

Pooled (IV)










55




Pooled (IV)











56




Pooled (IV)











57




Pooled (IV)






58

Table 6.10(U): District wise Estimate of MPCE (MMRP) and their RSE's for central, state and pooled sample





Pooled (IV)










59




Pooled (IV)











60




Pooled (IV)











61




Pooled (IV)







62

Table 6.11 (R): District wise WPR per 1000 (PS+SS) for central, state and pooled sample

Sector: Rural (Schedule 10)


Male Female Persons



(MR) Pooled

(IV) Central State Pooled (MR)

Pooled (IV)

1 Nandurbar 580 630 605 580 605 490 548 533 592 560 576 587 2 Dhule 570 546 558 569 363 524 443 497 469 536 502 496 3 Jalgaon 564 581 573 566 376 510 443 378 467 548 507 468 4 Buldhana 583 525 554 536 409 424 416 412 497 474 486 488 5 Akola 688 548 618 607 200 338 269 201 446 449 447 449 6 Washim 437 684 560 475 163 317 240 163 310 495 403 310 7 Amravati 657 577 617 645 463 293 378 420 568 436 502 542 8 Wardha 553 615 584 567 443 408 426 436 496 506 501 498 9 Nagpur 562 556 559 556 411 304 358 318 496 447 472 449

10 Bhandara 598 643 621 616 492 288 390 385 545 479 512 518 11 Gondiya 586 617 601 600 561 400 480 531 573 511 542 528 12 Gadchiroli 602 646 624 606 524 514 519 524 559 586 572 559 13 Chandrapur 720 591 655 671 490 325 407 489 600 457 529 545 14 Yavatmal 614 555 584 556 489 275 382 316 560 413 487 424 15 Nanded 443 587 515 443 341 217 279 323 396 405 401 396 16 Hingoli 444 577 511 463 388 141 265 142 417 343 380 417 17 Parbhani 580 568 574 568 310 441 376 413 444 503 474 502 18 Jalna 489 589 539 520 581 248 415 327 533 421 477 529 19 Aurangabad 569 582 575 582 363 204 284 208 474 413 444 416 20 Nashik 588 585 587 588 417 314 366 331 501 458 479 476 21 Thane 604 521 562 539 293 237 265 292 447 374 411 378 24 Raigad 532 540 536 532 307 274 291 305 420 406 413 413 25 Pune 604 635 619 609 392 396 394 393 500 517 508 500 26 Ahmednagar 484 469 476 480 492 355 424 392 488 418 453 433

63


Male Female Persons



(MR) Pooled


Pooled (IV)

27 Bid 624 568 596 623 378 285 331 332 510 435 473 504 28 Latur 532 547 540 532 234 153 193 214 391 343 367 383 29 Osmanabad 641 551 596 616 405 163 284 173 518 365 442 380 30 Solapur 606 569 588 605 427 407 417 427 518 488 503 518 31 Satara 627 570 598 570 405 417 411 407 516 498 507 508 32 Ratnagiri 606 534 570 571 328 206 267 236 461 353 407 393 33 Sindhudurg 656 512 584 545 374 96 235 147 527 307 417 345 34 Kolhapur 563 635 599 583 392 312 352 318 476 479 477 478 35 Sangli 601 542 572 598 308 355 332 333 448 450 449 448

Maharashtra 576 569 573 575 396 324 360 359 488 450 469 474

64

Table 6.11 (U): District wise WPR per 1000 (PS+SS) for central, state and pooled sample

Sector: Urban (Schedule 10)


Male Female Persons



(MR) Pooled


Pooled (IV)

1 Nandurbar 441 492 471 480 276 52 142 148 376 282 320 301 2 Dhule 473 504 491 504 163 71 108 71 339 303 318 303 3 Jalgaon 608 507 548 508 157 132 142 135 395 328 355 331 4 Buldhana 600 571 583 590 143 195 174 191 375 371 373 372 5 Akola 626 490 545 540 156 85 113 101 391 305 339 337 6 Washim 437 546 502 470 130 118 123 130 305 332 321 312 7 Amravati 522 547 537 537 57 116 93 59 307 339 326 316 8 Wardha 558 522 536 524 209 137 166 148 389 327 352 329 9 Nagpur 573 542 554 557 160 136 146 150 369 346 355 358 10 Bhandara 588 486 526 579 421 139 252 240 507 311 389 454 11 Gondiya 509 536 525 525 115 134 127 118 332 338 336 332 12 Gadchiroli 599 618 611 609 198 209 205 199 404 396 399 402 13 Chandrapur 609 594 600 596 161 105 127 119 376 334 351 345 14 Yavatmal 519 504 510 506 128 145 138 141 331 332 331 332 15 Nanded 502 432 460 478 63 70 67 66 289 255 269 275 16 Hingoli 641 515 566 586 151 121 133 134 416 332 366 375 17 Parbhani 480 554 525 495 91 157 131 157 284 357 328 331 18 Jalna 586 549 564 586 156 73 106 127 369 332 347 368 19 Aurangabad 533 476 499 476 173 86 121 86 339 293 311 293 20 Nashik 485 513 502 500 141 151 147 149 321 347 337 335 21 Thane 624 574 594 622 149 155 153 149 411 383 394 410 22 Mumbai 612 618 616 612 198 135 160 197 425 406 413 425 24 Raigad 570 637 610 635 89 143 121 117 369 386 379 384 25 Pune 544 550 548 546 123 161 146 142 350 369 361 358 26 Ahmednagar 503 496 499 503 139 328 253 143 319 422 381 319 27 Bid 554 479 509 528 104 62 79 70 316 272 289 293

65


Male Female Persons



(MR) Pooled


Pooled (IV)

28 Latur 431 463 450 457 32 51 44 43 229 275 257 264 29 Osmanabad 635 533 574 585 228 100 151 102 418 332 367 347 30 Solapur 568 506 531 541 318 171 230 172 439 344 382 355 31 Satara 503 573 545 553 84 207 158 119 307 401 363 365 32 Ratnagiri 497 534 519 514 131 192 168 148 314 370 348 336 33 Sindhudurg 542 487 509 513 127 90 104 111 355 289 315 301 34 Kolhapur 516 635 587 540 147 126 134 139 338 392 371 351 35 Sangli 572 514 537 515 119 135 129 130 352 340 345 341

Maharashtra 575 565 569 574 159 141 148 153 380 369 374 378

66

Table 6.12 (R): District wise LFPR per 1000 for central, state and pooled sample Sector: Rural (Schedule 10)


PS+SS CWS CDS



(MR) Pooled


Pooled (IV)

1 Nandurbar 592 560 576 587 519 560 539 523 471 538 505 478

2 Dhule 469 536 502 496 409 519 464 448 379 497 438 418

3 Jalgaon 468 548 508 469 436 535 486 437 418 524 471 419

4 Buldhana 500 479 489 492 433 450 442 439 419 371 395 399

5 Akola 456 449 452 449 446 456 451 455 421 399 410 399

6 Washim 310 495 403 310 315 495 405 315 298 471 384 298

7 Amravati 568 436 502 542 564 432 498 538 551 409 480 522

8 Wardha 496 506 501 498 487 494 491 488 459 493 476 464

9 Nagpur 507 448 478 450 488 454 471 455 470 454 462 454

10 Bhandara 547 507 527 532 518 507 513 514 515 507 511 512

11 Gondiya 587 523 555 540 538 529 533 532 530 529 529 529

12 Gadchiroli 561 586 573 561 517 586 552 518 498 586 542 498

13 Chandrapur 600 457 529 545 582 457 519 536 574 448 511 527

14 Yavatmal 563 413 488 424 561 413 487 424 555 384 469 396

15 Nanded 396 408 402 396 397 404 401 397 390 398 394 390

16 Hingoli 418 343 380 418 388 363 376 388 380 337 358 380

17 Parbhani 449 503 476 502 449 493 471 493 444 468 456 468

18 Jalna 533 421 477 529 513 421 467 509 436 417 426 436

19 Aurangabad 478 416 447 418 460 414 437 415 441 409 425 411

20 Nashik 501 458 479 477 495 463 479 477 487 447 467 465

21 Thane 450 394 422 397 422 379 401 382 412 372 392 375

24 Raigad 420 415 418 418 392 381 386 387 376 364 370 369

25 Pune 515 518 516 515 514 513 513 514 505 507 506 505

26 Ahmednagar 488 428 458 441 471 429 450 438 455 410 432 420

27 Bid 510 437 473 504 486 423 455 481 453 410 432 450

28 Latur 391 343 367 383 394 343 369 386 391 343 367 383

29 Osmanabad 518 366 442 380 507 355 431 369 497 354 425 368

30 Solapur 518 490 504 518 501 493 497 501 492 480 486 491

31 Satara 521 508 515 516 424 508 466 451 404 496 450 432

32 Ratnagiri 462 354 408 395 462 351 406 392 418 339 379 371

33 Sindhudurg 528 327 428 365 527 322 425 360 483 301 392 352

34 Kolhapur 481 485 483 483 450 473 461 465 419 469 444 450

35 Sangli 449 451 450 449 453 450 452 453 402 441 421 407

Maharashtra 491 453 472 477 469 449 459 462 450 434 442 444

67

Table 6.12 (U): District wise LFPR per 1000 for central, state and pooled sample Sector: Urban (Schedule 10)


PS+SS CWS CDS



(MR) Pooled


Pooled (IV)

1 Nandurbar 376 290 324 308 360 290 318 306 357 290 317 305

2 Dhule 339 304 318 304 334 304 316 304 334 303 316 303

3 Jalgaon 395 344 364 346 379 337 354 339 373 332 349 335

4 Buldhana 375 372 373 373 372 368 370 369 348 334 340 336

5 Akola 392 329 354 355 389 329 353 354 385 316 344 344

6 Washim 312 333 324 317 298 333 319 307 297 320 311 304

7 Amravati 307 344 329 317 306 344 328 316 302 334 321 311

8 Wardha 400 344 366 346 386 336 356 338 377 338 354 339

9 Nagpur 381 362 369 373 373 362 366 368 365 362 363 364

10 Bhandara 513 333 405 468 523 336 411 476 514 336 407 470

11 Gondiya 356 360 358 356 350 360 356 350 348 359 354 348

12 Gadchiroli 404 407 406 405 375 407 394 383 368 407 391 378

13 Chandrapur 376 339 354 350 371 337 351 347 367 336 349 345

14 Yavatmal 331 333 332 333 331 331 331 331 329 322 325 323

15 Nanded 296 262 276 282 296 262 276 282 296 262 276 282

16 Hingoli 416 351 377 386 406 351 373 381 406 346 370 379

17 Parbhani 299 360 336 339 275 349 320 322 270 341 312 315

18 Jalna 373 345 356 373 373 345 356 373 364 345 352 364

19 Aurangabad 341 300 316 300 330 300 312 300 327 299 310 299

20 Nashik 325 352 341 339 320 352 340 337 315 345 333 331

21 Thane 427 396 408 426 426 396 408 425 419 392 403 418 22 Mumbai 446 413 426 446 447 413 426 447 438 412 422 438

24 Raigad 369 399 387 395 367 399 386 394 356 394 379 389

25 Pune 366 376 372 371 360 375 369 366 352 372 364 361

26 Ahmednagar 330 446 400 331 330 441 396 330 325 400 370 325

27 Bid 316 301 307 309 302 301 301 301 289 298 294 293

28 Latur 229 275 257 264 229 275 257 264 227 276 256 264

29 Osmanabad 438 332 375 349 438 332 375 349 430 323 366 341

30 Solapur 440 349 385 359 433 349 382 359 426 345 378 355

31 Satara 313 408 370 372 307 405 366 368 306 406 366 366

32 Ratnagiri 337 408 380 365 337 408 380 365 337 407 379 364

33 Sindhudurg 371 306 332 319 371 298 327 311 361 295 321 306

34 Kolhapur 343 397 375 355 332 397 371 346 330 397 370 345

35 Sangli 359 356 357 356 359 356 357 356 348 353 351 352

Maharashtra 392 379 384 390 389 378 383 387 382 375 378 381

68

Table 6.13 (R): District wise RSE of estimated WPR per 1000 (PS+SS) for central, state and pooled sample



