Poverty, Employment & Human Development

A family may cross the rupee line and still be poor in every way that matters — no toilet, no clean fuel, a child out of school, a mother anaemic. To capture this, NITI Aayog publishes the National Multidimensional Poverty Index (National MPI), built on the globally used Alkire–Foster method developed with UNDP and OPHI. Its data source is the National Family Health Survey (NFHS).

On both NITI Aayog National MPI reports — the baseline (NFHS-4, 2015-16) and the second (NFHS-5, 2019-21) — Bihar recorded the highest multidimensional poverty head-count ratio among all States. But read the second number too: Bihar also showed one of the sharpest declines in the country between the two rounds. Bihar is simultaneously India's poorest large state and one of its fastest-improving. Write both halves of that sentence in a Mains answer.

• Recurring floods. North Bihar is among India's most flood-prone regions — the Kosi ("Sorrow of Bihar"), Gandak, Burhi Gandak and Bagmati destroy standing crops, homes and assets almost every year, pushing recovered families back into poverty.
• Low industrialisation. The bifurcation of 2000 gave the mineral and heavy-industry belt to Jharkhand, leaving Bihar with farming. The long-running freight equalisation policy had already removed the cost advantage of locating factories near coal and iron.
• Land fragmentation. Very high population density and inheritance-based division have left most holdings marginal (below one hectare), too small to generate a surplus or bear risk.
• Out-migration. With few local jobs, working-age men migrate to Delhi, Punjab, Haryana, Gujarat and Maharashtra. Remittances support households but the skill and energy of the young leave the state.
• Low urbanisation and a very young population. Census 2011 put Bihar's urban population at only about 11%, among the lowest in India, while a large child population raises the dependency ratio.

A person is unemployed only if three things are true together: he is able to work, willing to work at the going wage, and actively seeking or available for work — yet has no work. Miss any of the three and he is simply outside the labour force. Now, unemployment wears several faces, and the paper almost always tests you on matching the face to the name.

Until 2017, employment data came from the NSSO's five-yearly Employment–Unemployment Surveys. Since April 2017 the National Statistical Office (NSO) runs the Periodic Labour Force Survey (PLFS), which gives far more frequent estimates — annual figures for rural and urban India, plus quarterly urban bulletins. PLFS is now the standard source for every employment number you quote.

• Usual Status (US, ps+ss): reference period of the last 365 days. A person is counted employed if he worked for a relatively longer part of the year. Because the window is long, this gives the lowest unemployment rate.
• Current Weekly Status (CWS): reference period of the last 7 days. A person is employed if he worked for at least one hour on any one day of that week.
• Current Daily Status (CDS): counts each half-day of the last 7 days as employed or unemployed and adds up person-days. It captures intensity of work, so it reveals underemployment and gives the highest unemployment rate.

One more structural fact frames everything: India's workforce is overwhelmingly informal / unorganised — commonly cited as around nine out of ten workers — meaning no written contract, no paid leave, no social security, and no protection when a shock like a lockdown or a flood arrives. Bihar's labour force is even more heavily agricultural and informal than the national average, which is why welfare programmes rather than labour law do the heavy lifting here.

The keystone is MGNREGA. The Act was passed in 2005 (as NREGA; renamed Mahatma Gandhi NREGA in 2009) and it does something no earlier scheme did: it makes employment a legal right. Every rural household whose adult members volunteer for unskilled manual work is entitled to at least 100 days of wage employment in a financial year. It is demand-driven — work must be provided on demand, within 15 days, ordinarily within 5 km of the village, failing which an unemployment allowance is payable. At least one-third of beneficiaries are to be women.

Why does MGNREGA matter so much in Bihar specifically? Because Bihar exports labour. When work dries up at home, families migrate; when migration breaks down — as it did during the COVID-19 lockdown of 2020, when lakhs of Bihari workers walked home — MGNREGA is the only employer of last resort standing in the village. It also stabilises rural wages and, through pond-digging, embankment and plantation works, can be turned towards flood-proofing the very districts that need it most.

• Saat Nischay (Seven Resolves) — I, announced 2015. Bihar's own development charter. Its resolves cover: employment and self-help support for youth (Student Credit Card, Kushal Yuva Program, Swayam Sahayata Bhatta); 35% reservation for women in state government jobs; electricity to every household; piped drinking water to every household (Har Ghar Nal ka Jal); pucca lanes and drains; household toilets and sanitation; and expanded higher-education opportunities.
• Saat Nischay-II, announced 2020. The second-generation charter, broadly covering youth skills and entrepreneurship (Yuva Shakti), women's empowerment (Sashakt Mahila), irrigation water to every field, clean villages and clean cities, better connectivity, and health facilities for all.

HDI is the geometric mean of the three normalised indices and ranges from 0 to 1. Countries are grouped into very high, high, medium and low human development. India has been placed in the medium human development group, ranking in roughly the 130s among about 190 countries in recent Human Development Reports — with the value and rank improving gradually. Quote the group and the direction confidently; be careful with the exact rank, since it changes every report.

• Inequality-adjusted HDI (IHDI): the HDI discounted for inequality in each of the three dimensions. If a society were perfectly equal, IHDI would equal HDI; the gap between HDI and IHDI is the "loss" due to inequality.
• Gender Inequality Index (GII): measures gender-based disadvantage across reproductive health, empowerment and the labour market. Careful — a higher GII means MORE inequality, the opposite of HDI. (The Gender Development Index is different: it is the ratio of female HDI to male HDI.)
• Multidimensional Poverty Index (MPI): the UNDP–OPHI index of overlapping deprivations, launched in 2010 in place of the older Human Poverty Index; NITI Aayog's National MPI is India's adaptation of it.

To measure inequality itself, economists use the Lorenz curve — a graph (given by Max Lorenz, 1905) plotting the cumulative share of population against the cumulative share of income. A 45° straight line would mean perfect equality; the more the curve sags away from that line, the greater the inequality. The Gini coefficient (Corrado Gini, 1912) converts that sag into a single number: the area between the line of equality and the Lorenz curve, as a fraction of the whole triangle. 0 = perfect equality, 1 = perfect inequality — so, like GII, a higher Gini is worse.

Finally, the global framework. The Sustainable Development Goals — 17 goals and 169 targets — were adopted by the UN in September 2015 as the 2030 Agenda for Sustainable Development, succeeding the eight Millennium Development Goals (2000–2015). In India, NITI Aayog is the nodal body and publishes the SDG India Index, which scores every State and UT out of 100 and classifies them as Aspirant, Performer, Front Runner or Achiever. Bihar has typically been placed at or near the bottom of this index — while steadily raising its own score from one edition to the next.

Now put the state's numbers on the table. Census 2011 recorded Bihar's literacy rate at 61.8% — the lowest among all Indian States — against an all-India figure of 74.0%. Within that, male literacy was about 71.2% and female literacy about 51.5%, so nearly one in two Bihari women could not read. That single gap explains much of the state's position on health, nutrition and fertility indicators, because a mother's schooling shapes her family's outcomes more than almost any other variable.

On spending, note the direction rather than a shifting rupee figure: Bihar devotes a notably high share of its total budget to education — among the highest shares among Indian States — and has been raising health spending, expanding health sub-centres, ASHA coverage and institutional deliveries. The catch is the low base: a poor state's high percentage is still a small amount per child and per patient. That is the honest answer to "why does Bihar spend so much and rank so low?"