Editorial 1 : Declining poverty ratio: a continuing trend
Context
The release of the fact sheet of the Household Consumption Expenditure Survey for 2022-23 (HCES) by the National Sample Survey Office (NSSO) led to estimations of poverty and inequality trends by many researchers. Some of these studies also discussed comparability of data and measurement issues.
Trends in poverty, inequality
- The estimated poverty ratios declined from 29.5% in 2011-12 to 10% in 2022-23 (1.77% points per year) based on the Rangarajan Committee’s poverty lines and from 21.9% in 2011-12 to 3% in 2022-23 (1.72% points per year) based on the Tendulkar Committee’s poverty lines.
- According to the estimates on inequality provided by Subramanian, between 2011-12 and 2022-23, the Gini coefficient declined from 0.278 to 0.269 for rural areas (0.009-point decline); and from 0.358 to 0.318 for urban areas (0.04-point decline).
- This means poverty declined significantly between 2011-12 and 2022-23, though the rate of decline was lower compared to the 2004-05 to 2011-12 period.
- Inequality declined between 2011-12 and 2022-23 particularly in urban areas. It is to be noted that all these estimates depend on where the poverty line is drawn.
- The NSSO has changed the reference or recall period of data collection over time to improve the reporting of consumption.
- Three estimates of consumption are available depending upon the recall period of different types of expenditure: uniform reference period (URP); mixed reference period (MRP); and modified mixed reference period (MMRP).
- Experts say the varying reference periods for different items underlying the MMRP estimates may be expected to yield estimates that are closer to their true value.
- The Tendulkar Committee estimated poverty ratios on the basis of MRP for 1993-94 and 2004-05.
- However, the Rangarajan Committee used MMRP for estimating poverty ratios for 2009-10 and 2011-12. These estimates are comparable with those of 2022-23.
- For the sake of comparability, we cannot give up what is considered to be the appropriate mix of the recall periods.
Measurement issues
- The Expert Group (Tendulkar) did not construct a poverty line. It adopted the officially measured urban poverty line of 2004-05 based on the Expert Group (Lakdawala) methodology and converted this poverty line, which is URP-consumption based, into MRP-consumption.
- It took the urban poverty line as derived from the Lakdawala line as given and derived from it the rural poverty line.
- The urban poverty line used by the Lakdawala Committee had calorie norms and so, the Tendulkar Committee also indirectly used these norms.
- The poverty line is based on private consumption expenditure. If we take into account public expenditure, the actual well being of the household will be higher than what is indicated by the poverty line.
- The HCES 2022-23 tried to get imputed values for some items of public expenditure. The value figures for items received free entirely or at low prices by the households have been imputed using an appropriate method.
- However, a look at the average monthly per capita expenditure (MPCE) shows it captured little of the total public expenditure on subsidised and free items given to the households.
- The average MPCE with imputation as compared to MPCE without imputation was only 2.3% higher for rural areas and 0.96% for urban. We need to capture these values better as public expenditure on these items is substantial.
Conclusion
Thus, there has been a decline in poverty. The inequality in consumption expenditure has come down a bit. Usually, income inequality is higher than inequality in consumption expenditure. There is no unique way of measuring poverty. The higher the poverty cut off, the more will be the number of poor.
Editorial 2 : An overview of the Smart Cities Mission
Context
The Smart Cities Mission was launched on June 25, 2015, with the key objective of promoting cities to provide core infrastructure, clean and sustainable environment and give a decent quality of life to their citizens through the application of ‘smart solutions’.
Defining smart cities
- The term ‘Smart City’ has been used widely ever since 2009, after the great financial crash.
- Smart cities were defined by urban practitioners as new Silicon Valleys built with a strong integration of a network of airports, highways, and other types of communications, a so-called intellectual city with advanced ICT.
- Hundred cities were selected for five years under the mission. However, the mission did not clearly define a smart city.
- It stated, “there is no universally accepted definition of a Smart City.... The conceptualisation of Smart City... varies from city to city and country to country, depending on the level of development, willingness to change and reform, resources and aspirations of the city residents.
Mission strategy
- Pan-city initiative in which at least one Smart Solution is applied city-wide
- Develop areas step-by-step – three models of area-based developments
- Retrofitting,
- Redevelopment,
- Greenfield
The core infrastructure elements
- Adequate water supply,
- Assured electricity supply,
- Sanitation, including solid waste management,
- Efficient urban mobility and public transport,
- Affordable housing, especially for the poor,
- Robust IT connectivity and digitalization,
- Good governance, especially e-Governance and citizen participation,
- Sustainable environment,
- Safety and security of citizens, particularly women, children and the elderly, and
- Health and education.
The Financing
- The Smart City Mission operated as a Centrally Sponsored Scheme (CSS) and the Central Government proposes to give financial support to the Mission to the extent of Rs. 48,000 crores over five years i.e. on an average Rs. 100 crore per city per year.
- An equal amount, on a matching basis, will have to be contributed by the State/ULB; therefore, nearly Rupees one lakh crore of Government/ULB funds will be available for Smart Cities development.
Concerns/Challenges
- The selection of 100 cities on a competitive basis was flawed due to the diversity in existing urban realities. The scheme was divorced from the ground realities of urban India — the urbanisation here is dynamic and not static like the West.
- The SCM became an exclusionary scheme wherein not more than 1% of a city’s geographical area was selected for development. State and local governments lack fine-grained data or the capability to analyse them in order to understand the evolving needs of their communities.
- Additionally, the SPV model designed for smart cities was not aligned with the 74th Constitutional Amendment, which led to many cities objecting to the governance structure.
- In the name of executing smart city projects, there was displacement of people living in poorer localities. Street vendors, for example, were displaced and urban commons were disrupted.
- Another major consequence of the SCM has been enhanced urban flooding. Some of the towns which have historically never been flooded were made vulnerable because of infrastructure development projects that spoiled or dismantled the water channels and contours.
Way forward
- Smart cities cannot be a solution to urban crisis happening in India. It needs understanding of problem rationally through data collected systematically.
- Since the smart cities programme aims at affordable housing and modern transportation, government has to facilitate smoother land acquisition with appropriate rehabilitation and resettlement
- Citizen participation is important right from policy inputs, implmentation and execution because citizens are the ultimate beneficiaries of smart cities.
- Smart cities development requires smart leadership which has to come from all the three tiers of the government.