DESK REVIEWS | 01.03. Economic and social situation

DESK REVIEW | 01.03. Economic and social situation

According to the World Bank metrics, Brazil is an upper middle-income country and one of the biggest economies in the world. In 2017, the GDP per capita (PPP – current international $), was 15,553.4 – representing a total economic turnover of 2,056 trillion USD. Comparatively, Mexico has 1.15 trillion USD and Argentina has 637.6 billion. Brazil has experienced a remarkable growth in the last decade, which made  the country become the fifth largest economy in the world (The World Bank, 2019).

References:

The World Bank. (2019). The World Bank Data. https://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD

The economy of Hong Kong is a highly developed free-market economy characterised by low taxation, almost free port trade and well-established international financial market. In 2018, the GDP of Hong Kong is recorded at HK$2,845.3 billion with an annual growth rate of +5.9%. The GDP per capita is recorded at HK$381,870 with an annual growth rate of +5.1% (Census and Statistics Department, 2019c). Hong Kong has been classified as high-income by the World Bank (World Bank, 2019).

References:

Census and Statistics Department. (2019c). Hong Kong in Figures 2019 Edition. Hong Kong. Retrieved from https://www.statistics.gov.hk/pub/B10100062019AN19B0100.pdf

World Bank. (2019). Hong Kong SAR, China Retrieved from: https://data.worldbank.org/country/hong-kong-sar-china?view=chart

As per the World Bank categorisation, India is a lower-middle-income country. As the seventh largest economy in the world, in 2020, India had a Gross Domestic Product (GDP) of 2.6 trillion US dollars (World Bank, 2020a). Moreover, the GDP per capita in India was recorded as 1927 US dollars in 2020 (World Bank, 2020b).

References:

World Bank. (2020a). GDP per capita, India | Data. Available from  https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?locations=IN

World Bank. (2020b). India | Data. Available from https://data.worldbank.org/country/india

According to the World Bank, Indonesia is an emerging middle-income country and ‘the world’s 10th largest country in terms of purchasing power parity and an annual growth rate of 5.6% (Agustina et al., 2019, p.78; World Bank, 2019a). Since 1999, the poverty rate has reduced by more than half to 9.8% in 2018. Substantial progress has also been made with regards to GDP. Between the years 2000 and 2018, Indonesia’s GDP per capita steadily increased from $807 to $3,877 (World Bank, 2019a).

References:

Agustina, R., Dartanto, T., Sitompul, R., Susiloretni, K. A., Suparmi, Achadi, E. L., Taher, A., Wirawan, F., Sungkar, S., Sudarmono, P., Shankar, A. H., Thabrany, H., Susiloretni, K. A., Soewondo, P., Ahmad, S. A., Kurniawan, M., Hidayat, B., Pardede, D., Mundiharno, … Khusun, H. (2019). Universal health coverage in Indonesia: concept, progress, and challenges. The Lancet, 393(10166), 75–102. https://doi.org/10.1016/S0140-6736(18)31647-7

World Bank. (2019a). Indonesia. https://www.worldbank.org/en/country/indonesia/overview

Key developmental challenges affecting access to health care and economic growth include political instability and climate change. Real Gross Domestic Product (GDP) was estimated to be 5.9% in 2018 with mainly services accounting for 52.5% of the growth since 2017, agriculture (the backbone of the Kenyan economy) for 23.7%, and industry for 23.8% on the supply side and private consumption as the key driver of growth on the demand side (African Development Bank Group, 2019). Real GDP was projected to grow by 6.0% in 2019 and 6.1% in 2020. The public debt–to-GDP ratio was 57% at the end of June 2018 (African Development Bank Group, 2019) reflecting a volatile economy.

References:

African Development Bank Group. (2019). Kenya Economic Outlook. https://www.afdb.org/en/countries-east-africa-kenya/kenya-economic-outlook

Mexico is among the ten largest countries in the world, it is the second largest economy in Latin America after Brazil. It ranks as the 15th world economy, according to its Gross Domestic Product (GDP) at exchange rate, and the 11th in terms of GDP at Purchasing Power Parity (PPP). It has been classified as an upper middle-income country by the World Bank (CEPAL, 2018; OECD, 2017a; Banco Mundial, 2019). The Mexican currency is the Mexican Peso (MXN) and the current exchange rate by the Central Bank as of 18 January 2019 is 19.1 pesos per USD and 21.7 pesos per Euro (Banco de México, 2018).

Mexico has an open economy, oriented to exports and highly regulated free trade agreements with more than 40 countries including the European Union, Japan, Central and South America, as well as the North American Free Trade Agreement (NAFTA) with the United States and Canada, which is currently under revision and negotiation. This has put Mexico within the highest 10 export economies in the world. The country’s growth is projected to increase from 2.0% in 2017 to 2.2% in 2018 and 2.5% in 2019, supported by higher US growth. However, the growth forecast was lower than expected in April 2018, reflecting the impact on investment and domestic demand of prolonged uncertainty related to trade (International Monetary Fund, 2018).

While Mexico has been a member of the OECD since 1994, its per capita Gross National Income is the lowest among the Organisation for Economic Co-operation and Development (OECD) members –58% below the OECD average in 2016, in terms of Purchasing Power Parity. Compared to upper middle-income countries (UMICs), however, Mexico’s per capita Gross National Income (GNI) is 7% above the average of that group (The World Bank, 2019).

References:

Banco de México. (2018). Mercado cambiario, tipo de cambio, Banco de México.

Banco Mundial. (2019). México: proyectos.

CEPAL. (2018). Estudio Económico de América Latina y el Caribe, 2018 (LC/PUB.2018/17-P).

International Monetary Fund. (2018). World Economic Outlook Challenges to Steady Growth.

OCDE. (2017a). Estudios Económicos de la OCDE México (OCDE Publishing, Ed.). OCDE Publishing. https://www.oecd.org/eco/surveys/mexico-2017-OECD-Estudios-economicos-de-la-ocde-vision-general.pdf

The World Bank. (2019). Mexico Data. https://data.worldbank.org/country/mexico

The South African GDP per capita (PPP, purchasing power parity) is recorded as US$12 294.88 in 2017. GDP decreased by 0.7% in the second quarter of 2018, with the largest negative contributors being agriculture (-0.8, i.e., decreasing by 29.2%), transport (-0.4, i.e., decreasing by 4.9%), and trade (-0.3, i.e., 1.9%) (StatsSA, 2018a). Positive contributions primarily came from the mining (0.4, i.e., increasing 4.9%) and finance, real estate and business service industries (1.9%) (StatsSA, 2018a). The third quarter in 2018 saw the Real GDP (measured by production) increasing by 2.2% for which the largest contributors to growth were the manufacturing (7.5%, contributing 0.9 of percentage point to GDP), finance (2.3%, 0.5 percentage point), and transport and trade industries (5.7%, 0.5 percentage point) (StatsSA, 2018b). These figures have been significantly affected by the COVID-19 pandemic and associated lockdowns with a reduction in productivity and increase in unemployment by 2021.

The World Bank categorises South Africa as an Upper-middle-income country (The World Bank, 2018a).  South Africa is one of the most unequal countries in the world and this categorisation by the World Bank is not what most of the South Africans experience in terms of their living conditions.

References:

StatsSA. (2018a). Gross Domestic Product: Second Quarter. In Statistics South Africa: Release date 04 September 2018. https://doi.org/10.1080/00128775.1994.11648537

StatsSA. (2018b). Gross domestic product: Third quarter. Available from: https://www.statssa.gov.za/publications/P0441/P04413rdQuarter2018.pdf

The World Bank. (2018a). Overcoming Poverty and Inequality in South Africa:An Assessment of Drivers, Constraints and Opportunities. Available from: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/530481521735906534/overcoming-poverty-and-inequality-in-south-africa-an-assessment-of-drivers-constraints-and-opportunities

Brazil’s GDP in 2018 was US$1.6 trillion. The country’s economy is composed of services (the main productive sector), followed by industry (e.g.: textiles, shoes, chemicals, cement, lumber, iron ore, tin, vehicles etc.); and agriculture (e.g.: coffee, soybeans, wheat, rice, corn, sugarcane, cocoa, citrus and beef) (Brazilian Institute of Geography and Statistics, 2019i, 2019h).

References:

Brazilian Institute of Geography and Statistics. (2019h). Produto Interno Bruto—PIB | IBGE. https://www.ibge.gov.br/explica/pib.php

Brazilian Institute of Geography and Statistics. (2019i). SIDRA – Tabela 1846: Valores a preços correntes.

The four key industries in Hong Kong were 1) financial services (% of GDP in 2017: 18.9%), 2) tourism (4.5%), 3) trading and logistics (21.5%), and 4) professional and other producer services (12.2%). In 2017, these four industries generated a total of value added of $1,456.6 billion (57.1% of GDP) and employed 1,780,200 persons (46.6% of total employment) (Census and Statistics Department, 2019b).

References:

Census and Statistics Department. (2019b). The Four Key Industries and Other Selected Industries. Hong Kong: Census and Statistics Department, HKSAR. Retrieved from https://www.statistics.gov.hk/pub/B71905FA2019XXXXB0100.pdf

The GDP composition by sector of origin shows that the services accounted for 53.9% of GDP in 2017-18, while industry, agriculture, and manufacturing accounted for 29.1%, 17.1%, and 16.7%, respectively, in the same year (Ministry of Finance, 2018).

References:

Ministry of Finance (2018). Contribution of various sectors to GDP. Press Information Bureau. Government of India. Available from: https://pib.gov.in/newsite/PrintRelease.aspx?relid=186413

In 2017, the majority of GDP was produced in services (45.4%), followed by industry (41%), and agriculture (13.7%). Industry in Indonesia is active in the areas of ‘petroleum and natural gas, textiles, automotive, electrical appliances, apparel, footwear, mining, cement, medical instruments and appliances, handicrafts, chemical fertilizers, plywood, rubber, processed food, jewellery, and tourism’. Agricultural products include ‘rubber and similar products, palm oil, poultry, beef, forest products, shrimp, cocoa, coffee, medicinal herbs, essential oil, fish […] and spices’ (CIA World Factbook, 2019).

References:

CIA World Factbook. (2019). Indonesia. https://www.cia.gov/the-world-factbook/countries/indonesia/

In spite of the political instability in Kenya, tourism accounted for 20% of the economy, demonstrating the significance of this sector in the country’s economy (Central Intelligence Agency, 2019). The agriculture, service, industry, and private consumption sector are also quite significant as mentioned in 01.03.01.

References:

Central Intelligence Agency. (2019). The World Factbook: Africa – Kenya. https://www.cia.gov/the-world-factbook/countries/kenya/

The services (tertiary) sector is the largest part of the economy, representing 61% of GDP in the third semester of 2018. The secondary sector (comprising mining, manufacture, construction, gas, and electricity) and the primary sector (agriculture, fisheries, cattle and livestock, and forestry) represent 31.4% and 3.1% of GDP, respectively[1]. Of the primary sector, 65% corresponds to livestock activities. The primary sector is one of the sectors, which receives the least foreign investment and, while it continues to develop, it has lagged compared to other sectors of the economy.