Male Female Persons



(MR) Pooled


Pooled (IV)

1 Nandurbar 0.87 6.05 4.49 0.86 2.43 2.31 2.40 1.68 0.71 1.84 1.37 0.66

2 Dhule 0.87 5.17 3.63 0.85 6.31 1.97 4.01 1.89 3.53 3.78 3.68 2.59

3 Jalgaon 2.90 9.56 7.15 2.77 0.89 5.11 4.19 0.88 0.95 7.45 5.72 0.94

4 Buldhana 2.59 1.38 2.14 1.22 5.60 9.32 7.76 4.80 4.07 5.35 4.72 3.24

5 Akola 5.54 5.95 5.74 4.08 0.35 7.59 6.74 0.35 2.96 0.43 2.11 0.43

6 Washim 0.49 0.73 0.68 0.41 0.98 9.90 9.26 0.97 0.19 4.75 4.13 0.19

7 Amravati 5.04 13.88 9.93 4.74 1.26 3.45 2.18 1.20 3.31 8.68 5.95 3.11

8 Wardha 2.00 3.25 2.77 1.70 6.83 14.14 10.83 6.16 2.58 5.88 4.57 2.37

9 Nagpur 7.68 0.11 5.46 0.11 7.85 4.07 6.83 3.63 7.76 1.70 5.88 1.66

10 Bhandara 3.63 4.21 3.95 2.75 5.08 8.26 6.26 4.47 4.35 6.08 5.19 3.55

11 Gondiya 2.36 2.38 2.37 1.68 0.34 1.03 0.67 0.33 1.04 0.71 0.91 0.59

12 Gadchiroli 1.20 3.58 2.75 1.14 1.58 8.45 6.02 1.55 0.34 5.81 4.21 0.34

13 Chandrapur 8.60 13.40 10.84 7.27 0.02 0.48 0.27 0.02 4.13 6.89 5.36 3.57

14 Yavatmal 6.57 1.13 4.94 1.11 7.46 6.48 7.51 5.06 6.95 2.73 5.89 2.56

15 Nanded 0.23 10.74 8.66 0.23 2.64 9.98 5.94 2.57 1.34 10.36 7.47 1.33

16 Hingoli 7.88 15.02 12.95 7.01 8.97 1.73 9.33 1.71 0.24 7.86 5.02 0.24

17 Parbhani 8.66 0.89 6.22 0.89 6.51 2.40 4.29 2.27 7.58 0.80 5.06 0.79

18 Jalna 5.10 6.22 5.81 3.96 8.24 10.79 9.35 7.13 1.31 8.46 5.38 1.30

19 Aurangabad 5.37 0.95 3.82 0.94 3.95 1.24 3.64 1.19 4.72 1.08 3.63 1.05

20 Nashik 1.00 2.95 2.20 0.95 5.11 2.99 4.51 2.60 3.11 2.97 3.05 2.15

21 Thane 7.52 4.54 6.44 3.89 0.18 2.22 1.41 0.17 3.64 1.03 2.89 0.99

24 Raigad 0.03 2.36 1.68 0.03 0.52 2.91 1.98 0.51 0.27 0.31 0.29 0.20

25 Pune 1.16 2.58 2.04 1.06 0.83 2.02 1.55 0.77 0.18 2.31 1.66 0.18

26 Ahmednagar 0.40 0.66 0.54 0.34 4.85 4.09 4.66 3.16 2.44 1.45 2.08 1.25

27 Bid 1.20 10.22 6.94 1.19 6.43 8.63 7.37 5.21 2.34 9.47 6.42 2.27

69


Male Female Persons



(MR) Pooled


Pooled (IV)

28 Latur 0.50 2.31 1.69 0.49 2.73 7.33 4.72 2.59 1.03 2.69 1.94 0.96

29 Osmanabad 2.86 5.37 4.13 2.53 4.38 2.32 4.52 2.13 3.65 1.68 3.18 1.54

30 Solapur 1.37 7.92 5.51 1.35 0.14 1.69 1.17 0.14 0.63 4.82 3.34 0.62

31 Satara 2.15 0.23 1.60 0.23 2.60 5.85 4.57 2.38 2.37 2.87 2.63 1.83

32 Ratnagiri 2.87 3.33 3.08 2.18 7.61 7.05 7.64 5.30 5.34 5.38 5.40 3.82

33 Sindhudurg 2.00 1.40 1.81 1.15 2.83 5.19 3.52 3.08 2.38 1.86 2.34 1.51

34 Kolhapur 3.62 5.26 4.62 2.99 8.23 2.93 6.74 2.77 5.98 4.14 5.14 3.41

35 Sangli 1.47 6.81 4.69 1.43 2.29 1.85 2.06 1.44 1.90 4.38 3.38 1.74

Maharashtra 0.70 1.16 0.95 0.60 0.83 1.01 0.91 0.64 0.65 0.93 0.79 0.53

70

Table 6.13 (U): District wise RSE of estimated WPR per 1000 (PS+SS) for central, state and pooled sample



Male Female Persons



(MR) Pooled


Pooled (IV)

1 Nandurbar 7.50 3.66 3.34 3.29 0.59 2.71 5.60 0.72 4.78 3.20 3.98 2.68 2 Dhule 14.96 0.25 3.26 0.25 15.36 0.88 6.67 0.88 15.13 0.54 4.03 0.54 3 Jalgaon 15.04 1.88 3.06 1.86 11.80 5.36 6.00 4.89 13.51 3.54 3.79 3.42 4 Buldhana 6.64 9.13 2.98 5.37 9.24 1.78 5.54 1.75 7.93 3.34 3.73 3.08 5 Akola 14.21 13.75 3.05 9.95 8.53 8.53 6.57 6.29 11.37 11.36 3.87 8.09 6 Washim 10.81 13.05 3.25 8.37 1.24 7.18 6.48 1.22 6.66 10.11 4.04 5.57 7 Amravati 4.99 3.82 3.12 3.03 2.76 8.12 7.71 2.65 3.96 5.90 4.01 3.29 8 Wardha 8.11 1.90 3.10 1.85 9.05 5.64 5.49 4.86 8.56 1.92 3.81 1.88 9 Nagpur 1.10 1.17 3.06 0.80 0.65 0.90 5.93 0.53 0.86 1.03 3.82 0.66

10 Bhandara 1.67 6.69 3.11 1.63 6.22 13.98 4.30 6.52 3.87 10.37 3.57 3.70 11 Gondiya 3.26 2.59 3.15 2.03 4.21 7.85 6.45 3.72 0.09 5.20 3.94 0.09 12 Gadchiroli 2.12 1.99 2.92 1.45 2.84 8.66 5.05 2.70 2.46 3.80 3.61 2.07 13 Chandrapur 7.26 2.74 2.94 2.57 9.87 8.98 6.26 6.78 8.62 6.05 3.83 4.96 14 Yavatmal 13.77 5.07 3.19 4.76 11.72 5.98 6.16 5.34 12.79 5.51 3.96 5.06 15 Nanded 8.36 13.23 3.34 7.09 10.13 11.10 8.84 7.50 9.22 12.18 4.37 7.37 16 Hingoli 13.90 19.66 3.00 11.42 13.94 15.87 6.19 10.54 13.92 17.91 3.73 11.06 17 Parbhani 4.21 7.32 3.17 3.66 8.85 0.44 6.45 0.44 6.56 3.90 4.02 3.37 18 Jalna 1.05 16.18 3.03 1.04 2.68 7.73 6.73 2.65 0.84 12.31 3.85 0.84 19 Aurangabad 17.74 0.31 3.21 0.31 18.69 0.48 6.33 0.48 18.25 0.40 4.06 0.40 20 Nashik 4.55 4.03 3.23 3.02 4.78 2.56 5.96 2.26 3.87 3.35 3.94 2.53 21 Thane 5.92 33.80 2.95 5.84 5.14 35.28 5.85 5.09 5.52 34.46 3.62 5.45 22 Mumbai 0.15 10.40 2.91 0.15 0.73 6.11 5.59 0.72 0.25 8.51 3.54 0.25 24 Raigad 16.73 3.01 2.93 2.96 13.41 7.90 6.68 6.99 15.34 5.49 3.71 5.17 25 Pune 2.68 3.59 3.08 2.15 4.07 3.05 6.04 2.47 3.13 3.32 3.80 2.28 26 Ahmednagar 2.73 15.76 3.23 2.69 5.40 16.79 4.69 5.22 1.39 16.22 3.74 1.38 27 Bid 5.14 8.13 3.17 4.35 7.38 6.01 7.91 4.78 6.33 7.08 4.21 4.73

71


Male Female Persons



(MR) Pooled


Pooled (IV)

28 Latur 4.49 1.90 3.41 1.75 2.81 1.53 11.12 1.38 3.66 1.74 4.54 1.57 29 Osmanabad 5.74 6.93 2.99 4.44 10.99 2.61 5.63 2.56 8.54 4.93 3.73 4.29 30 Solapur 4.68 5.97 3.11 3.69 11.78 1.66 4.61 1.65 8.37 3.89 3.65 3.54

31 Satara 30.99 17.33 3.11 15.15 29.85 19.03 5.94 17.73 30.46 18.13 3.83 15.70 32 Ratnagiri 20.42 20.40 3.18 14.44 23.09 25.09 5.66 17.28 21.76 22.65 3.90 15.74 33 Sindhudurg 4.95 5.22 3.18 3.60 7.68 12.55 6.94 6.64 6.19 3.65 4.02 3.15 34 Kolhapur 4.48 7.10 3.00 3.80 2.80 4.37 6.18 2.36 3.67 5.79 3.77 3.11 35 Sangli 12.36 1.79 3.10 1.78 8.88 5.54 6.39 4.71 10.67 3.52 3.88 3.35

Maharashtra 1.52 4.41 3.02 1.44 1.53 2.44 5.89 1.30 1.49 3.49 3.73 1.37

72

Table 6.14 (R): District wise RSE of LFPR for central, state and pooled sample



PS+SS CWS CDS



(MR) Pooled


Pooled (IV)


