2 datasets found
  1. r

    Data from: Human capital and the middle-income trap revisited

    • researchdata.edu.au
    Updated Oct 11, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yarram Subba; Hoang Nam; Chambra Mundachalil; Subba Reddy Yarram; Nam Hoang; Mundachalil Jayadevan Chambra; CM Jayadevan; CM Jayadevan (2022). Human capital and the middle-income trap revisited [Dataset]. https://researchdata.edu.au/human-capital-middle-trap-revisited/3389232
    Explore at:
    Dataset updated
    Oct 11, 2022
    Dataset provided by
    University of New England, Australia
    University of New England
    Authors
    Yarram Subba; Hoang Nam; Chambra Mundachalil; Subba Reddy Yarram; Nam Hoang; Mundachalil Jayadevan Chambra; CM Jayadevan; CM Jayadevan
    Description

    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

  2. Religious Services in Australia - Market Research Report (2015-2030)

    • ibisworld.com
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    IBISWorld, Religious Services in Australia - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/au/industry/religious-services/681/
    Explore at:
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2013 - 2028
    Area covered
    Australia
    Description

    Australia has become an increasingly secular nation over the past five years. This trend has posed challenges to the Religious Services industry. This trend has continued, despite high immigration rates from regions with strong religious adherence aside from 2020-21 which was a full year of international border closures. Overall, the decline in adherence to most traditional Christian faiths is outstripping growth in adherence to most non-Christian religions. As a result, revenue generated by religious groups is expected to decline at an annualised 5.1% over the five years through 2023-24, to $3.9 billion, with margins declining to 8.6%.Cost-living-pressures have weighed on religious donations over the three years through 2023-24. Rising interest rates, inflation and rental costs have put many consumers under financial strain limiting their ability to contribute to their religious organisation. Declines have been mostly seen among lower- and middle-income earners who are struggling to cover rental costs and service their mortgages. Higher income earners are more insulated against changing economic conditions and have largely sustained their donation spending. As these higher income earners account for almost 70% of donations, industry revenue has been protected from steeper declines. These trends are expected to contribute to a 1.2% decline in industry revenue in the current year.Despite the nation becoming increasingly secular, forecast growth in household discretionary income, strong growth in net migration, and positive consumer sentiment are projected to boost donations to religious organisations over the next five years. However, falling adherence and attendance at religious services are anticipated to limit revenue growth. Overall, industry revenue is forecast to increase at an annualised 1.6% over the five years through 2028-29, to reach $4.2 billion.

  3. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Yarram Subba; Hoang Nam; Chambra Mundachalil; Subba Reddy Yarram; Nam Hoang; Mundachalil Jayadevan Chambra; CM Jayadevan; CM Jayadevan (2022). Human capital and the middle-income trap revisited [Dataset]. https://researchdata.edu.au/human-capital-middle-trap-revisited/3389232

Data from: Human capital and the middle-income trap revisited

Related Article
Explore at:
Dataset updated
Oct 11, 2022
Dataset provided by
University of New England, Australia
University of New England
Authors
Yarram Subba; Hoang Nam; Chambra Mundachalil; Subba Reddy Yarram; Nam Hoang; Mundachalil Jayadevan Chambra; CM Jayadevan; CM Jayadevan
Description

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

Search
Clear search
Close search
Google apps
Main menu