Oil production[2] is one of the main components of the secondary sector. To date, Mexican oils (Petroleos Mexicanos), PEMEX is the largest company in Mexico, the largest tax contributor, and remains as the main source of public funds – around 30% to 40% depending on the international price of oil barrel. However, PEMEX also has a large debt (due to net losses). Within the secondary sector, the manufacture industry and construction are two areas with large participation in the overall economy, representing with 54.7% and 24.3% of the sector, respectively. Within manufacturing, the auto-industry, largely concentrated on exports, represents 22% of all manufactures and 12% of total product within this sector (INEGI, 2018d).

The third (services) sector includes commerce, restaurants, hotels, transportation, communications, financial and personal services, as well as health and education. It has grown at an average annual increase rate of 3% in the period 2003-2016. The sector is comprised by very small businesses, largely self-employed, as well as large companies and multinationals using cutting-edge technology (CEFP, 2018; INEGI, 2018d).

Despite the most recent global economic crisis, decreasing oil prices and government income, Mexico’s economy has maintained a slight economic growth. This economic performance has been supported by internal demand and is the result of important structural reforms and solid macroeconomic policies that have generated low or decreasing inflation and interest rates, and increased per capita income (OECD, 2017a).

[1] Producto Interno Bruto, PIB

[2] Production remained a government monopoly through the company Petroleos Mexicanos (PEMEX) until recent reforms in 2013 when production was open to private investment.

References:

CEFP. (2018). Evolución de la Actividad Productiva Nacional y de las Entidades Federativas 2003-2018. https://www.cefp.gob.mx/publicaciones/documento/2018/cefp0222018.pdf

INEGI. (2018d). Sistema de Cuentas Nacionales de México. Producto Interno Bruto Trimestral. Año Base 2013. Tabulados básicos. https://www.inegi.org.mx/programas/pib/2013/#Documentacion

OECD. (2017a). Estudios Económicos de la OCDE México (OCDE Publishing, Ed.). OCDE Publishing. https://www.oecd.org/eco/surveys/mexico-2017-OECD-Estudios-economicos-de-la-ocde-vision-general.pdf

The table below summarises the main productive sectors of the South African economy, compiled from data source (StatsSA, 2018b):

Table 6: Composition of the economy (main productive sectors)

Sector Industry Increased (%) during 3rd quarter of 2018
Primary Agriculture, forestry, fishing 6.5
Secondary Manufacturing 7.5
Tertiary Trade, catering and accommodation 3.2
Transport, storage and communication 5.7
Finance, real estate and business services 2.3
General government services 1.5
Personal services 0.7
References:

StatsSA. (2018b). Gross domestic product: Third quarter. Available from: https://www.statssa.gov.za/publications/P0441/P04413rdQuarter2018.pdf

The total public debt in Brazil (aggregating the national, state, and municipal governments) was 77.6% of the national GDP in 2018. The public debt can be separated into internal debt (approximately 70% of the GDP) and external (less than 10% of the GDP) (Central Bank of Brazil, 2019). We could not find information about private debt.

References:

Central Bank of Brazil. (2019). Estatísticas fiscais. Estatísticas fiscais. https://www.bcb.gov.br/estatisticas/estatisticasfiscais

For public debt, in the first quarter of 2019, the Gross External Debt (ED) on Hong Kong (measuring total outstanding gross external liabilities other than equity liabilities) was $12,695.3 billion, which was equivalent to 4.4 times of GDP. The components of ED were attributable to the banking sector (62.0%), other sectors (22.4%) (consisting of 73.2% long-term and 26.8% short-term liabilities), and debt liabilities in direct investment (intercompany lending) (15.4%). ED of the Government amounted to $26.7 billion, of which nearly all was long-term liabilities. This was attributable to non-residents’ holdings of debt securities issued by the Government. ED of the Hong Kong Monetary Authority amounted to $3.4 billion, of which 81.3% ($2.8 billion) was long-term liabilities of Exchange Fund Notes (Census and Statistics Department, 2019a).

For private debt, residential mortgage lending constitutes the major proportion of household loans in Hong Kong, while the remainder comprises personal loans such as unsecured lending through credit card and other private purposes. The growth in household loans accelerated from 3.9% in the second half of 2018 to 6.7% in the first half of 2019. It was driven by a stable growth in residential mortgage loans and a strong growth in loans for other private purposes in private banking and wealth management customers, which were secured by various financial assets (i.e., stocks, mutual funds, and insurance policies). With household debt growing faster than the nominal GDP, the household debt-to-GDP ratio rose to 75.5% in the second quarter of 2019 (Hong Kong Monetary Authority, 2019).

References:

Census and Statistics Department. (2019a). Balance of Payments, International Investment Position and External Debt Statistics of Hong Kong (First Quarter 2019). Hong Kong: Census and Statistics Department, HKSAR. Retrieved from https://www.statistics.gov.hk/pub/B10400012019QQ01B0100.pdf

Hong Kong Monetary Authority. (2019). Half-Yearly Monetary & Financial Stability Report (September 2019). Hong Kong Retrieved from https://www.hkma.gov.hk/media/eng/publication-and-research/quarterly-bulletin/qb201909/E_Half-yearly_201909.pdf.

The Centre’s debt-GDP ratio increased to 64.3% in 2020-2021 (RE) (Reserve Bank of India, 2021). Whereas household debt to GDP rose from 35.4% in the first quartile of 2020-2021 to 37.1% in the second quartile of 2020-2021 (Reserve Bank of India, 2021).

References:

Reserve Bank of India (2021). Press Releases. RBI Bulletin-March 2021. Government of India. Available from: https://www.rbi.org.in/Scripts/BS_PressReleaseDisplay.aspx?prid=51299

It is estimated that public debt amounted to 28.8% of GDP in 2017 (CIA World Factbook, 2019). In Indonesia, household debt was estimated to amount to US$104 billion in 2014 (Ghose et al., 2016).

References:

CIA World Factbook. (2019). Indonesia. https://www.cia.gov/the-world-factbook/countries/indonesia/

Ghose, R., Dave, S., Shirvaikar, A., Horowitz, K., Tian, Y., Levin, J., & Ho, S. (2016). Digital Disruption: How FinTech is Forcing Banking to a Tipping Point. In Citi GPS: Global Perspectives & Solutions (Issue March). https://www.ivey.uwo.ca/media/3341211/citi-2016-fintech-report-march.pdf

National debt has been increasing since 2014 (25.65 billion dollars). In 2018, it amounted to 52.37 billion dollars and was projected to be 109.9 billion dollars in 2024 (Plecher, 2019). This is because Kenya has been relying heavily on public debt, aid and grants as a source of financing thus increasing the public debt stock and affecting private investment (Ngugi, 2016).

References:

Ngugi, W. N. (2016). Effect of Public Debt on Economic Growth in Kenya. Kenyatta University.http://erepository.uonbi.ac.ke/bitstream/handle/11295/98782/Kobey_Effect+Of+Public+Debt+On+Economic+Growth+In+Kenya.pdf?sequence=1

Plecher, H. (2019). Kenya: National debt from 2014 to 2024 (in billion U.S. dollars).

Household debt

The financial position of households[1] in Mexico has maintained a growing trend in recent years. As of June 2018, the increase registered in the last 5 years represented 5% of the GDP, with a similar growth in savings, both voluntary and mandatory. This result occurred during the same period in which the indebtedness of households also increased by 2% of the GDP, driven mainly by the expansion of credit to consumption and financial inclusion (Banco de México, 2018).

As financial inclusion increases in Mexico, household debt[2] has increased in the past decade. According to data from the Central Bank, household debt reached 16% as a proportion of Gross Domestic Product (GDP) in 2018. This represents the highest level since the beginning of recording this information in 1994. In contrast, in 2000 one of the lowest levels of household debt in recent years were reported at 8% of total GDP (Banco de México, 2018).

Regarding household debt in 2018, approximately 60% of the total financing received corresponded to mortgage loans and 40% to consumer credit. Most mortgages are granted through the two main social security institutions’ housing institutions INFONAVIT (for private sector workers) and FOVISSSTE (for public sector employees). These two institutions granted 64.9% of all mortgages, followed by banks with close to 34% of the total. In terms of total consumption and debt/credit, credit cards represent the most frequent source of consumer credit. By June 2018, 17.4 million people in Mexico had at least one credit card. This number is 3.4% higher than the number of people with at least on credit care in the same month in 2017 (Banco de México, 2018).

While household debt has increased over the past decade, it is not considered to a high risk as it is thought that this occurs in an environment where household income has improved because of real wage recovery and higher employment.

Public Debt

Between 2012 and 2018, the growth of total foreign debt, has been very important and reflects a difference of 9 percentage points of GDP, increasing from 28% to 37%. As a percentage of GDP, total external debt in 2018 is very similar to that of 1996, which was the year of the last major financial crisis experienced in the country. Of the total external debt in 2018, which amounted to 446 million US, 306.4 million USD (26% of GDP) are public external debt (publicly/government guaranteed), and 139.7 million USD (12% of GDP) are private sector external debt (not guaranteed by the government). For that same year, the level of international reserves reported by the Central Bank was 176,648.6 million USD and total revenue from exports was 450,572.2 million USD (Banco de Mexico, 2018; Secretaría de Hacienda y Crédito Público, 2018, 2019).

In terms of monetary data (balance of public debt), by end of February 2019, the Historical Balance of the Requirements of the Public Sector Finance (SHRFSP) amounted to 10,499,200,000 pesos. The internal component of the SHRFSP was located at 6,725.1 thousand million pesos, while the external component were 3,774.1 million pesos. Net debt of the federal public sector (Federal Government, State Companies, and development banking) at the end of February 2019 stood at 10 trillion 815.7 pesos.

[1] Calculated as financial assets minus received credits as proportion of GDP.

[2] Defined as the total outstanding debt of households to banks and other financial institutions as percent of GDP.

References:

Banco de México. (2018). Mercado cambiario, tipo de cambio, Banco de México.

Secretaría de Hacienda y Crédito Público. (2018). Informes sobre la situación económica, las finanzas públicas y la deuda pública. Cuarto trimestre 2018.

Secretaría de Hacienda y Crédito Público. (2019). Informes de la situación de las finanzas públicas y la deuda pública. https://www.finanzaspublicas.hacienda.gob.mx/es/Finanzas_Publicas/Informes_al_Congreso_de_la_Union

Historically the South African Government debt has steadily increased from January 2016 (US$40 265 Million), peaking at US$81 061 Million by January 2018. Government Debt for 2018 has now decreased from US$70 549 Million in the second quarter of 2018, to US$67 998 Million (third quarter) (Trading Economics, 2019). Household debt grew by 4.6% on average in 2018 and amounts to R165 billion (SARB, 2019).

