Table 1 shows the findings of the FIML approach for system estimation, including coefficients and standard error estimates, z-statistics, p values, and summary statistics. Table 1 shows the results of the system of equations estimation. All of the coefficients are positive and statistically significant, with the exception of the newborn mortality rate coefficient, which is also significant but with a negative sign. The residuals capture the effect of unobservable factors, and they’re all positive and significant at the 5% level. It suggests that having a greater GDP per capita and a lower infant mortality rate leads to a longer life expectancy at birth, implying that individuals in these five countries are living longer. Our theories and hypotheses back up these findings. Because the newborn mortality rate coefficient has a negative sign, it is assumed to play a role in explaining the trend in life expectancy. The findings show that a country’s population health and socioeconomic development have a significant impact on life expectancy at birth; in other words, as a country’s population health and socioeconomic development improves, infant mortality rates decrease, and life expectancy at birth appears to rise. Through increased economic growth and development in a country, GDP per capita raises life expectancy at birth, resulting in a longer lifespan. Both the GDP per capita and infant mortality variables show signals that are compatible with the research hypotheses and support the arguments for socioeconomic development’s influence on lifespan. This suggests that the extent and form of the demographic transition process in these five EU accession candidate nations were defined by the justifications of the first demographic transition in terms of socioeconomic conditions.
Sensitivity analysis
The results’ sensitivity was investigated in terms of the nations and statistical model assumptions, the level of variation in life expectancy, and the individual effects of both explanatory factors. When looking at the equation statistics for each of the countries in Table 2, it is clear that Albania has the highest adjusted R-squared of 0.97. Furthermore, Macedonia, Serbia, and Bosnia and Herzegovina all have high adjusted R-squared values of around 0.90, 0.87, and 0.86, respectively. Montenegro has the lowest adjusted R-squared score of only 0.36. As a result, we may conclude that the indicated variables have the greatest impact on life expectancy at birth in Albania and Macedonia, Bosnia and Herzegovina, and Serbia. Specifically, the impacts and influences of the selected independent (socioeconomic) variables: GDP per capita and infant mortality rate, respectively, explain 85 to 97 percent of the changes in life expectancy at birth in these four nations from 1990 to 2017. The remaining 3 to 15% of differences are unaccounted for by this model and are attributable to other causes.
There are several intriguing and relevant results when looking at the individual effects of both explanatory variables (infant mortality rate and GDP per capita) within each country. Bosnia and Herzegovina and Albania, which are nearly equal in importance, had the most substantial negative effects of the infant mortality rate on life expectancy at birth, at a level of 5%. Within all countries, Serbia’s positive effect of GDP per capita on life expectancy at birth is greater than that of the others.
What is the relationship between GDP and life expectancy?
“Adriana Lleras-Muney, an economics professor at the University of California, Los Angeles, describes the situation as “quite perplexing.” “We know that people in wealthy countries live longer than those in impoverished nations. GDP and life expectancy have a strong association, implying that more money is better. Despite this, we discover that when the economy is doing well, when it is growing faster than normal, more people are dying.”
Does GDP help people live longer?
To be more explicit, for every 1% rise in GDP per capita, life expectancy increases by 5.38 years; for every 1% increase in public health spending as a percentage of total government spending, life expectancy increases by 0.327 years.
Is there a link between GDP and life satisfaction?
GDP is a rough indicator of a society’s standard of living because it does not account for leisure, environmental quality, levels of health and education, activities undertaken outside the market, changes in income disparity, improvements in diversity, increases in technology, or the cost of living.
Why do unemployment and GDP have such a significant relationship?
Why is there such a close link between unemployment and GDP in the United States? Consumer spending accounts for two-thirds of the GDP in the United States. When the unemployment rate rises, consumer spending decreases. Here’s a graph that shows a country’s nominal and real GDP growth.
What elements help people live longer?
According to a new study led by the Harvard T.H. Chan School of Public Health, maintaining five healthy habits during adulthood eating a healthy diet, exercising regularly, maintaining a healthy body weight, not drinking too much alcohol, and not smoking can add more than a decade to life expectancy.
Over the course of the nearly 30-year study period, researchers discovered that American women and men who lived the healthiest lifestyles were 82 percent less likely to die from cardiovascular disease and 65 percent less likely to die from cancer than those who lived the least healthy lifestyles.