10 Bhandara 4.35 6.08 3.70 3.54 4.35 6.08 3.73 3.54 4.35 6.08 3.73 3.54 11 Gondiya 1.04 0.71 0.64 0.59 1.04 0.71 0.63 0.59 1.04 0.91 0.69 0.69 12 Gadchiroli 0.34 5.81 2.97 0.34 0.34 5.81 3.09 0.34 0.34 5.80 3.14 0.34 13 Chandrapur 4.13 6.89 3.79 3.57 4.13 6.89 3.81 3.56 4.13 6.88 3.81 3.56 14 Yavatmal 6.95 2.73 4.17 2.56 6.95 2.73 4.17 2.56 6.95 2.74 4.26 2.56 15 Nanded 1.34 10.36 5.30 1.33 1.34 10.36 5.27 1.33 1.34 10.37 5.28 1.33 16 Hingoli 0.24 7.86 3.54 0.24 0.23 7.85 3.79 0.23 0.23 7.70 3.62 0.23 17 Parbhani 7.58 0.80 3.60 0.79 7.58 0.80 3.64 0.79 7.58 0.16 3.69 0.16 18 Jalna 1.31 8.46 3.81 1.30 1.31 8.46 3.89 1.30 1.31 8.46 4.19 1.29 19 Aurangabad 4.72 1.08 2.57 1.05 4.72 1.08 2.54 1.05 4.72 1.07 2.50 1.04 20 Nashik 3.11 2.97 2.15 2.15 3.11 2.97 2.15 2.15 3.11 2.97 2.15 2.15 21 Thane 3.65 1.03 2.00 0.99 3.64 1.03 1.98 0.99 3.64 1.03 1.98 0.99 24 Raigad 0.27 0.31 0.21 0.21 0.27 0.31 0.21 0.20 0.27 0.25 0.18 0.18 25 Pune 0.18 2.31 1.16 0.18 0.18 2.31 1.16 0.18 0.18 2.31 1.16 0.18 26 Ahmednagar 2.44 1.45 1.47 1.25 2.44 1.45 1.45 1.25 2.44 1.45 1.46 1.25 27 Bid 2.34 9.47 4.55 2.27 2.34 9.47 4.58 2.27 2.34 9.48 4.67 2.27 28 Latur 1.03 2.69 1.37 0.96 1.03 2.69 1.36 0.96 1.03 2.69 1.37 0.96

73


PS+SS CWS CDS



(MR) Pooled


Pooled (IV)

29 Osmanabad 3.65 1.68 2.25 1.54 3.65 1.68 2.26 1.54 3.65 1.68 2.24 1.53 30 Solapur 0.63 4.82 2.36 0.62 0.63 4.82 2.41 0.62 0.63 4.84 2.41 0.62 31 Satara 2.37 2.87 1.86 1.83 2.37 2.87 1.90 1.84 2.37 2.87 1.91 1.84 32 Ratnagiri 5.34 5.38 3.82 3.82 5.34 5.38 3.82 3.82 5.34 5.39 3.81 3.81 33 Sindhudurg 2.38 1.86 1.63 1.50 2.38 1.86 1.64 1.50 2.38 2.40 1.73 1.73 34 Kolhapur 5.98 4.14 3.63 3.41 5.98 4.14 3.61 3.41 5.99 4.14 3.57 3.41 35 Sangli 1.90 4.38 2.39 1.74 1.90 4.38 2.38 1.74 1.90 4.41 2.48 1.74

Maharashtra 0.65 0.93 0.56 0.53 0.65 0.93 0.56 0.53 0.65 0.93 0.56 0.53

74

Table 6.14 (U): District wise RSE of LFPR for central, state and pooled sample



PS+SS CWS CDS



(MR) Pooled


Pooled (IV)


10 Bhandara 3.87 10.37 12.93 3.68 3.88 10.37 12.88 3.68 3.88 10.37 5.50 3.68 11 Gondiya 0.10 5.19 7.82 0.10 0.10 5.19 7.88 0.10 0.10 4.89 2.97 0.10 12 Gadchiroli 2.46 3.80 5.80 2.07 2.46 3.80 5.96 2.07 2.46 3.80 2.55 2.07 13 Chandrapur 8.62 6.05 9.44 4.96 8.62 6.05 9.45 4.96 8.62 6.02 5.03 4.94 14 Yavatmal 12.79 5.51 9.73 5.06 12.79 5.51 9.72 5.06 12.79 5.64 6.17 5.16 15 Nanded 9.22 12.18 17.81 7.36 9.22 12.18 17.81 7.36 9.22 12.18 7.99 7.36 16 Hingoli 13.92 17.91 25.76 11.03 13.92 17.91 25.98 11.02 13.92 17.89 11.75 11.02 17 Parbhani 6.56 3.90 6.70 3.36 6.57 3.90 6.77 3.37 6.57 3.88 3.41 3.36 18 Jalna 0.84 12.31 17.89 0.84 0.84 12.31 17.88 0.84 0.84 12.31 7.23 0.84 19 Aurangabad 18.26 0.40 7.90 0.40 18.26 0.40 7.75 0.40 18.26 0.40 7.70 0.40 20 Nashik 3.87 3.35 5.40 2.53 3.87 3.35 5.42 2.54 3.87 3.37 2.56 2.54 21 Thane 5.52 34.46 50.18 5.45 5.52 34.46 50.25 5.45 5.52 34.47 20.26 5.45 22 Mumbai 0.25 8.51 12.36 0.25 0.25 8.51 12.35 0.25 0.25 8.50 4.97 0.25 24 Raigad 15.34 5.49 10.31 5.17 15.34 5.49 10.32 5.17 15.34 5.43 6.69 5.12 25 Pune 3.13 3.32 5.18 2.28 3.13 3.32 5.21 2.28 3.13 3.32 2.37 2.28 26 Ahmednagar 1.39 16.22 27.15 1.38 1.39 16.22 27.06 1.38 1.39 16.31 10.59 1.38

75


PS+SS CWS CDS



(MR) Pooled


Pooled (IV)

27 Bid 6.33 7.09 10.74 4.72 6.33 7.09 10.92 4.72 6.33 7.09 4.97 4.72 28 Latur 3.66 1.74 3.09 1.57 3.66 1.74 3.09 1.57 3.65 1.68 1.69 1.53 29 Osmanabad 8.55 4.93 7.68 4.29 8.55 4.93 7.68 4.29 8.55 5.05 4.83 4.37 30 Solapur 8.37 3.89 6.52 3.54 8.37 3.89 6.53 3.54 8.37 3.91 4.34 3.55 31 Satara 30.46 18.13 31.72 15.70 30.45 18.13 31.79 15.71 30.45 18.50 15.98 15.95 32 Ratnagiri 21.75 22.65 37.32 15.76 21.75 22.65 37.32 15.76 21.75 22.65 16.52 15.76 33 Sindhudurg 6.18 3.65 5.75 3.15 6.18 3.65 5.72 3.15 6.18 3.46 3.37 3.03 34 Kolhapur 3.67 5.79 9.29 3.11 3.67 5.79 9.39 3.11 3.67 5.79 3.95 3.11 35 Sangli 10.67 3.53 6.79 3.35 10.67 3.53 6.79 3.35 10.67 3.53 4.74 3.35

Maharashtra 1.49 3.49 5.19 1.37 1.49 3.49 5.21 1.37 1.49 3.49 2.16 1.37

76

DETAILED TABLES

Table 21: Per thousand distribution of persons by usual activity category taking also into consideration the subsidiary economic status of persons categorized 'not working' in the principal status.

STATE: MAHARASHTRA Sector = Rural Pooled sample Male

District code

District Name

per thousand distribution of persons(PS+SS) Estimated persons(00)(PS+SS)

11-21 31 41 & 51 11-51 81 11-81 91-99 all 11-21 31 41 & 51 11-51 81 11-81 91-99 11-99

1 Nandurbar 369 17 219 605 0 605 395 1000 1841 86 1091 3018 0 3018 1967 4985 2 Dhule 260 62 235 557 0 557 443 1000 1811 435 1636 3882 0 3882 3083 6964 3 Jalgaon 241 64 267 573 1 574 426 1000 3108 825 3443 7376 18 7394 5484 12878 4 Buldhana 241 38 276 555 6 561 439 1000 2520 400 2888 5808 65 5872 4593 10465 5 Akola 167 36 406 609 5 615 385 1000 777 166 1886 2829 25 2854 1789 4642 6 Washim 151 42 355 548 0 548 452 1000 742 207 1748 2697 0 2697 2227 4923 7 Amravati 281 19 316 616 1 617 383 1000 2347 159 2638 5144 8 5153 3197 8350 8 Wardha 235 73 277 584 0 584 416 1000 899 278 1061 2237 0 2237 1595 3832 9 Nagpur 254 86 219 559 2 562 438 1000 1822 619 1570 4012 17 4029 3143 7172 10 Bhandara 186 16 417 619 24 642 358 1000 868 75 1951 2894 111 3006 1674 4679 11 Gondiya 313 58 229 600 22 622 378 1000 1576 295 1153 3023 109 3132 1903 5035 12 Gadchiroli 200 35 392 627 2 629 371 1000 883 154 1729 2766 8 2774 1639 4413 13 Chandrapur 260 40 356 655 0 655 345 1000 1798 274 2465 4537 0 4537 2389 6926 14 Yavatmal 220 49 317 585 1 586 414 1000 2419 535 3485 6438 10 6449 4556 11005 15 Nanded 333 32 154 519 0 519 481 1000 3586 346 1656 5588 1 5589 5181 10770 16 Hingoli 232 30 256 518 1 519 481 1000 1094 142 1209 2444 4 2448 2270 4717 17 Parbhani 393 9 172 574 5 579 421 1000 2107 47 923 3077 27 3104 2257 5361 18 Jalna 278 46 222 546 0 546 454 1000 2082 342 1666 4090 0 4090 3399 7490 19 Aurangabad 270 48 256 574 6 580 420 1000 2887 510 2734 6131 63 6194 4491 10685 20 Nashik 349 58 180 586 0 587 413 1000 4516 746 2325 7587 2 7589 5349 12938 21 Thane 170 150 238 559 16 575 425 1000 2173 1922 3047 7142 204 7346 5433 12780 24 Raigad 210 132 194 537 11 548 452 1000 1640 1033 1517 4190 88 4278 3527 7806

77

District

code

District Name


11-21 31 41 & 51 11-51 81 11-81 91-99 all 11-21 31 41 & 51 11-51 81 11-81 91-99 11-99

25 Pune 313 106 200 619 15 634 366 1000 4830 1630 3087 9546 239 9785 5640 15424 26 Ahmednagar 262 44 170 476 9 485 515 1000 4668 786 3029 8482 153 8635 9171 17806 27 Bid 382 20 192 594 0 594 406 1000 3976 207 2002 6185 0 6185 4231 10416 28 Latur 318 45 176 539 0 539 461 1000 3021 423 1675 5119 0 5119 4376 9494 29 Osmanabad 348 43 204 596 0 596 404 1000 1957 243 1149 3348 1 3349 2268 5617 30 Solapur 292 76 220 587 1 588 412 1000 3777 979 2852 7608 13 7620 5330 12950 31 Satara 337 107 155 599 10 609 391 1000 3746 1185 1723 6654 113 6767 4348 11115 32 Ratnagiri 350 33 187 570 2 572 428 1000 2087 197 1110 3394 11 3405 2549 5954 33 Sindhudurg 347 31 212 589 18 608 392 1000 1307 115 796 2218 69 2288 1476 3763 34 Kolhapur 336 92 171 599 8 607 393 1000 4231 1153 2159 7544 98 7642 4954 12596 35 Sangli 356 81 131 567 1 568 432 1000 3788 858 1393 6039 12 6051 4599 10649

