Analysing female labour of the North East States and Union territories

The Female Labour Force Participation Rate measures the share of women participating in the labour force. It captures the level of female participation in work or labour-force activity. The Average Annual Percentage Point change measures how quickly that rate changes each year. It is useful for comparing improvement across States and regions.

For example, rural Arunachal Pradesh recorded an AAPP of 8.28 percentage points between 2019–20 and 2025. The rural all-India benchmark was 2.58 points. This means Arunachal Pradesh improved more than three times as quickly as the national average, regardless of its starting level.

These measures answer different questions. FLFPR shows where participation stands, while AAPP shows the speed of movement. The article therefore combines the 2019–20 FLFPR baseline with later AAPP values. That comparison distinguishes States catching up from a low base, States sustaining high participation, and States progressing slowly.

Female labour force participation increased in both rural and urban India between 2019–20 and 2025. The change was much larger in rural areas. This matters because the national figures show not only rising participation, but also a clear difference in the strength of improvement between rural and urban settings.

Rural FLFPR climbed from 33% to 45.9%. That is an increase of 12.9 percentage points over the period. Urban FLFPR rose from 23.3% to 27.7%, an increase of 4.4 percentage points. The rural rise was therefore substantially larger than the urban rise.

The AAPP figures reinforce this contrast. Rural India improved by 2.58 percentage points per year, compared with 0.88 points in urban India. Rural participation thus gained 1.7 percentage points more per year. However, national averages conceal sharp differences among States and Union Territories.

The fastest changes were recorded by Arunachal Pradesh in both rural and urban areas. Its rural AAPP was 8.28 percentage points per year, while its urban AAPP was 5.24 points. These figures were well above the all-India benchmarks of 2.58 points for rural areas and 0.88 points for urban areas.

At the slowest end, Lakshadweep recorded a negative rural AAPP of −2.34 percentage points. Its urban AAPP was also negative, contributing to the urban low of −1.30 points. Other places with negative urban AAPP included Puducherry, Ladakh and Delhi. Delhi and Lakshadweep also recorded rural declines.

The range shows why national averages need careful interpretation. Rural results stretched from +8.28 in Arunachal Pradesh to −2.34 in Lakshadweep. Urban results ranged from +5.24 to −1.30 points. The article also identifies Meghalaya, Nagaland, Manipur, Chandigarh, the Andaman and Nicobar Islands, Assam, Tripura and Jammu and Kashmir as strong urban improvers.

AAPP measures only the pace of change. It does not show the participation level at the beginning of the period. That starting point matters because a State can improve quickly from a low base, or improve quickly while already having relatively high female participation. These are different forms of progress.

Arunachal Pradesh, Assam, Manipur and Tripura began below the rural all-India 2019–20 benchmark but recorded above-average AAPP. They were therefore improving faster while catching up. Nagaland, Meghalaya, Andaman and Nicobar, and Jammu and Kashmir began above the benchmark and also recorded above-average AAPP. Their gains show that rapid improvement can continue from a higher base.

The combined picture is more useful for judging performance. It identifies low-base catch-up, continued progress at high participation levels, and slow movement despite a high starting level. For instance, Ladakh, Sikkim, Puducherry, Mizoram and Lakshadweep had relatively high baselines but below-average AAPP. The baseline prevents misleading comparisons.

The rural–urban AAPP contrast shows where participation has been changing faster. Rural India recorded an average annual increase of 2.58 percentage points, while urban India recorded 0.88 points. Rural improvement was therefore 1.7 percentage points higher each year. This is the clearest national pattern in the data.

The levels tell the same story. Rural FLFPR rose from 33% to 45.9% between 2019–20 and 2025. Urban FLFPR rose from 23.3% to 27.7%. Rural participation began higher and also recorded the larger increase. Arunachal Pradesh led both settings, but the urban spread remained wide, from +5.24 to −1.30 points.

The contrast does not mean every rural State outperformed every urban State. National averages conceal substantial State-level variation. Rural northeastern States and several Union Territories exceeded the rural benchmark, while urban outcomes included strong gains and negative AAPP in Puducherry, Ladakh, Delhi and Lakshadweep.

A State’s starting level and its later pace measure different aspects of progress. States beginning with low participation may gain quickly because their baseline leaves considerable room for improvement. States already near higher levels can also continue gaining if conditions support further participation. Therefore, high starting participation does not automatically mean slow future progress.

Arunachal Pradesh and Assam illustrate low-base improvement. In rural areas, both began below the 2019–20 all-India benchmark but recorded AAPP above the national average. In urban areas, Arunachal Pradesh, Chandigarh, Assam and Tripura combined relatively low baselines with above-average AAPP. Their pattern indicates faster catch-up rather than simply high participation.

Nagaland and Meghalaya show the other pathway. They began with relatively high participation and still recorded above-average AAPP. The article identifies this as continued rapid gain from a higher base. Together, these examples show why baseline and AAPP must be read together to understand changing labour-force geography.

The labour force generally includes people who are working and people available for, or actively seeking, work. FLFPR therefore measures participation in the labour market, not only the number of women currently employed. A rise can mean more women entered work, began looking for jobs, or became available for work.

Several changes can raise participation. Better work opportunities may attract women into jobs. More job-seeking can increase the measured labour force even before employment rises. Education patterns may change when women study or enter work. Household responsibilities can shift, making labour-market participation more feasible. Improvements in how work is measured can also identify activities that were previously missed.

The article establishes rising FLFPR but does not identify which of these mechanisms caused each State’s change. Its evidence shows uneven movement: rural FLFPR rose from 33% to 45.9%, while urban FLFPR rose from 23.3% to 27.7%. Understanding the reasons requires analysis beyond AAPP and baseline comparisons.