The average life expectancy in the United States is 79.3 years, which is lower than almost all other high-income countries. In 2015, the United States was rated 31st in the world for life expectancy. The goal of the current study was to determine how much healthy lifestyle characteristics can help people live longer in the United States.
Researchers at Harvard Chan looked at 34 years of data from 78,865 women and 27 years of data from 44,354 men who took part in the Nurses’ Health Study and the Health Professionals Follow-up Study, respectively. The researchers looked at how five low-risk lifestyle factors not smoking, a low BMI (18.5-24.9 kg/m2), at least 30 minutes of moderate to vigorous physical activity per day, moderate alcohol intake (for example, one 5-ounce glass of wine per day for women, or two glasses for men), and a healthy diet might affect mortality.
What variables influence a country’s life expectancy?
Reduced infant mortality, improving living standards, improved lifestyles and education, as well as breakthroughs in healthcare and medicine, have all contributed to an increase in life expectancy at birth over the previous century.
During the last century, economic development and improvements in some environmental circumstances (for example, in many urban areas), improved lifestyles, developments in healthcare and medicine, including lower infant mortality, have resulted in a steady increase in life expectancy at birth.
Gender, genetics, access to health care, hygiene, diet and nutrition, exercise, lifestyle, and crime rates all play a role in life expectancy. According to evidence-based studies, longevity is determined by two key factors: heredity and lifestyle choices.
According to twin studies, heredity accounts for about 20-30% of an individual’s lifetime, with the remainder owing to individual actions and environmental factors that can be changed. Furthermore, it was shown that at the age of 80, lifestyle plays absolutely no role in health and longevity, and that almost everything in senior age is due to genetic factors.
Why Do Women Live Longer Than Men?
Women outlive men on average, and this was true in pre-industrial periods as well as today. Smaller bodies (and thus less stress on the heart), a better immune system (since testosterone works as an immunosuppressant), and a lower proclivity to engage in physically risky activities are all reasons for this.
It’s also possible that women have evolved to live longer in order to assist in the care of grandkids and great grandchildren.
Will you live longer if you come from a family who have lived long lives?
The Long Life Family Study (LLFS) has recently confirmed that severe mortality-related diseases are less common in the family of long-lived people than in the general population. (Evidence from the Long Life Family Study: Are Members of Long-Lived Families Healthier than Their Equally Long-Lived Peers) An multinational collaboration to look into the genetics and familial factors that contribute to remarkable survival, longevity, and aging well.
Seven conditions were shown to be much less common in siblings in a long-lived family than in comparable aged controls, according to researchers:
The LLFS siblings, on the other hand, were more likely to be treated for arthritis, cataracts, osteoporosis, and glaucoma. These long-lived sib-ships’ spouses, offspring, and offspring spouses all had a much lower risk of Alzheimer’s, diabetes, and heart failure. As a result, it appears that both hereditary and environmental variables are at work. Given that the majority of the offspring generation is still under the age of seventy-five, it will be fascinating to watch if the early evidence for a health advantage in long-lived families’ genetic and marital relatives strengthens as the cohort grows older.
Male and female longevity are influenced by differences in education, career possibilities, lifestyle behaviors, social mobility, and the larger local environment. Where we reside appears to have an impact on how long we live. However, there are things we can do regardless of where we live to increase our chances of living a longer and healthier life.
- Don’t smoke, binge drink, eat a nutritious diet, and exercise on a regular basis. This can give you an extra ten years of life.
- Maintain and strengthen your social networks, whether they are with family or friends. According to several research, this has a health-protective impact.
- Even if you didn’t perform well in school, take advantage of any educational chances that come your way as an adult. This appears to be beneficial to one’s health.
- Volunteer – Regardless of where you reside, there are likely to be chances to volunteer, and some research suggest that doing so might assist maintain mental health and extend life expectancy.
How to Work Out Your Age in Days Weeks/Months/Years/Years/Years/Years/ Find out how many days you’ve been living, what day of the week you were born on, and how many days, weeks, months, and years you’ve lived since your birthday.
Check Your True Health Age with the Biological Age Calculator – Your approximate health age or biological age, as well as your predicted life expectancy, are calculated using the real age calculator.
Mr. Le Van So and Mrs. Nguyen Thi Loi, an old Asian couple who have been married for 70 years and are still very much in love.
