| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Above 4.7% | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Above 4.8% | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Above 4.9% | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Above 5.0% | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Above 5.1% | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Above 5.2% | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Above 5.3% | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Above 5.4% | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Above 5.5% | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Above 5.6% | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks how the officially reported unemployment rate for India in March 2026 will be categorized across ten outcomes; it matters because that headline statistic is a timely indicator of labor market health and influences policy, markets, and business decisions.
India’s labor market is shaped by a mix of formal-sector hiring, informal and agricultural employment, seasonal cycles, and evolving participation rates. Different data providers and surveys (government releases, private surveys) can show divergent readings, and March sits at the end of India’s fiscal year, when seasonal and policy-driven effects can be especially visible.
Prediction market prices summarize the collective view of traders about which outcome bucket the reported figure will fall into; they move as new information (economic data, policy announcements, surveys) arrives and reflect prevailing uncertainty, not certainties.
Resolution timing and the specific published series are defined by the market’s rules on KALSHI; consult the event’s resolution clause for the named data source and whether the market uses the first published figure, a revised figure, or another defined release.
The ten outcomes divide the range of possible reported unemployment rates into mutually exclusive buckets; at resolution the single outcome whose defined range contains the published March 2026 value pays out, so check the market page for the exact bucket boundaries and payout rules.
Seasonality (including fiscal-year-end effects), the rural agricultural employment cycle, and recent trends in labor force participation and urban hiring are all relevant; also account for differences between survey providers and the likelihood of revisions when comparing past March readings to current expectations.
Major fiscal announcements (new employment programs or public works), significant shifts in monetary policy, large-scale corporate hiring or layoffs, trade shocks, natural disasters, or health emergencies can all change near-term hiring and therefore the reported unemployment figure.
Handling of revisions or methodology changes is governed by the market’s resolution rules; some markets resolve to the first published official number from the named source, while others specify a final revised figure—review the event’s resolution policy or contact KALSHI support for clarification.