This layer shows childhood poverty figures at a country scale. Population figures were obtained in 2023.This layer uses bivariate choropleth mapping to symboloise the relationship between children living in poverty (as defined globally) and children engaged in economic activity (i.e. work).Global patterns indicate that children are most impacted by poverty. Across the globe, a staggering 333 million children live in conditions of extreme poverty. This layer has been designed to help school children in New Zealand and the South Pacific explore these claims.

Underwater visual census data from the Poor Knights Islands, New ZealandData consist of counts of abundances of each of p = 47 species in each of N = 56 sites at the Poor Knights Islands, New Zealand. At each site, divers performed a visual census in each of nine 25 m × 5 m transects, and these transect-level counts were summed to yield a single count value for each species at each site. There were three different times of sampling: September 1998 (15 sites), March 1999 (21 sites) and September 1999 (20 sites). These times of sampling span the point in time when the Poor Knights Islands were classified as a no-take marine reserve (October 1998).

The data were originally obtained as part of an ongoing monitoring programme of the status of fish communities for the Poor Knights Islands, funded by New Zealand’s Department of Conservation (DoC). Initial analyses of these data appear in the following report, which should be cited directly if these data are to be used in any other context.

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Historical dataset showing New Zealand poverty rate by year from N/A to N/A.

For the past 20 years, the New Zealand Deprivation Index (NZDep) has been the universal measure of area-based social circumstances for New Zealand (NZ) and often the key social determinant used in population health and social research. This paper presents the first theoretical and methodological shift in the measurement of area deprivation in New Zealand since the 1990s and describes the development of the New Zealand Index of Multiple Deprivation (IMD).We briefly describe the development of Data Zones, an intermediary geographical scale, before outlining the development of the New Zealand Index of Multiple Deprivation (IMD), which uses routine datasets and methods comparable to current international deprivation indices. We identified 28 indicators of deprivation from national health, social development, taxation, education, police databases, geospatial data providers and the 2013 Census, all of which represented seven Domains of deprivation: Employment; Income; Crime; Housing; Health; Education; and Geographical Access. The IMD is the combination of these seven Domains. The Domains may be used individually or in combination, to explore the geography of deprivation and its association with a given health or social outcome.Geographic variations in the distribution of the IMD and its Domains were found among the District Health Boards in NZ, suggesting that factors underpinning overall deprivation are inconsistent across the country. With the exception of the Access Domain, the IMD and its Domains were statistically and moderately-to-strongly associated with both smoking rates and household poverty.The IMD provides a more nuanced view of area deprivation circumstances in Aotearoa NZ. Our vision is for the IMD and the Data Zones to be widely used to inform research, policy and resource allocation projects, providing a better measurement of area deprivation in NZ, improved outcomes for Māori, and a more consistent approach to reporting and monitoring the social climate of NZ.

Have you ever considered where pockets of poverty exist and who is most affected? Unfortunately, global patterns indicate that children are most impacted by poverty. Across the globe, a staggering 333 million children live in conditions of extreme poverty. Why is poverty such a critical issue? Because it affects the overall well-being of a person. Those living in poverty often encounter barriers to basic necessities like food, shelter, and healthcare. Growing up without consistent nutrition, shelter, and safety can have long-lasting developmental impacts on children and can cause lifelong problems. For more, read: Child poverty | UNICEF

Using a poverty metric of 2.15 U.S. dollars per day, 37 percent of the women in Sub-Saharan Africa were living in extreme poverty in 2023. This is expected to fall to one third by 2023. On the other hand, less than one percent of the population in Europe and North America as well as Australia and New Zealand were living in extreme poverty. Nevertheless, there are also many people in these regions struggling to make ends meet.

Raster chart image of: NZ 5571 Poverty Bay and Approaches to Gisborne: Gisborne Harbour and Entrance

This data was compiled for the use at the following scale: 7000

File reference: NZ557102.tif

THIS DATA DOES NOT REPLACE NAUTICAL CHARTS AND MUST NOT TO BE USED FOR NAVIGATION.

The hydrographic raster data made available through the LINZ Data Service is based on the Paper Navigational Charts published and maintained by the New Zealand Hydrographic Authority at Land Information New Zealand (LINZ).

The online New Zealand Chart Catalogue provides more detailed and the most up to date information about New Zealand charts: New Zealand Chart Catalogue

Information on symbols and abbreviations used on nautical charts: Symbols and Abbreviations

Hydrographic standards and specifications for nautical charts and publications: Standards and Specifications

The 2023 NZ Deprivation Index helps us see which communities across Aotearoa face the highest levels of socio-economic deprivation. These areas—ranked decile 8, 9 and particularly decile 10—are where whānau often deal with low incomes, limited work opportunities, poor housing, and restricted access to essential services.Understanding why these areas rank highly can help iwi, hapū, community trusts, and service providers target funding and resources where they’re needed most.Access the data online without download (Source data before the maps below):

New Zealand NZ: IMF Account: Fund Position: USD: UFC: Outstanding Loans: Structural Adj. Facility, Poverty Reduction and Growth Facility & Trust Fund data was reported at 0.000 USD mn in Jun 2018. This stayed constant from the previous number of 0.000 USD mn for Mar 2018. New Zealand NZ: IMF Account: Fund Position: USD: UFC: Outstanding Loans: Structural Adj. Facility, Poverty Reduction and Growth Facility & Trust Fund data is updated quarterly, averaging 0.000 USD mn from Mar 1945 (Median) to Jun 2018, with 294 observations. New Zealand NZ: IMF Account: Fund Position: USD: UFC: Outstanding Loans: Structural Adj. Facility, Poverty Reduction and Growth Facility & Trust Fund data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s New Zealand – Table NZ.IMF.IFS: IMF Account: Fund Position: Quarterly.