References:

SARB. (2019). Quarterly bulletin: March 2019 (no.291). Available from: https://www.resbank.co.za/en/home/publications/publication-detail-pages/quarterly-bulletins/quarterly-bulletin-publications/2019/9148

Trading Economics. (2019). South Africa Government Debt to GDP. Trading Economics, 1–8. Available from: https://tradingeconomics.com/south-africa/government-debt

The country has experienced an increase in the number of people living in extreme poverty (from 6.6% in 2016 to 7.4% in 2017; that is from 13.5 million to 15.2 million people). There was also an increase in the proportion of people living below the poverty line (income of up to $5.50 a day). In 2017, this number stood at 26.5%, compared to 25.7% the year before. Such rates represent a change from 52.8 million to 54.8 million people. Most of people affected —over 25 million — live in the North Eastern region of the country (Brazilian Institute of Geography and Statistics, 2018c). The GINI index in Brazil was reported at 51.3 in 2015 (Trading Economics, 2019). With regards to gender equality, national figures (2016) reveal gender inequality across the country. For example, women devote about 73% more hours to domestic and/or household chores than men (18.1 hours versus 10.5 hours). The greatest inequality in the distribution of hours dedicated to these activities is in the Northeast Region, where women dedicate about 80% more hours than men, reaching 19 more hours a week. Black or mixed-race women are the ones that dedicate themselves the most to the care of people and/or household chores, with a record of 18.6 hours per week in 2016. Such figures vary little for men when considering ethnicity or region of residence (Brazilian Institute of Geography and Statistics, 2018b, 2019b).

References:

Brazilian Institute of Geography and Statistics. (2018b). Estatísticas de Gênero Indicadores sociais das mulheres no Brasil.

Brazilian Institute of Geography and Statistics. (2018c). Síntese dos Indicadores Sociais, uma análise das condições de vida da populção brasileira.

Brazilian Institute of Geography and Statistics. (2019b). Gender Statistics—Social indicators of women in Brazil. IBGE.

Trading Economics. (2019). Brazil—Gini Index. https://tradingeconomics.com/brazil/gini-index-wb-data.html

 

Since 2013, the Hong Kong Government has officially defined the poverty line as 50% of the median monthly domestic household income. The poverty lines of from 1-person to 6-person+ household in 2017 were HK$4,000, HK$9,800, HK$15,000, HK$19,900, HK$20,300, and HK$22,500 respectively (HKSAR Government, 2018). Households with monthly household income lower than the poverty line are defined as “poor households” and all members of these households are referred as “poor population”.

The poverty situation of Hong Kong can be reflected by four sets of indicators, including one set of “before-intervention” statistics and three sets of “after-intervention” statistics. The “before-intervention” poverty statistics are compiled with the assumption of no prevailing government policies and measures, which form an objective benchmark for assessing the effectiveness of intervention. It only includes household members’ employment earnings, investment income, and non-social-transfer cash income. “After-intervention” poverty statistics are compiled by further including the income provided by the government policies and measures, such as taxation, recurrent-cash benefits, non-recurrent cash benefits, and in-kind benefits. In 2017, the poverty rate before intervention was 20.1% (1,376,600 persons). After recurrent cash intervention, the poverty rate improved to 14.7% (1,008,800 persons). Among those aged 65 and over, the poverty rate after recurrent cash intervention was 30.5% (340,000 persons) (HKSAR Government, 2018).

Inequality between a society’s rich and poor is often measured by the Gini coefficient, with zero indicating equality. In 2016, the Gini coefficient of Hong Kong based on original monthly household income was 0.539 and that based on post-tax post-social transfer monthly household income was 0.473. It was the highest over the past 45 years with an increase of 0.006 points since 2006, and worse than other developed economies such as Singapore (0.356), United States (0.391), United Kingdom (0.351), Australia (0.337), and Canada (0.318) (Census and Statistics Department, 2017a; Oxfam Hong Kong, 2018).

For gender inequality in income, the median monthly income of males and females in 2016 were $16,890 and $12,000 respectively, with males’ income 40.8% higher. Also, there was a higher percentage of working women (9.1%) (excluding foreign domestic helpers) with monthly income from main employment below $6,000 than that of men (4.6%). The difference between income of working women and men can be attributed to differences between working women and men in industrial and occupational distributions, educational attainment, working experience, and nature of work. For example, proportionally more women (19.8%) than men (8.7%) worked as clerical support workers who had relatively lower monthly income from main employment in 2016. On the other hand, there was a higher proportion of men (21.2%) working as managers and administrators and professionals than women (13.1%) who had relatively higher monthly income (Census and Statistics Department, 2017a).

References:

Census and Statistics Department. (2017a). Hong Kong 2016 Population By-census – Thematic Report: Household Income Distribution in Hong Kong. Retrieved from https://www.censtatd.gov.hk/hkstat/sub/sp459.jsp?productCode=B1120096

HKSAR Government. (2018). Hong Kong Poverty Situation Report 2017. Hong Kong: HKSAR Government Retrieved from https://www.povertyrelief.gov.hk/eng/pdf/Hong_Kong_Poverty_Situation_Report_2017(2018.11.19).pdf.

Oxfam Hong Kong. (2018). Hong Kong Inequality Report. Retrieved from https://www.oxfam.org.hk/tc/f/news_and_publication/16372/Oxfam_inequality%20report_Eng_FINAL.pdf

According to the World Bank (2011), the GINI index for India in 2011 was 35.7. In 2017, the Inequality-Adjusted Human Development Index (IHDI) ranked India at 130 worldwide, with a score of 0.468 (United Nations Development Programme (UNDP), 2017).

References:

United Nations Department of Economic and Social Affairs, Population Division (UNDP). (2017). World Population Prospects. The 2017 Revision. Available from: https://www.un.org/development/desa/publications/world-population-prospects-the-2017-revision.html

World Bank. (2011). GINI Index (World Bank Estimate). Available from: https://data.worldbank.org/indicator/si.pov.gini

The United Nations Human Development Index (HDI) of Indonesia has increased from 0.528 in 1990 to 0.694 in 2018 (Agustina et al., 2019, p.78; United Nations Development Programme, 2018). This leads to a ranking of Indonesia in place 116 out of 189 countries (United Nations Development Programme, 2018). As with other indicators, there was considerable regional variety reported for the HDI (Sukamdi & Mujahid, 2015, p.xi).

Inequality in Indonesia has widened considerably between the years 2000 (28.5) and 2013 (39.9), but slightly diminished since 2017 (Gini index:38.1) (World Bank, 2018b).

Agustina and colleagues (2019, p.78) further report that the proportion of people in Indonesia living on ‘less than $1.90 per day in PPP’ declined substantially between 1984 (70.3%) and 2017 (5.7%); however, ‘high variability across and within provinces and districts’ remains.

Due to the absence of comprehensive social protection, older people in Indonesia are extremely vulnerable. According to Kidd and colleagues (2018, p.1), the highest rate of extreme poverty can be found among people aged 65 and over, with approximately 80 per cent of this age group living ‘households with a per capita consumption below IDR 50,000’ per day (below US$4). The proportion among those aged 80 and older is considered to be even higher. Women and those without family support are particularly vulnerable (Kidd et al., 2018, p.1).

References:

Agustina, R., Dartanto, T., Sitompul, R., Susiloretni, K. A., Suparmi, Achadi, E. L., Taher, A., Wirawan, F., Sungkar, S., Sudarmono, P., Shankar, A. H., Thabrany, H., Susiloretni, K. A., Soewondo, P., Ahmad, S. A., Kurniawan, M., Hidayat, B., Pardede, D., Mundiharno, … Khusun, H. (2019). Universal health coverage in Indonesia: concept, progress, and challenges. The Lancet, 393(10166), 75–102. https://doi.org/10.1016/S0140-6736(18)31647-7

Kidd, S., Gelders, B., & Rahayu, S. K. (2018). Implementing Social Protection for the Elderly in Indonesia. http://www.tnp2k.go.id/filemanager/files/Perlindungan Sosial Lansia/Elderly Brief – English Version.pdf

Sukamdi, & Mujahid, G. (2015). Internal Migration in Indonesia. UNFPA Indonesia Monograph Series No.3, xii, 90.

United Nations Development Programme. (2018). 2018 Statistical Update: Human Development Indices and Indicators. Human Development Reports. https://hdr.undp.org/en/content/human-development-indices-indicators-2018-statistical-update

World Bank. (2018b). GINI index (World Bank estimate) – Indonesia. World Development Indicators. https://data.worldbank.org/indicator/SI.POV.GINI?locations=ID&view=chart

Even though Kenya is recognized as a lower-middle income country, most of its residents continue to live below the poverty line in rural areas. Poverty levels vary across different cities and towns in Kenya with a lower incidence of multidimensional poverty in Nairobi (capital city of Kenya) and satellite towns such as Ruiru (22%) and Thika (27%). This figure is higher in other cities such as Mombasa (44%) and Kisumu (46%). Additionally, location-based horizontal inequality estimates are higher in the capital city and Thika town. Although these urban centers show relatively lower overall poverty levels compared to other urban centers, they register higher inequalities in deprivation scores between their different sub-locations (Shifa & Leibbrandt, 2017).

Nevertheless, Kenya’s level of inequality is moderate in comparison to Tanzania, Uganda, and Ghana as the Gini index dropped from 0.45 in 2005/06 to 0.39 in 2015/16 while in rural areas it fell from 0.37 to 0.33, demonstrating a remarkable positive change for an indicator that seldom changes over time (International Bank for Reconstruction and Development/The World Bank, 2018). The current monetary and non-monetary poverty indicators in Kenya are better than most countries in Sub-Saharan Africa. Specifically, Kenya’s adult literacy level is among the highest in Africa and performs better in access to improved sanitation compared to countries with a similar poverty headcount (World Bank Group, 2018).

There is very low financial protection from catastrophic health expenditure under the current health insurance system in Kenya. The absence of Universal Health Coverage (UHC) and the considerable costs associated with accessing health care often drain household resources. This has predisposed an estimated 1 to 1.1 million individuals (not only from lower income groups but also those with middle and higher income) to a high risk of being pushed or trapped into poverty (Salari et al., 2019).

References:

International Bank for Reconstruction and Development/The World Bank. (2018). Fiscal Incidence Analysis for Kenya: Using the Kenya Integrated Household Budget Survey 2015/16. Washington, DC. https://openknowledge.worldbank.org/bitstream/handle/10986/30263/Kenya-Fiscal-Incidence-Analysis.pdf?sequence=1&isAllowed=y

Salari, P., Di Giorgio, L., Ilinca, S., & Chuma, J. (2019). The catastrophic and impoverishing effects of out-of-pocket healthcare payments in Kenya, 2018. BMJ Global Health, 4(6). https://doi.org/10.1136/bmjgh-2019-001809

Shifa, M., & Leibbrandt, M. (2017). Urban Poverty and Inequality in Kenya. Urban Forum, 28(4), 363–385. http://doi.org/10.1007/s12132-017-9317-0

World Bank Group. (2018). 17th Edition of the Kenya Economic Update: Policy Options to Advance the Big 4 – Unleashing Kenya’s Private Sector to Drive Inclusive Growth and Accelerate Poverty Reduction. Nairobi, Kenya. https://openknowledge.worldbank.org/handle/10986/29676

Mexico has a much higher level of income inequality than other OECD countries, with its Gini coefficient (0.45) exceeding by far the OECD average (0.37), but closer to the Latin American average (Lambert & Park, 2019). According to the International Monetary Fund, IMF, the main reasons why poverty rates remain high are the country’s meagre per capita growth rates and deficiencies in the planning and targeting of social policies. It has also been noted that, while conditional cash transfer programs have been very effective at reducing inequality, other social programs have disproportionately benefited individuals at the top rather than at the bottom of the income distribution (Lambert & Park, 2019).

