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Thai Revenue Inequality: Provinces vs Industries Gini 2026

Updated 10 October 2026Data as of 17 July 2026Verified

In short

Geography is the most unequal way to slice Thai revenue. The 77 provinces score a Gini of 0.8845, as of 17 July 2026. Bangkok alone books 63.14 percent of province revenue. The 1,196 revenue-bearing 5-digit codes score 0.8655, and the 21 sections score 0.8114. Place concentrates money harder than industry does.

0.88
Province Gini
77 named provinces
0.87
Industry code Gini
1,196 codes with revenue
0.81
Industry section Gini
21 sections
63.1%
Bangkok share of province revenue
48.4%
Wholesale and retail share of section revenue

Is Thai revenue more unequal by place or by industry?

By place. A Gini coefficient built only from revenue shares scores 0.8845 across the 77 named provinces (DBD, 2026). The 1,196 five-digit industry codes that report revenue score 0.8655. The 21 industry sections score 0.8114. Zero means every slice earns the same and one means a single slice earns everything, so all three views sit in extreme territory. The ranking is still clear. Province comes first, codes second, sections third. Bangkok drives the province result, because it books 63.14 percent of all province revenue on its own. The next four provinces, Samut Prakan, Chon Buri, Rayong and Pathum Thani, bring the top five to 80.54 percent. The 38 smallest provinces share just 2.32 percent between them.

Gini coefficient of revenue by way of slicing, times 100

  • 77 provinces88
  • 1,196 five-digit codes87
  • 21 industry sections81

Figures in Gini times 100.

Higher means revenue is packed into fewer slices. All three views score above 81.

How much the biggest slices hold

ViewSlicesGiniLargest sliceTop 5 slicesTop 10 slices
Province770.884563.14%80.54%88.08%
Industry section210.811448.38%89.48%96.62%
5-digit code1,1960.865512.79%27.26%34.51%

Share of total revenue held by the largest slices in each view, as of 17 Jul 2026.

The five provinces that make up 80 percent of revenue

ProvinceRevenue share
Bangkok63.14%
Samut Prakan6.02%
Chon Buri4.76%
Rayong4.00%
Pathum Thani2.62%

Revenue share of the five largest provinces among the 77 named provinces, as of 17 Jul 2026.

Why a single Gini hides two different stories

The section view and the code view tell different tales underneath high scores. Wholesale and retail trade holds 48.38 percent of section revenue, and manufacturing adds 31.38 percent, so two sections carry 79.76 percent. Inside the code view, no single code holds more than 12.79 percent. Sections are broad buckets, so a few giant ones dominate. Codes cut the same money into 1,196 pieces, which spreads the top but leaves a long tail of tiny codes. The bottom half of codes holds only 0.85 percent of revenue. Geography has no such buffer. A company sits in one province, and most of the big ones sit in Bangkok and the eastern industrial belt.

Why this matters

Anyone sizing a Thai market should check the map before the industry list. A sector story can look broad and still be a Bangkok story, because the capital holds nearly two baht in every three. Regional strategies face the opposite problem. Thirty-eight provinces together are worth about two baht in every hundred, so a national rollout built on provincial averages will mislead. The honest takeaway is that inequality here is structural. It shows up whether you cut by place, by section or by code. What differs is where the weight lands, and place carries the most.

Definitions

Gini coefficient
A measure of inequality from zero to one. Zero means every slice has an equal share and one means a single slice has everything. Here it is computed from revenue shares of provinces, sections or codes, not from people or incomes.
TSIC section
One of 21 lettered top-level industry groups in the Thai Standard Industrial Classification, such as wholesale and retail trade or manufacturing.
5-digit TSIC code
The most detailed level of the Thai Standard Industrial Classification used in the registry, a finer split of each section.
Revenue share
A slice's total reported revenue divided by the total across all slices in the same view.

Assumptions

Methodology

All figures come from filed financial statement revenue aggregates in the Department of Business Development registry, as of 17 July 2026. Province shares use the 77 named provinces, which are Bangkok plus 76 others. Two province rows with no name are excluded, one of which has no revenue. Section shares use all 21 sections. Code shares use the 1,196 of 1,228 five-digit codes with positive revenue. The Gini coefficient is computed from revenue shares alone, using the standard sorted-share formula, with no concentration ratios or HHI. Revenue is as reported by companies and is not adjusted for double counting between firms.

How we verified this

References

  1. Department of Business Development. (2026). Registered juristic persons and financial statement aggregates. Ministry of Commerce, Thailand. https://www.dbd.go.th/

Frequently asked questions

Is Thai revenue more concentrated by province or by industry?

By province. The province Gini is 0.8845, against 0.8655 for 5-digit codes and 0.8114 for sections, as of 17 July 2026.

How much revenue does Bangkok hold?

Bangkok holds 63.14 percent of revenue across the 77 named provinces, based on filed financial statements in the DBD registry.

Why is the section Gini lower than the code Gini?

A Gini depends on how many slices there are. Codes split revenue into 1,196 pieces, many of them tiny, which lengthens the tail and lifts the score above the 21-section figure.

Does a high Gini mean the economy is unhealthy?

No. It describes how revenue is spread across places or industries, not whether the economy is performing well. Large firms cluster in a few places and sectors in almost every country.

Cite this page

Chatpong L. (2026). Thai Revenue Inequality: Provinces vs Industries Gini 2026. Max Data Insights. https://maxdatathailand.com/insights/how-unequal-is-thai-revenue-across-provinces-sections-and-industry-codes-2026

Data & corrections

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Written by

Chatpong L.

Founder, Max Data, Max Solutions Co., Ltd.

Chatpong L. leads Max Data, a company-intelligence platform built on Thailand's official business registry. He writes about the structure of the Thai economy using primary registry data. His work covers company formation, industry concentration, and regional business activity.

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This page reports company-level and aggregate statistics only. It names no individuals and makes no claims about any person. Figures are provided for information and may be revised as source data updates.