In G20 countries, the share of the population that earned at least the equivalent of the highest 10 percent of global income earners as of 2022 in purchasing power parity (PPP) terms varies from over two thirds in Australia to only *** percent in Indonesia. The United States recorded the second-highest upper-class share of the G20 countries. However, looking at for instance China, approximately ** percent of the population counts as middle class or above, whereas just ***** percent counts as upper class or higher.

Middle-income trap refers to the economic growth strategies that transition low-income countries into middle-income ones but fail to transition the middle-income countries into high-income countries. We observe the existence of a middle-income trap for upper-middle- and lower middle-income countries. We examine the reasons for the middle-income trap using the Bayesian model averaging (BMA) and generalized method of moments (GMM). We also explore the transformation of middle-income economies into high-income economies using logistic, probit and Limited Information Maximum Likelihood (LIML) regression analyses. Random forest analysis is also used to check the robustness of the findings. BMA analysis shows that education plays an enabling role in high-income countries in determining economic growth, whereas the full poten tial of education is not fully utilized in middle-income countries. GMM estimations show that the education coefficient is positive and significant for high-income and middle-income countries. This implies that education plays a decisive positive role in achieving economic growth and gives a path to escape from the middle-income trap. However, the education coefficient for middle-income countries is approximately half that of high-income countries. Therefore, the findings of this study call for additional investment and focused strategies relating to human capital endowments

Key information about Australia Household Income per Capita

• Australia Annual Household Income per Capita reached 30,914.027 USD in Jun 2020, compared with the previous value of 34,767.371 USD in Jun 2018.
• Australia Annual Household Income per Capita data is updated yearly, available from Jun 1995 to Jun 2020, with an averaged value of 25,207.153 USD.
• The data reached an all-time high of 43,819.349 USD in Jun 2012 and a record low of 15,753.318 USD in Jun 2001.
• In the latest reports, Retail Sales of Australia grew 4.217 % YoY in May 2023.

CEIC calculates Annual Household Income per Capita from annual Weekly Average Household Income multiplied by 52, annual Number of Household and quarterly Total Population and converts it into USD. The Australian Bureau of Statistics provides Average Household Income in local currency, Number of Household and Total Population. Federal Reserve Board average market exchange rate is used for currency conversions. Household Income per Capita is in annual frequency, ending in June of each year. Household Income per Capita prior to 2008 based on 2017-2018 price.

In financial year 2020, over 460 thousand households in Australia had a gross weekly household income of 6,000 Australian dollars or more. On the other end of the spectrum, over 30,000 households had a negative income and around over 32,000 had no income.

Australia Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Europe & Central Asia data was reported at 0.276 % in 2023. This records an increase from the previous number of 0.256 % for 2022. Australia Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Europe & Central Asia data is updated yearly, averaging 0.307 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 0.767 % in 1963 and a record low of 0.015 % in 1978. Australia Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Europe & Central Asia data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Exports. Merchandise exports to low- and middle-income economies in Europe and Central Asia are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Europe and Central Asia region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.;World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.;Weighted average;

Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Sub-Saharan Africa data was reported at 0.742 % in 2023. This records a decrease from the previous number of 0.860 % for 2022. Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Sub-Saharan Africa data is updated yearly, averaging 0.988 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 2.421 % in 2012 and a record low of 0.231 % in 1992. Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Sub-Saharan Africa data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Imports. Merchandise imports from low- and middle-income economies in Sub-Saharan Africa are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Sub-Saharan Africa region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.;World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.;Weighted average;

Merchandise imports from low- and middle-income economies outside region (% of total merchandise imports) in Australia was reported at 6.0179 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Australia - Merchandise imports from developing economies outside region (% of total merchandise imports) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