Regardless of continuing poverty alleviation strategies and other social programmes, income is highly concentrated, and the latest report of the National Council for the Evaluation of Social Policy, CONEVAL 2016, estimated that 7.6% of the Mexican population live in extreme poverty and 36% live in moderate poverty[1] (CONEVAL, 2018). Since 2009, the Mexican government has measured poverty using a multidimensional index of social deprivation (CONEVAL, 2018). The index has shown differential rates according to its subcomponents, such as access to education, social security, and access to health services, among others.

Regarding gender equality, there has been important progress since the year 2001 when President Vicente Fox created the National Institute for Women as an independent body within the federal government to coordinate compliance with national policy regarding equality and the eradication of violence against women. The institute is in charge of guaranteeing equal development and rights between men and women, through the development of public policies and other mechanisms such as media campaigns and publications. This institute also works with the legislative branch and the executive at federal and state level to follow up on the implementation and supervision of gender equality law. In addition, fundamental steps have been taken through the passing of legislation focused on eliminating discrimination and inequalities[2].

However, important challenges remain. A study in 2016 showed that, among those in paid work, women’s wages were, on average, between 17% and 47% lower than men’s. There were differences according to the state where they lived in and a wider difference by type of occupation. While the wage divide decreases as educational attainment increases, the wage divide between men and women prevails. Among those with no formal education, women’s wages are almost half of men’s, with a total difference of -50% and -33% for those with a college or university degree. In addition, among the population aged 15 years and older, 28% of women report having no own income, that is, they depend on others to subsist. Among men in this same age group, only 6% find themselves in this position, showing another facet of income inequality by gender in the country (INMUJERES, 2016).

Regarding general health inequalities, inequality in financial protection related to socioeconomic status has decreased significantly in parallel with the general decrease in the lack of financial protection. On the other hand, large inequality persists in indicators of access to health services and health indicators, both by socioeconomic status and by other social indicators (Gutierrez et al., 2014).

[1] The National Council for the Evaluation of Social Policy generates a Social Deprivation Index taking into account the following factors: educational lagging, access to health services, access to social security, space and quality of the household, basic services and access to food. Extreme poverty includes individuals that presents deprivation or lacks three or more of these factors, while moderate poverty includes those lacking two factors.

[2] Specifically, the General Law for Equality among Women and Men (Ley General para la Igualdad entre Mujeres y Hombres), a National Norm for Labour Equality and No Discrimination (Norma Mexicana NMX-R-025-SCFI-2015 en Igualdad Laboral y No Discriminación) generated as a collaboration between INMUJERES, the Labour and Social Prevision Secretariat (STPS), and the National Center for the Prevention of all Discrimination (CONAPRED), and a General Law for a Life Free of Violence for Women (Ley General de Acceso de las Mujeres a una Vida Libre de Violencia). Within the federal administration, mainstreaming of gender issues and gender equality has been the focus of many efforts in the last presidential terms.

References:

CONEVAL. (2018). Diez años de medición de pobreza multidimensional en México: avances y desafíos en política social. https://www.coneval.org.mx/Medicion/MP/Paginas/Pobreza-2018.aspx

Gutiérrez, J. P., García-Saisó, S., Dolci, G. F., & Ávila, M. H. (2014). Effective access to health care in Mexico. BMC Health Services Research, 14(1). https://doi.org/10.1186/1472-6963-14-186

INMUJERES. (2016). Brecha salarial de género en México. http://www.imf-formacion.com/blog/corporativo/igualdad-2/brecha-salarial-de-genero/

Lambert F, & Park H. (2019). Income Inequality and Government Transfers in Mexico.

South Africa faces a ‘triple challenge’ of high poverty, inequality, and unemployment and it has been identified as one of the world’s most unequal countries in the world (The World Bank, 2018a). The Living Conditions Survey (2014/15) found that the country’s Gini coefficient increased at the end of Apartheid (i.e., 0.61 in 1996) to 0.63 in 2015 as one of the highest in the world[1] (The World Bank, 2018a).

South Africa sees a polarisation of its employment market and is divided into two extreme job types: on the one end of the spectrum there is a small number of people with high earning jobs which once obtained, they are unlikely to give up and the other extreme where the majority of the population work at low earning jobs – the latter being more fluid and witnessing exits from employment (The World Bank, 2018a). The National Minimum Wage (NMW) was set at ZAR3500 per month across all sectors from May 2018 (with domestic and agriculture minimums set at 75 and 90% respectively (The World Bank, 2018a). Race and gender statistical trends remain biased where African and female workers on average earn significantly less than male and white workers (The World Bank, 2018a). Despite a notable decline in the observed gender inequality after 2011 (The World Bank, 2018a), the average gender pay gap in South Africa is reported at 28.6% in the Global Wage Report for the year 2018/19 (i.e., where women earn an average of 28.6% less than men for the same job). Women are generally earning less in South Africa leading to female-headed households being 10% more likely to become impoverished (and 2% less likely to escape it) than households headed by their male-counterparts (The World Bank, 2018a). Women still comprise less than 50% of positions of influence, for example 32% of Supreme Court of Appeal judges, 31% of advocates, 30% of ambassadors and 24% of Heads of State-owned enterprises (StatsSA, 2018c). Less than a third (32%) of managers in South Africa are women, and tend to dominate the domestic worker, clerical and technician occupations (men dominating the rest) (StatsSA, 2018c). By 2017, senior level management (decision-making level) are over-represented by men who dominate in both the public (60.7%) and private (68.5%) sectors (SAHRC, 2017a). Top level management in both public and private sectors also continue to be overrepresented by men, where women comprise 32.6% of top positions in government and 21.6% in the private sector (Department of Labour, 2017).

The majority of South Africans live in poverty (76%), of which nearly half are considered chronically poor and living at the upper-bound national poverty line of ZAR 992 per person per month (The World Bank, 2018a). Middle class earners constitute 20% of the working population between 2008 and 2015 and are a comparably smaller proportion than in other countries (The World Bank, 2018a). South Africa has also seen an increase in its poverty rate from 36 to 40% between 2011 and 2015 (The World Bank, 2018a). Poverty has also ‘deepened’ during this period as well and shows a 2.4 point increase (i.e., 16.4 to 18.8%) when calculated at the US$1.9 a day poverty line. Female-headed households, black South Africans, the less educated, the unemployed and bigger families experience higher levels of poverty (The World Bank, 2018a).

Rural areas in South Africa have the highest concentration of poverty (60.3% in 2006 and 59.7% in 2015), for which the Eastern Cape, KwaZulu-Natal, and Limpopo are the three poorest provinces in the country (2006-2015) (The World Bank, 2018a).

[1] Gini coefficient: Numbers range from 0 to 1; the higher the number/closer to 1, the greater the degree of income inequality

References:

Department of Labour. (2017). Commission for Employment Equity Annual Report 2017-2018. Availabe from: https://www.abp.org.za/wp-content/uploads/2018/07/Commission-for-Employment-Equity-18th-Annual-Report.pdf

SAHRC. (2017a). RESEARCH BRIEF ON GENDER AND EQUALITY IN SOUTH AFRICA 2013 to 2017. Available from: https://www.sahrc.org.za/home/21/files/RESEARCH%20BRIEF%20ON%20GENDER%20AND%20EQUALITY%20IN%20SOUTH%20AFRICA%202013%20to%202017.pdf

StatsSA. (2018c). How do women fare in the South African labour market? Statistics South Africa. http://www.statssa.gov.za/?p=11375

The World Bank. (2018a). Overcoming Poverty and Inequality in South Africa:An Assessment of Drivers, Constraints and Opportunities. Available from: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/530481521735906534/overcoming-poverty-and-inequality-in-south-africa-an-assessment-of-drivers-constraints-and-opportunities

Brazil was the only country in the Americas that is among the world’s ten countries with the highest number of people affected by disasters between 1995 and 2015. Most incidents are related to rain/flooding-related disasters (Federal University of Santa Catarina, 2013). From 2008 to 2013, 40.9% of Brazilian municipalities suffered at least one natural disaster. Around 2,376 cities were affected by gradual flooding, abrupt floods and/or landslides in that period. Gradual flooding alone left 1,406,713 people homeless or displaced. Almost 50% of the 5,570 city councils around the country had no resources to deal with these occurrences (Brazilian Institute of Geography and Statistics, 2019e). In the last four years, two large environmental accidents happened in the state of Minas Gerais, which were associated with crime. The first was in 2015: a dam disruption in the city of Mariana led to 19 deaths, communities were destroyed, rivers were polluted and the vegetation was devastated (Brazil Agency (EBC), 2018). A little more than three years later, another dam disruption occurred in the same state, but in the city of Brumadinho. This disaster led to 179 accounted deaths and 134 people disappeared. A “muddy sea” invaded the region destroying communities and the entire city of Brumadinho and put forest areas at risk of contamination. Both environmental disasters were under the responsibility of a company called Vale do Rio Doce (Brazil Agency (EBC), 2019).

References:

Brazil Agency (EBC). (2018, November 5). Tragédia Mariana. Agência Brasil. http://agenciabrasil.ebc.com.br/geral/noticia/2018-11/tragedia-de-mariana-completa-3-anos-veja-linha-do-tempo

Brazil Agency (EBC). (2019, February 25). Tragédia em Brumadinho. Agência Brasil. http://agenciabrasil.ebc.com.br/geral/noticia/2019-02/tragedia-em-brumadinho-completa-um-mes-com-134-desaparecidos

Brazilian Institute of Geography and Statistics. (2019e). Perfil dos municípios brasileiros 2013. IBGE. https://biblioteca.ibge.gov.br/visualizacao/livros/liv86302.pdf

Federal University of Santa Catarina. (2013). Atlas brasileiro de desastres naturais 1991 a 2012.

Hong Kong’s climate is seasonal due to alternating wind direction between winter and summer. From September to December there are pleasant breezes, plenty of sunshine, and comfortable temperatures. January and February are cloudier, with occasional cold fronts followed by dry northerly winds. March and April are milder although there are occasional spells of high humidity. The period from April to August is hot and humid with occasional showers and thunderstorms. The months from July to September are most likely to be affected by severe weather phenomena such as tropical cyclones, monsoon troughs, and thunderstorms. There are on average about 30 tropical cyclones form in the western North Pacific or China Seas every year, and about half of them reach typhoon strength. Heavy rain from tropical cyclones may last for a few days and subsequent landslips and flooding sometimes cause considerably more damage than the winds (Hong Kong Observatory, 2018, November 30). Waterspouts and hailstorms occur infrequently, snow and tornadoes are rare, and there is a very small chance of major earthquakes (Hong Kong Observatory, 2018, November 27). Moreover, Hong Kong is not seriously affected by tsunami (Hong Kong Observatory, 2018, November 8).

