Economic Data Analysis, Part II

Last week, we talked about using current events – in this case the State of the Union – as a starting point for lessons in all subjects. As a mathematics teacher, I took advantage of the speech as an entry point to conversations about global and national economics, and how to ask better questions as well as actually use data to analyze trends and form your own opinions. If you haven’t already, check out some of the prompts that I used as a starting point for my class lesson the day after the speech. You may even be able to adapt some of these questions into your classes! 

Now, before we jump into things, I guess I have to give my usual disclaimer. I dislike the party system. I am not affiliated with a political party. I try to use data to make informed decisions, and those decisions are often all over the board on the left-right spectrum, if only that spectrum didn’t include so much BS that I detest – the issues that politicians use to stir up emotions in people rather than reason. As nobel-economist Paul Krugman notes in his new book Arguing with Zombies, “In 21st-century America, accepting what the evidence says about an economic question will be seen as a partisan act.” Yes, it’s easy as a teacher to avoid trying to teach any of this stuff. But now, in this day and age, we need to more than ever.

Alright, picking off from where we left off last week, the prompt for students was to download this data set and begin analyzing it in Excel. I wanted them to do several things: first, calculate the ‘rich/poor ratio’ for every data-row shown, then, choose five countries for which you would like to compare the rich/poor ratios, and finally represent the country’s rich/poor ratio over time in a visual manner (e.g. create a graph). Keep in mind that this group of seniors have worked with Excel (Google Docs) over the course of the last six months in the context of polling statistics and financial literacy, including creating an entire amortization schedule using spreadsheets. 

This assignment, however, forces them to work with more data than they have ever seen. In order to answer my question, then, they also had to make use of some tools like the new Google Docs ‘Slicer’. As is typically the case for me, I gave them the hint that the tool might be useful, but forced them to use tenacity in pursuit with internet-based learning and figure out how to use it on their own (by reading the help bar associated with the tool as well as searching for instructions or tutorial videos on Google). 

After slicing the data for the countries they want, they are still faced with a conundrum: there is too much data to efficiently graph a chart that compares the rich/poor ratio for multiple countries over the entire 34 year time period. Thus, they need to re-organize the data to make graphing more efficient. Essentially, they need to create this: 

Screenshot 2020-02-20 at 5.04.36 PM

Notice that this table is reformatted to have ONLY the rich/poor ratio for each country shown, allowing us to create the following graph: 

I asked my class about what my graph tells us, which is that in the US, the top ten percent of richest citizens were between 11 and 20 times richer than the poorest ten percent – a ratio exceeded (on my graph) only by the Russian Federation! Thus, the conclusion we draw is that the US has much higher levels of inequity than the rest of the world. 

But HOLD ON there – is that a solid conclusion? What biases might my graph hold? What other countries did I choose, and how might that have affected our interpretations? What do we know about these countries and their histories/governmental systems that might give us more depth of insights into the data we just displayed? Obviously, this discussion eventually leads to me displaying another graph:

Does this graph lead us to draw different conclusions about the amount of inequity present in the United States? What do we know about these countries that may help us explain their rich/poor ratios? 

Ultimately, the point of this exercise was to convey the idea that we need to be able to quantitatively analyze our world if we are to understand its dynamics and be informed and engaged citizens, but that for all data that we can analyze, there are still ways of displaying the data that may draw us to different conclusions. Thus, for all of objective information that data can give us, there is always still a human element to understanding our world – a dose of morality overlaid on top of the cold, hard numbers. How will we choose to use our morality to draw proper conclusions? What questions do we still need to ask that will help us better understand this data? 

Well, one potential question was brought up during the last post I wrote on this topic – we are always hearing people like Bernie or Warren talk about the ‘top 1%’ – so how rich are the top 1% of Americans vs. the top 10%? Is that piece of data important as well? This is where my class dove back into the open-source economics textbook from core-econ; we analyzed the following chart from section 1.11:


As we can see, the modern state of affairs as captured by this particular measurement appears to be much more equitable than it has been in the past; however, the top 1% still control around 20% of the wealth of each of these nations! Thus, not only is it our responsibility to analyze quantitative data in order to make our own decisions about the economy, but we must also seek out a multitude of measures that can help us break down and express global trends in economic equity on a more complete level. 

To bring all of this back to the State of the Union, our students will still need a continuing education in economics and politics in order to understand common issues like our inflation rate and the role of the Federal Reserve. However, this can at least give them a starting point for discussions. For example, some students asked ‘Why do these inequities that we have been discussing arise?’ and began to answer their own question from a logical starting point: “Well, from a business perspective, there has to be an incentive for acting the way we act, and the incentive for a lot of our elected officials is all messed up – they serve richer voters disproportionately because that’s who donates to campaigns.” They even had the wherewithal to connect this statement to Andrew Yang’s comments during the PBS NewsHour/Politico debate in December: “And the question is why am I the lone candidate of color on this stage? Fewer than 5% of Americans donate to political campaigns. You know what you need to donate to political campaigns? Disposable income.” Don’t go all American on them now. They weren’t trying to claim that the ‘Freedom Dividend’ was the greatest idea they’d ever heard; they were just connecting the dots that the governmental system, the economic system, and inequities within a country are all connected in a big feedback loop that we should be paying attention to and thinking about more deeply. 


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