## Regional Income Disparaties in Panama

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**Canonical URL:** [Regional Income Disparaties in Panama](https://www.imf.org/-/media/files/publications/selected-issues-papers/2025/english/sipea2025125.pdf)

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### A. Introduction and Background
- Panama’s Gini coefficient in 2019 was 49.1, compared with a world average of 39.7 and a Latin America & Caribbean average of 47.9.
- High income inequality in Panama is driven largely by income inequality between regions rather than within regions.
- Urban Panama Canal corridor (including Panama City and Colón) concentrates shipping, logistics, trade and tourism, generating high labor productivity and higher incomes.
- Rural and indigenous provinces face structural constraints—poor infrastructure, limited access to health and education services, and weak market linkages—that keep output and employment rates low.
- Household income contrasts:
  - In urban provinces like Panamá and Panamá Oeste, a large share of families earn more than B/.1,000 per month.
  - In comarcas such as Guna Yala, the majority earn under B/. 250 per month.
- Accounting decomposition summary:
  - Regional differences in per capita GDP are largely the result of differences in labor productivity.
  - Variations in employment rates also contribute but to a much smaller extent.
  - Productivity differences are related to population density, sectoral composition (share of agriculture), informal employment, infrastructure gaps, educational attainment, and access to healthcare.

### B. Regional Overview
- Urban provinces:
  - Panama City: principal financial and commercial hub; concentration of high-value financial services, global enterprises, and premium real estate.
  - Colón: trade and maritime center anchored by the Colón Free Trade Zone; supports logistics-related employment.
  - Chiriquí: export-oriented agriculture (coffee, livestock); David as regional trade node; Boquete as tourism destination.
- Rural provinces:
  - Bocas del Toro: tourism, banana cultivation, artisanal fishing; constrained by inadequate infrastructure and limited formal employment.
  - Veraguas: diversified economy (agriculture, fisheries, nascent ecotourism); limited industrial investment and value-addition capacity.
  - Darién: least developed; subsistence agriculture, forestry, informal cross-border trade; geographic isolation and weak transport networks.
- Indigenous comarcas:
  - Ngäbe-Buglé, Emberá-Wounaan, Guna Yala record the lowest per-capita incomes and highest poverty incidence.
  - Economic activities are small-scale agriculture, fishing, traditional crafts, coastal fishing, coconut production and niche tourism, with restrictive land-tenure and scarce public investment limiting expansion.

### C. Differences in Per Capita GDP: A Bookkeeping Perspective
- Employment-to-population ratios:
  - Panamá Province: 63 percent (highest).
  - Chiriquí: 38 percent.
  - Ngäbe-Buglé Comarca: 40 percent.
  - Veraguas: 41 percent.
- Employment gaps vs. income impact:
  - Example: If Ngäbe-Buglé matched Panamá Province’s employment rate, its per capita GDP would increase from approximately USD 2,000 to about USD 3,000.
  - Nonetheless, employment differences explain only a small fraction of regional GDP per capita gaps.
- Labor productivity:
  - Urban regions (Panama City, Colón) have the highest labor productivity and GDP per capita.
  - Rural provinces (Herrera, Los Santos, Chiriquí) have modest productivity.
  - Darién and Veraguas lag further behind.
  - Indigenous comarcas (Ngäbe-Buglé, Guna Yala) have the lowest productivity and GDP per capita.
- Decomposition magnitudes (relative to Panamá):
  - Ngäbe‑Buglé: roughly –2.0 log‑points from lower productivity and less than –0.3 log‑points from reduced employment.
  - Guna Yala: ≈–1.5 log‑points productivity shortfall vs. –0.5 log‑points employment gap.
  - Mid‑tier provinces (Veraguas, Darién, Bocas del Toro): productivity deficits of around –0.5 to –0.6 log‑points.
  - Colón, Chiriquí, Panamá Oeste: near zero in both productivity and employment differences.
  - Across low-GDP regions, labor productivity gaps dominate employment-rate differences.

### D. Factors Explaining the Differences
- Population density:
  - Higher population density correlates with higher labor productivity through agglomeration economies, knowledge spillovers, and labor market efficiencies.
  - Panamá and Panamá Oeste are the wealthiest regions and rank highest in weighted population density.
  - Sparsely inhabited comarcas (Ngäbe‑Buglé, Emberá‑Wounaan) combine low densities with the lowest GDP per capita.
- Share of agriculture:
  - Heavy reliance on agriculture in low-density areas lowers productivity because value‑added per worker in farming is far below industry and services.
  - In Panamá and Colón fewer than one in ten workers are in agriculture; average productivity is much higher there.
  - Droughts and low rainfall in Herrera and Los Santos have depressed crop yields and regional productivity.
- Informal employment:
  - Informality rates:
    - Ngäbe‑Buglé: roughly 72 percent of jobs informal.
    - Guna Yala: roughly 91 percent of jobs informal.
    - Panamá Province: 44 percent informal.
    - Colón: 46 percent informal.
  - High informality limits formal contracts, access to credit, skills training and capital investment, depressing output per worker.
- Indigenous population shares:
  - Regions with larger indigenous populations generally have lower incomes.
  - In Panama City and Colón indigenous peoples account for less than 10 percent of residents.
  - In some rural provinces and comarcas indigenous shares reach as high as 76 percent, coinciding with the lowest GDP per capita.
  - The gap reflects underinvestment in infrastructure, schooling and services affecting indigenous communities.
- Educational attainment:
  - Urban provinces (Panamá, Colón): about one in three adults have a university degree.
  - Ngäbe‑Buglé: 7 percent of residents never complete a formal degree; 14 percent go on to university.
  - Darién: almost 30 percent of adults have no degree or only a primary degree.
  - Low schooling limits access to higher-paying jobs and training, perpetuating productivity gaps.
- Healthcare access:
  - Health professionals per 1,000 residents:
    - Ngäbe‑Buglé: 0.25 per 1,000.
    - Emberá‑Wounaan: 0.17 per 1,000.
    - Guna Yala: 1.66 per 1,000.
  - Urban provinces (Panamá, Herrera) have the highest ratios; Darién and Panamá Oeste suffer shortages.
  - Uneven health staffing reduces human‑capital development and worker productivity.
- Transportation infrastructure:
  - Road network density affects market access and mobility.
  - Provinces with more than 1,000 km of roads: Panamá, Coclé, Colón.
  - Comarca Guna Yala: ~30 km of roads, severely limiting mobility.
  - Chiriquí and Veraguas: over 3,000 km of roadways apiece, linking agricultural areas to processing and export points.

### E. Conclusion
- Panama’s pronounced income inequality is partly a consequence of stark interregional disparities in per‑capita output.
- Accounting decomposition shows differences in labor productivity account for the bulk of regional GDP per capita gaps; employment‑to‑population differences are secondary.
- Urban provinces around the Canal corridor (Panamá, Panamá Oeste, Colón) have high productivity due to dense economic activity in services, logistics and trade.
- Rural provinces and indigenous comarcas face low productivity due to:
  - Low population density.
  - Heavy reliance on low‑value agriculture.
  - High informality.
  - Limited educational attainment.
  - Uneven health‑care access.
  - Sparse transport and other infrastructure.
- Measured labor productivity shortfalls across almost every region outside the Canal corridor range from 0.5 to over 2 log‑points and largely drive the divergence in incomes.

*Prepared by Mai Hakamada; IMF Selected Issues Paper SIP/2025/125 (completed July 9, 2025).*

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_Source: https://www.imf.org/-/media/files/publications/selected-issues-papers/2025/english/sipea2025125.pdf_