The Household, Income and Labour Dynamics in Australia (HILDA) Survey is a household-based panel study which began in 2001. The survey is conducted for the (Federal) Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA). The Nielsen Company conducted the fieldwork from 2001 to 2008; Roy Morgan Research 2009-. The primary objective of HILDA is to support questions falling into three broad areas: -Income dynamics - focusing on how households respond to policy changes aimed at improving financial incentives, and interactions between changes in family status and poverty. -Labour market dynamics - focusing on low-to-middle income households, female participation, and work to retirement transitions; and -Family dynamics - focusing on family formation, well-being and separation, along with post-separation arrangements for children, and on links between income support and family formation and breakdown. HILDA has the following key features: -It collects information about economic and subjective well-being, labour market dynamics and family dynamics. -Special questionnaire modules are included each wave. -The wave 1 panel consisted of 7,682 households and 19,914 individuals. -Interviews are conducted annually with all adult members of each household. -The panel members are followed over time. -The funding has been guaranteed for twelve waves, though the survey is designed to continue for longer than this. -Academic and other researchers can apply to use the General Release datasets for their research (see Access conditions). As of October 2011 nine waves of data are available to researchers. User Manuals at http://melbourneinstitute.com/hilda/doc/doc_hildamanual.html

Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: South Asia data was reported at 2.749 % in 2023. This records a decrease from the previous number of 3.010 % for 2022. Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: South Asia data is updated yearly, averaging 1.131 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 3.855 % in 1961 and a record low of 0.759 % in 1985. Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: South Asia data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Imports. Merchandise imports from low- and middle-income economies in South Asia are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the South Asia region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.;World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.;Weighted average;

Merchandise exports to low- and middle-income economies outside region (% of total merchandise exports) in Australia was reported at 7.201 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Australia - Merchandise exports to developing economies outside region (% of total merchandise exports) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

This series of information sheets introduces health literacy, its relevance to public policy, and the ways it can be used to inform the promotion of good health, the prevention and management of communicable and noncommunicable diseases, and the reduction of health inequities. It provides information and links to further resources to assist organizations and governments to incorporate health literacy responses into practice, service delivery systems, and policy.

Abstract

This file contains data on Gini coefficients, cumulative quintile shares, explanations regarding the basis on which the Gini coefficient was computed, and the source of the information. There are two data-sets, one containing the "high quality" sample and the other one including all the information (of lower quality) that had been collected.

The database was constructed for the production of the following paper:

Deininger, Klaus and Lyn Squire, "A New Data Set Measuring Income Inequality", The World Bank Economic Review, 10(3): 565-91, 1996.

This article presents a new data set on inequality in the distribution of income. The authors explain the criteria they applied in selecting data on Gini coefficients and on individual quintile groups’ income shares. Comparison of the new data set with existing compilations reveals that the data assembled here represent an improvement in quality and a significant expansion in coverage, although differences in the definition of the underlying data might still affect intertemporal and international comparability. Based on this new data set, the authors do not find a systematic link between growth and changes in aggregate inequality. They do find a strong positive relationship between growth and reduction of poverty.

Geographic coverage

In what follows, we provide brief descriptions of main features for individual countries that are included in the data-base. Without being comprehensive, these notes are intended to indicate some of the considerations underlying our decision to include or exclude certain observations.

Argentina Various permanent household surveys, all covering urban centers only, have been regularly conducted since 1972 and are quoted in a wide variety of sources and years, e.g., for 1980 (World Bank 1992), 1985 (Altimir 1994), and 1989 (World Bank 1992). Estimates for 1963, 1965, 1969/70, 1970/71, 1974, 1975, 1980, and 1981 (Altimir 1987) are based only on Greater Buenos Aires. Estimates for 1961, 1963, 1970 (Jain 1975) and for 1970 (van Ginneken 1984) have only limited geographic coverage and do not satisfy our minimum criteria.

Despite the many urban surveys, there are no income distribution data that are representative of the population as a whole. References to national income distribution for the years 1953, 1959, and 1961(CEPAL 1968 in Altimir 1986 ) are based on extrapolation from national accounts and have therefore not been included. Data for 1953 and 1961 from Weisskoff (1970) , from Lecaillon (1984) , and from Cromwell (1977) are also excluded.

Australia Household surveys, the result of which is reported in the statistical yearbook, have been conducted in 1968/9, 1975/6, 1978/9, 1981, 1985, 1986, 1989, and 1990.