Maharashtra 284 61 228 573 5 578 422 1000 80884 17370 64793 163047 1469 164516 120084 284600

(Activity status codes as per Annexure 3)

78


STATE: MAHARASHTRA Sector = Rural Pooled sample Female

District code

District Name


11-21 31 41 & 51 11-51 81 11-81 91-

99 all 11-21 31 41 & 51 11-51 81 11-81 91-99 11-99

1 Nandurbar 347 4 192 544 0 544 456 1000 1673 19 925 2617 0 2617 2197 4814 2 Dhule 213 14 212 439 0 439 561 1000 1275 82 1270 2626 0 2626 3362 5989 3 Jalgaon 168 5 265 437 0 437 563 1000 2120 61 3350 5531 5 5536 7122 12657 4 Buldhana 173 3 240 416 0 417 583 1000 1778 31 2474 4283 4 4287 6004 10292 5 Akola 23 7 244 274 4 278 722 1000 101 28 1057 1187 17 1204 3130 4334

6 Washim 24 3 213 241 0 241 759 1000 113 15 997 1125 0 1125 3550 4675

7 Amravati 126 6 237 369 0 369 631 1000 968 44 1825 2837 0 2837 4848 7685 8 Wardha 148 2 276 425 1 426 574 1000 618 9 1153 1780 2 1782 2401 4183 9 Nagpur 168 5 186 359 10 369 631 1000 926 25 1028 1979 55 2034 3481 5516

10 Bhandara 80 4 323 407 3 409 591 1000 351 17 1420 1788 11 1800 2595 4395 11 Gondiya 245 30 209 484 4 488 512 1000 1178 143 1006 2327 20 2347 2465 4812 12 Gadchiroli 116 5 398 519 0 519 481 1000 523 24 1795 2342 0 2342 2166 4508 13 Chandrapur 87 4 319 410 0 410 590 1000 631 31 2321 2983 0 2983 4296 7280 14 Yavatmal 79 13 276 368 2 370 630 1000 769 129 2681 3580 17 3597 6128 9725 15 Nanded 106 1 164 272 3 275 725 1000 1047 14 1614 2675 33 2708 7125 9832 16 Hingoli 80 3 154 238 0 238 762 1000 402 16 770 1187 0 1187 3810 4997 17 Parbhani 214 2 160 375 0 375 625 1000 1183 8 885 2076 0 2076 3457 5533 18 Jalna 186 0 200 386 0 386 614 1000 1323 0 1422 2745 0 2745 4359 7104 19 Aurangabad 154 2 149 305 0 305 695 1000 1379 18 1336 2732 2 2734 6219 8953 20 Nashik 173 20 169 362 0 362 638 1000 2137 241 2090 4469 0 4469 7869 12338 21 Thane 137 22 102 262 9 270 730 1000 1835 296 1372 3504 116 3620 9768 13388 24 Raigad 171 14 103 288 0 288 712 1000 1353 107 815 2275 2 2278 5627 7905 25 Pune 259 5 130 394 1 395 605 1000 3884 81 1941 5905 13 5918 9068 14986

79

District

code

District Name


11-21 31 41 & 51 11-51 81 11-81 91-

99 all 11-21 31 41 & 51 11-51 81 11-81 91-99 11-99

26 Ahmednagar 197 8 221 426 1 427 573 1000 2889 113 3248 6249 19 6268 8407 14674 27 Bid 151 12 164 327 2 328 672 1000 1374 109 1496 2978 15 2993 6123 9116 28 Latur 64 4 123 192 0 192 808 1000 597 41 1144 1781 0 1781 7514 9296 29 Osmanabad 138 9 148 294 1 295 705 1000 776 48 836 1660 4 1664 3979 5643 30 Solapur 228 23 166 417 0 417 583 1000 2888 287 2105 5280 1 5282 7389 12671 31 Satara 286 21 104 411 5 416 584 1000 2998 225 1089 4311 51 4362 6135 10497 32 Ratnagiri 194 3 66 263 0 263 737 1000 1336 19 456 1811 1 1813 5084 6896 33 Sindhudurg 177 5 53 235 1 236 764 1000 598 17 180 795 3 798 2586 3384 34 Kolhapur 251 9 94 355 3 357 643 1000 3128 117 1172 4417 34 4451 8006 12457 35 Sangli 239 6 89 334 0 334 666 1000 2591 63 969 3623 0 3623 7237 10861 Maharashtra 172 9 178 359 2 361 639 1000 46742 2478 48240 97461 426 97887 173508 271395


80


STATE: MAHARASHTRA Sector = Rural Pooled sample Persons

District code

District Name


11-21 31 41 & 51 11-51 81 11-81 91-

99 all 11-21 31 41 & 51 11-51 81 11-81 91-99 11-99

1 Nandurbar 359 11 206 575 0 575 425 1000 3513 104 2017 5634 0 5635 4164 9798 2 Dhule 238 40 224 502 0 502 498 1000 3086 516 2906 6508 0 6508 6445 12953 3 Jalgaon 205 35 266 505 1 506 494 1000 5229 886 6792 12907 23 12929 12606 25535 4 Buldhana 207 21 258 486 3 489 511 1000 4298 432 5361 10091 69 10160 10597 20757 5 Akola 98 22 328 447 5 452 548 1000 879 194 2943 4016 42 4058 4918 8976 6 Washim 89 23 286 398 0 398 602 1000 855 222 2745 3821 0 3821 5777 9598 7 Amravati 207 13 278 498 1 498 502 1000 3315 203 4464 7981 8 7990 8045 16035 8 Wardha 189 36 276 501 0 501 499 1000 1517 287 2213 4017 2 4020 3996 8015 9 Nagpur 217 51 205 472 6 478 522 1000 2748 644 2598 5991 73 6063 6624 12688

10 Bhandara 134 10 371 516 14 530 470 1000 1220 92 3371 4683 123 4805 4269 9074 11 Gondiya 280 44 219 543 13 556 444 1000 2754 438 2159 5350 129 5479 4368 9847 12 Gadchiroli 158 20 395 573 1 573 427 1000 1406 178 3524 5107 8 5116 3805 8921 13 Chandrapur 171 21 337 529 0 529 471 1000 2429 305 4787 7520 0 7520 6685 14205 14 Yavatmal 154 32 297 483 1 485 515 1000 3188 664 6166 10018 28 10046 10683 20730 15 Nanded 225 17 159 401 2 403 597 1000 4633 360 3270 8263 34 8296 12306 20602 16 Hingoli 154 16 204 374 0 374 626 1000 1495 157 1979 3631 4 3635 6079 9714 17 Parbhani 302 5 166 473 2 475 525 1000 3290 55 1808 5152 27 5179 5714 10893 18 Jalna 233 23 212 468 0 468 532 1000 3405 342 3088 6836 0 6836 7758 14594 19 Aurangabad 217 27 207 451 3 455 545 1000 4266 528 4070 8863 65 8928 10710 19638 20 Nashik 263 39 175 477 0 477 523 1000 6653 987 4416 12056 2 12058 13218 25276 21 Thane 153 85 169 407 12 419 581 1000 4008 2218 4419 10646 320 10966 15202 26168 24 Raigad 191 73 148 412 6 417 583 1000 2994 1140 2332 6466 90 6556 9155 15710

81

District code

District Name


11-21 31 41 & 51 11-51 81 11-81 91-

99 all 11-21 31 41 & 51 11-51 81 11-81 91-99 11-99

25 Pune 287 56 165 508 8 516 484 1000 8713 1711 5028 15452 251 15703 14707 30410 26 Ahmednagar 233 28 193 454 5 459 541 1000 7556 899 6276 14731 172 14903 17578 32481 27 Bid 274 16 179 469 1 470 530 1000 5349 316 3498 9163 15 9178 10354 19532 28 Latur 193 25 150 367 0 367 633 1000 3618 463 2819 6900 0 6900 11890 18790 29 Osmanabad 243 26 176 445 0 445 555 1000 2733 291 1984 5008 5 5013 6246 11260 30 Solapur 260 49 193 503 1 504 496 1000 6665 1267 4956 12888 14 12902 12719 25621 31 Satara 312 65 130 507 8 515 485 1000 6743 1409 2812 10964 165 11129 10483 21612 32 Ratnagiri 266 17 122 405 1 406 594 1000 3423 215 1567 5205 13 5218 7633 12850 33 Sindhudurg 267 18 137 422 10 432 568 1000 1905 132 976 3014 72 3086 4062 7147 34 Kolhapur 294 51 133 477 5 483 517 1000 7359 1270 3332 11961 132 12093 12960 25053 35 Sangli 297 43 110 449 1 450 550 1000 6380 921 2361 9662 12 9674 11836 21510 Maharashtra 230 36 203 469 3 472 528 1000 127626 19848 113034 260508 1895 262403 293592 555995


82


STATE: MAHARASHTRA Sector = Urban Pooled Sample Male

District code

District Name


11-21 31 41 & 51 11-51 81 11-81 91-

99 all 11-21 31 41 & 51 11-51 81 11-81 91-99 11-99


10 Bhandara 234 188 106 529 15 544 456 1000 140 112 64 316 9 325 273 599 11 Gondiya 215 211 97 522 25 547 453 1000 166 163 75 403 20 423 349 772 12 Gadchiroli 196 303 111 609 13 622 378 1000 58 90 33 181 4 185 112 297 13 Chandrapur 188 229 182 600 2 603 397 1000 493 600 477 1570 6 1576 1039 2615 14 Yavatmal 225 148 137 510 1 511 489 1000 570 376 348 1293 3 1296 1239 2535 15 Nanded 208 138 119 465 13 478 522 1000 734 488 421 1643 46 1690 1845 3535 16 Hingoli 251 158 143 552 3 555 445 1000 249 157 142 548 3 551 442 993 17 Parbhani 216 105 199 520 17 537 463 1000 482 235 443 1159 38 1197 1031 2228 18 Jalna 143 187 226 556 18 574 426 1000 267 350 422 1039 34 1073 796 1869 19 Aurangabad 164 251 86 501 7 508 492 1000 982 1498 513 2993 40 3033 2943 5976 20 Nashik 166 191 146 503 6 509 491 1000 1351 1557 1190 4098 47 4145 4005 8150 21 Thane 168 400 26 594 16 611 389 1000 6609 15731 1022 23362 640 24001 15306 39307 22 Mumbai 225 367 23 615 14 630 370 1000 13808 22495 1387 37691 875 38566 22677 61243 24 Raigad 185 373 47 604 10 614 386 1000 649 1310 166 2125 34 2159 1356 3515 25 Pune 173 322 54 548 15 563 437 1000 4616 8579 1430 14625 396 15022 11649 26671 26 Ahmednagar 235 140 123 498 35 533 467 1000 1010 601 527 2139 150 2289 2006 4295

83

District code

District Name


11-21 31 41 & 51 11-51 81 11-81 91-

99 all 11-21 31 41 & 51 11-51 81 11-81 91-99 11-99

27 Bid 194 175 132 501 22 523 477 1000 369 334 251 954 43 997 908 1904 28 Latur 231 115 107 453 0 453 547 1000 626 311 291 1227 0 1227 1481 2707 29 Osmanabad 265 116 181 562 10 571 429 1000 289 127 197 612 10 623 467 1090 30 Solapur 211 202 119 532 6 538 462 1000 1140 1090 641 2870 33 2903 2495 5399 31 Satara 307 165 69 542 13 554 446 1000 771 414 174 1360 32 1392 1119 2511 32 Ratnagiri 290 195 43 528 60 588 412 1000 367 247 54 668 76 744 522 1266 33 Sindhudurg 252 165 95 512 33 545 455 1000 77 50 29 156 10 166 139 304 34 Kolhapur 311 198 89 598 5 602 398 1000 1568 996 449 3013 23 3035 2004 5039 35 Sangli 248 199 90 537 22 559 441 1000 794 635 288 1716 69 1785 1410 3195 Maharashtra 208 295 66 569 14 583 417 1000 45479 64491 14396 124366 3039 127406 91246 218651


84

Table 21: Per thousand distribution of persons by usual activity category taking also into consideration the subsidiary economic status

of persons categorized 'not working' in the principal status.