References:

Hong Kong Observatory. (2018, November 8). Tsunami Monitoring and Warning in Hong Kong. Retrieved from http://www.weather.gov.hk/gts/equake/tsunami_mon_e.htm

Hong Kong Observatory. (2018, November 27). Chance of a Significant Earthquake in Hong Kong. Retrieved from http://www.weather.gov.hk/gts/equake/sig_eq_chance_e.htm

Hong Kong Observatory. (2018, November 30). Climate of Hong Kong. Retrieved from http://www.weather.gov.hk/cis/climahk_e.htm

India is at risk for several natural disasters. Out of the 7,516 km of Indian coastline, 5,700 km of coastline is prone to tsunamis and cyclones (National Disaster Management Authority, 2019). Approximately, 58.6% of the total landmass is prone to moderate to high intensity earthquakes. Moreover, 12% of land is susceptible to floods (National Disaster Management Authority, 2019) .

References:

National Disaster Management Authority. (2019). Vulnerability Profile. Government of India.

As discussed above (01.02.02), environmental aspects are an important risk factor to economic productivity in Indonesia. According to the Global Facility for Disaster Reduction and Recovery, reconstruction following disaster costs the Indonesia government between $300 and $500 million annually. Costs during major disasters can amount to 0.3 per cent of national GDP and up to 45 per cent of provincial GDP. In addition, loss of life, damage to infrastructure, destruction of agricultural crops, and a reduction in income from tourism are considerable costs to bear (GFDRR, 2019). Lasting change, caused by ‘rising sea levels and changing weather patterns’, due to climate change pose a serious risk to Indonesia’s development.

Following the 2004 tsunami, the Government of Indonesia implemented a law on disaster management in 2007 and established the National Disaster Management Agency (BNBP) in 2008.  Activities to improve resilience and to reduce risk include relocation of families from high risk areas or road improvement work in areas prone to earthquake and landslides (GFDRR, 2019).

References:

GFDRR. (2019). Indonesia. Global Facility for Disaster Reduction and Recovery. https://www.gfdrr.org/en/indonesia

 

Kenya experiences: (i) natural hazards such as recurring droughts, landslides, lightening and thunderstorms, flooding during rainy seasons but limited volcanic activities; and (ii) environmental pollution including water pollution from urban and industrial waste, water shortage and degraded water quality resulting from use of pesticides and fertilisers, deforestation, soil erosion, desertification, and poaching. The level of destruction is increasing leading to more deaths, loss of livelihoods and infrastructure destruction (Central Intelligence Agency, 2019; United Nations Development Programme, 2007).

Another aspect hampering Kenya’s effort to improve its annual growth is inadequate infrastructure. The current efforts through multisectoral collaboration with international financial institutions and donors have raised capital in the global market by investing in infrastructure. One of the most recent projects is the construction of the Chinese financed standard gauge railway between Nairobi and Mombasa (Central Intelligence Agency, 2019).

References:

Central Intelligence Agency. (2019). The World Factbook: Africa – Kenya. https://www.cia.gov/the-world-factbook/countries/kenya/

United Nations Development Programme. (2007). Kenya Natural Disaster Profile. Enhanced security Unit. https://meteorology.uonbi.ac.ke/sites/default/files/cbps/sps/meteorology/Project%20on%20Disasters.pdf

Mexico has a long history and constant hazard of large earthquakes and volcanic eruptions. Volcán de Colima, south of Guadalajara, erupted in 1994, and El Chichón, in southern Mexico in 1983. Although dormant for decades, Popocatépetl and Iztaccíhuatl occasionally send out smoke clearly visible in Mexico City and ashes that sometimes reach the city. Popocatépetl showed renewed activity in 1995 and 1996, forcing the evacuation of several nearby villages and led to concern about the effect that a large-scale eruption might have on the heavily populated region nearby. Popocatépetl’s activity and all related concerns continue to date (Abeldaño Zúñiga & González Villoria, 2018).

In addition, the country registers more than 90 earthquakes every year with intensity of 4 degrees or higher on the Richter scale and has had major earthquakes over the past decades. Most recently, in September 1985, an earthquake measuring 8.0 on the Richter scale and centred in the subduction zone off Acapulco, killed more than 4,000 people in Mexico City, more than 300 kilometres away. The same region was rocked in September 2017 by a magnitude 8.1 earthquake that killed nearly 100 people and damaged thousands of buildings. A more damaging 7.1 earthquake in central Mexico later that month left more than 400 dead, including at least 228 in Mexico City.

It is estimated that 90% of natural disasters are hydro-meteorological and affect mainly the southeast of the country. Finally, there is an average of 23 hurricanes with winds of more than 63 km/h between the months of May and November. Of these, on average, 14 hurricanes occur in the Pacific Ocean and 9 in the Gulf of Mexico and the Caribbean Sea (United Nations Office for Outer Space Affairs, 2015). According to the United Nations, Mexico is classified amongst the top 30 countries worldwide exposed to three or more natural disasters of multiple magnitudes per year (United Nations Office for Outer Space Affairs, 2015).

Mexico has a National Civil Protection Program 2008-2012 that promotes a multi-institutional coordination, in the area of civil protection in order to protect the life, the environment and the patrimony of society. Thus, in an emergency, the first authority that has knowledge should provide immediate assistance and inform the specialised civil protection authorities. The hierarchical order goes from municipal authorities to the state ones and, finally, the federal ones. The municipal authority is the first specialised instance, and if its response capacity is overcome, then it must resort to the state authority, and so on, until it reaches the federal authorities.

In addition, the DN-III Plan organised by the Navy and Armed Forces, is in charge of organising and mobilising relocations (shelters, safe houses) for hurricane watch and of conducting recovery and reconstruction actions in case of disasters or damages after these events. Finally, the federal government operates a Natural Disaster Fund and the delivery of support to the population (Gobierno de México, 2008), but there are not any policies/plans for people living with dementia and other disabilities in case of emergencies.

References:

Abeldaño Zúñiga, R. A., & González Villoria, A. M. (2018). Desastres en México de 1900 a 2016: patrones de ocurrencia, población afectada y daños económicos. Revista Panamericana de Salud Pública, 42, 1–8. https://doi.org/10.26633/rpsp.2018.55

Gobierno de México. (2008). Programa Nacional de Protección Civil 2008-2012. Diario Oficial de La Federación. http://dof.gob.mx/nota_detalle_popup.php?codigo=5060600

United Nations Office for Outer Space Affairs. (2015). The Force of Nature in Mexico, as seen from space. http://www.unoosa.org/oosa/en/informationfor/articles/the-force-of-nature-in-mexico–as-seen-from-space.html

The country is currently experiencing an electricity crisis with the implementation of ‘load-shedding’ (i.e., blackouts) since 2008 as ESKOM (i.e., South Africa’s power utility) struggles to meet demand.

The Western Cape Province has also been experiencing its most severe drought since 2015, with water levels beginning to rise in September 2018 (see https://en.wikipedia.org/wiki/Cape_Town_water_crisis). By 2021 this drought had been resolved in the Western Cape but remains critical in some other provinces such as the Eastern Cape.

Government data published in May 2019 showed that 12.7% of the population are currently unemployed, with the highest concentration among young people, women, black, and mixed-race individuals. The unemployment rate in the age group 14 to 17 years reached 44.5%. Among those aged 18 to 24 years, the proportion of unemployed reached 31.9% in the Northeast region. However, the largest proportion of unemployment is concentrated among the population aged 25-59 (57.2%), followed by people aged 18 to 24 (31.8%), adolescents (8.3%) and people aged 60+ (2.6%). Women made up the majority (52.6%) of the unemployed population and the population outside the workforce (64.6%). Among men, the unemployment rate was 10.9% in the first quarter 2019, while among women it was 14.9% (Brazilian Institute of Geography and Statistics, 2019j).

References:

Brazilian Institute of Geography and Statistics. (2019j, April 30). Desemprego sobe para 12,7% com 13,4 milhões de pessoas em busca de trabalho. IBGE – Agência de Notícias. https://agenciadenoticias.ibge.gov.br/agencia-noticias/2012-agencia-de-noticias/noticias/24283-desemprego-sobe-para-12-7-com-13-4-milhoes-de-pessoas-em-busca-de-trabalho

In 2018, the labour force statistics estimated that the unemployment rate was 2.8% (112.0 thousand people) and the underemployment rate was 1.1% (43.2 thousand people). The unemployment rates by gender for male and female were 3.2% and 2.9%, respectively (Census and Statistics Department, 2019i).

References:

Census and Statistics Department. (2019i). Table E489: Land area, mid-year population and population density by District Council district. Retrieved from: https://www.censtatd.gov.hk/hkstat/sub/sp150.jsp?productCode=D5320189

The unemployment rate for those aged 15 years and above in India was estimated to be 5.8% between 2018-2019 (Ministry of Labour and Employment, 2021). This fell to 4.8% in 2019-2020.

In the year 2019-2020, the labour force participation for those aged 15+ increased to 53.5% from 50.2% in 2018-2019 (Ministry of Labour and Employment, 2021).

References:

Ministry of Labour and Employment. (2021). Employment Situation Improves. Government of India. Available from: https://pib.gov.in/PressReleseDetailm.aspx?PRID=1779665

The unemployment rate in Indonesia was 5.4% in 2017 (CIA World Factbook, 2019). The World Bank estimates that total youth unemployment (15-24 years) as percentage of the labour force amounted to 15.84% in 2018 (World Bank, 2019b).

Employment in the informal economy, which means employment without formal arrangements, is estimated to make up over 60 per cent of the workforce (International Labour Organization (ILO), n.d.-a). This prevailing practice causes some difficulties in estimating employment and unemployment rates in Indonesia. Furthermore, as pointed out above (01.03.04) and further discussed under (01.04) the absence of social protection means that older people are often engaged in economic activity by formal or informal employment into very old age (Kidd et al., 2018).

References:

CIA World Factbook. (2019). Indonesia. https://www.cia.gov/the-world-factbook/countries/indonesia/

International Labour Organization (ILO). (n.d.-a). Informal economy in Indonesia and Timor-Leste. Retrieved March 9, 2019, from https://www.ilo.org/jakarta/areasofwork/informal-economy/lang–en/index.htm#banner

Kidd, S., Gelders, B., & Rahayu, S. K. (2018). Implementing Social Protection for the Elderly in Indonesia. http://www.tnp2k.go.id/filemanager/files/Perlindungan Sosial Lansia/Elderly Brief – English Version.pdf

World Bank. (2019b). Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) – Indonesia. World Development Indicators. https://data.worldbank.org/indicator/SL.UEM.1524.ZS?locations=ID

Employment (status, sector, and hours), conditions of work (wages, compensation costs, working poverty) and characteristics of job seekers (education, labour productivity) form some of the key indicators of labour market. Kenya’s bulging youth unemployment rate is more than 20%, primarily due to reduced education opportunities. This is also reflected in the general population where unemployment and under-employment are extremely high (about 40% of the population) with a higher rate of unemployment among women (2.9%) compared to men (2.6%) (Central Intelligence Agency, 2019; International Labour Organization (ILO), 2016). A third of those employed (with 83% of all employment opportunities provided by the informal sector) in Kenya work for more than 48 hours per week.