Data for 1962 (Cromwell, 1977) and 1966/67 (Sawyer 1976) were excluded as they covered only tax payers. Jain's data for 1970 was excluded because it covered income recipients only. Data from Podder (1972) for 1967/68, from Jain (1975) for the same year, from UN (1985) for 78/79, from Sunders and Hobbes (1993) for 1986 and for 1989 were excluded given the availability of the primary sources. Data from Bishop (1991) for 1981/82, from Buhman (1988) for 1981/82, from Kakwani (1986) for 1975/76, and from Sunders and Hobbes (1993) for 1986 were utilized to test for the effect of different definitions. The values for 1967 used by Persson and Tabellini and Alesina and Rodrik (based on Paukert and Jain) are close to the ones reported in the Statistical Yearbook for 1969.

Austria: In addition to data referring to the employed population (Guger 1989), national household surveys for 1987 and 1991 are included in the LIS data base. As these data do not include income from self-employment, we do not report them in our high quality data-set.

Bahamas Data for Ginis and shares are available for 1973, 1977, 1979, 1986, 1988, 1989, 1991, 1992, and 1993 in government reports on population censuses and household budget surveys, and for 1973 and 1975 from UN (1981). Estimates for 1970 (Jain 1975), 1973, 1975, 1977, and 1979 (Fields 1989) have been excluded given the availability of primary sources.

Bangladesh Data from household surveys for 1973/74, 1976/77, 1977/78, 1981/82, and 1985/86 are available from the Statistical Yearbook, complemented by household-survey based information from Chen (1995) and the World Development Report. Household surveys with rural coverage for 1959, 1960, 1963/64, 1965, 1966/67 and 1968/69, and with urban coverage for 1963/64, 1965, 1966/67, and 1968/69 are also available from the Statistical yearbook. Data for 1963/64 ,1964 and 1966/67, (Jain 1975) are not included due to limited geographic coverage, We also excluded secondary sources for 1973/74, 1976/77, 1981/82 (Fields 1989), 1977 (UN 1981), 1983 (Milanovic 1994), and 1985/86 due to availability of the primary source.

Barbados National household surveys have been conducted in 1951/52 and 1978/79 (Downs, 1988). Estimates based on personal tax returns, reported consistently for 1951-1981 (Holder and Prescott, 1989), had to be excluded as they exclude the non-wage earning population. Jain's figure (used by Alesina and Rodrik) is based on the same source.

Belgium Household surveys with national coverage are available for 1978/79 (UN 1985), and for 1985, 1988, and 1992 (LIS 1995). Earlier data for 1969, 1973, 1975, 1976 and 1977 (UN 1981) refer to taxable households only and are not included.

Bolivia The only survey with national coverage is the 1990 LSMS (World Development Report). Surveys for 1986 and 1989 cover the main cities only (Psacharopoulos et al. 1992) and are therefore not included. Data for 1968 (Cromwell 1977) do not refer to a clear definition and is therefore excluded.

Botswana The only survey with national coverage was conducted in 1985-1986 (Chen et al 1993); surveys in 74/75 and 85/86 included rural areas only (UN 1981). We excluded Gini estimates for 1971/72 that refer to the economically active population only (Jain 1975), as well as 1974/75 and 1985/86 (Valentine 1993) due to lack of national coverage or consistency in definition.

Brazil Data from 1960, 1970, 1974/75, 1976, 1977, 1978, 1980, 1982, 1983, 1985, 1987 and 1989 are available from the statistical yearbook, in addition to data for 1978 (Fields 1987) and for 1979 (Psacharopoulos et al. 1992). Other sources have been excluded as they were either not of national coverage, based on wage earners only, or because a more consistent source was available.

Bulgaria: Data from household surveys are available for 1963-69 (in two year intervals), for 1970-90 (on an annual basis) from the Statistical yearbook and for 1991 - 93 from household surveys by the World Bank (Milanovic and Ying).

Burkina Faso A priority survey has been undertaken in 1995.

Central African Republic: Except for a household survey conducted in 1992, no information was available.

Cameroon The only data are from a 1983/4 household budget survey (World Bank Poverty Assessment).

Canada Gini- and share data for the 1950-61 (in irregular intervals), 1961-81 (biennially), and 1981-91 (annually) are available from official sources (Statistical Yearbook for years before 1971 and Income Distributions by Size in Canada for years since 1973, various issues). All other references seem to be based on these primary sources.

Chad: An estimate for 1958 is available in the literature, and used by Alesina and Rodrik and Persson and Tabellini but was not included due to lack of primary sources.