Some of the Longest Living People Include
The Gerontology Research Group verifies current longevity records using modern criteria and maintains a list of super-centenarians; nonetheless, there are numerous additional unsubstantiated longevity claims. Individuals who possess records include:
- Sarah Knauss (1880-1999, 119 years and 97 days) was the world’s second-oldest documented person and the oldest American.
- Christian Mortensen (1882-1998, 115 years, 252 days) is the oldest individual in history whose age can be verified using contemporary technology.
- Jeanne Calment (1875-1997, 122 years, 164 days) is the oldest person in history whose age can be verified using contemporary technology. This is the modern human life span, which is determined by the oldest person ever documented to have lived.
While some other people have survived between 110 and 114 years, the above persons are the only ones known to have lived for more than 114 years. Benjamin Franklin, Thomas Jefferson, John Adams, Cato the Elder, Thomas Hobbes, and Michaelangelo are among the people who lived to reach 75 years old or more before the twentieth century.
Will Humans Live Longer in the Future?
According to the United States Census Bureau, life expectancy in the United States will be in the mid-80s by 2050 (up from 77.85 in 2006) and will eventually peak in the low-90s, barring major scientific advances that can change the rate of human aging itself, rather than just treating the effects of aging as it is done today. However, recent rises in the incidence of lifestyle disorders including obesity, diabetes, hypertension, and heart disease may significantly impede or reverse the industrialized world’s trend toward longer life expectancy.
Some argue that molecular nanotechnology will significantly increase human life expectancy. If these technologies can enhance the rate of increase in life span to a level of twelve months per year, this is referred to as effective biological immortality and is the goal of radical life extension.
Why do certain countries have longer life expectancies than others?
In Sierra Leone and the Central African Republic, life expectancy is 52 years, while in Japan and Hong Kong, it is 84 years. “>1] a stunning 32-year gap. These high health disparities are partially a reflection of global financial disparities. Wealthier countries have a longer average life expectancy than poorer ones, which can be attributed to greater living standards, more effective health systems, and more resources invested in health determinants (such as sanitation, housing, and education). Preston discovered a cross-sectional logarithmic curve relationship between national income per capita and life expectancy, in which life expectancy increases rapidly with national income at first, before tapering off, with higher income countries receiving diminishing returns for increases in national income. This is a good example “The “Preston curve” was a fitted trendline, with some countries falling above the trendline, achieving higher life expectancy than predicted from their income, and others falling below the trendline, achieving lower life expectancy than expected from their income. While it is still critical to address severe wealth disparities between countries, it is equally critical to explore why some countries have longer or shorter life expectancies than would be expected based on their GDP. The term is used by us “To describe countries that achieve better population health outcomes and, as a result, longer life expectancy than would be expected from their wealth, the phrase “punching above their weight” (PAW) is used. We, on the other hand, employ the term “Punching below their weight” (PBW) is a term used to describe countries that do not translate their wealth into improved population health and long life expectancies. Preston hypothesized that within-country disparities would lead to punching below weight, and he theorized on the drivers of countries punching above or below weight.
The reasons why some countries punch above or below their weight are still a mystery, and this is the gap that the study detailed here aimed to fill. Previous research has mostly focused on health outcomes in LMICs and the impact of the health system on health outcomes, with little emphasis paid to other potential contributing factors. The important 1985 research ‘Good Health at Low Cost’ gathered expert perspectives made at a conference on the achievements of four low-income countries with good health outcomes: Sri Lanka, China, Costa Rica, and Kerala State in India. The conference’s concluding statement identified five factors that helped these countries achieve good health outcomes at a low cost: I political commitment to health advancement, ii) valuing equity and community participation, iii) provision of quality education, particularly for women, iv) sufficient and sustained investment in primary health care, and v) strong intersectoral linkages to support health.
In 2011, a follow-up study was conducted on the four nations from the Good Health at Low Cost project, and five new case study countries were chosen: Bangladesh, Ethiopia, Kyrgyzstan, Thailand, and the Indian state of Tamil Nadu. To analyze the case studies, the researchers gathered health indicator data, analyzed literature, and used theoretical frameworks. Their findings revealed that the creation of strong and resilient health-care systems, backed by good governance and agility in the face of political turmoil, conflict, and natural disasters, contributed to significant improvements in health status. Although these studies emphasized the relevance of transportation infrastructure, gender equity, and education, they largely focused on the role of health services. The confluence of broader social, environmental, political, and commercial determinants of health has received little attention. Studying these factors in both punching above and punching below weight countries could provide more insight into how countries can maximize population health outcomes given their wealth levels.
