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Horizontal and Vertical Inequalities
Explaining Disparities in Access to
Urban Sanitation
Evidence from National Sample Su...
Key Discussion Points
• Latest urban sanitation statistics in India. Data from Census 2011 and NSS 2011-’12.
• Benefits of...
Urban Sanitation in India
Statistics:
• Toilets: In-house toilets - 81% Improved Toilets – 79% Piped Sewer – 38% On-
site ...
Variation across Consumption Quintiles (UP)
0
2,000
4,000
6,000
8,000
10,000
0 1 0 1 0 1 0 1 0 1
First Second Middle Fourt...
Variation across Consumption Quintiles (UP)
0
2,000
4,000
6,000
8,000
No Drain Open DrainClosed Drain No Drain Open DrainC...
Research Questions of the Study
• What kind of disparities exist in the urban water and sanitation sectors in
India? Explo...
National Sample Survey Data and
Analysis
Insights from Data (NSS Data)
• Advantages:
 Large sample size – 95,548 households (53,393 rural and 42,155 urban
househo...
Logistic Model for Analysis
and
Where,
Independent variables (X) considered for the model are:
• Monthly per-capita Consum...
Odds Ratios for Continuous and Categorical
Variables:
Odds Ratio for Continuous Variable – Monthly Per Capita Expenditure ...
Results (Shown for some states and some predictors)
Household
Characterisitics
Punjab Rajasthan Bihar
West
Bengal
Jharkhan...
1.1
1.9
12.6
1.8
2.0
1.0
3.1
7.9
1.7
7.2
1.1
3.7
10.8
2.2
4.2
1.1
3.1
4.5
2.4
5.5
1.1
28.2
0.3
0.1
mpcenew1
Open Drain
Clo...
Predicted Probabilities for In-House
Toilets for Key Predictors:
Independent and Interactive Effects
Public Infrastructure/Services:
Varying drainage infrastructure levels in different states result in varying predicted
pro...
• Wide caste based disparities in probability for IHL in some states
• Convergence of probabilities at lower MPCE in state...
Slum and Non-Slum Areas:
• Higher inequalities in access to toilets in highly urbanised states like Gujarat,
Maharashtra a...
Caste and Drainage (Interaction) I:
Provision of public infrastructures – open drains and closed drains are shown to incre...
Caste and Drainage (Interaction) II: For Different States
Interaction shown here for two states at their respective median...
Conclusion:
• Access to public infrastructure such as drainage and improved drinking
water supply have significant effect ...
Policy Implications
• Shift from subsidy based policies to infrastructure building programmes
for provision of improved wa...
Thank you
Follow us on twitter:
@CPRIndia_SCIFI , @CPR_India
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Horizontal and Vertical Inequalities Explaining Disparities in Access to Urban Sanitation

Horizontal and Vertical Inequalities Explaining Disparities in Access to Urban Sanitation: Evidence from National Sample Survey of India.

Presentation by Aditya Bhol, made at the Population Association of America Conference in Chicago on 28th April 2017

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Horizontal and Vertical Inequalities Explaining Disparities in Access to Urban Sanitation

  1. 1. Horizontal and Vertical Inequalities Explaining Disparities in Access to Urban Sanitation Evidence from National Sample Survey of India Aditya Bhol Centre for Policy Research, New Delhi
  2. 2. Key Discussion Points • Latest urban sanitation statistics in India. Data from Census 2011 and NSS 2011-’12. • Benefits of NSS data for multivariate analysis • Key Research Questions • Results of logistic analysis to measure state-wise disparities • Policy Implications : Using the results of the analysis to interpret the impact of current sanitation programmes and schemes
