Suriname Survey of Living Conditions: 2016-2017
Metadata & use
| Identifier | https://doi.org/10.60966/vrk6-j676 |
|---|---|
| License | Creative Commons Attribution–NonCommercial–NoDerivs 3.0 IGO |
| Citation |
Beuermann, Diether, et al. (2018). Suriname Survey of Living Conditions: 2016-2017. IDB Open Data. https://doi.org/10.60966/vrk6-j676 |
| Published date | 2018-09-07 |
| Modified date | 2026-10-02 |
| Tags/Keywords | Consumption · Living Conditions |
| Language |
|
| In Series | Living Conditions Datasets |
| Temporal coverage | 2016-2017 |
| Country |
Suriname
|
| Region | Latin America and the Caribbean |
| Publisher |
Inter-American Development Bank
|
| Author |
Beuermann, Diether
Flores Cruz, Ramiro
Electricity Bureau of Suriname
|
| Data collection type | Survey Data |
| Statistical type | Cross-sectional Data |
| Data structure | Structured Data |
| Data notes |
What is the Suriname Survey of Living Conditions?The Suriname Survey of Living Conditions (SSLC) is a comprehensive national survey that measures the living conditions of people in Suriname. It provides the main source of official statistics on household welfare, poverty, and inequality in the country. When was the survey conducted?Fieldwork took place between October 2016 and September 2017, covering a full 12-month cycle. This ensured that the data reflected seasonal variations in employment, consumption, and income. What aspects of living conditions does it measure?The dataset covers multiple dimensions of Suriname living conditions, including: - Income and consumption - Education and health - Employment and labor markets - Housing quality and access to services - Agriculture, assets, and remittances How is poverty measured in this dataset?The SSLC uses a consumption-based poverty approach. It calculates poverty rates based on household consumption rather than income, providing a more accurate picture of welfare and inequality across regions and population groups. What makes this survey nationally representative?The sample design uses a two-stage stratified sampling method covering urban, rural, and interior areas. This ensures that the survey represents Suriname’s geographic and socioeconomic diversity. What are the main data files included?
How can researchers use this data?Analysts can use the dataset to:
- Assess living standards and poverty levels What documentation is included for users?The dataset package includes:
- Methodological report and codebook explaining survey design What makes this dataset important for understanding living in Suriname?It provides the most detailed view of Suriname’s household welfare in recent years, capturing how people live, work, and spend across all regions. Policymakers rely on the SSLC to track poverty trends, design social programs, and monitor national development goals. Who conducted the survey?The SSLC was designed and implemented by Sistemas Integrales in collaboration with the Government of Suriname and the Inter-American Development Bank (IDB). Is Suriname safe for families?The survey includes a crime and personal safety module that covers whether respondents were victims of crime in the past 12 months, whether crimes were reported to the police, fear of crime, and household spending on security measures. What are the pros and cons of moving to Suriname?Pros highlighted in the dataset: - Paramaribo appears materially better off than poorer regions, with lower poverty and higher average consumption. - The survey covers core living-condition dimensions such as housing, education, health, employment, and safety, suggesting these are meaningful aspects of daily life in Suriname. Cons highlighted in the dataset: - Poverty is significant nationally: overall poverty was 26.2% and extreme poverty 1.7% at the person level. - There are strong regional disparities, especially in the interior, where person-level poverty reached 47.9% and extreme poverty 15.7%. - The survey also identifies 13.1% of households as vulnerable, meaning above the poverty line but still at risk of falling into poverty. That is a nice statistical way of saying “the floor is wobbly.” |