The percentage of income held by the richest 20 percent of the population in Panama decreased by 2.1 percentage points (-3.78 percent) compared to the previous year. Therefore, the percentage of income held in Panama saw its lowest number in that year with 53.5 percent. These figures refer to the share of total income held by the highest 20 percent of earners in a given population.Find more key insights for the percentage of income held by the richest 20 percent of the population in countries like El Salvador and Honduras.

Between 2010 and 2022, Panama's data on the degree of inequality in income distribution based on the Gini coefficient totaled 50.9. This coefficient represents a deterioration compared to last year. Panama was deemed as the third most unequal country in Latin America.

The Gini coefficient measures the deviation of the distribution of income (or consumption) among individuals or households in a given country from a perfectly equal distribution. A value of 0 represents absolute equality, whereas 100 would be the highest possible degree of inequality.

Graph and download economic data for Income Inequality in Bay County, FL (2020RATIO012005) from 2010 to 2023 about Bay County, FL; Panama City; inequality; FL; income; and USA.

Panama: Gini income inequality index: Pour cet indicateur, La Banque mondiale fournit des données pour la Panama de 1979 à 2023. La valeur moyenne pour Panama pendant cette période était de 53.34 index points avec un minimum de 48.7 index points en 1979 et un maximum de 58.6 index points en 1989.

Panama Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 25.400 % in 2023. This records an increase from the previous number of 25.200 % for 2021. Panama Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 30.700 % from Dec 1979 (Median) to 2023, with 29 observations. The data reached an all-time high of 37.300 % in 1989 and a record low of 25.200 % in 2021. Panama Poverty Headcount Ratio at Societal Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Panama Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 2.400 % in 2021. Panama Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 2.400 % from Dec 2021 (Median) to 2021, with 1 observations. The data reached an all-time high of 2.400 % in 2021 and a record low of 2.400 % in 2021. Panama Multidimensional Poverty Headcount Ratio: World Bank: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

National and international tests have yielded low reading comprehension results for education in Panama, although there is limited information regarding literacy development and performance. There are wide gaps in social inequality, access to technology, and public versus private school achievement. Considering this, after a year off from regular face-to-face classes and a partial transition to online education due to the COVID-19 pandemic, the present study utilizes existing data to carry out a pre-post comparison of the reading performance of fourth (n = 167) and sixth (n = 164) grade students in the province of Panama employing a subsample stratified by educational system for comparability (Mann–Whitney U test, α = 0.05). The pre-post comparison was also carried out independently in both the public (n = 235) and private (n = 106) systems, as well as an additional comparison of the average weekly hours of online academic engagement in both systems during the pandemic in fourth (n = 117) and sixth grade (n = 109). The results support a significant decrease in reading performance. Based on the comparative analysis, findings indicate that public school students interacted online with their teachers significantly less than their private schools’ counterparts; and that, in the same sample, only the public-school students exhibited a significant decrease in reading speed by phonological and lexical route with a medium effect size compared to pre-pandemic standards, greater than those reported in other contexts. This highlights the need to develop effective strategies to narrow the existing educational gaps in the country, which seem to have widened due to the pandemic, with particular emphasis on reading performance in primary school.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Panama City. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Panama City, the median income for all workers aged 15 years and older, regardless of work hours, was $42,227 for males and $29,412 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 30% between the median incomes of males and females in Panama City. With women, regardless of work hours, earning 70 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Panama City.

- Full-time workers, aged 15 years and older: In Panama City, among full-time, year-round workers aged 15 years and older, males earned a median income of $55,662, while females earned $45,628, leading to a 18% gender pay gap among full-time workers. This illustrates that women earn 82 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Panama City, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Panama City median household income by race. You can refer the same here

Panama Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data was reported at 1.330 % in 2017. This records an increase from the previous number of 0.610 % for 2008. Panama Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data is updated yearly, averaging 1.330 % from Dec 1997 (Median) to 2017, with 5 observations. The data reached an all-time high of 2.450 % in 2003 and a record low of 0.610 % in 2008. Panama Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Social: Poverty and Inequality. This indicator shows the fraction of a country’s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the 60% median consumption but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).;Global Health Observatory. Geneva: World Health Organization; 2023. (https://www.who.int/data/gho/data/themes/topics/financial-protection);Weighted average;This indicator is related to Sustainable Development Goal 3.8.2 [https://unstats.un.org/sdgs/metadata/].

Income share held by third 20% of Panama surged by 6.40% from 12.50 % in 2021 to 13.30 % in 2023. Since the 1.49% dip in 2019, income share held by third 20% climb by 0.76% in 2023. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.

National and international tests have yielded low reading comprehension results for education in Panama, although there is limited information regarding literacy development and performance. There are wide gaps in social inequality, access to technology, and public versus private school achievement. Considering this, after a year off from regular face-to-face classes and a partial transition to online education due to the COVID-19 pandemic, the present study utilizes existing data to carry out a pre-post comparison of the reading performance of fourth (n = 167) and sixth (n = 164) grade students in the province of Panama employing a subsample stratified by educational system for comparability (Mann–Whitney U test, α = 0.05). The pre-post comparison was also carried out independently in both the public (n = 235) and private (n = 106) systems, as well as an additional comparison of the average weekly hours of online academic engagement in both systems during the pandemic in fourth (n = 117) and sixth grade (n = 109). The results support a significant decrease in reading performance. Based on the comparative analysis, findings indicate that public school students interacted online with their teachers significantly less than their private schools’ counterparts; and that, in the same sample, only the public-school students exhibited a significant decrease in reading speed by phonological and lexical route with a medium effect size compared to pre-pandemic standards, greater than those reported in other contexts. This highlights the need to develop effective strategies to narrow the existing educational gaps in the country, which seem to have widened due to the pandemic, with particular emphasis on reading performance in primary school.