STATE: MAHARASHTRA Sector = Urban Pooled Sample Female

District code District Name


11-21 31 41 & 51 11-51 81 11-81 91-99 all 11-21 31 41 &

51 11-51 81 11-81 91-99 11-99


10 Bhandara 96 26 130 252 16 268 732 1000 56 15 77 149 9 158 432 590 11 Gondiya 39 21 65 125 20 145 855 1000 27 15 45 86 14 100 588 687 12 Gadchiroli 94 39 71 205 0 205 795 1000 30 12 23 66 0 66 255 320 13 Chandrapur 35 59 33 127 4 131 869 1000 103 172 97 371 12 384 2535 2919 14 Yavatmal 38 38 62 138 1 139 861 1000 90 89 146 324 1 326 2020 2346 15 Nanded 25 12 29 67 0 67 933 1000 85 42 97 224 0 224 3128 3352 16 Hingoli 82 21 26 129 25 154 846 1000 70 18 23 111 21 132 722 854 17 Parbhani 45 13 68 126 0 126 874 1000 101 30 151 282 0 282 1950 2233 18 Jalna 4 28 61 92 3 95 905 1000 6 45 99 150 5 155 1477 1631 19 Aurangabad 42 51 37 130 2 132 868 1000 255 305 220 781 14 795 5230 6025 20 Nashik 49 51 48 148 3 151 849 1000 347 358 338 1044 21 1065 6009 7073 21 Thane 45 100 7 153 12 164 836 1000 1477 3247 234 4957 374 5332 27148 32480 22 Mumbai 42 117 4 162 12 174 826 1000 2072 5730 175 7977 586 8564 40565 49129

85



11-21 31 41 & 51 11-51 81 11-81 91-99 all 11-21 31 41 &

51 11-51 81 11-81 91-99 11-99

24 Raigad 44 65 12 122 3 125 875 1000 137 201 38 376 10 386 2705 3092 25 Pune 57 75 15 148 5 153 847 1000 1324 1740 352 3416 110 3526 19580 23106 26 Ahmednagar 136 65 54 255 3 258 742 1000 506 244 202 952 10 961 2771 3732 27 Bid 25 45 5 76 19 94 906 1000 50 88 10 148 37 185 1775 1959 28 Latur 11 17 17 45 0 45 955 1000 26 40 42 108 0 108 2312 2420 29 Osmanabad 85 10 49 144 2 146 854 1000 87 10 50 148 3 150 878 1028 30 Solapur 90 93 53 237 0 237 763 1000 483 499 285 1268 0 1268 4090 5358 31 Satara 69 49 34 152 0 152 848 1000 154 109 75 337 0 337 1884 2221 32 Ratnagiri 98 75 7 181 9 189 811 1000 116 89 9 213 10 224 956 1180 33 Sindhudurg 27 63 14 105 0 105 895 1000 8 18 4 29 0 29 249 279 34 Kolhapur 69 43 20 133 5 138 862 1000 319 201 92 612 24 636 3978 4614 35 Sangli 56 29 44 128 2 130 870 1000 159 82 124 364 5 369 2469 2838

Maharashtra 51 76 22 149 8 157 843 1000 9591 14500 4216 28307 1470 29777 160093 189870


86


STATE: MAHARASHTRA Sector = Urban Pooled Sample Persons



11-21 31 41 & 51 11-51 81 11-81 91-99 all 11-21 31 41 &

51 11-51 81 11-81 91-99 11-99


10 Bhandara 165 108 118 391 15 407 593 1000 197 128 141 465 18 483 705 1189 11 Gondiya 132 121 82 335 23 358 642 1000 193 177 119 489 33 522 937 1459 12 Gadchiroli 143 166 90 399 6 406 594 1000 89 102 56 247 4 251 367 618 13 Chandrapur 108 139 104 351 3 354 646 1000 596 771 574 1941 18 1959 3575 5534 14 Yavatmal 135 95 101 331 1 332 668 1000 660 465 493 1618 5 1622 3260 4882 15 Nanded 119 77 75 271 7 278 722 1000 819 530 518 1867 46 1914 4973 6887 16 Hingoli 172 95 89 357 13 370 630 1000 318 176 164 658 24 682 1164 1847 17 Parbhani 131 59 133 323 9 332 668 1000 583 265 594 1441 38 1479 2982 4461 18 Jalna 78 113 149 340 11 351 649 1000 273 395 521 1189 38 1228 2273 3500 19 Aurangabad 103 150 61 314 5 319 681 1000 1237 1803 733 3773 55 3828 8173 12002 20 Nashik 112 126 100 338 4 342 658 1000 1698 1915 1528 5142 68 5210 10013 15223 21 Thane 113 264 17 394 14 409 591 1000 8086 18977 1256 28319 1014 29333 42454 71787 22 Mumbai 144 256 14 414 13 427 573 1000 15881 28225 1563 45668 1461 47130 63242 110372 24 Raigad 119 229 31 379 7 385 615 1000 786 1511 204 2501 44 2545 4062 6607 25 Pune 119 207 36 362 10 373 627 1000 5940 10319 1782 18041 506 18547 31229 49776

87



11-21 31 41 & 51 11-51 81 11-81 91-99 all 11-21 31 41 &

51 11-51 81 11-81 91-99 11-99

26 Ahmednagar 189 105 91 385 20 405 595 1000 1516 846 729 3091 160 3251 4777 8028 27 Bid 108 109 68 285 20 306 694 1000 419 422 261 1102 79 1181 2683 3864 28 Latur 127 68 65 260 0 260 740 1000 652 351 333 1335 0 1335 3792 5127 29 Osmanabad 177 65 117 359 6 365 635 1000 376 137 247 760 13 773 1345 2118 30 Solapur 151 148 86 385 3 388 612 1000 1623 1589 926 4138 33 4171 6586 10757 31 Satara 195 111 53 359 7 365 635 1000 925 523 249 1697 32 1730 3003 4732 32 Ratnagiri 198 137 26 360 35 396 604 1000 483 336 63 882 86 968 1478 2446 33 Sindhudurg 144 116 56 317 17 334 666 1000 84 68 33 185 10 195 388 583 34 Kolhapur 196 124 56 375 5 380 620 1000 1887 1197 540 3624 47 3671 5982 9653 35 Sangli 158 119 68 345 12 357 643 1000 952 717 412 2080 74 2154 3879 6033

Maharashtra 135 193 46 374 11 385 615 1000 55070 78992 18613 152674 4509 157183 251339 408521


88



STATE: MAHARASHTRA Sector = Combined Pooled Sample Male



11-21 31 41 & 51 11-51 81 11-81 91-99 all 11-21 31 41 &

51 11-51 81 11-81 91-99 11-99


10 Bhandara 191 35 382 608 23 631 369 1000 1009 187 2015 3211 120 3331 1947 5278 11 Gondiya 300 79 211 590 22 612 388 1000 1742 457 1227 3426 128 3555 2253 5807 12 Gadchiroli 200 52 374 626 3 628 372 1000 941 244 1762 2947 12 2959 1751 4710 13 Chandrapur 240 92 308 640 1 641 359 1000 2291 873 2942 6107 6 6113 3428 9541 14 Yavatmal 221 67 283 571 1 572 428 1000 2988 911 3832 7732 14 7745 5795 13540 15 Nanded 302 58 145 506 3 509 491 1000 4320 834 2077 7232 47 7278 7027 14305 16 Hingoli 235 52 237 524 1 525 475 1000 1342 299 1351 2992 7 2999 2712 5710 17 Parbhani 341 37 180 558 9 567 433 1000 2589 281 1366 4236 65 4301 3288 7589 18 Jalna 251 74 223 548 4 552 448 1000 2350 692 2088 5130 34 5163 4196 9359 19 Aurangabad 232 121 195 548 6 554 446 1000 3869 2008 3247 9124 103 9227 7434 16661 20 Nashik 278 109 167 554 2 556 444 1000 5867 2303 3515 11685 50 11734 9353 21088 21 Thane 169 339 78 586 16 602 398 1000 8782 17653 4069 30504 844 31348 20739 52087 22 Mumbai 225 367 23 615 14 630 370 1000 13808 22495 1387 37691 875 38566 22677 61243 24 Raigad 202 207 149 558 11 569 431 1000 2289 2343 1683 6315 122 6437 4884 11321

89



11-21 31 41 & 51 11-51 81 11-81 91-99 all 11-21 31 41 &

51 11-51 81 11-81 91-99 11-99


Maharashtra 251 163 157 571 9 580 420 1000 126362 81861 79190 287413 4509 291922 211329 503251


90


STATE: MAHARASHTRA Sector = Combined Pooled Sample Female



11-21 31 41 & 51 11-51 81 11-81 91-99 all 11-21 31 41 &

51 11-51 81 11-81 91-99 11-99



91



Maharashtra 122 37 114 273 4 277 723 1000 56333 16978 52457 125768 1896 127664 333601 461265

92



STATE: MAHARASHTRA Sector = Combined Pooled Sample Persons



11-21 31 41 & 51 11-51 81 11-81 91-99 all 11-21 31 41 &

51 11-51 81 11-81 91-99 11-99



93



Maharashtra 189 102 136 428 7 435 565 1000 182695 98840 131647 413182 6404 419586 544931 964517

94

Table 34: Per 1000 distribution of persons-days by current weekly activity


District code

District Name

per thousand distribution of persons(CWS) Estimated persons(00)(CWS)

11-21,61,62 31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,62 31,71,72 41-51 11-72 81 & 82 11-82 91-99 11-99


10 Bhandara 227 16 351 592 48 642 358 1000 1063 75 1642 2771 227 3006 1674 4679 11 Gondiya 301 45 221 551 40 607 393 1000 1514 226 1115 2772 199 3055 1981 5035 12 Gadchiroli 211 30 386 625 2 629 371 1000 931 133 1702 2759 8 2774 1639 4413 13 Chandrapur 243 40 359 641 13 655 345 1000 1683 274 2489 4438 92 4537 2389 6926 14 Yavatmal 196 48 340 582 2 586 414 1000 2161 523 3743 6401 22 6449 4556 11005 15 Nanded 338 32 148 518 0 518 482 1000 3638 348 1589 5575 3 5578 5192 10770 16 Hingoli 233 30 254 517 1 518 482 1000 1101 142 1198 2440 4 2444 2273 4717 17 Parbhani 393 9 163 565 12 577 423 1000 2106 49 874 3029 63 3092 2269 5361 18 Jalna 264 47 228 539 0 539 461 1000 1977 352 1708 4037 1 4039 3451 7490 19 Aurangabad 270 48 255 563 6 580 420 1000 2889 518 2723 6012 63 6194 4491 10685 20 Nashik 346 56 181 582 0 583 417 1000 4471 725 2340 7535 2 7538 5400 12938