References:

Central Intelligence Agency. (2019). The World Factbook: Africa – Kenya. . https://www.cia.gov/the-world-factbook/countries/kenya/

International Labour Organization (ILO). (2016). Country profile. https://www.ilo.org/dyn/normlex/en/f?p=1000:11110:0::NO:11110:P11110_COUNTRY_ID:103315

Unemployment slightly decreased in the immediate years previous to the year 2018 when it was estimated that 60% of the economically active population were employed (formal, informal and self-employed). Within total working age population, women’s participation, while increasing, still lags compared to men and to women in other Latin American countries, with 43.6% of total women 15 years and older reported in the labour force compared to 77.7% of men[1] (STPS, 2019).

Informal employment[2] amounts to approximately 57% of total working population. However, out of 100 Mexican pesos generated in the country, 77 come from formal employment and 23 from the informal economy (INEGI, n.d.-a). In relation to the group of people employed in the informal sector (16.0 million in 2018), 14.9% were self-employed in agriculture (no income/pay, no benefits), 14.6% worked in paid domestic services, but with no social security benefits, 9.3% worked without pay, and the remaining 61.2% were wage earners but without social security benefits (INEGI, n.d.-b; 2020).

The working status of older adults in Mexico is relevant. According to the National Employment and Occupation Survey, in 2018, 34.1% of adults 60 years and older were employed, and of these, 49.6% were self-employed (INEGI, 2018a).

[1]  Tasa Neta de Participación por Sexo: (PEA/PET en porcentaje)

[2] For statistics purposes the National Institute of Geography and Statistics, INEGI defines informal employment as that is those not affiliated to a social security institution granting health and employment benefits granted within social security insurance.

References:

INEGI. (2018a). Estadísticas a propósito del día internacional de las personas de edad (Adultos mayores). Datos nacionales. https://www.inegi.org.mx/contenidos/saladeprensa/aproposito/2018/edad2018_nal.pdf

INEGI. (2020). Estadísticas a propósito del día del trabajo. Datos nacionales. Comunicado de prensa núm. 166/20; 29 de abril de 2020. https://www.inegi.org.mx/contenidos/saladeprensa/aproposito/2020/trabajoNal.pdf

INEGI. (n.d.-a). Características educativas de la población. Retrieved March 16, 2022, from https://www.inegi.org.mx/temas/educacion/

INEGI. (n.d.-b). Directorio Estadístico Nacional de Unidades Económicas. DENUE. Retrieved March 16, 2020, from https://www.inegi.org.mx/app/mapa/denue/

STPS. (2019). Informaciòn laboral.

During the third quarter (July-Sept) of 2018, South Africa’s unemployment rate increased by 0.3 percentage point to 27.5% (StatsSA, 2018d). Compared to the second quarter (2018), employed persons increased by 92 000 (i.e., to 16.4 million), while persons slipping into unemployment increased by 127 000 (i.e., to 6.2 million) for the same period (StatsSA, 2018d). Currently, the national unemployment rate recorded for the first quarter of 2019 stands at 27.6% (StatsSA, 2019b). This trend in increasing unemployment has continued with a significant impact of the COVID-19 pandemic and associated lockdowns.

The latest statistical release indicates a further decrease in employment between the fourth quarter in 2018, with declines recorded in both the formal and informal sectors (StatsSA, 2019b). During the first quarter in 2019, the unemployment rate increased in 6 of the 9 provinces, with Mpumalanga (2.2%), Limpopo and Free State (2.0%), and Eastern Cape (1.3%) recording the largest increases in unemployment (StatsSA, 2019b).

In 2018, the expanded unemployment rate (i.e., including people who have stopped looking for work) increased from 36.7% in the second quarter to 37.2% in the third quarter, with higher rates for women (41.2%) than for men (33.7%) (StatsSA, 2018d, 2018c). This trend continued into the first quarter of 2019 with a recorded expanded unemployment rate of 38% (StatsSA, 2019b).

Regardless of race, men in South Africa are more likely to be in paid employment compared to women, who by the second quarter of 2018 totalled 55.2% of workers involved in non-market activities (StatsSA, 2018c).

Based on these figures, the female South African workforce continues to experience lack of opportunities, systematic inequality, and indirect discrimination (SAHRC, 2017a).

Table 7: South African labour force by age (Jul-Sept 2018)

15-24 yrs

(thousand)

25-34 yrs

(thousand)

35-44 yrs

(thousand)

45-54 yrs

(thousand)

55-64 yrs

(thousand)

Population 15–24 yrs 10308 9963 8137 5716 3861
Labour force 2664 7404 6535 4252 1734
Employed 1257 4890 5100 3570 1564
Unemployed 1408 2514 1435 683 170
Not economically active 7644 2559 1602 1463 2127

Source (data): (StatsSA, 2018d), p.23-24.

Table 8: South African labour force by gender (Jul-Sept 2018)

Third Quarter (Jul-Sept 2018) Men

(thousand)

Women

(thousand)

Population 15–64 years 18790 19195
Labour force 12349 10240
Employed 9156 7225
Formal sector (non-agriculture) 6427 4827
Informal sector (non-agriculture) 1892 1125
Agriculture 565 277
Private households 271 995
Unemployed 3194 3016
Not economically active 6440 8955
Discouraged work seekers 1213 1520
Other (not economically active) 5228 7435
Rates (%)
Unemployment rate 25.9 29.4
Employed/population ratio (absorption) 48.7 37.6
Labour force participation rate 65.7 53.3

Source (data): (StatsSA, 2018d), p.19-20.

References:

SAHRC. (2017a). RESEARCH BRIEF ON GENDER AND EQUALITY IN SOUTH AFRICA 2013 to 2017. Available from: https://www.sahrc.org.za/home/21/files/RESEARCH%20BRIEF%20ON%20GENDER%20AND%20EQUALITY%20IN%20SOUTH%20AFRICA%202013%20to%202017.pdf

StatsSA. (2017a). Public healthcare: How much per person? Statistics South Africa: Statistical Release. http://www.statssa.gov.za/?p=10548

StatsSA. (2018c). How do women fare in the South African labour market? Statistics South Africa. http://www.statssa.gov.za/?p=11375

StatsSA. (2018d). Quarterly Labour Force Survey. Available from: https://www.statssa.gov.za/?p=11882

StatsSA. (2019b). Quarterly Labour Force Survey: Q1 2019. Available from: https://www.statssa.gov.za/publications/P0211/Presentation_QLFS_Q1_2019.pdf

In 2019, we identified the highest proportion  of people having informal jobs (these are jobs without constitutional work rights, without formal job contract): 41.4% (Brazilian Institute of Geography and Statistics, n.d.). Data from a National Survey from 2015 (PNAD), showed that among the private sector, 20.6% of the workers were informal workers (that means without formal job contract) (Brazilian Institute of Geography and Statistics, 2015b).

References:

Brazilian Institute of Geography and Statistics. (n.d.). Desemprego cai para 11,8% com informalidade atingindo maior nível da série histórica. Retrieved December 3, 2019, from https://agenciadenoticias.ibge.gov.br/agencia-noticias/2012-agencia-de-noticias/noticias/25534-desemprego-cai-para-11-8-com-informalidade-atingindo-maior-nivel-da-serie-historica

Brazilian Institute of Geography and Statistics. (2015b). Pesquisa Nacional por Amostra de Domicílios—2015. https://biblioteca.ibge.gov.br/visualizacao/livros/liv98887.pdf

Economy activities are highly regulated and mostly taxed in Hong Kong. Most of employers are regulated by the Companies Ordinance and the Society Ordinance, whereas all forms of employment, including full-time, part-time, permanent, and temporary, are protected by the Employment Ordinance and Employee’s Compensation Ordinance. For self-employed individuals without a contractual agreement, their rights and benefits are less protected, and their income is taxable. As a result, the size of informal economy in Hong Kong is very small. The followings are the two major types of informal workers in Hong Kong: 1) foreign domestic helpers and 2) hawkers.

Foreign domestic helper is the main type of informal care workers in Hong Kong. By the end of 2018, there were a total of 386,075 foreign domestic helpers in Hong Kong (Census and Statistics Department, 2019j) and they comprised 5.2% of HK population as well as 9.7% of labour force (Census and Statistics Department, 2019j). Their income is not taxable. It is important to note that, unlike other countries, the rights and benefits of foreign domestic helpers in Hong Kong are protected, as well as the local citizens by the Employment Ordinance and monitored by the Immigration Department.

Hawkers refer to vendors selling street food and inexpensive goods in Hong Kong. Due to concerns about the city’s hygiene and health, the Government has begun to decrease the number of hawker licenses and impose stricter restrictions on hawking activities since 1970s. The number of licensed hawkers had dropped from over 70,000 in 1940s to 50,000 in 1970s. By the end of 2018, there were only 5,531 licensed hawkers, including fixed-pitch or itinerant (i.e., travelling) hawkers. At the same time, the Food and Environmental Hygiene Department has exerted strict control over illegal hawking activities and there were only around 1,511 hawkers by the end of 2018 (Food and Environmental Hygiene Department, 2019, September 5).

References:

Census and Statistics Department. (2019j). Women and Men in Hong Kong – Key Statistics 2019 Edition. Hong Kong Retrieved from https://www.statistics.gov.hk/pub/B11303032019AN19B0100.pdf

Food and Environmental Hygiene Department. (2019, September 5). Hawker Control. Retrieved from https://www.fehd.gov.hk/english/pleasant_environment/hawker/control.html

In 2018-2019, the proportion of workers in the non-agricultural sectors that were engaged in the informal sector was reported as 64.8% (National Statistical Office (NSO), 2020). The share of the informal non-agricultural sector was reported as 54.1% among female workers and 71.5% among male workers (National Statistical Office (NSO), 2020a).

References:

National Statistical Office (NSO). (2020a). Periodic Labour Force Survey [PLFS]. Ministry of Statistics and Programme Implementation, Government of India.

Based on labour force surveys, it has been estimated that between 61 and 70 per cent of the labour force are employed in the informal sector (Alatas & Newhouse, 2010; Firdausy, 2000). Rothenberg and colleagues (2016) explain the development of the Indonesia economy and its impact on the informal sector. Since the 1970s, Indonesia has developed from a ‘primarily agriculture-based economy’ to an economy based largely on manufacturing and services. In terms of GDP, the share of agriculture declined from 45 per cent (1970) to 14 per cent in 2014. The authors further explain that the reduction in agriculture coincided initially with urbanisation that led to an increase in the informal sector within urban areas. Growth in the manufacturing and service sectors led to an increase in formal sector employment ‘from 34.7 per cent to 44.9 per cent in 1997’ (Alatas & Newhouse, 2010, p.32). However, the economic crisis in 1998 led to shift from people formerly employed in the formal sector becoming employed in the informal sector. The following political crisis, resulting in ‘a regime change and political reform’ aimed to increase minimum wages. This development is understood to have contributed to the ‘weak recovery of formal sector employment’ (Rothenberg et al., 2016, pp.99-100).