20.70 (%) in 2019. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.

Panama PA: Multidimensional Poverty Index: scale 0-1 data was reported at 0.083 NA in 2017. Panama PA: Multidimensional Poverty Index: scale 0-1 data is updated yearly, averaging 0.083 NA from Dec 2017 (Median) to 2017, with 1 observations. The data reached an all-time high of 0.083 NA in 2017 and a record low of 0.083 NA in 2017. Panama PA: Multidimensional Poverty Index: scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Social: Poverty and Inequality. ;Government statistical agencies. Data for EU countires are from the EUROSTAT;;

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Panama City Beach. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Panama City Beach, the median income for all workers aged 15 years and older, regardless of work hours, was $53,041 for males and $33,732 for females.

These income figures highlight a substantial gender-based income gap in Panama City Beach. Women, regardless of work hours, earn 64 cents for each dollar earned by men. This significant gender pay gap, approximately 36%, underscores concerning gender-based income inequality in the city of Panama City Beach.

- Full-time workers, aged 15 years and older: In Panama City Beach, among full-time, year-round workers aged 15 years and older, males earned a median income of $67,226, while females earned $55,584, leading to a 17% gender pay gap among full-time workers. This illustrates that women earn 83 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Panama City Beach.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Panama City Beach median household income by race. You can refer the same here

Panama PA: Multidimensional Poverty Headcount Ratio: Female: % of female population data was reported at 18.500 % in 2017. Panama PA: Multidimensional Poverty Headcount Ratio: Female: % of female population data is updated yearly, averaging 18.500 % from Dec 2017 (Median) to 2017, with 1 observations. The data reached an all-time high of 18.500 % in 2017 and a record low of 18.500 % in 2017. Panama PA: Multidimensional Poverty Headcount Ratio: Female: % of female population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Social: Poverty and Inequality. ;Government statistical agencies. Data for EU countires are from the EUROSTAT;;

Panama PA: Multidimensional Poverty Headcount Ratio: Household: % of total households data was reported at 12.200 % in 2017. Panama PA: Multidimensional Poverty Headcount Ratio: Household: % of total households data is updated yearly, averaging 12.200 % from Dec 2017 (Median) to 2017, with 1 observations. The data reached an all-time high of 12.200 % in 2017 and a record low of 12.200 % in 2017. Panama PA: Multidimensional Poverty Headcount Ratio: Household: % of total households data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Social: Poverty and Inequality. ;Government statistical agencies. Data for EU countires are from the EUROSTAT;;

Panama PA: Multidimensional Poverty Headcount Ratio: % of total population data was reported at 19.100 % in 2017. Panama PA: Multidimensional Poverty Headcount Ratio: % of total population data is updated yearly, averaging 19.100 % from Dec 2017 (Median) to 2017, with 1 observations. The data reached an all-time high of 19.100 % in 2017 and a record low of 19.100 % in 2017. Panama PA: Multidimensional Poverty Headcount Ratio: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Social: Poverty and Inequality. ;Government statistical agencies. Data for EU countires are from the EUROSTAT;;

Based on the degree of inequality in income distribution measured by the Gini coefficient, Colombia was the most unequal country in Latin America as of 2022. Colombia's Gini coefficient amounted to 54.8. The Dominican Republic recorded the lowest Gini coefficient at 37, even below Uruguay and Chile, which are some of the countries with the highest human development indexes in Latin America. The Gini coefficient explained The Gini coefficient measures the deviation of the distribution of income among individuals or households in a given country from a perfectly equal distribution. A value of 0 represents absolute equality, whereas 100 would be the highest possible degree of inequality. This measurement reflects the degree of wealth inequality at a certain moment in time, though it may fail to capture how average levels of income improve or worsen over time. What affects the Gini coefficient in Latin America? Latin America, as other developing regions in the world, generally records high rates of inequality, with a Gini coefficient ranging between 37 and 55 points according to the latest available data from the reporting period 2010-2023. According to the Human Development Report, wealth redistribution by means of tax transfers improves Latin America's Gini coefficient to a lesser degree than it does in advanced economies. Wider access to education and health services, on the other hand, have been proven to have a greater direct effect in improving Gini coefficient measurements in the region.

Panama PA: Poverty Gap at $6.85 a Day: 2017 PPP: % data was reported at 4.800 % in 2023. This records an increase from the previous number of 4.700 % for 2021. Panama PA: Poverty Gap at $6.85 a Day: 2017 PPP: % data is updated yearly, averaging 13.600 % from Dec 1979 (Median) to 2023, with 29 observations. The data reached an all-time high of 29.800 % in 1989 and a record low of 4.300 % in 2019. Panama PA: Poverty Gap at $6.85 a Day: 2017 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Social: Poverty and Inequality. Poverty gap at $6.85 a day (2017 PPP) is the mean shortfall in income or consumption from the poverty line $6.85 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Panama PA: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data was reported at 9.100 Intl $/Day in 2023. This records a decrease from the previous number of 9.580 Intl $/Day for 2018. Panama PA: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data is updated yearly, averaging 9.340 Intl $/Day from Dec 2018 (Median) to 2023, with 2 observations. The data reached an all-time high of 9.580 Intl $/Day in 2018 and a record low of 9.100 Intl $/Day in 2023. Panama PA: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) of the bottom 40%, used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.