Panama

Flag of the Republic of Panama

For Panama, Esri provides a standard demographics dataset sourced from data supplied by Michael Bauer Research GmbH and a bilingual (English/Español) advanced demographics dataset sourced from data supplied by Esri Panama. Visit Where to find ArcGIS Data to learn more about using Esri Demographics.

Release dates

The standard demographics dataset was updated in October 2025; the vintage is 2025 (Unemployed Population 2024).
The advanced demographics dataset was initially released in November 2026; the vintage is 2024.

Settlement points

Esri's Panamanian standard demographics settlement points use the European Commission Global Human Settlement Layer (GHSL), 100-meter resolution 2025 Population Raster Layer. The points were verified using the latest Esri imagery. More information about the data can be found at https://ghslsys.jrc.ec.europa.eu.
The advanced demographics settlement points use the June 2026 Overture Maps Open Data (retrieved from https://registry.opendata.aws/overture). The settlement points contain estimated housing units derived from address points and building footprint polygons. Various additional layers were used to remove possible non-residential points.

Geography levels

Esri geography name	Local geography name	Standard demographics count	Advanced demographics count
Country	Panamá	1	1
Provinces	Provincias	14	13
Districts	Distritos	83	82
Subdistricts	Corregimientos	—	699
Sectors	Sectores	—	963

Visualize demographic data variables

The data browser is an interface to help you visualize and explore the data categories and analysis variables available in Esri Demographics. See Explore data variables to learn more about this visualization tool.

Standard demographics use cases

The Esri standard demographics dataset for Panama is updated with Michael Bauer Research GmbH data updates to this region, approximately every two years. See the Related links section below for a variable list and release notes.

The following sections include example use cases that may help you understand Panamanian standard demographics.

Total Population

Total Population What is measured: The total number of individuals living in a specific area.

How you use it: Population counts are often used by local and national governments for policy planning, resource allocation, and informed decision-making based on the needs of various population groups within a country or region. You can use this data to explore the allocation of public services, economic development, political representation, social research, and resources available for disaster preparedness.

Population Density

Population Density What is measured: The number of people per unit of area (square mile or square kilometer).

How you use it: Population Density is typically used for national and local projects such as infrastructure design, urban planning to allocate and distribute public services, and environmental impact assessments of human activity based on where people are concentrated.

Population per Mill

Population per Mill What is measured: The region's proportional share of the total national population.

How you use it: Population per Mill is used to understand the comparative distribution of population in a country or region based on a per-thousand ratio. This data is used to support market trend analysis, infrastructure planning, and regional and national policy development. Population distribution is often used in health care to track disease prevalence or vaccination rates.

Male/Female Population Totals

Population by Gender Totals What is measured: The total number of females and males in a region's population.

How you use it: Population by Gender counts provide insight into the balance between females and males in a region, which is used for informed decision-making in areas such as education, workforce planning, health care, and skills training. This data is also used to help interpret complex results, such as health-care outcomes, crime statistics, targeted marketing campaigns, and housing shortages.

Population by 15-Year Age and Gender

Population Totals by Age and Gender What is measured: The distribution of regional population across 15-year age groups and gender.

How you use it: Total, Female, and Male Population by 15-Year Age counts can be used to help predict future social and economic trends and to plan for future resource allocation based on age groups in fields such as education, health care, and the labor force. This data is important for identifying potential challenges related to shifts in age or gender ratios within different age brackets.

Total Households

Total Households What is measured: The total number of households in a region.

How you use it: Total Household counts can help you understand the composition of a country's population based on how many people live in a single dwelling or housing unit. This data assists with informed decision-making in areas such as government policy, business strategy, community planning, and social research. You can use household counts to identify community needs, allocate public policy funds, perform business market analysis, and design targeted social programs. Local authorities use household counts to plan for community development projects, considering factors such as housing availability and density.

Average Household Size

Average Household Size What is measured: The median or average size of households (people who share the same living quarters) in a region.

How you use it: Average Household Size data helps you understand the overall population structure and informs policy decisions related to housing, resource allocation, and service provisioning. This data is used to analyze economic trends, specifically consumption patterns, based on the number of people sharing living spaces in a region.

Educational Attainment

Educational Attainment What is measured: Levels of education achieved by individuals in the regional population based on international, standardized metrics.

How you use it: Standardized Educational Attainment categories can improve understanding about the effectiveness of regional education programs. This data can be used to compare educational attainment or metrics across countries, regions, or globally. Standardized Educational Attainment is typically used to assess a country's economic potential, social development, and workforce capabilities. It can also be used to provide the parameters for public policies, workforce training, and social programs and to inform multiregional education program decision-making.