  3. 3. Urban Sanitation in India Statistics: • Toilets: In-house toilets - 81% Improved Toilets – 79% Piped Sewer – 38% On- site Systems( Septic tanks and Improved Pits) – 47% No Toilets – 19% Public Toilets – 6% Open Defecation – 13% (Census, 2011) • Drainage: Closed Drains – 45%, Open Drains – 37% and No Drains – 18% (Census, 2011) • Sewerage Treatment Facilities – 152 STPs [9 STPs under construction, 30 STPs non-operational and performance of 28 STPs not satisfactory] (CPCB, 2013) Definition of Environmental Sanitation - Safe confinement, treatment and disposal of human toilet waste and associated hygiene-related practices; solid waste management; generation of industrial and other specialized / hazardous wastes; drainage; and the management of drinking water supply (National Urban Sanitation Policy, 2008)
  4. 4. Variation across Consumption Quintiles (UP) 0 2,000 4,000 6,000 8,000 10,000 0 1 0 1 0 1 0 1 0 1 First Second Middle Fourth Fifth MPCE Uttar Pradesh Toilet Access across Consumption Quintiles Access to In-House Toilets (0=No IHL / 1=IHL) No IHL IHL First 727 788 Second 1100 1140 Middle 1480 1583 Fourth 2214 2500 Fifth 4150 4500 Consumption Quinitles Median MPCE
  5. 5. Variation across Consumption Quintiles (UP) 0 2,000 4,000 6,000 8,000 No Drain Open DrainClosed Drain No Drain Open DrainClosed Drain No Drain Open DrainClosed Drain No Drain Open DrainClosed Drain No Drain Open DrainClosed Drain First Second Middle Fourth Fifth MPCE Uttar Pradesh MPCE for Drainage Status across Consumption Quintiles No Drain Open Drain Closed Drain First 714 775 750 Second 1071 1100 1167 Middle 1500 1500 1600 Fourth 2500 2283 2500 Fifth 3900 4167 4500 Consumption Quinitles Median MPCE
  6. 6. Research Questions of the Study • What kind of disparities exist in the urban water and sanitation sectors in India? Exploration of different inequalities (vertical and horizontal) that are presumed to perpetuate deprivation of sanitation services • Vertical inequalities: Inequalities along consumption (proxy for income) expenditure of households • Horizontal Inequalities:  Disparities in access to public services:  Drainage  Water supply  Social Stratification (Caste Group)  Spatial Stratification (Slum/Non-Slum) • Are there state-wise disparities in access to sanitation? • What are the implications of the study on ongoing water and sanitation policies and programmes in India?
  7. 7. National Sample Survey Data and Analysis
  8. 8. Insights from Data (NSS Data) • Advantages:  Large sample size – 95,548 households (53,393 rural and 42,155 urban households surveyed)  Samples considered for the study – 32,321 sampled households from 15 selected states  Fairly representative of different regions of India  Pertinent questions on water, sanitation and hygiene were included in the survey questionnaire  Includes questions on various socio-economic indicators and housing conditions. Also includes consumption expenditure of households • Disadvantages:  Ambiguities in certain questions (wastewater outlets, land holdings)  Census towns are included in urban sector
  9. 9. Logistic Model for Analysis and Where, Independent variables (X) considered for the model are: • Monthly per-capita Consumption Expenditure (MPCE) • Drainage Status • Drinking Water Source • Drinking Water Access • Caste Status (Social Stratification) • Slum/ Non-Slum Status • NSS Region • House Condition • Drinking Water Sufficiency 𝑃 = 1 1 + 𝑒−𝑧 𝑧 = 𝛼 + 𝛽1 𝑋1 + 𝛽2 𝑋2 + ⋯+ 𝛽𝑘 𝑋𝑘 𝑙𝑜𝑔𝑖𝑡 𝑃 = log 𝑃 1 − 𝑃 = 𝑙𝑜𝑔 𝑂𝑑𝑑𝑠 = 𝑧 Economic Predictor Access to Public Services Social Status Spatial Predictors Behavioural Predictors