Foraminiferal faunas in 29 short cores (maximum depth 7 m) of estuarine and coastal wetland sediment were used to reconstruct the middle–late Holocene (last 7 ka) elevational history on the southern shores of Poverty Bay, North Island, New Zealand. This coast is on the southwest side of a rapidly subsiding area beneath western Poverty Bay. Modern Analogue Technique paleo-elevation estimates based on fossil foraminiferal faunas indicate that the four study areas have gradual late Holocene (

This StoryMap is designed to help you and your students to complete the Child Poverty New Zealand Activity

New Zealand NZ: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Poorest 40%: % of Population Aged 15+ data was reported at 98.967 % in 2017. This records a decrease from the previous number of 99.362 % for 2014. New Zealand NZ: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Poorest 40%: % of Population Aged 15+ data is updated yearly, averaging 99.362 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 99.377 % in 2011 and a record low of 98.967 % in 2017. New Zealand NZ: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Poorest 40%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s New Zealand – Table NZ.World Bank: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (poorest 40%, share of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted Average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems. By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Correlations between the IMD, its Domains, with rates of smoking and household poverty.

Child poverty statistics provide estimates of low income and material hardship rates for measures listed in the Child Poverty Reduction Act 2018.

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems. By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Here we describe Pittosporum roimata Gemmill & S.N. Carter, the only vascular plant endemic to the Poor Knights Islands, Northland, Aotearoa/New Zealand. This new species has previously been referred to as a distinct variant of Pittosporum cornifolium (tÄ whiri karo, wharewhareatua), a morphologically similar epiphytic shrub known from both main islands of New Zealand as well as other off shore islands. We have segregated this new species from P. cornifolium based on morphology, DNA sequence variation, as well as distribution. Pittosporum roimata is distinguished from P. cornifolium by a number of characters, including having larger thicker leaves with shorter petioles, flowers with yellow petals, larger inflorescences, and producing several terminal fruits per stem. Pittosporum roimata is locally common on the islands of Tawhiti Rahi, Aorangi, and Aorangaia, growing on rocky substrates associated with Xeronema callistemon (raupo taranga) and Metrosideros excelsa (pÅ hutukawa). Using...

References: Porter, A.T., Holan, S.H., and Wikle, C.K. (2015a) Multivariate spatial hierarchical Bayesian empirical likelihood methods for small area estimation. STAT, 4: 108--116. Porter, A.T., Holan, S.H., and Wikle, C.K. (2015b) Small Area Estimation via Multivariate Fay-Herriot Models with Latent Spatial Dependence. Australian & New Zealand Journal of Statistics. 57, 15--29.

Marine protected areas have long been proposed as a key tool to restore lost food web interactions and increase the resilience of ecosystems to climate change impacts. However, a changing climate can result in the arrival of new species or differentially affect native species, which can alter ecosystem dynamics and make it difficult to predict how ecosystems will respond to protection. The long-spined sea urchin Centrostephanus rodgersii is a well-known range extender with large impacts on kelp forest ecosystems, yet its response to warming and long-term marine protection has not been examined within its native range. We examine long-term trends in C. rodgersii and the endemic sea urchin Evechinus chloroticus following no-take protection within the Poor Knights Islands Marine Reserve, in northeastern Aotearoa New Zealand, from 1999-2022, and compare with population trends at an unprotected island group. Within the marine reserve, E. chloroticus decreased in density, became more cryptic, and urchin barrens associated with this species largely disappeared, whereas in fished areas, populations and extent of barrens remained stable. This differing response between the reserve and fished location is consistent with a top-down effect and greater abundance of predatory fish in the reserve. In contrast, the subtropical sea urchin C. rodgersii increased in abundance by 9.3 times in the Poor Knights Island Marine Reserve and 4.3 times at the fished location, with areas of urchin barrens associated with this species developing at both locations. This increase coincides with substantial warming over the monitoring period (0.25°C decade-1) and low numbers of key predators (rock lobster) at both reserve and fished locations. This highlights the emerging threat of C. rodgersii to rocky reefs in the region and how marine protection alone may not increase resilience to this threat. This suggests multifaceted management approaches are needed to mitigate the impacts of emerging pest species and increase the resilience of temperate reef ecosystems in a warming climate.

Out of all OECD countries, Cost Rica had the highest poverty rate as of 2022, at over 20 percent. The country with the second highest poverty rate was the United States, with 18 percent. On the other end of the scale, Czechia had the lowest poverty rate at 6.4 percent, followed by Denmark.

The significance of the OECD

The OECD, or the Organisation for Economic Co-operation and Development, was founded in 1948 and is made up of 38 member countries. It seeks to improve the economic and social well-being of countries and their populations. The OECD looks at issues that impact people’s everyday lives and proposes policies that can help to improve the quality of life.

Poverty in the United States

In 2022, there were nearly 38 million people living below the poverty line in the U.S.. About one fourth of the Native American population lived in poverty in 2022, the most out of any ethnicity. In addition, the rate was higher among young women than young men. It is clear that poverty in the United States is a complex, multi-faceted issue that affects millions of people and is even more complex to solve.