References:

Alatas, V., & Newhouse, D. (2010). Indonesia Jobs Report: Towards Better Jobs and Security for All (Vol.2): Main Report (English). http://documents.worldbank.org/curated/en/601901468285575499/Main-reportAlzheimer’sDiseaseInternational

Firdausy, C. M. (2000). The social impact of economic crisis on employment in Indonesia. http://www.ismea.org/asialist/Firdausy.html

Rothenberg, A. D., Gaduh, A., Burger, N. E., Chazali, C., Tjandraningsih, I., Radikun, R., Sutera, C., & Weilant, S. (2016). Rethinking Indonesia’s Informal Sector. World Development, 80, 96–113. https://doi.org/10.1016/j.worlddev.2015.11.005

The informal sector consists of both professionals and non-professionals engaging in small-scale commercial activities such as selling second-hand items, shoe-shining, street vendors, carpentry, vegetable selling, repair and construction work. These activities are not formally established, regulated or protected by the government and often times, simple skills are used to generate income and profits (Institute of Economic Affairs, 2012). There is a higher labour force participation rate among men (77.5%) compared to women (71.5%) (International Labour Organization (ILO), 2016). The considerable part of the population that is unemployed or in the informal work is severely under-insured, which limits their access to health care significantly.

References:

Institute of Economic Affairs. (2012). Informal sector and taxation in Kenya. https://s3-eu-west-1.amazonaws.com/s3.sourceafrica.net/documents/118220/The-informal-sector-and-taxation-in-Kenya-IEA.pdf

International Labour Organization (ILO). (2016). Country profile. https://www.ilo.org/dyn/normlex/en/f?p=1000:11110:0::NO:11110:P11110_COUNTRY_ID:103315

Reportedly, 85.5% of all new businesses in South Africa start up unregistered and operate in the informal economy (Williams, 2017). The following describes the informal economy in South Africa (Williams, 2017):

  1. Approximately 32.7% of non-agricultural workers are employed in the informal economy, of which more than half (54.4%) are in informal jobs in informal enterprises;
  2. 39% of employed women and 29% of employed men are working within the informal economy;
  3. The informal workforce comprises of 67% informal employees, 25% ‘own account’ workers, 5% employers and 3% unpaid family workers;
  4. 26% of employment within metropolitan areas is informal and is distributed across trade (29%), private households (29%), construction (12%), manufacturing (8%) and services (other than private households) (7%).

When compared to other countries (e.g., India where the informal economy comprises 84.3%, Brazil 42.3%, and China 34.4%), the informal economy in South Africa is less pervasive and found in particular industries (Williams, 2017).

During South Africa’s third quarter in 2018, the informal sector increased in employment by 188 000 when compared to the previous quarter (StatsSA, 2018d). These gains were mostly seen by industries of trade (+75 000), finance and other business services (+67 000), and construction (+48 000) (StatsSA, 2018d). Employment losses within the informal economy for the same period were largely found within the community and social services (decreased by 7 000), mining (-2 000), and utilities (-1 000) industries.

Essentially, the increase of economic engagement in the informal sector means that fewer South Africans are contributing to tax – a key source of revenue for South Africa.

References:

StatsSA. (2018d). Quarterly Labour Force Survey. Available from: https://www.statssa.gov.za/?p=11882

Williams, C. C. (2017). THE INFORMAL ECONOMY AS A PATH TO EXPANDING OPPORTUNITIES. https://doi.org/10.2139/ssrn.2804172

Education is a constitutional right in Brazil and is offered freely through state schools, from nursery to post-graduate levels (Fortuna, 2018). From nursery to high school, education can be either full time or part time and includes free meals. State schools/universities are funded through the Federal, State or Municipal governments. However, given the low quality of education up to the end of high school in most areas of the country, many Brazilian citizens with the available means end up paying for private education. Around 21.7% of all schools in the country are private. Whilst state-funded schools represent the majority, only 36% of all students attending state schools end up going to university, whereas this rate reaches 79.2% in the private sector (self-funded). Whilst 51% of white students went to university in 2017, only 33.4% of black and mixed-race minority groups had the opportunity. In the private sector, though black and mixed-race people continue to be disadvantaged, the difference between the two groups reduced by 10%. Those who go to university are also the richest – the largest proportion of students in higher education come from families who are among the richest twenty five per cent of the country (Brazilian Institute of Geography and Statistics, 2018a).

Brazil has a system by which people from state schools and ethnic minorities have a small advantage when applying to state universities and might be entitled to scholarships to attend private universities. The government also provides loans for those who do not fit the criteria to the latter. Data from 2016 shows that among the population aged 15 years and over, the illiteracy rate is 7.2% (11.8 million people) (Ferreira, 2017). In people aged 60+, this index is almost three times higher (20.4%). The Northeast is the area with the highest illiteracy rate in Brazil: 14.8%. The lowest index is registered in the Southern region, with an illiteracy rate of 3.6%. Again, more black people are illiterate in comparison to white people (9.9% vs. 4.5%, respectively). Males are slightly more illiterate than females (7.4% vs. 7.0%, respectively). Besides the 7.2% of illiterate people, 21% of Brazilian people are ‘functionally illiterate’ (people who are considered to be educated but who are unable to interpret day-to-day information, including the costs of products in the supermarket, for example). Altogether, there are almost 30% of people in Brazil who are unable to understand basic texts and numbers (INAF, 2018).

References:

Brazilian Institute of Geography and Statistics. (2018a). Escola privada coloca o dobro de alunos no ensino superior em relação à rede pública. https://www1.folha.uol.com.br/educacao/2018/12/escola-privada-coloca-o-dobro-de-alunos-no-ensino-superior-em-relacao-a-rede-publica.shtml

Ferreira, P. (2017). Brasil ainda tem 11,8 milhões de analfabetos, segundo IBGE. https://oglobo.globo.com/sociedade/educacao/brasil-ainda-tem-118-milhoes-de-analfabetos-segundo-ibge-22211755

Fortuna, D. (2018). MEC divulga dados do Censo Escolar da educação básica. Correio Web.

INAF. (2018). INAF BRASIL 2018. https://www.correiodopovo.com.br/notícias/ensino/brasil-tem-cerca-de-38-milhões-de-analfabetos-funcionais-1.268788

 

In Hong Kong, preschool education is not free and is operated by non-profit-making and private enterprises. Primary, junior secondary, and senior secondary education for a total of 12 years are universal, mandatory, and free. For post-secondary education, higher education institutions provide publicly-funded as well as self-financing programmes at or above sub-degree level (Education Bureau, 2019). Regarding the population’s education level in 2018, the total population of no schooling/pre-primary was 3.8% (243.9 thousand people), primary was 14.1% (920.3 thousand people), lower secondary was 15.0% (973.0 thousand people), upper secondary was 34.0% (2214.1 thousand people), post-secondary non-degree was 7.7% (503.2 thousand people), and post-secondary degree was 25.4% (1651.9 thousand people). Among those aged 60 and over, the distribution of educational attainment were: 12.6% no schooling/pre-primary, 37.2% primary, 18.3 % lower secondary, 21.1% upper secondary, 3.3% post-secondary non-degree, and 7.5% post-secondary degree (Census and Statistics Department, 2019i).

References:

Census and Statistics Department. (2019i). Table E489: Land area, mid-year population and population density by District Council district. Retrieved from: https://www.censtatd.gov.hk/hkstat/sub/sp150.jsp?productCode=D5320189

Education Bureau. (2019). Education System and Policy. Retrieved from https://www.edb.gov.hk/en/index.html

The overall literacy rate in India was reported to be 74.04% in 2011 (Census of India, 2011). As per the more recent National Sample Survey Household Consumption on Education in India (2017-2018) which surveyed 64,519 rural and 49,238 urban households, literacy rates in the those aged 7 years and above was reported as 77.7% in 2017-2018 (National Statistical Office, 2020b).The literacy rate was lower in rural areas (73.5%) than urban areas (87.7%) and literacy rates were found to be higher in males (84.7%) than in females (70.3%) (National Statistical Office, 2020b).

References:

Census of India. (2011). Literacy in India. Available from https://www.census2011.co.in/literacy.php

National Statistical Office. (2020b). Household Social Consumption on Education in India-NSS 75th Round. Ministry of Statistics and Programme Implementation, Government of India.

 

The Indonesian system is made up of non-compulsory pre-school, compulsory primary school (Pendidikan dasar), secondary school and higher education. The compulsory primary education is made up of primary school (Sekolah Dasar) and junior secondary school. Secondary education consists of compulsory junior secondary school (Sekolah Menengah Pertama, SMP) and senior secondary school. Finally, higher education is offered at five ‘different types of institutions’. These are: universities (universitas), academies (akademi), colleges (sekolah tinggi), polytechnics (politeknik) and institutes (institute) (NUFFIC, 2017, pp.5-7).

Education for 6 years was made compulsory in 1950 and extended to 9 years in 1994 (NUFFIC, 2017, p.5). In 2016, the Ministry of Education and Cultural Affairs launched the Program Indonesia Pintar (Smart Indonesia Programme) to support the plan of raising this compulsory education to 12 years (an additional 3 years of senior high school) (Permendikbud No.19/2016 Tentang Program Indonesia Pintar (Ministry of Education and Culture’s Regulation No. 19/2016 on Smart Indonesia Program), 2016).

A number of ministries are involved in the organisation and management of the education system. The Ministry of the Interior carries responsibility for primary education, while the Ministry of National Education (Kementerian Pendidikan Nasional) looks after secondary and higher education. Islamic Education is managed by the Ministry of Religious Affairs and agricultural schools (secondary) by the Ministry of Agriculture (NUFFIC, 2017, p.5).

Private education has a significant role, with over 66 per cent of institutions in secondary and higher education operated by the private sector. Varying tuition fees create barriers to access and lead to considerable differences in the quality of education provided (NUFFIC, 2017, p.5).

According to UNESCO (2020) the literacy rate among the population aged 15 years and older has increased between 2000 and 2018 from 81.52 (males: 88.02; females 75.02) to 95.66 (males: 97.33; females: 93.99), respectively. Among the population aged 65 and older, UNICEF estimates the literacy rate to have increased from 53.22 (males: 68.65; females: 39.76) in 2004 to 74.34 (males: 84.61; females 65,69) in 2018 (UNESCO Institute for Statistics (UIS), 2020).

References:

NUFFIC. (2017). Education system Indonesia described and compared with the Dutch system. https://www.nuffic.nl/sites/default/files/2020-08/education-system-indonesia.pdf

Permendikbud No.19/2016 tentang Program Indonesia Pintar (Ministry of Education and Culture’s regulation No. 19/2016 on Smart Indonesia Program), (2016) (testimony of Kementerian Pendidikan dan Kebudayaan).