Chile The first nation-wide survey that included not only employment income was carried out in 1968 (UN 1981). This is complemented by household survey-based data for 1971 (Fields 1989), 1989, and 1994. Other data that refer either only to part of the population or -as in the case of a long series available from World Bank country operations- are not clearly based on primary sources, are excluded.

China Annual household surveys from 1980 to 1992, conducted separately in rural and urban areas, were consolidated by Ying (1995), based on the statistical yearbook. Data from other secondary sources are excluded due to limited geographic and population coverage and data from Chen et al (1993) for 1985 and 1990 have not been included, to maintain consistency of sources..

Colombia The first household survey with national coverage was conducted in 1970 (DANE 1970). In addition, there are data for 1971, 1972, 1974 CEPAL (1986), and for 1978, 1988/89, and 1991 (World Bank Poverty Assessment 1992 and Chen et al. 1995). Data referring to years before 1970 -including the 1964 estimate used in Persson and Tabellini were excluded, as were estimates for the wage earning population only.

Costa Rica Data on Gini coefficients and quintile shares are available for 1961, 1971 (Cespedes 1973),1977 (OPNPE 1982), 1979 (Fields 1989), 1981 (Chen et al 1993), 1983 (Bourguignon and Morrison 1989), 1986 (Sauma-Fiatt 1990), and 1989 (Chen et al 1993). Gini coefficients for 1971 (Gonzalez-Vega and Cespedes in Rottenberg 1993), 1973 and 1985 (Bourguignon and Morrison 1989) cover urban areas only and were excluded.

Cote d'Ivoire: Data based on national-level household surveys (LSMS) are available for 1985, 1986, 1987, 1988, and 1995. Information for the 1970s (Schneider 1991) is based on national accounting information and therefore excluded

Cuba Official information on income distribution is limited. Data from secondary sources are available for 1953, 1962, 1973, and 1978, relying on personal wage income, i.e. excluding the population that is not economically active (Brundenius 1984).

Czech Republic Household surveys for 1993 and 1994 were obtained from Milanovic and Ying. While it is in principle possible to go back further, splitting national level surveys for the former Czechoslovakia into their independent parts, we decided not to do so as the same argument could be used to

Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: East Asia & Pacific data was reported at 39.958 % in 2023. This records a decrease from the previous number of 40.365 % for 2022. Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: East Asia & Pacific data is updated yearly, averaging 11.395 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 40.665 % in 2020 and a record low of 3.151 % in 1975. Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: East Asia & Pacific data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Imports. Merchandise imports from low- and middle-income economies in East Asia and Pacific are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the East Asia and Pacific region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.;World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.;Weighted average;

Merchandise imports from low- and middle-income economies in Middle East & North Africa (% of total merchandise imports) in Australia was reported at 0.27805 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Australia - Merchandise imports from developing economies in Middle East & North Africa (% of total merchandise imports) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Australia Exports: Low- and Middle-Income Economies: % of Total Goods Exports: East Asia & Pacific data was reported at 46.863 % in 2023. This records an increase from the previous number of 39.930 % for 2022. Australia Exports: Low- and Middle-Income Economies: % of Total Goods Exports: East Asia & Pacific data is updated yearly, averaging 14.118 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 46.863 % in 2023 and a record low of 5.705 % in 1960. Australia Exports: Low- and Middle-Income Economies: % of Total Goods Exports: East Asia & Pacific data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Exports. Merchandise exports to low- and middle-income economies in East Asia and Pacific are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the East Asia and Pacific region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.;World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.;Weighted average;

This interview is part of the Women, Risk and Aids Project (1989-90) archive which was created as part of the Reanimating Data Project (2018-20).Anonymised transcript of interview with Justine, who is living with her girlfriend and co-parenting their child. She talks about the gay scene in Sydney and the sexual norms that it allowed. Justine has had some patchy use of contraception throughout her sexual relationships, relying mainly on the pill, and has contracted STDs. Her sex education in Australia was quite poor, especially around things like abortion that were taught by pro-life religious groups. AIDS information came from the gay community itself, gay media and through her job in the council - she wouldn't trust the 'regular' news. It has been quite a worry for her, especially as she is socialising within gay communities. Justine came out while at school, and faced a lot of homophobia, but saw it as an opportunity to challenge restrictive social norms in her suburban community. She's not sure what she'd like to do in the future, but does not envisage staying with her current partner for a long time.

