Making Different Elections Comparable
TL;DR
The solution is a translation step.
The limits of direct comparison
By this point, two things are clear: projecting the latest election forward does not work, and comparing elections directly does not work either. The problem is not a lack of data. It is that different elections are being treated as if they speak the same language. They do not.
A better question
Instead of asking which election result should be trusted most, the better question is: what does this election result mean in Assembly terms?
Assembly-equivalent vote share
The Assembly election becomes the reference frame. Not because it is more important, but because it is the outcome being estimated. For every non-Assembly result, the question is: what does that result usually translate to in an Assembly election?
Party-specific translation
Here is where the earlier insight matters. The translation is not the same for every alliance. From historical data: LDF tends to gain when moving into Assembly elections. UDF tends to lose. NDA's relationship is more volatile.
| Conversion | NDA | UDF | LDF |
|---|---|---|---|
| Lok Sabha → Assembly | +0.5% | -5.6% | +6.8% |
| Local → Assembly | -0.5% | +1.6% | +5.7% |
Historical average offsets. Positive means the alliance does better in Assembly than the source election.
This table shows why a single adjustment cannot work. Each alliance needs its own translation rule.
What this fixes, and what it does not
This translation step makes different elections comparable, respects alliance-specific behavior, and turns raw percentages into meaningful indicators.
The results still need to be combined. Translation provides a better starting point, not the answer.