An independent economic index
Where growth is felt
but not counted.
A data-driven test of whether official state GDP understates activity where informality runs high, built from RBI GDP, GSTN collections, and PLFS employment across 32 states. The finding, reported in full below, does not support the hypothesis.
Read the findingsThe Informality Gap workbench
A five-year panel of 32 Indian states built from official RBI, GSTN, and PLFS data. The index has no tunable parameter: it is the standardized gap between GST growth and GSDP growth, tested against informal employment. Everything below is real data.
Findings
What the real data shows, including where it contradicts the hypothesis.
The index tests one hypothesis: that official state GDP understates real activity more where the informal economy is larger, which would show up as the formal-sector signal, GST collections, outrunning official GSDP growth by more in high-informality states. Across 32 states and five years, the data rejects it. Regressing the Informality Gap Index on the informal-employment share gives a slope of −2.10 (p = 0.005, R² = 0.24, Pearson r = −0.49). The relationship is negative: higher informality goes with a smaller gap between GST growth and GSDP growth, not a larger one.
The result holds under stress. Dropping the highest and lowest states leaves the slope at −1.65 (p = 0.007). Restricting to the four most recent years leaves it at −1.98 (p = 0.006). Running it with nominal GSDP at current prices instead of real GSDP, so both sides are nominal, gives −2.24 (p = 0.005). Every specification is negative and significant.
The directional check fails, and it is reported here rather than buried. The states expected to sit at the top, Uttar Pradesh, Bihar, and West Bengal, sit below the formal-heavy states Maharashtra, Gujarat, and Tamil Nadu, with a mean gap index of −0.35 against −0.04. Bihar, Jharkhand, and Chhattisgarh are near the bottom. The few states with the largest gaps are small northeastern states where GST grew fast from a tiny base.
What this can claim is narrow. GST is itself a formal-sector tax, so its growth partly reflects formalisation and compliance, which advance fastest in states that are already formal. That plausibly drives the negative sign: the formal signal accelerates where the formal economy is already large, not where informality is high. What this cannot claim is a measure of hidden output. The index is a proxy for the divergence between two official series, and on this data it does not behave the way the informal-economy hypothesis predicted. The honest conclusion is that this proxy does not detect GDP undercounting in high-informality states, and may be picking up formalisation instead.
Does informality predict the gap?
Live OLS of the informal-employment share against the divergence. Informal share is not used to build the index, so this test is not circular. The fitted line and every statistic are computed in your browser from the real panel.
Trajectories over time
How the chosen metric moves across the five survey years, including the sharp 2020-21 COVID contraction. Pick states to compare.
State ranking
Every state ordered by the chosen measure. Red marks the states in the directional sanity check (UP, Bihar, WB and Maharashtra, Gujarat, TN).
All figures are real. Sources: RBI Handbook of Statistics on Indian States (GSDP), GSTN (GST collections), PLFS / MOSPI (informal employment). See DATA_NOTES for methods and limitations.
About
Tremor is an independent research project estimating how much official state GDP figures in India understate real economic activity, using the gap between formal-sector signals and informal employment as an indirect measure.
Official GDP statistics are built primarily from data that formal businesses generate: tax filings, registered production, recorded transactions. But a large share of India's economy runs informally, and informal activity, by definition, doesn't leave the kind of paper trail these statistics depend on. This project doesn't try to measure the informal economy directly. Instead it reads its effects in the divergence between what formal-sector indicators like GST collections suggest and what official growth figures report, the same way a tremor at the surface reveals movement happening where you can't see it directly.
The project builds on questions raised in an earlier research paper on the informal economy, moving from a literature-based argument to a data-driven index that can be tested, checked for robustness, and revised if the evidence doesn't hold up. That earlier work on the informal economy was published in a peer-reviewed journal (IJSSER) and mentored by a Columbia University professor.