95

District code

District Name


11-21,61,62 31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,62 31,71,72 41-51 11-72 81 & 82 11-82 91-99 11-99

21 Thane 206 149 184 536 27 567 433 1000 2636 1909 2346 6845 351 7241 5539 12780 24 Raigad 223 139 141 496 39 543 457 1000 1742 1087 1102 3875 304 4235 3571 7806 25 Pune 321 104 178 602 31 634 366 1000 4950 1609 2749 9284 476 9784 5640 15424 26 Ahmednagar 261 44 161 466 15 482 518 1000 4652 786 2861 8293 275 8574 9232 17806 27 Bid 413 20 154 587 0 587 413 1000 4304 207 1600 6112 0 6112 4304 10416 28 Latur 318 45 176 539 0 539 461 1000 3021 423 1675 5119 0 5119 4376 9494 29 Osmanabad 348 43 204 596 1 597 403 1000 1955 244 1148 3347 6 3353 2264 5617 30 Solapur 290 75 219 578 2 587 413 1000 3755 977 2837 7488 32 7601 5349 12950 31 Satara 314 106 145 563 19 583 417 1000 3488 1174 1611 6258 206 6479 4636 11115 32 Ratnagiri 351 33 185 568 2 570 430 1000 2087 197 1099 3383 11 3394 2560 5954 33 Sindhudurg 345 31 212 587 20 607 393 1000 1298 115 796 2209 77 2286 1478 3763 34 Kolhapur 334 95 156 585 10 596 404 1000 4210 1198 1970 7371 127 7504 5091 12596 35 Sangli 391 80 114 585 1 587 413 1000 4163 856 1214 6232 16 6248 4401 10649 Maharashtra 286 61 217 561 11 574 426 1000 81258 17321 61647 159621 3075 2E+05 121299 284600


96

Table 34: Per 1000 distribution of persons-days by current weekly activity STATE: MAHARASHTRA Sector = Rural Pooled sample Female

District code

District Name


11-21,61,62

31,71,72 41-51 11-72 81 &

82 11-82 91-99 all 11-21,61,62

31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99


10 Bhandara 114 4 216 334 42 376 624 1000 502 17 950 1466 184 1652 2743 4395 11 Gondiya 220 30 204 449 3 457 543 1000 1056 143 984 2161 17 2200 2612 4812 12 Gadchiroli 106 5 366 478 0 478 522 1000 477 24 1652 2153 0 2153 2355 4508 13 Chandrapur 94 4 294 392 0 392 608 1000 683 31 2137 2851 0 2851 4429 7280 14 Yavatmal 79 13 276 360 0 368 632 1000 764 128 2685 3501 1 3579 6147 9725 15 Nanded 109 1 159 269 3 273 727 1000 1071 14 1563 2648 33 2681 7152 9832 16 Hingoli 60 3 174 237 0 237 763 1000 298 16 871 1183 0 1184 3813 4997 17 Parbhani 204 1 157 361 7 368 632 1000 1127 6 866 1999 36 2035 3497 5533 18 Jalna 176 0 200 376 0 376 624 1000 1251 0 1420 2670 0 2670 4434 7104 19 Aurangabad 162 2 115 278 0 279 721 1000 1453 18 1026 2486 2 2499 6455 8953 20 Nashik 178 20 170 367 0 367 633 1000 2197 241 2093 4531 0 4531 7807 12338 21 Thane 122 22 75 209 19 238 762 1000 1636 296 1003 2801 249 3185 10204 13388

97

District code

District Name


11-21,61,62

31,71,72 41-51 11-72 81 &

82 11-82 91-99 all 11-21,61,62

31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99

24 Raigad 139 14 58 210 20 231 769 1000 1098 107 457 1661 161 1822 6082 7905 25 Pune 251 7 105 362 26 389 611 1000 3766 100 1577 5427 387 5831 9155 14986 26 Ahmednagar 194 8 199 400 12 412 588 1000 2841 113 2927 5877 170 6051 8624 14674 27 Bid 151 12 134 296 2 298 702 1000 1373 109 1218 2700 15 2715 6402 9116 28 Latur 68 4 121 193 2 195 805 1000 628 41 1126 1794 18 1812 7484 9296 29 Osmanabad 147 9 117 272 0 272 728 1000 827 48 659 1533 1 1536 4107 5643 30 Solapur 227 23 153 383 1 404 596 1000 2881 287 1944 4859 13 5125 7546 12671 31 Satara 213 21 99 333 5 338 662 1000 2233 225 1039 3492 53 3549 6948 10497 32 Ratnagiri 192 3 66 261 0 261 739 1000 1321 23 456 1801 1 1802 5094 6896 33 Sindhudurg 171 5 53 229 1 230 770 1000 579 17 180 774 3 779 2605 3384 34 Kolhapur 226 9 85 319 5 325 675 1000 2815 117 1055 3973 58 4045 8413 12457 35 Sangli 236 6 77 316 0 319 681 1000 2561 63 832 3427 4 3460 7400 10861 Maharashtra 159 9 163 328 7 338 662 1000 43128 2531 44136 89051 1822 91617 179778 271395


98

Table 34: Per 1000 distribution of persons-days by current weekly activity STATE: MAHARASHTRA Sector = Rural Pooled sample Persons

District code

District Name


11-21,61,62 31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,62 31,71,7

2 41-51 11-72 81 & 82 11-82 91-99 11-99


10 Bhandara 172 10 286 467 45 513 487 1000 1564 92 2591 4237 410 4658 4416 9074 11 Gondiya 261 38 213 501 22 534 466 1000 2570 370 2098 4934 216 5255 4593 9847 12 Gadchiroli 158 18 376 551 1 552 448 1000 1408 156 3354 4912 8 4927 3994 8921 13 Chandrapur 166 21 326 513 6 520 480 1000 2365 305 4626 7289 92 7387 6818 14205 14 Yavatmal 141 31 310 478 1 484 516 1000 2925 651 6428 9902 23 10027 10702 20730 15 Nanded 229 18 153 399 2 401 599 1000 4708 362 3152 8223 36 8259 12344 20602 16 Hingoli 144 16 213 373 0 374 626 1000 1399 157 2068 3624 4 3628 6086 9714 17 Parbhani 297 5 160 462 9 471 529 1000 3233 55 1740 5028 99 5127 5766 10893 18 Jalna 221 24 214 460 0 460 540 1000 3228 352 3128 6708 1 6709 7885 14594 19 Aurangabad 221 27 191 433 3 443 557 1000 4342 536 3750 8497 66 8693 10946 19638 20 Nashik 264 38 175 477 0 477 523 1000 6668 966 4432 12066 2 12069 13207 25276 21 Thane 163 84 128 369 23 398 602 1000 4272 2205 3348 9646 600 10426 15742 26168 24 Raigad 181 76 99 352 30 386 614 1000 2840 1194 1559 5536 464 6057 9653 15710

99


25 Pune 287 56 142 484 28 513 487 1000 8716 1709 4326 14711 863 15615 14795 30410 26 Ahmednagar 231 28 178 436 14 450 550 1000 7494 899 5788 14170 445 14625 17856 32481 27 Bid 291 16 144 451 1 452 548 1000 5677 316 2819 8811 15 8826 10706 19532 28 Latur 194 25 149 368 1 369 631 1000 3648 463 2801 6913 18 6931 11859 18790 29 Osmanabad 247 26 160 433 1 434 566 1000 2782 292 1806 4880 7 4889 6371 11260 30 Solapur 259 49 187 482 2 497 503 1000 6636 1264 4781 12347 45 12726 12895 25621 31 Satara 265 65 123 451 12 464 536 1000 5720 1399 2650 9750 259 10029 11583 21612 32 Ratnagiri 265 17 121 403 1 404 596 1000 3408 220 1555 5184 13 5196 7654 12850 33 Sindhudurg 263 18 137 417 11 429 571 1000 1877 132 976 2983 79 3064 4083 7147 34 Kolhapur 280 52 121 453 7 461 539 1000 7025 1315 3024 11345 185 11549 13504 25053 35 Sangli 313 43 95 449 1 451 549 1000 6724 919 2046 9659 20 9708 11801 21510 Maharashtra 224 36 190 447 9 458 542 1000 124386 19852 105783 248672 4897 254918 301077 555995

100





11-21,61,62

31,71,72

41-51 11-72 81 &

82 11-82 91-99 all 11-

21,61,6231,71,

72 41-51 11-72 81 & 82 11-82 91-99 11-99



101



11-21,61,62

31,71,72

41-51 11-72 81 &

82 11-82 91-99 all 11-

21,61,6231,71,

72 41-51 11-72 81 & 82 11-82 91-99 11-99


Maharashtra 207 293 63 561 18 582 418 1000 45364 64043 13873 122728 4031 127311 91340 218651


102

Table 34: Per 1000 distribution of persons-days by current weekly activity STATE: MAHARASHTRA Sector = Urban Pooled Sample Female

District

code District Name


11-21,61,62

31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,6231,71,7

2 41-51 11-72 81 & 82 11-82 91-99 11-99



103

District

code District Name


11-21,61,62

31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,6231,71,7

2 41-51 11-72 81 & 82 11-82 91-99 11-99

22 Mumbai 41 116 4 160 15 175 825 1000 1998 5683 175 7845 742 8597 40531 49129 24 Raigad 44 65 12 122 3 125 875 1000 137 201 38 376 10 386 2705 3092 25 Pune 53 76 11 139 6 145 855 1000 1225 1748 247 3220 140 3360 19746 23106 26 Ahmednagar 132 65 53 250 3 252 748 1000 491 244 197 932 10 942 2790 3732 27 Bid 19 45 5 69 19 87 913 1000 36 88 10 135 37 171 1788 1959 28 Latur 11 17 17 45 0 45 955 1000 26 40 42 108 0 108 2312 2420 29 Osmanabad 85 10 49 133 2 146 854 1000 87 10 50 137 3 150 878 1028 30 Solapur 87 92 52 227 2 233 767 1000 465 495 278 1218 9 1247 4111 5358 31 Satara 64 49 34 147 0 147 853 1000 142 109 75 326 0 326 1895 2221 32 Ratnagiri 98 75 7 181 9 189 811 1000 116 89 9 213 10 224 956 1180 33 Sindhudurg 27 63 14 105 0 105 895 1000 8 18 4 29 0 29 249 279 34 Kolhapur 66 43 20 129 5 135 865 1000 306 200 91 597 24 621 3993 4614 35 Sangli 56 29 44 128 2 130 870 1000 159 82 124 364 5 369 2469 2838

Maharashtra 48 76 20 143 10 153 847 1000 9036 14422 3824 27225 1831 29113 160757 189870


104

Table 34: Per 1000 distribution of persons-days by current weekly activity STATE: MAHARASHTRA Sector =Urban Pooled Sample Persons



