Higher and more equal: a case for optimism

Some good news for the holiday season. The human population has made much progress the past few decades. We are richer, happier and healthier than ever before, and the world population became more equal. Here are data that show improvements on the most important metrics.


The average income levels (adjusted for inflation) are increasing in all continents. Global GDP per capita increased from around $4000 in 1960, to almost $9000 in 1990, to almost $15.000 today. At the same time, the global income inequality is declining, from a Gini-coefficient of 67 to 57 over the last three decades. Also, the number of people living in extreme poverty (consumption per capita less than 1,90 international dollars per day) declined from 1840 million (35% of the world population) in 1990 to less than 800 million (10% of the population) today. That is an average rate of one person out of extreme poverty per second. Interestingly, most people believe that the proportion of the world population living in extreme poverty has increased, so they have overly pessimistic judgments.

Life expectancy

Life expectancy positively correlates with income and shows an increasing trend in all world regions over the past decades. The global average life expectancy at birth increased from 52 years in 1960 over 65 years in 1990 to 72 years today. Interestingly, most people tend to think that average life expectancy is less than 60 years, so they have overly pessimistic judgments. Also the healthy life expectancy (the number of healthy life years) has increased, and the global inequality in life expectancy has decreased over the past decades.

Life satisfaction and happiness

The average life satisfaction score (on a range from 0 to 10) and the percentage of people who say they are happy have increasing trends and both positively correlate with income (GDP per capita) and life expectancy. This correlation is present when looking at different countries, looking within countries and looking at the evolution over time. The happiness inequality shows a decreasing trend, even in countries with increasing income inequality. So we can expect that the global inequality in life satisfaction is also decreasing. Interestingly, people tend to strongly underestimate the happiness of others, so they have overly pessimistic judgments.


The total fertility rate (number of children born to a woman over her lifetime) decreased from 5 in 1950, to 3 in 1990, to less than 2,5 today. This is close to the replacement level of 2,1 children. That means there is – as far as we know – only one species that managed to avoid overpopulation (or overreproduction): the human species. Other species have much higher fertility rates (often more than 10 children per animal), which results in an overpopulation: a lot of newborn non-human animals cannot survive until reproductive age. Those non-human animals give birth to many children, but more than 90% of those children die soon after they are born, and they experience a lot of problems that are typically associated with overpopulation, such as deadly diseases and mass starvation. Each generation of a non-human animal species experiences a drastic collapse due to overreproduction, because more than 90% of the newborn population dies at an early age. This is an extreme overreproduction problem in nature. In contrast, in the human species, almost all newborn children can have long fulfilling lives.

Africa, the area that has the highest human population growth levels and the highest fertility rates (often more than 4 children per woman), is still much less crowded than areas where all children can have long happy lives, such as Western-Europe. The human population density in Africa is on average 43 people per km², compared to 179 people per km² in Western-Europe. Even in 2068, with an expected density of 130 people per km², Africa will be less densely populated than modern day Western-Europe. And by that time, the fertility rate in Africa will be dropped as well and extreme poverty can be eradicated. So it becomes unlikely that the human species will face an overpopulation problem of the same level as the one faced by all other wild animal species, where more than 90% of the newborn children die.


Putting it all together, I think there is a lot of evidence to be optimistic and to acknowledge two things.

1: The world is getting better (at least for humans), so some things to improve the world are effective and do work. There is plenty of evidence for this statement, as written in books such as Steven Pinker’s The Better Angels of Our Nature and Enlightenment Now, Hans Rosling’s Factfulness, Matt Ridley’s The Rational Optimist and Michael Shermer’s The Moral Arc.

2: The world is far from good enough, so we need more effective altruism to keep on improving the world in the most effective ways. Work needs to be done, especially on reducing farm animal suffering, wild animal suffering and catastrophic extinction risks.

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3 reacties op Higher and more equal: a case for optimism

  1. Wendy Dresen zegt:

    A positive vibe to start the new year☺️

  2. pessimistic zegt:

    In reply, some reasons for pessimism:

    1 Regarding inequality:
    Use the absolute GINI rather than the relative GINI
    and use longer time series

    2 Regarding poverty, the morally most relevant measure is where needs are greater than resources

    3 The number of animals exploited for food is astronomical. That number also keeps growing and it grows faster than the number of humans who are lifted from extreme poverty

    • stijnbruers zegt:

      1. I prefer the relative Gini index as a measure of inequality, for several reasons. First, there is the decreasing marginal utility of income, so a difference between earning $10 and $20 is stronger than a difference between earing $110 and $120. Second, absolute Gini is the multiplication of relative Gini with the average income level. I consider an increase in the relative Gini as bad but an increase in average income as good (therefore in my article I mentioned the increase in average income per capita), so absolute Gini multiplies a bad with a good, which makes it confusing. Third, relative Gini is always bounded between 0 and 1, which makes it a good index, whereas absolute Gini is unbounded. Fourth, one can choose A.(1-RG) as a goal function to be maximized, where A is the average income and RG is the relative Gini index. In this sense, a term A.RG – which equals the absolute Gini index – is included (subtracted). But if A increases and RG decreases, the goal function increases.
      I don’t see why longer time series are required: the point is there exist a recent episode where inequality decreased. In other words: if we move from the present back to the past, we first see an increase in inequality.

      2. I don’t understand this point

      3. I absolutely agree: for the animals, the world is becoming worse.

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