Unemployed Population

Unemployed Population What is measured: The number of individuals actively seeking employment who are currently unemployed in a region.

How you use it: Unemployed Population counts help policymakers, researchers, and businesses identify patterns, target specific job-seeking groups with support programs, and make informed decisions about specific economic policies aimed at reducing unemployment. This data is useful in areas such as job training, education, and regional development, particularly when combined with other variables, such as age, gender, race, education level, and location. Regional unemployment data is used to identify trends and disparities, such as whether specific populations are disproportionately affected by unemployment. This data can inform the design of unemployment benefits, job training programs, and economic stimulus packages tailored to regional demographic needs. Unemployed Population data can also be used to perform labor market analysis, helping predict future market needs, trends, and challenges.

Purchasing Power

What is measured: The ability of individuals or households to buy goods and services in a region. Purchasing Power data consists of four metrics:

Total—The sum of all regional household disposable income.
Per Mill—The region's proportional share of the nation's disposable income.
Per Capita—The per-person average of all regional disposable income.
Index—The comparison of regional disposable income to the national average, which has an index value of 100. For example, if a region's purchasing power index is 89, it has 11 percent less disposable income than the national average; if the region's index is 117, it has 17 percent more purchasing power than average.

How you use it: Purchasing Power data can help improve understanding of the potential consumer market in a country or region, specifically to determine pricing strategies and market potential options. This data can be used to develop targeted product, business, and sales strategies when entering a new market or expanding within an existing one.

Advanced demographics sample questions and use cases

Panama's advanced demographics provide additional insight about this region for most data categories. You will find a range of detailed information about Panamanian regional population, detailed age categories, education, income percentages and discretionary savings, marital status, and spending habits. See the Advanced demographics related links section below for release notes and variable lists in English and Spanish.

Some sample questions that could be answered using Panama's advanced demographics include the following:

What is the child dependency ratio in Arraiján?
What regions have the highest average age in Panama?
How many households in Colón are divorced?
Where is the highest concentration of Panamanian monthly spending on streaming services?

The following sections include example use cases that may help you understand Panamanian advanced demographics.

Purchasing Power: Per Mill

Purchasing power per mill What is measured: The estimated regional population's monthly share of Panama's total disposable income, expressed per thousand people (or per mill).

How you use it: Panamanian purchasing power per mill can be used to optimize B2B and B2C supply chains and pricing strategies for consumer goods companies expanding outside of Panama City. While Panama has a high GDP per capita on paper, economic wealth is heavily concentrated in the capital. By tracking purchasing power per thousand residents across different provinces, businesses can make data-driven expansion decisions.

For example, companies can use this metric to distribute premium goods to high-purchasing-power clusters (like specific zones in Chiriquí or Panama Oeste) while supplying high-volume, budget-friendly items to regions with lower per capita wealth (such as Comarca Ngäbe-Buglé). Instead of applying a uniform pricing model nationwide, fast-moving consumer goods (FMCG) brands can adjust their margins or package sizes to match the hyperlocal financial realities of a specific district's population density.

For retail, banking, or fast-food franchises, tracking purchasing power per mill highlights the exact communities that can support a new brick-and-mortar footprint, balancing raw population count with actual spending capability.

Population by 5-Year Age Cohorts

5-Year Age What is measured: The distribution and proportion of residents grouped into consecutive 5-year intervals (such as 0–4, 5–9, 10–14, and so on) relative to the total population.

How you use it: A primary reason to track Panamanian population by 5-year age cohorts is strategic healthcare resource allocation and infrastructure planning.

Panama is currently experiencing a demographic transition, where some regions retain high youth populations while others are aging rapidly. Segmenting the population into 5-year brackets (for example, 0–4, 60–64, 65–69) allows the Ministry of Health (MINSA) and the Social Security Fund (CSS) to make data-driven decisions.

Regions like the Comarca Ngäbe-Buglé historically maintain much higher fertility rates than urban centers like Panama City. Tracking the 0–4 cohort helps authorities project vaccine quotas, allocate pediatricians, and build localized maternal care clinics where childhood population density is actively growing.
In provinces like Los Santos and Herrera, the population is aging significantly faster than the national average. By monitoring the growth of the 60–64, 65–69, and 70+ brackets, health officials can forecast the local burden of chronic diseases (like diabetes and hypertension) and establish specialized geriatric care facilities before local clinics become overwhelmed.
The Ministry of Education (MEDUCA) can use these specific brackets to predict shifts from primary to secondary school enrollment. If a specific district in West Panama (Panamá Oeste) shows a large spike in the 5–9 age bracket, local government knows to expand primary school capacity and prepare to expand high schools within five years.