Merchandise exports to low- and middle-income economies in Europe & Central Asia (% of total merchandise exports) in Australia was reported at 0.27606 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Australia - Merchandise exports to developing economies in Europe & Central Asia (% of total merchandise exports) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Australia Biohacking Market growth is driven by increasing internet penetration, wellness trends, and growing middle-class income levels.

Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data was reported at 1.783 % in 2023. This records a decrease from the previous number of 1.789 % for 2022. Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data is updated yearly, averaging 1.010 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 1.912 % in 2017 and a record low of 0.347 % in 1969. Australia Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Imports. Merchandise imports from low- and middle-income economies in Latin America and the Caribbean are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Latin America and the Caribbean region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.;World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.;Weighted average;

The Australian taxi industry, currently valued at approximately $3.73 billion (2025 estimated), is experiencing robust growth, projected to expand at a compound annual growth rate (CAGR) of 9.60% from 2025 to 2033. This growth is fueled by several key factors. Increasing urbanization and population density in major Australian cities like Sydney and Melbourne are driving demand for convenient and efficient transportation solutions. The rising adoption of smartphone technology and the increasing popularity of ride-hailing apps like Uber and Ola are significantly impacting the industry, shifting consumer preferences towards online booking options. Furthermore, the expanding middle class with increased disposable income contributes to higher spending on transportation services, boosting the market. However, the industry faces challenges such as stringent government regulations regarding licensing and fares, intense competition from ride-sharing platforms, and fluctuating fuel prices which impact operational costs. The segmentation of the market reveals a strong preference for online bookings, with a growing demand for SUVs/MPVs reflecting changing consumer needs. Companies like Uber Technologies Inc., Ola, and local players like Legion Cabs and GoCatch are key players vying for market share, adapting to technological advancements and consumer expectations. The competitive landscape fosters innovation, resulting in improved service offerings, technological integrations and more competitive pricing strategies. The future of the Australian taxi industry is dynamic. While the dominance of ride-hailing apps continues to shape the market, traditional taxi services are also adapting, often incorporating technological upgrades to enhance customer experience and operational efficiency. The industry’s growth trajectory will depend on successfully navigating regulatory hurdles, maintaining cost-effectiveness in a competitive landscape, and continuing to meet evolving consumer preferences. Further diversification of services, such as airport transfers and specialized transportation, will be crucial for sustained growth. Regional variations in market penetration exist; larger metropolitan areas naturally experience greater demand and higher adoption of technology compared to more rural regions. The industry's ability to leverage technological innovations to offer efficient, safe, and affordable services will be key to sustained success. This comprehensive report provides a detailed analysis of the Australian taxi industry, covering the period from 2019 to 2033. It leverages historical data (2019-2024), focusing on the base year 2025 and forecasting market trends until 2033. The report examines key market players, including Uber Technologies Inc, Taxi Apps Pty Ltd (GoCatch), GM Cabs, and others, offering invaluable insights for investors, businesses, and policymakers. With a focus on high-growth segments, including ride-hailing and ridesharing services, this report is essential for understanding the dynamic landscape of the Australian taxi market. Recent developments include: October 2022: Ingenico, the most trusted technological partner for payment acceptance, and Live Payments, one of Australia's leading payment service providers, announced their cooperation for long-term strategic partnerships to equip retailers and taxis with seamless and convenient payment and commerce solutions., October 2022: Uber announced the addition of the 500 Polestar 2s from Australia's largest provider of vehicle subscriptions to the rideshare segment. It announced its plans to offer them as the backbone of new electric rideshare from 2023 called Custom Electric for the taxi services in Sydney., April 2023: GM Cabs, the integral taxi service in Australia with a network of 30,000 taxis, announced the official launch of Taxi-Share 2023, a progressive and hybrid taxi service that combines the best of taxis and rideshare under the GM Cabs brand.. Key drivers for this market are: Growing Tourism Industry in Australia. Potential restraints include: Varying Government Regulations on Taxi Services. Notable trends are: Online Booking Holds the Highest Share.