11-21,61,62 31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,62 31,71,72 41-51 11-72 81 & 82 11-82 91-99 11-99


10 Bhandara 167 107 120 392 20 413 587 1000 198 127 143 466 23 491 698 1189 11 Gondiya 130 121 80 327 23 355 645 1000 190 177 117 477 34 518 941 1459 12 Gadchiroli 140 166 81 387 6 393 607 1000 87 102 50 239 4 243 375 618 13 Chandrapur 103 148 95 345 6 351 649 1000 567 818 525 1909 31 1941 3593 5534 14 Yavatmal 135 95 99 326 2 331 669 1000 660 465 483 1592 10 1617 3265 4882 15 Nanded 118 77 75 270 8 278 722 1000 811 528 519 1859 55 1914 4973 6887 16 Hingoli 173 92 85 347 16 367 633 1000 320 171 157 641 29 677 1169 1847 17 Parbhani 128 58 103 288 25 315 685 1000 573 257 461 1284 114 1405 3056 4461 18 Jalna 79 111 149 339 12 350 650 1000 275 389 521 1185 41 1227 2274 3500 19 Aurangabad 96 153 45 294 20 314 686 1000 1149 1834 541 3523 243 3766 8235 12002

105


20 Nashik 110 125 99 334 6 341 659 1000 1676 1908 1508 5090 93 5185 10038 15223 21 Thane 112 264 17 393 15 408 592 1000 8012 18944 1248 28200 1093 29297 42490 71787 22 Mumbai 145 251 15 407 17 427 573 1000 15980 27714 1601 44910 1845 47139 63232 110372 24 Raigad 120 227 30 377 7 384 616 1000 792 1500 201 2493 47 2540 4067 6607 25 Pune 115 209 31 355 15 370 630 1000 5733 10382 1556 17656 723 18396 31381 49776 26 Ahmednagar 185 104 90 379 22 401 599 1000 1489 838 719 3046 176 3222 4805 8028 27 Bid 106 108 54 269 33 301 699 1000 411 416 210 1037 126 1164 2700 3864 28 Latur 128 69 61 257 2 260 740 1000 658 353 315 1317 9 1335 3792 5127 29 Osmanabad 177 61 121 354 6 365 635 1000 376 128 256 749 13 773 1345 2118 30 Solapur 153 143 82 371 6 385 615 1000 1644 1542 883 3992 68 4137 6620 10757 31 Satara 191 110 51 352 9 361 639 1000 902 522 243 1667 42 1710 3023 4732 32 Ratnagiri 198 137 26 360 35 396 604 1000 483 336 63 882 86 968 1478 2446 33 Sindhudurg 144 116 56 317 12 330 670 1000 84 68 33 185 7 192 391 583 34 Kolhapur 194 124 54 372 5 377 623 1000 1874 1196 520 3588 47 3637 6016 9653 35 Sangli 158 119 68 345 12 357 643 1000 952 717 412 2080 74 2154 3879 6033

Maharashtra 133 192 43 367 14 383 617 1000 54400 78465 17697 149953 5862 156424 252098 408521

106





11-21,61,62 31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,62 31,71,72 41-51 11-72 81 & 82 11-82 91-99 11-99



107



11-21,61,62 31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,62 31,71,72 41-51 11-72 81 & 82 11-82 91-99 11-99

22 Mumbai 228 360 23 605 18 629 371 1000 13982 22031 1426 37066 1103 38542 22701 61243 24 Raigad 212 211 112 529 30 564 436 1000 2397 2386 1265 5992 341 6389 4932 11321 25 Pune 225 243 96 563 25 590 410 1000 9459 10243 4058 23720 1059 24819 17276 42095 26 Ahmednagar 256 62 153 471 20 491 509 1000 5649 1380 3384 10407 442 10855 11247 22102 27 Bid 380 43 146 569 7 577 423 1000 4679 536 1800 7014 90 7104 5216 12320 28 Latur 299 60 160 519 1 520 480 1000 3653 736 1948 6327 9 6345 5856 12202 29 Osmanabad 335 54 202 590 2 593 407 1000 2243 362 1353 3959 17 3975 2731 6707 30 Solapur 269 110 188 559 5 572 428 1000 4934 2024 3442 10261 91 10491 7858 18349 31 Satara 312 116 131 558 18 577 423 1000 4248 1587 1780 7599 248 7863 5763 13626 32 Ratnagiri 340 61 160 561 12 573 427 1000 2454 443 1153 4051 87 4138 3082 7220 33 Sindhudurg 338 41 203 581 21 602 398 1000 1375 165 825 2365 84 2449 1619 4068 34 Kolhapur 328 124 136 588 8 597 403 1000 5778 2194 2399 10362 149 10521 7114 17635 35 Sangli 358 108 108 574 6 580 420 1000 4957 1490 1501 7948 85 8033 5811 13844

Maharashtra 252 162 150 561 14 577 423 1000 126622 81364 75520 282349 7106 290611 212640 503251


108

Table 34: Per 1000 distribution of persons-days by current weekly activity STATE: MAHARASHTRA Sector = Combined Pooled Sample Female



11-21,61,62 31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,62 31,71,72 41-51 11-72 81 & 82 11-82 91-99 11-99



109



11-21,61,62 31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,62 31,71,72 41-51 11-72 81 & 82 11-82 91-99 11-99


Maharashtra 113 37 104 252 8 262 738 1000 52163 16953 47960 116276 3653 120730 340535 461265


110

Table 34: Per 1000 distribution of persons-days by current weekly activity STATE: MAHARASHTRA Sector = Combined Pooled Sample Persons



11-21,61,62 31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,62 31,71,72 41-51 11-72 81 & 82 11-82 91-99 11-99


10 Bhandara 172 21 266 458 42 502 498 1000 1762 219 2734 4703 434 5149 5114 10263 11 Gondiya 244 48 196 479 22 511 489 1000 2761 547 2215 5411 250 5772 5534 11306 12 Gadchiroli 157 27 357 540 1 542 458 1000 1495 259 3404 5151 12 5170 4369 9538 13 Chandrapur 149 57 261 466 6 473 527 1000 2933 1122 5151 9198 122 9328 10411 19739 14 Yavatmal 140 44 270 449 1 455 545 1000 3585 1116 6911 11494 33 11644 13967 25611 15 Nanded 201 32 134 367 3 370 630 1000 5519 890 3672 10082 91 10172 17317 27489 16 Hingoli 149 28 193 369 3 372 628 1000 1720 328 2226 4265 33 4306 7255 11561 17 Parbhani 248 20 143 411 14 425 575 1000 3806 312 2201 6312 213 6532 8823 15355 18 Jalna 194 41 202 436 2 439 561 1000 3503 741 3649 7893 43 7936 10159 18094

111



11-21,61,62 31,71,72 41-51 11-

72 81 &

82 11-82

91-99 all 11-

21,61,62 31,71,72 41-51 11-72 81 & 82 11-82 91-99 11-99

19 Aurangabad 174 75 136 380 10 394 606 1000 5490 2370 4290 12021 308 12459 19181 31640 20 Nashik 206 71 147 424 2 426 574 1000 8344 2874 5941 17156 96 17254 23245 40499 21 Thane 125 216 47 386 17 406 594 1000 12284 21149 4596 37846 1693 39723 58232 97955 22 Mumbai 145 251 15 407 17 427 573 1000 15980 27714 1601 44910 1845 47139 63232 110372 24 Raigad 163 121 79 360 23 385 615 1000 3632 2694 1760 8029 512 8597 13720 22317 25 Pune 180 151 73 404 20 424 576 1000 14449 12092 5883 32367 1587 34010 46176 80186 26 Ahmednagar 222 43 161 425 15 441 559 1000 8982 1737 6507 17217 621 17847 22661 40508 27 Bid 260 31 129 421 6 427 573 1000 6088 732 3028 9849 141 9990 13405 23396 28 Latur 180 34 130 344 1 346 654 1000 4307 816 3116 8230 27 8266 15651 23917 29 Osmanabad 236 31 154 421 2 423 577 1000 3158 421 2062 5629 20 5662 7716 13378 30 Solapur 228 77 156 449 3 464 536 1000 8280 2806 5664 16338 113 16862 19515 36378 31 Satara 251 73 110 433 11 446 554 1000 6622 1921 2893 11417 302 11738 14606 26344 32 Ratnagiri 254 36 106 397 6 403 597 1000 3892 555 1618 6065 99 6164 9133 15296 33 Sindhudurg 254 26 131 410 11 421 579 1000 1961 200 1009 3168 87 3257 4474 7730 34 Kolhapur 256 72 102 430 7 438 562 1000 8899 2511 3545 14932 231 15187 19520 34706 35 Sangli 279 59 89 426 3 431 569 1000 7676 1635 2458 11740 94 11863 15680 27543

Maharashtra 185 102 128 413 11 426 574 1000 178785 98317 123480 398625 10759 411342 553175 964517


112

Table 36: Per 1000 distribution of persons-days by current daily activity


District

code

District Name

per thousand distribution of persons days Estimated persons days(00) 11-

21,61,62

31,71,72 41-51 11-72 81 &

82 11-82 91-99 all 11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99


10 Bhandara 226 16 345 584 55 642 358 1000 7406 524 11315 19140 1794 21039 11716 32755 11 Gondiya 294 59 199 536 53 604 396 1000 10362 2062 6992 18859 1852 21268 13930 35197 12 Gadchiroli 216 30 369 609 9 624 376 1000 6660 928 11404 18808 270 19262 11629 30890 13 Chandrapur 243 40 348 629 24 655 345 1000 11801 1915 16871 30518 1169 31756 16725 48481 14 Yavatmal 203 48 307 538 26 583 417 1000 15642 3661 23617 41438 1994 44914 32118 77032 15 Nanded 338 32 146 516 1 518 482 1000 25474 2418 11043 38935 100 39035 36352 75387 16 Hingoli 231 30 244 505 5 510 490 1000 7586 993 8031 16610 165 16775 16098 32873 17 Parbhani 392 9 147 548 12 560 440 1000 14876 348 5573 20796 442 21238 16696 37934 18 Jalna 260 47 208 510 7 522 478 1000 13657 2462 10890 26715 345 27353 25075 52428 19 Aurangabad 267 49 239 540 19 573 427 1000 19958 3627 17870 40359 1407 42862 31918 74780 20 Nashik 344 56 178 577 2 580 420 1000 31193 5072 16099 52275 167 52531 38034 90566