A wide range of social, political, and commercial determinants of health, which interact through a web of causations working within and across interrelated systems, have been highlighted in research. Policies and actions in and outside of health care systems that address social determinants of health, such as poverty and hunger alleviation, education, access to good water, housing, sanitation, and labor rights, as well as climate change action, have an impact on population health. This complicated, varied set of long-term processes makes it difficult for researchers to figure out how to enhance national population health outcomes. While Preston curves are often studied as a cross-section of a single point in time, countries’ historical legacies will vary, incorporating variables such as colonialism and the history of political institutions and their relationship to economic growth. Awareness current economic and health results requires an understanding of a country’s history.
The Punching Above Weight (PAW) Research Network (https://www.flinders.edu.au/southgate-institute-health-society-equity/punching-above-weight-network) includes the authors of this research. The network was founded in 2017 to investigate the core question of why some countries have a longer or shorter life expectancy than would be expected based on their GDP. Through scoping assessments of three countries: Ethiopia (PAW), Brazil (PAW), and the United States (PAW), the research detailed in this paper intended to determine the extent to which existing literature and data can address the question (PBW).
Why is GDP not a reliable economic indicator?
- It ignores the underground economy: Because GDP is based on official data, it ignores the size of the underground sector, which might be large in some countries.
- In a globally open economy, it is geographically limited: Gross National Product (GNP), which quantifies the production of a nation’s population and businesses regardless of their location, is seen as a better measure of output than GDP in some situations. For example, GDP does not account for earnings made in a country by international enterprises and remitted to foreign investors. This has the potential to exaggerate a country’s actual economic production. In 2012, Ireland’s GDP was $210.3 billion and its GNP was $164.6 billion, with the difference of $45.7 billion (or 21.7 percent of GDP) owing mostly to profit repatriation by foreign corporations based in Ireland.
- It prioritizes economic output above economic well-being: GDP growth alone is insufficient to assess a country’s development or citizens’ well-being. For example, a country’s GDP growth may be high, but this may come at a large cost to society in terms of environmental effect and income imbalance.
What is the problem with GDP?
This is just beginning to change, with new definitions enacted in 2013 adding 3% to the size of the American economy overnight. Official statistics, however, continue to undercount much of the digital economy, since investment in “intangibles” now outnumbers investment in physical capital equipment and structures. Incorporating a comprehensive assessment of the digital economy’s growing importance would have a significant impact on how we think about economic growth.
In fact, there are four major issues with GDP: how to assess innovation, the proliferation of free internet services, the change away from mass manufacturing toward customization and variety, and the rise of specialization and extended production chains, particularly across national borders. There is no simple answer for any of these issues, but being aware of them can help us analyze today’s economic figures.
Innovation
The main tale of enormous rises in wealth is told by a chart depicting GDP per capita through time: relatively slow year-on-year growth gives way to an exponential increase in living standards in the long run “History’s hockey stick.” Market capitalism’s restless dynamism is manifested in the formation and expansion of enterprises that produce innovative products and services, create jobs, and reward both workers and shareholders. ‘The’ “Economic growth is fueled by the “free market innovation machine.”
Why is GDP a poor indicator of economic growth?
Living standards have risen all throughout the world as a result of economic expansion. Modern economies, on the other hand, have lost sight of the reality that the conventional metric of economic growth, gross domestic product (GDP), just measures the size of a country’s economy and does not reflect the welfare of that country. However, politicians and economists frequently use GDP, or GDP per capita in some situations, as an all-encompassing metric for measuring a country’s progress, combining economic success with societal well-being. As a result, measures that promote economic growth are perceived as positive for society.
We now understand that the reality is more complicated, and that focusing just on GDP and economic gain as a measure of development misses the negative consequences of economic expansion, such as climate change and income inequality. It’s past time to recognise GDP’s limitations and broaden our definition of development to include a society’s quality of life.
This is something that a number of countries are starting to do. In India, for example, where we both advise the government, an Ease of Living Index is being developed to gauge quality of life, economic ability, and sustainability.
Our policy interventions will become more aligned with the qualities of life that citizens actually value, and society will be better served, if our development measures go beyond an antagonistic concentration on increased productivity. But, before we try to improve the concept of GDP, it’s important to understand where it came from.
