Share of population in poverty ($3 a day) 1986

Share of population in poverty ($3 a day) statistics by country with historical data from Our World in Data.

17 data pointsGlobal CoverageWorld Bank (WB)

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Complete Data Rankings

Rank
1
Lesotho flag
Lesotho
62.817
2
Guatemala flag
Guatemala
47.387
3
Iran flag
Iran
21.81
4
Costa Rica flag
Costa Rica
19.264
5
Brazil flag
Brazil
16.68
6
Côte d'Ivoire flag
Côte d'Ivoire
10.419
7
Dominican Republic flag
Dominican Republic
8.717
8
Canada flag
Canada
0.998
9
United States flag
United States
0.747
10
Poland flag
Poland
0.491
11
Israel flag
Israel
0.479
12
Italy flag
Italy
0.247
13
United Kingdom flag
United Kingdom
0.247
14
Norway flag
Norway
0.245
15
Jordan flag
Jordan
0
16
Luxembourg flag
Luxembourg
0
17
Taiwan flag
Taiwan
0

Top 10 Countries

  1. #1Lesotho flagLesotho
  2. #2Guatemala flagGuatemala
  3. #3Iran flagIran
  4. #4Costa Rica flagCosta Rica
  5. #5Brazil flagBrazil
  6. #6Côte d'Ivoire flagCôte d'Ivoire
  7. #7Dominican Republic flagDominican Republic
  8. #8Canada flagCanada
  9. #9United States flagUnited States
  10. #10Poland flagPoland

Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.

Bottom 10 Countries

  1. #17Taiwan flagTaiwan
  2. #16Luxembourg flagLuxembourg
  3. #15Jordan flagJordan
  4. #14Norway flagNorway
  5. #13United Kingdom flagUnited Kingdom
  6. #12Italy flagItaly
  7. #11Israel flagIsrael
  8. #10Poland flagPoland
  9. #9United States flagUnited States
  10. #8Canada flagCanada

Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.

Analysis & Context

Overview of Share of Population in Poverty ($3 a Day) in 1986

The country with the highest share of its population living in poverty at $3 a day in 1986 was Lesotho, with an alarming rate of 62.82%, while the global range of this metric among the 17 countries with available data varied from 0.00% to 62.82%. The average share of the population living in poverty across these nations was 11.21%, and the median was notably lower at 0.75%.

Geographic Disparities in Poverty Rates

The stark differences in the share of the population living in poverty can often be attributed to geographic and economic factors. For instance, Guatemala had the second highest rate at 47.39%, reflecting the challenges faced by Central American countries, such as political instability and limited access to education and healthcare. In contrast, wealthier countries like Canada and the United States exhibited significantly lower poverty rates, at 0.998% and 0.747%, respectively. This disparity highlights how geographic location often correlates with economic opportunity and social safety nets available to citizens.

In Africa, Côte d'Ivoire and Brazil also presented notable figures, with poverty rates of 10.42% and 16.68%, respectively. These rates underscore the ongoing economic challenges in these regions, often exacerbated by historical factors such as colonialism and ongoing political conflicts. Such conditions have a long-lasting impact on economic development and poverty alleviation efforts.

Year-over-Year Changes and Economic Implications

From the data, the average change in poverty rates across the 17 countries was a decrease of 3.81%, or -5.5%. Notably, Brazil experienced the most significant decrease of -15.74%, a reduction of 48.6%, indicating substantial improvements in economic conditions or effective social programs aimed at poverty reduction. This substantial decline may reflect Brazil's economic reforms during the 1980s aimed at stabilizing its economy post-hyperinflation.

Conversely, Canada saw a slight increase of +0.25% (an increase of 33.9%), which may suggest emerging economic challenges or shifts in policy that affected lower-income populations. Similarly, the United Kingdom and United States experienced minor fluctuations, with changes of +0.03% (13.2%) and negligible changes, indicating relative stability in their poverty rates during this period. These patterns demonstrate the complex interplay between economic growth, policy effectiveness, and social welfare systems.

Structural Factors Influencing Poverty Rates

The underlying structural factors contributing to the poverty rates are multifaceted. In countries like Lesotho, high poverty rates are often linked to economic dependency on agriculture, which is vulnerable to climatic changes. Additionally, limited access to education and healthcare exacerbates the cycle of poverty. On the other hand, nations with lower poverty rates, such as Norway (0.244%) and Luxembourg (0%), benefit from robust welfare systems and diversified economies that provide safety nets for their populations.

Furthermore, economic policies play a crucial role in shaping poverty rates. Countries that have implemented effective social safety nets and inclusive economic policies tend to report lower poverty levels. For instance, the comparatively low rates in Poland (0.491%) and Canada (0.998%) can be attributed to their progressive taxation systems and social services that support vulnerable populations.

In conclusion, the data from 1986 on the share of the population living in poverty at $3 a day reveals significant disparities influenced by geographic, economic, and policy-related factors. Understanding these dynamics is essential for crafting targeted poverty alleviation strategies that address the unique challenges faced by different countries.

Data Source

World Bank (WB)

The World Bank is like a cooperative, made up of 189 member countries. These member countries, or shareholders, are represented by a Board of Governors, who are the ultimate policymakers at the World Bank. Generally, the governors are member countries' ministers of finance or ministers of development. They meet once a year at the Annual Meetings of the Boards of Governors of the World Bank Group and the International Monetary Fund.

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Historical Data by Year

Explore Share of population in poverty ($3 a day) data across different years. Compare trends and see how statistics have changed over time.

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