  10. 10. Odds Ratios for Continuous and Categorical Variables: Odds Ratio for Continuous Variable – Monthly Per Capita Expenditure in increments of hundreds (MPCE/100) Odds Ratio for Categorical Variable – Drainage Status (Closed Drain) 𝑂𝑑𝑑𝑠 𝑅𝑎𝑡𝑖𝑜 𝑓𝑜𝑟 𝑀𝑃𝐶𝐸/100 = 𝑂𝑑𝑑𝑠 𝑓𝑜𝑟 𝑎 ℎ𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑 𝑤𝑖𝑡ℎ 𝑡𝑜𝑖𝑙𝑒𝑡 𝑓𝑜𝑟 𝑒𝑣𝑒𝑟𝑦 𝑅𝑠 100 𝑖𝑛𝑐𝑟𝑒𝑎𝑠𝑒 𝑖𝑛 𝑀𝑃𝐶𝐸 𝑂𝑑𝑑𝑠 𝑓𝑜𝑟 𝑎 ℎ𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑 𝑤𝑖𝑡ℎ𝑜𝑢𝑡 𝑡𝑜𝑖𝑙𝑒𝑡 𝑓𝑜𝑟 𝑒𝑣𝑒𝑟𝑦 𝑅𝑠 100 𝑖𝑛𝑐𝑟𝑒𝑎𝑠𝑒 𝑖𝑛 𝑀𝑃𝐶𝐸 = P IHL=1|MPCE=M+100 /P IHL=1|MPCE=M P IHL=0|MPCE=M+100 /P IHL=0|MPCE=M = 𝑒𝑥𝑝 𝛽 𝑀𝑃𝐶𝐸 𝑂𝑑𝑑𝑠 𝑅𝑎𝑡𝑖𝑜 𝑓𝑜𝑟 𝐷𝑟𝑎𝑖𝑛𝑎𝑔𝑒 = 𝑂𝑑𝑑𝑠 𝑓𝑜𝑟 𝑎 ℎ𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑 𝑤𝑖𝑡ℎ 𝑡𝑜𝑖𝑙𝑒𝑡 𝑤𝑖𝑡ℎ 𝐶𝑙𝑜𝑠𝑒𝑑 𝐷𝑟𝑎𝑖𝑛𝑎𝑔𝑒 𝐴𝑐𝑐𝑒𝑠𝑠 𝑂𝑑𝑑𝑠 𝑓𝑜𝑟 𝑎 ℎ𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑 𝑤𝑖𝑡ℎ𝑜𝑢𝑡 𝑡𝑜𝑖𝑙𝑒𝑡 𝑤𝑖𝑡ℎ 𝐶𝑙𝑜𝑠𝑒𝑑 𝐷𝑟𝑎𝑖𝑛𝑎𝑔𝑒 𝐴𝑐𝑐𝑒𝑠𝑠 = P IHL=1|Closed Drain /P IHL=1|No Drain P IHL=0|Closed Drain /P IHL=0|No Drain = 𝑒𝑥𝑝 𝛽 𝐶𝑙𝑜𝑠𝑒𝑑 𝐷𝑟𝑎𝑖𝑛
  11. 11. Results (Shown for some states and some predictors) Household Characterisitics Punjab Rajasthan Bihar West Bengal Jharkhand Gujarat Kerala Tamil Nadu MPCE/100 1.065*** 1.030*** 1.107*** 1.047*** 1.075*** 1.068*** 1.047 1.084*** Open Drains 1.685 3.969*** 3.257*** 2.894*** 2.618*** 3.691*** 6.832*** 3.503*** Closed Drains 11.458*** 9.602*** 6.472*** 1.24 1.663 6.642*** 4.608 6.476*** OBC 1.587 1.683** 2.343*** 2.283*** 3.148*** 1.658* 3.947*** 3.830*** General 2.084* 7.698*** 5.545*** 1.726*** 7.357*** 2.911*** 1.416 16.045*** Improved Source 0.871 .469* 3.664 0.96 2.123* .561* 0.656 .396*** Within House or Building 8.417*** 5.468*** 5.076*** 3.306*** 4.357*** 5.041*** 3.186** 5.695*** Non-Slum Household 1.375 1.338 1.369 3.269*** 3.642** 8.189*** 0.443 1.766** N 1056 1701 1246 3411 837 2012 1917 2856 pseudo R-sq 0.475 0.414 0.395 0.338 0.5 0.528 0.333 0.462 Water Access (Ref: Other Sources) Slum Status (Ref: Slum Household) Note: Robust Standard Error in square bracket[]; Reference group in parantheses (); * p<0.05, ** p<0.01, *** p<0.001 Drainage Status (Ref: No Drains) Caste Status (Ref: SC/ST) Drinking Water Source (Ref: Unmproved Source)
  12. 12. 1.1 1.9 12.6 1.8 2.0 1.0 3.1 7.9 1.7 7.2 1.1 3.7 10.8 2.2 4.2 1.1 3.1 4.5 2.4 5.5 1.1 28.2 0.3 0.1 mpcenew1 Open Drain Closed Drain OBC General 0.0 10.0 20.0 30.0 Punjab Rajasthan UP Bihar Assam 1.0 2.8 1.2 2.3 1.7 1.1 2.9 1.9 3.0 6.0 1.0 4.0 6.2 1.1 2.9 1.1 4.9 11.3 1.6 2.3 1.1 4.0 5.8 1.6 2.9 mpcenew1 Open Drain Closed Drain OBC General 0.0 10.0 20.0 30.0 WB Jharkhand Odisha MP Gujarat 1.0 1.6 4.2 1.5 2.1 1.1 6.6 23.6 1.4 4.0 1.1 3.5 22.1 3.6 8.3 1.0 6.1 5.0 4.7 1.6 1.1 3.0 5.5 4.2 22.4 mpcenew1 Open Drain Closed Drain OBC General 0.0 10.0 20.0 30.0 Maharastra AP Karnataka Kerala TN Variation Across States for Key Predictors Predictors shown here are MPCE(continuous variable with an increment of Rs 100/1.5$ approximately), drainage status and caste status. (MPCE) (MPCE) (MPCE) Proxy for Income Public Infrastructure Social Groups
  13. 13. Predicted Probabilities for In-House Toilets for Key Predictors: Independent and Interactive Effects