113

District

code

District Name

per thousand distribution of persons days Estimated persons days(00) 11-

21,61,62

31,71,72 41-51 11-72 81 &

82 11-82 91-99 all 11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99

21 Thane 209 149 175 525 32 565 435 1000 18728 13314 15638 47006 2890 50570 38888 89458 24 Raigad 214 139 137 485 52 542 458 1000 11690 7607 7459 26476 2855 29611 25000 54611 25 Pune 322 104 137 560 66 629 371 1000 34749 11258 14788 60459 7102 67897 40073 107970 26 Ahmednagar 263 44 137 442 31 475 525 1000 32838 5501 17072 55130 3857 59268 65377 124645 27 Bid 395 20 145 560 9 569 431 1000 28796 1443 10599 40838 660 41498 31392 72890 28 Latur 318 45 175 537 2 539 461 1000 21124 2958 11614 35696 113 35808 30652 66460 29 Osmanabad 352 43 195 589 2 592 408 1000 13833 1704 7674 23174 66 23277 16041 39317 30 Solapur 295 75 186 542 15 571 429 1000 26752 6838 16858 49158 1330 51778 38836 90615 31 Satara 313 105 128 541 28 574 426 1000 24322 8184 9973 42115 2150 44630 33174 77804 32 Ratnagiri 349 33 168 550 17 567 433 1000 14446 1376 6961 22783 707 23490 17929 41418 33 Sindhudurg 342 31 201 575 27 601 399 1000 8888 804 5227 14919 690 15609 10344 25952 34 Kolhapur 333 94 155 577 11 593 407 1000 29318 8314 13681 50909 1000 52313 35858 88171 35 Sangli 379 80 106 564 5 570 430 1000 28209 5989 7866 42045 404 42469 32056 74525 Maharashtra 284 61 198 538 22 565 435 1000 565229 121755 393372 1070657 44808 1125164 866342 1991506


114


STATE: MAHARASHTRA Sector = Rural Pooled sample Female

District

code

District Name

per thousand distribution of persons_days Estimated persons_days(00) 11-

21,61,62

31,71,72 41-51 11-72 81 &

82 11-82 91-99 all 11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99


10 Bhandara 111 4 192 306 65 372 628 1000 3419 120 5902 9417 2008 11449 19314 30763 11 Gondiya 206 30 191 422 24 451 549 1000 6910 1003 6430 14187 810 15154 18449 33603 12 Gadchiroli 102 5 350 456 7 464 536 1000 3203 166 11047 14399 212 14628 16915 31542 13 Chandrapur 93 4 278 375 0 376 624 1000 4742 217 14181 19117 0 19140 31817 50957 14 Yavatmal 69 13 225 285 26 333 667 1000 4670 899 15292 19401 1778 22639 45437 68076 15 Nanded 99 1 155 255 3 259 741 1000 6802 100 10673 17575 238 17814 51007 68821 16 Hingoli 53 3 152 208 0 208 792 1000 1863 109 5321 7286 0 7293 27686 34979 17 Parbhani 208 1 137 340 8 354 646 1000 8025 43 5310 13155 322 13699 24961 38660 18 Jalna 145 0 166 311 12 323 677 1000 7208 0 8258 15461 583 16049 33680 49729 19 Aurangabad 146 2 97 244 12 257 743 1000 9147 124 6084 15284 764 16120 46554 62674 20 Nashik 158 20 166 341 1 344 656 1000 13640 1688 14336 29457 86 29751 56615 86366 21 Thane 111 22 69 194 21 223 777 1000 10398 2074 6453 18149 1977 20902 72815 93717 24 Raigad 117 14 46 177 21 198 802 1000 6470 749 2568 9769 1136 10923 44357 55280 25 Pune 250 7 75 331 47 379 621 1000 26245 703 7903 34745 4899 39751 65148 104899

115

District

code

District Name


21,61,62

31,71,72 41-51 11-72 81 &

82 11-82 91-99 all 11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99

26 Ahmednagar 194 7 155 353 24 381 619 1000 19950 765 15872 36225 2515 39102 63618 102720 27 Bid 136 12 110 258 12 270 730 1000 8665 754 7013 16432 778 17210 46574 63784 28 Latur 66 4 119 190 2 192 808 1000 4285 284 7768 12337 141 12478 52591 65069 29 Osmanabad 144 9 112 263 1 265 735 1000 5690 339 4434 10377 24 10488 29014 39502 30 Solapur 224 23 138 367 13 398 602 1000 19897 2011 12270 32585 1114 35292 53406 88698 31 Satara 200 21 85 306 9 315 685 1000 14699 1562 6242 22478 625 23129 50350 73478 32 Ratnagiri 150 3 55 208 6 215 785 1000 7220 163 2662 10046 308 10354 37891 48245 33 Sindhudurg 119 5 46 158 1 171 829 1000 2810 122 1079 3731 23 4034 19545 23579 34 Kolhapur 196 9 78 271 8 291 709 1000 17050 819 6832 23653 706 25408 61794 87202 35 Sangli 217 6 56 276 2 280 720 1000 16463 443 4247 20935 129 21283 54669 75952

Maharashtra 148 9 138 291 17 312 688 1000 281205 17835 262360 552526 31576 592976 1306139 1899116


116


STATE: MAHARASHTRA Sector = Rural Pooled sample Persons

District

code District Name


21,61,62

31,71,72 41-51 11-72 81 &

82 11-82 91-99 all 11-

21,61,62

31,71,72 41-51 11-72 81 & 82 11-82 91-99 11-99



117

District

code District Name


21,61,62

31,71,72 41-51 11-72 81 &

82 11-82 91-99 all 11-

21,61,62

31,71,72 41-51 11-72 81 & 82 11-82 91-99 11-99


Maharashtra 218 36 169 417 20 442 558 1000 846434 139590 655732 1623183 76384 1718141 2172481 3890622


118




per thousand distribution of persons_days Estimated persons_days(00)

11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 all 11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99



119



11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 all 11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99


Maharashtra 206 293 59 554 22 580 420 1000 315620 447848 89902 847362 33904 887274 642769 1530043


120

Table 36: Per 1000 distribution of persons-days by current daily activity STATE: MAHARASHTRA Sector = Urban Pooled Sample Female



11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 all

11-21,61,6

2

31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99



121



11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 all

11-21,61,6

2

31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99


Maharashtra 42 75 18 135 10 145 855 1000 55448 100315 23881 179003 13293 192936 1135887 1328823


122

Table 36: Per 1000 distribution of persons-days by current daily activity STATE: MAHARASHTRA Sector =Urban Pooled Sample Persons



21,61,62

31,71,72 41-51 11-72 81 &

82 11-82

91-99 all 11-

21,61,6231,71,7

2 41-51 11-72 81 & 82 11-82 91-99 11-99



123



21,61,62

31,71,72 41-51 11-72 81 &

82 11-82

91-99 all 11-

21,61,6231,71,7

2 41-51 11-72 81 & 82 11-82 91-99 11-99


Maharashtra 130 192 40 359 17 378 622 1000 371068 548163 113783 1026365 47196 1080211 1778656 2858867


124





21,61,62

31,71,72 41-51 11-72 81 &

82 11-82

91-99 all

11-21,61,6

2 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99



125



21,61,62

31,71,72 41-51 11-72 81 &

82 11-82

91-99 all

11-21,61,6

2 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99


Maharashtra 250 162 137 545 22 571 429 1000 880849 569604 483274 1918019 78712 2012438 1509111 3521549


126


STATE: MAHARASHTRA Sector = Combined Pooled Sample Female



21,61,62 31,71,72 41-51 11-72 81 & 82 11-82 91-

99 all 11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99



127



21,61,62 31,71,72 41-51 11-72 81 & 82 11-82 91-

99 all 11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99


Maharashtra 104 37 89 227 14 243 757 1000 336653 118150 286241 731529 44869 785913 2442026 3227939


128


STATE: MAHARASHTRA Sector = Combined Pooled Sample Persons

District

code District Name


21,61,62

31,71,72 41-51 11-72 81 & 82 11-82 91-

99 all 11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99



129

District

code District Name


21,61,62

31,71,72 41-51 11-72 81 & 82 11-82 91-

99 all 11-21,61,62 31,71,72 41-51 11-72 81 &

82 11-82 91-99 11-99


Maharashtra 180 102 114 393 18 415 585 1000 1217502 687753 769515 2649548 123581 2798351 3951137 6749488


130

Annexure – 1

Sample size: Number of first stage units (villages/urban frame survey blocks)

District Rural Urban State Central Pooled State Central Pooled

Thane 20 20 40 108 72 180 Mumbai 0 0 0 114 98 212 Raigad 16 16 32 12 8 20 Ratnagiri 16 16 32 8 4 12 Sindhudurg 8 8 16 8 4 12 Pune 24 24 48 80 52 132 Solapur 24 24 48 24 16 40 Satara 20 20 40 12 8 20 Kolhapur 24 24 48 20 12 32 Sangli 20 20 40 12 8 20 Ahmadnagar 24 24 48 20 12 32 Nandurbar 12 12 24 8 4 12 Dhule 12 12 24 12 8 20 Jalgaon 22 24 46 20 12 32 Nashik 23 24 47 40 24 64 Nanded 20 20 40 12 8 20 Hingoli 8 8 16 8 4 12 Parbhani 8 8 16 12 8 20 Jalna 12 12 24 12 8 20 Aurangabad 16 16 32 20 12 32 Bid 16 16 32 12 8 20 Latur 16 16 32 12 8 20 Osmanabad 12 12 24 8 4 12 Buldhana 16 16 32 12 8 20 Akola 8 8 16 12 8 20 Washim 8 8 16 8 4 12 Amravati 16 16 32 20 12 32 Yavatmal 20 20 40 12 8 20 Wardha 8 8 16 12 8 20 Nagpur 12 12 24 47 32 79 Bhandara 8 8 16 8 4 12 Gondiya 12 12 24 8 4 12 Gadchiroli 8 8 16 8 4 12 Chandrapur 12 12 24 12 8 20 State 501 504 1005 753 502 1255

131

Annexure – 2

Abbreviations used in this Report MPCE : Monthly Per Capita Consumption Expenditure URP : Uniform Reference Period MRP : Mixed Reference Period MMRP : Modified Mixed Reference Period RSE : Relative Standard Error IV : Inverse of Variance MR : Matching Ratio WPR : Worker Population Ratio LFPR : Labour Force Participation Rate PS+SS : Principal Status+ Subsidiary Status CWS : Current Weekly Status CDS : Current Daily Status

132

Annexure – 3 Description of Activity status code Working (or Employed) i) Self-employed 11 - Worked in household enterprises (self-employed) as own-account worker 12 - Worked in household enterprises (self-employed) as an employer 21 - Worked in household enterprises (self-employed) as helper ii) Regular wage / Salaried employee 31- Worked as regular wage/salaried employee iii) Casual labour 41 - Worked as casual wage labour in public works other than Mahatma Gandhi NREG public works 42 - Worked as casual wage labour in Mahatma Gandhi NREG public works 51 - Worked as casual wage labour in other types of works 61 - Did not work owing to sickness though there was work in household enterprise 62 - Did not work owing to other reasons though there was work in household enterprise 71 - Did not work owing to sickness but had regular salaried/wage employment 72 - Did not work owing to other reasons but had regular salaried/wage employment Not working but seeking/available for work (or Unemployed) 81 - Sought work or did not seek but was available for work (for usual status approach) 81 - Sought work (for current weekly status approach) 82 - Did not seek but was available for work (for current weekly status approach) Neither working nor available for work (or Not in Labour Force) 91 - Attended educational institutions 92 - Attended to domestic duties only 93 - Attended to domestic duties and was also engaged in free collection of goods (vegetables, roots, firewood, cattle feed, etc.), sewing, tailoring, weaving, etc. for household use 94 - Rentiers, pensioners, remittance recipients, etc. 95 - Not able to work owing to disability 97 - Others (including beggars, prostitutes, etc.) 98 - Did not work owing to sickness (for casual workers only) 99 - Children of age 0-4 years

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