UNESCO Institute for Statistics (UIS). (2020). Indonesia. http://uis.unesco.org/en/country/id

In the recent past, Kenya’s enrollment numbers for primary education was 100% due to free primary education (Hall, 2017). In 2012, the gross enrolment ratio (total enrolment in secondary education, regardless of age, expressed as a percentage of the population of official secondary education age) in secondary schools was 67.6% which increased at an average annual rate of 4.67% since 1981 (29.3%) (Knoema, 2019b). However, only 3.3% of women and 4.7% of men enrolled in tertiary education but sometimes the education obtained does not provide the necessary skillsets for the job market  (Samuel Hall, 2017), contributing to an average of 10.48% unemployment rate (CEIC, 2019). It is worthy to note that the literacy rate in Kenya increased by 5.57% between 2007 and 2014. By 2014, the adult literacy rate was 78.73% (83.78% for females and 74.01% for males). The literacy rate for those aged 15 to 24 was 86.53% (86.14 for females and 86.94% for males) (Country Economy, 2019). In 2018, the adult literacy rate increased to 81.5% (Knoema, 2019a).

A major barrier to achieving higher levels of education are the high levels of poverty. Despite the fact that the government provides free secondary school education, most are boarding schools and parents still bear the cost of paying for meals in schools, boarding fees, buying uniform and examination fees. This results in children dropping out of school in cases where parents cannot afford these costs (James, Simiyu, & Riechi, 2016; Khamati & Nyongesa, 2013). Another contributing factor is the delay in disbursement of funds or treasury underfunding for secondary school fees and inconsistency in increasing the government’s contribution despite inflation, which makes the actual cost of secondary school education higher (Republic of Kenya, 2016a; Shiundu, 2017).

Other factors contributing to reduced school retention include peer pressure related to minimal interest in schooling, early marriages, pregnancies, domestic duties and negligence by parents (James et al., 2016). The few students who are able to withstand such pressures and stay in school are affected by (Khamati & Nyongesa, 2013):

  1. Delay in successful implementation of free secondary schools due to factors such as poor management (accountability, preparing budgets and general management of resources).
  2. Initial increase in enrollment in secondary schools leading to overstretching of the available resources including laboratories hence compromising the quality of education. This affects enrollment in tertiary education and results in more than 60% of the youth (aged 18 to 35) working in the informal sector, contributing to a high degree of income inequality.
References:

CEIC. (2019). Kenya Unemployment Rate. https://www.ceicdata.com/en/indicator/kenya/unemployment-rate

Country Economy. (2019). Kenya – Literacy rate. https://countryeconomy.com/demography/literacy-rate/kenya

Hall, S. (2017). Youth Employment in Kenya Literature Review. Nairobi. https://static1.squarespace.com/static/5cfe2c8927234e0001688343/t/5d42d9d220ada4000196692f/1564662260539/Samuel-Hall-Youth-Employment-in-Kenya-2017-for-the-British-Council.pdf

James, A. M., Simiyu, A. M., & Riechi, A. (2016). Factors Affecting Subsidized Free Day Secondary Education in Enhancing Learners Retention in Secondary Schools in Kenya. Journal of Education and Practice, 7(20), 49–55. https://files.eric.ed.gov/fulltext/EJ1109168.pdf

Khamati, M. J., & Nyongesa, W. J. (2013). Factors Influencing the Implementation of Free Secondary Education in Mumias District, Kenya. Journal of Social Science for Policy Implications, 1(1), 32–47. http://jsspi.com/journals/jsspi/Vol_1_No_1_June_2013/4.pdf

Knoema. (2019a). Kenya – Adult (15+) literacy rate. https://knoema.com/atlas/Kenya/topics/Education/Literacy/Adult-literacy-rate

Knoema. (2019b). Kenya – Gross enrolment ratio in secondary education. https://knoema.com/atlas/Kenya/topics/Education/Secondary-Education/Gross-enrolment-ratio-in-secondary-education

Republic of Kenya. (2016a). Education Sector Report, 2017/18 – 2019/20. https://planipolis.iiep.unesco.org/sites/default/files/ressources/kenya_education_sector_report.pdf

Shiundu, A. (2017). FACTSHEET: Cost of providing ‘truly’ free secondary education in Kenya. https://africacheck.org/fact-checks/factsheets/factsheet-cost-providing-truly-free-secondary-education-kenya

 

The educational system in Mexico is shared between central and regional authorities. Each of the 32 federal entities (31 states and Mexico City) operates their own education services and administrative norms that have not guaranteed equal success in the implementation of recent policy reforms or granted increased quality of education (Education Policy Outlook – OECD, n.d.). The National Union of Education Workers[1], with leaders in each state, has a strong lobby power and plays an important role in defining primary education policy issues, while most decisions in lower secondary education are taken by the central or state governments. Expenditure on education institutions as a percentage of GDP (for all educational levels combined) is above the OECD average, with a higher share of private funding than the OECD average (OECD, 2013). Mexico made upper secondary education compulsory in 2012 (aiming for universal coverage by 2022), extending compulsory education from early childhood and education and care (ECEC) starting at age 4-5 to around age 15.

According to the OECD’s Programme for International Student Assessment, PISA, Mexico is among the few countries with improvements in both equity and quality of education. Although its performance remains below the OECD average in mathematics, science, and reading, Mexico has achieved improvements in mathematics and reading, but remains unchanged with respect to their performance in science across assessment cycles. However, grade repetition is high, and there is a gap with other OECD countries in upper secondary and tertiary attainment, enrolment, graduation, and performance (OECD, 2013).

Literacy in Mexico is defined as those 15 years and older who cannot read or write a short message. Literacy rates among the population 15 years and older in 2015 was 95.3 with slight difference between men (96.2) and women (94.6). Among adults aged 65 years and older, gender differences are larger with rates of 84.5 and 77.4 for men and women, respectively (80.7 total) (UNESCO, n.d.). In addition, by 2015, large differences prevail among states with respect to their total literacy with rates of 84 in more deprived states such as Oaxaca and Chiapas and Mexico City and 98 in the State of Mexico and Mexico City (INEGI, n.d.-b).

[1] Sindicato Nacional de Trabajadores de la Educación, SNTE.

References:

Education Policy Outlook – OECD. (n.d.). Retrieved February 20, 2019, from http://www.oecd.org/education/policy-outlook/

INEGI. (n.d.-b). Directorio Estadístico Nacional de Unidades Económicas. DENUE. Retrieved March 16, 2020, from https://www.inegi.org.mx/app/mapa/denue/

OECD. (2013). Education Policy Outlook Mexico. http://www.oecd.org/education/policy-outlook/

UNESCO. (n.d.). Education and Literacy data by country. Retrieved March 16, 2021, from http://uis.unesco.org/en/country/mx

Two national departments are responsible for education in South Africa, namely (1) the Department of Basic Education (primary and secondary schooling) (DBE), and (2) Department of Higher Education and Training (DHET) (post-schooling education and training) (South African Government, 2018a). Education in South Africa is compulsory from grade 1 to 9 (age 7 to 15), and optional from grade 10-12 (Expatica, 2018). Public schools are funded by government and are run at provincial level. As a result, educational quality and standards vary between provinces and tend to be higher in bigger cities than in less developed areas (Expatica, 2018).

According to the General Household Survey of 2018, almost half of South African children aged 0-4 years remained home with parents/guardians (49.2%) with 38.4% attending grade R/day-care/educational facility outside of their home (StatsSA, 2019a). Attendance at ECD facilities was most common in major cities, such as Gauteng (49.8%), Free State (48.3%), and the Western Cape (43.7%).

In 2018, 32.2% of children and youth 5 years and older attended an educational institution of some kind, with 87.7% of this age range being in school and 4.5% in higher education institutions (StatsSA, 2019a). There is a noticeable delay in educational attainment whereby 11.4% of school-attending individuals are still attending secondary school by the age of 24, with very few entering tertiary levels of education (StatsSA, 2019a).

Women within this age range (5-24) who were not attending an education institution listed the following as their main reasons: (1) having no money for fees (25.2%), (2) poor academic performance (19%), and (3) family commitments (18.1%). Their male counterparts listed (1) poor academic performance (21.7%), (2) no money for fees (19.7%), and (3) education is useless (14%) as their main reasons (StatsSA, 2016).

According to the General Household Survey of 2015 (StatsSA, 2016), literacy was measured in terms of functional literacy (irrespective of a Grade 7 education) whereby respondents should (with reference to at least one language) indicate whether they have ‘no difficulty’, ‘some difficulty’, ‘a lot of difficulty’ or are ‘unable to’ read newspapers, magazines and books, or write a letter (StatsSA, 2016). Using this measure, literacy for persons over the age of 20 increased from 91.9% in 2010 to 93.7% in 2015 (StatsSA, 2016). The highest adult literacy rates for persons aged 20 and over were evident in the Western Cape Province (97.8%), followed closely by Gauteng (97.7%) and the Free State (94.5%).

More recently, the Organisation for Economic Co-operation and Development (OECD) has released a report on the status of education for partnering countries: “Education at a Glance 2018” (OECD, 2018), summarising the following for South Africa:

  • The younger generations (25–34-year-olds) are increasing their representation at higher education levels (i.e., 76% attaining secondary education);
  • Only 6% of adults are attaining tertiary level education;
  • 16% of children (5-14 years old) are not enrolled in any form of education (South Africa rating lowest across all partner countries);
  • For children under 5 years old, few are enrolled in pre-primary education (i.e., any form of Early Childhood Education and Care services) (17%), and less than 40% enrolled in school. School enrolment increases for 6-year-olds (75%) whereas at this age it’s universal at 98% for partner countries;
  • Many learners in secondary education are over-age (21%) and 16% in upper secondary general programmes are repeaters (rating highest across partner countries for both over-age and repeaters); and
  • Compared to partner OECD countries, South Africa also has the highest rate of persons 20–24-year-olds who are unemployed or not in any form of education or training.

Tertiary education in South Africa is very expensive. Since 2015, a student-led movement termed the “FeesMustFall” led a series of protests across South African universities to stop the increase of student fees and increase state expenditure for universities (see https://en.wikipedia.org/wiki/FeesMustFall). This movement succeeded in 2015 in preventing the increase of fees for 2016. However, protests flared up again in 2016 after it was announced that fees will increase in 2017 but will be capped at 8% (universities would decide by how much they would increase). This movement therefore reflects the limitations South Africans experience in accessing tertiary education.

References:

Expatica. (2018). Education in South Africa. https://www.expatica.com/za/education/children-education/education-in-south-africa-803205/

OECD. (2018). Education at a Glance: Country Note for South Africa. https://doi.org/10.1787/eag-2018-en

StatsSA. (2016). General Household Survey. Available from:  https://www.statssa.gov.za/publications/P0318/P03182015.pdf

StatsSA. (2019a). General Household Survey 2018. Available from: https://www.statssa.gov.za/?p=12180

South African Government. (2018a). Education. South African Government. Available from: https://www.gov.za/about-sa/education