The origins of GDP
The contemporary idea of GDP, like many of the other omnipresent things that surround us, was born out of battle. While Simon Kuznets is frequently credited with inventing GDP (after attempting to quantify the US national income in 1932 in order to comprehend the full magnitude of the Great Depression), the present concept of GDP was defined by John Maynard Keynes during WWII.
Keynes, who was working in the UK Treasury at the time, released an essay in 1940, one year into the war with Germany, protesting about the insufficiency of economic statistics in calculating what the British economy might produce with the available resources. He stated that the lack of statistics made estimating Britain’s capacity for mobilization and combat problematic.
According to him, the sum of private consumption, investment, and government spending should be used to calculate national income. He rejected Kuznets’ version, in which the government’s income was represented but not its spending. Keynes observed that if the government’s wartime purchase was not factored into national income calculations, GDP would decline despite actual economic expansion. Even after the war, his approach of measuring GDP, which included government spending in a country’s income and was driven by wartime necessities, quickly gained favor around the world. It is still going on today.
How GDP falls short
However, a metric designed to judge a country’s manufacturing capability in times of conflict has clear limitations in times of peace. For starters, GDP is an aggregate measure of the value of goods and services generated in a certain country over a given time period. There is no consideration for the positive or negative consequences produced during the production and development process.
For example, GDP counts the number of cars we make but ignores the pollutants they emit; it adds the value of sugar-sweetened beverages we sell but ignores the health issues they cause; and it includes the cost of creating new cities but ignores the worth of the crucial forests they replace. “Itmeasures everything in short, except that which makes life worthwhile,” said Robert Kennedy in his famous election speech in 1968.
The destruction of the environment is a substantial externality that the GDP measure has failed to reflect. The manufacturing of more things increases an economy’s GDP, regardless of the environmental damage it causes. So, even though Delhi’s winters are becoming packed with smog and Bengaluru’s lakes are more prone to burns, a country like India is regarded to be on the growth path based on GDP. To get a truer reflection of development, modern economies need a better measure of welfare that takes these externalities into account. Expanding the scope of evaluation to include externalities would aid in establishing a policy focus on their mitigation.
GDP also fails to account for the distribution of income across society, which is becoming increasingly important in today’s world as inequality levels rise in both the developed and developing worlds. It is unable to distinguish between an unequal and an egalitarian society if their economic sizes are identical. Policymakers will need to account for these challenges when measuring progress as rising inequality leads to increased societal discontent and division.
Another feature of modern economies that makes GDP obsolete is its disproportionate emphasis on output. From Amazon grocery buying to Uber cab bookings, today’s cultures are increasingly driven by the burgeoning service economy. The concept of GDP is increasingly falling out of favor as the quality of experience overtakes unrelenting production. We live in a society where social media provides vast amounts of free knowledge and entertainment, the value of which cannot be quantified in simple terms. In order to provide a more true picture of the modern economy, our measure of economic growth and development must likewise adjust to these changes.
How we’re redefining development in India
In order to have a more holistic view of development and assure informed policymaking that isn’t solely focused on economic growth, we need additional metrics to supplement GDP. Bhutan’s attempt to assess Gross National Happiness, which takes into account elements including equitable socioeconomic development and excellent governance, and the UNDP’s Human Development Index (HDI), which includes health and knowledge in addition to economic prosperity, are two examples.
India is also started to focus on the ease of living of its population as a step in this approach. Following India’s recent push toward ease of doing business, ease of living is the next step in the country’s growth strategy. The Ease of Living Index was created by the Ministry of Housing and Urban Affairs to assess inhabitants’ quality of life in Indian cities, as well as their economic ability and sustainability. It’s also expected to become a measurement tool that can be used across districts. We feel that this more comprehensive metric will provide more accurate insights into the Indian economy’s current state of development.
The ultimate goal is to create a more just and equitable society that is prosperous and provides citizens with a meaningful quality of life. How we construct our policies will catch up with a shift in what we measure and perceive as a barometer of development. Economic development will just be another tool to drive an economy with well-being at its core in the path that society chooses. In such an economy, GDP percentage points, which are rarely linked to the lives of ordinary folks, will lose their prominence. Instead, the focus would shift to more desirable and genuine wellbeing determinants.