Both Selim Jahan’s podcast on human development and Hans Rosling’s critique of current data usage in humanitarian efforts emphasized the importance of moving away from the traditional methods of analyzing standards of living and moving on to a more holistic approach to big data analysis if we are to efficiently target our resources in providing effective humanitarian aid. While it may be true that percentage growth in GDP by country does have some impact on income, and therefore wellbeing, both authors reveal important underlying problems of relying on these traditional statistics. According to Jahan and Rosling, the main problems of using these old methods stem from their oversimplification of real-world problems. For instance, Jahan states that official statistics for employment only include paying jobs located outside the informal sector. As a result, employment paints a holy inaccurate picture of current problems facing targeted countries by disregarding essential work such as caretaking and cultural advancements. Even if these measurements could consider more variables, Rosling points out that it is almost never the case that all citizens in one country live in the same society. Even in cases where countries that need aid receive it, each dollar goes disproportionately to the wealthy due to a lack of precision in our aid efforts.
As a solution, both authors imply that the solution to our current inadequate data is to take advantage of modern technology. Using big data, we can not only better integrate a wider variety of important variables but create high resolution maps that are much more precise than entire countries. According to both authors, such an approach will allow us to create an accurate assessment of that problems facing humanitarian agencies and ensure that resources are allocated where they are needed most.
Even in a developed country such as the United States, I can see the need for replacing old methods of analysis such as traditional statistics by country with an aggregated approach that uses computers to make our models more accurate and precise. Our healthcare system currently spends more per citizen on healthcare than any other country in the world, yet our quality of care is inadequate when compared to other industrialized countries. If we were to use the methods described by Jahan and Rosling, overhead costs and premium payments could be drastically reduced, freeing up desperately needed funds for infrastructure and education. Similarly, the current statistics used in the United States such as average income and labor force participation fail to capture the externalities create by poverty. An example of this includes California, a state government that made rational decisions based on our current statistics by attempting to attract new better educated residents by gentrifying many of its downtown urban areas, but failed to account for the subsequent rise in rent. The increase in housing prices in combination with a lack of an increase in income created a severe housing crisis. If our world could transfer to the methods proposed by Jahan and Rosling, even countries as rich as the United States could benefit tremendously.
While Selim Khan does acknowledge the importance of traditional statistics such as economic growth and wages in the advancement of human development, he argues that our typical understanding of the definition of human development is fundamentally wrong. Khan argues that typical measurements not only cannot account for the important necessity of having choices and input in our daily lives, but also cannot account for the equally important non-wage-earning work, such as artistic work and caretaking. In addition to not being able to measure progress, Selim Khan points out that the traditional measurements of human development may draw attention away from what he sees as the three most important problems facing progress today: the exploitation of child labor, a persistent gender wage gap, and our ineffectiveness in properly responding to both manmade and natural disasters. As a solution, Selim Khan suggests that we not just “look at the door” of statistics, but instead use measurements such as the human development index to paint a more holistic picture of the problems that our society has yet to overcome.
In order to illustrate the importance of healthcare in the development of economic growth, Hans Rosling uses descriptive statistics to illustrate the growth of South Korea’s economy vs. Brazil’s economy over the course of fifty years. While Brazil was significantly more wealthy than South Korea during the 1960s, South Korea’s focus on healthcare created a better educated and safer population that was able to quickly overtake Brazil in terms of GDP growth during the years following the Korean war. Rosling provided further evidence by illustrating the child mortality rate and GDP per capita of the United Arab Emirates, which had tremendous wealth due to oil, but still lagged other countries until money was properly invested into essential services such as hospitals and education. In addition to the importance of healthcare, Rosling warned the audience of using average data to generalize not only regions such as sub-Saharan Africa, but even countries such as South Africa. By splitting up countries into their respective income brackets, Rosling demonstrated that even populations within the same borders can live vastly different lives and that contextualization is essential to effectively providing aid for human development.