  14. 14. Public Infrastructure/Services: Varying drainage infrastructure levels in different states result in varying predicted probabilities of households owning a toilet. Access to closed drains gives the highest predicted probabilities for all the states while no drains result in the lowest probabilities of households to own toilets. Note: All other independent variables are held constant at respective means 0 .2 .4 .6 .8 1 0 20 40 60 80 100 MPCE/100 No Drain Open Drain Closed Drain GUJARAT PredictedProbabilitiesforIHL 0 .2 .4 .6 .8 1 0 20 40 60 80 100 MPCE/100 No Drain Open Drain Closed Drain MAHARASHTRA 0 .2 .4 .6 .8 1 0 20 40 60 80 100 MPCE/100 No Drain Open Drain Closed Drain ANDHRA PRADESH
  15. 15. • Wide caste based disparities in probability for IHL in some states • Convergence of probabilities at lower MPCE in states with less disparities 0 .2 .4 .6 .8 1 0 20 40 60 80 100 MPCE/100 SC/ST OBC General KARNATAKA PredictedProbabilitiesforIHL 0 .2 .4 .6 .8 1 0 20 40 60 80 100 MPCE/100 SC/ST OBC General KERALA 0 .2 .4 .6 .8 1 0 20 40 60 80 100 MPCE/100 SC/ST OBC General TAMIL NADU Caste Status (Social Stratification):
  16. 16. Slum and Non-Slum Areas: • Higher inequalities in access to toilets in highly urbanised states like Gujarat, Maharashtra and Tamil Nadu. .2 .4 .6 .8 1 0 20 40 60 80 100 MPCE/100 Slum Non Slum MAHARSHTRA PredictedProbabilitiesforIHL .2.4.6.8 1 0 20 40 60 80 100 MPCE/100 Slum Non Slum ANDHRA PRADESH .2.4.6.8 1 0 20 40 60 80 100 MPCE/100 Slum Non Slum KARNATAKA Spatial Inequalities:
  17. 17. Caste and Drainage (Interaction) I: Provision of public infrastructures – open drains and closed drains are shown to increase the probabilities of households, irrespective of their social group, to own a toilet. Note: Similar treatment of the data shows significant improvement in the probabilities when improved drinking water is supplied to households. 0 .2 .4 .6 .8 1 0 20 40 60 80 100 MPCE/100 SC/ST OBC General BIHAR (No Drains) PredictedProbabilitiesforIHL 0 .2 .4 .6 .8 1 0 20 40 60 80 100 MPCE/100 SC/ST OBC General BIHAR (Open Drains) 0 .2 .4 .6 .8 1 0 20 40 60 80 100 MPCE/100 SC/ST OBC General BIHAR (Closed Drains)
  18. 18. Caste and Drainage (Interaction) II: For Different States Interaction shown here for two states at their respective median MPCE The slants of the lines show the disparities in probabilities for houeholds to own toilets based on access to different drainage infrastructure The gaps between the lines show the caste based disparities 0 .2 .4 .6 .8 1 Pr(Ihl) No Drain Open Drain Closed Drain Drainage Status SC/ST OBC General UTTAR PRADESH 0 .2 .4 .6 .8 1 Pr(Ihl) No Drain Open Drain Closed Drain Drainage Status SC/ST OBC General TAMIL NADU
  19. 19. Conclusion: • Access to public infrastructure such as drainage and improved drinking water supply have significant effect on access to toilets • Intersectionality: Vertical and horizontal inequalities jointly exacerbate the likelihood to own an in-house toilet • Ownership of toilets is subject to financial, technical, infrastructural and behavioural factors • Existence of group inequalities in different degrees in the states considered and they explain some disparities in access to sanitation services
  20. 20. Policy Implications • Shift from subsidy based policies to infrastructure building programmes for provision of improved water supply and drainage • Explore and innovate in low-cost alternative solutions to improve overall sanitation to prove for unserved and under-served urban population • Mitigate structural inequalities by bringing about urban reforms • Address group inequalities and provide services equally
  21. 21. Thank you Follow us on twitter: @CPRIndia_SCIFI , @CPR_India

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