Analysis of Development Measures

… from the UNDP (United Nations Development Programme), 2020 Human Development Report. You need to analyze the following tables (you can access them from this page, too):

Making sense of information in tables

1. Table 1, Human Development Index
   1. you can display up to 100 countries [entries], which reduces the full table to two pages);
   2. You can also look at scores by country, over time.
   3. full explanation
2. Table 5, Gender Inequality Index
   1. full explanation
3. There are several other subsequent tables you might find useful as you explain results, but you don’t need to analyze them, or include them in the report–optional.
4. Don’t get hung up on the numbers! Some of them make sense (like births/1000 women, or % of parliament seats held by women), but in some cases it’s probably more meaningful just to look at relative positions–which countries are high/low? Which have the greatest/least disparities?

Guidance 

So, you’re to analyze two tables from the HDR: the HDI (Human Development Index) table, the Gender Inequality Index (GII) table, and the Environmental Sustainability dashboard ( . . . it’s a table). For each table, I would like a 1-2-page analysis of what you learned/observed. Describe what the statistics tell you about development (Table 1), and about the status of women (Table 5).  I would expect for each you’d provide:

1. a brief 1-2 sentence summary of what the table is trying to measure;
2. description and analysis of what you learned from the table (e.g., about gender differences on development measures, the usefulness of the measure, the possible difficulties of collecting reliable data for this measure, possible alternative measures that might better represent gender differences, maybe a better idea of where extreme gender differences exist in the world, or merely a better understanding of global inequalities by country, by continent, government type, etc.). Remember, though—you can use ‘developed’ countries for comparison, but they should not be the focus of your paper. Also make sure you describe how any indices were calculated (you should understand the difference between an index and a simple indicator or measure–it is not complicated).
3. a critique of the measures used—do they actually measure what they claim to? Are there other better measures available? How difficult might it be to collect data? Are there missing data that render the measures less meaningful?

Make sure you check out the supporting materials on the pages linked above—they will help you understand these measures and how they are used. But be skeptical–you’ll be reading some articles that suggest skepticism is warranted.

This assignment is in part about ‘statistical literacy’—can you take statistics, in this case in table form, understand and make sense of them, and identify what is important about them? These tables include both direct measures and indices (an index is a compilation of measures). So in other words, the HDI is a combination of three separate measures: how long people live, on average; how much education people have, on average; and how much money people have, on average. Especially with the income, an average can be very deceptive. For instance, if we took the average income of the students in class, let’s say 10 students, and everyone makes anywhere from $10,000 to $100,000 (no, that wouldn’t be me!), we might get an average somewhere around $30,000-$40,000. But if one of us were a millionaire, and all of the sudden it was $1.2 million divided by 10, the average would be $120,000. Only one person is doing really well, but that person brings the average way up. Check out Equatorial Guinea if you want to understand how one corrupt dictator plundering the treasury can influence GNI per capita.

Now, if we instead measured median incomes–that means took everyone’s income, and put it in order from least to most, and then chose the mid-point income–we would better represent how most people were doing. But that can also be deceptive if a lot of people in the country don’t really have much income, because they’re growing their own food instead (or fishing, or herding, etc.).

So for instance, one approach might be to take 3-4 countries and compare their numbers–say one from high/very high development, one from medium, a couple from low (that represent different geographic regions). You can look them up on country profiles and see how the numbers might have changed over time. Or you could base them on the GNI per capita minus HDI rank–where a positive number suggests: not much wealth, but distributed more evenly; and a negative number means: the wealth may be substantial, but it isn’t distributed well at all, meaning high rates of inequality. So you could pick a few countries that score really in the negative range, in the positive range, or even around zero (still trying to represent low-medium-high, though).

For example, a perennially-near-the-bottom country, Central African Republic, where life expectancy was 51 years in 2017. That doesn’t mean that people die of old age at 50. It does probably suggest high rates of infant and/or maternal mortality, lack of access to health care or public health improvements (clean water, for instance), or war/conflict, and of course poverty/famine. But we don’t know for sure unless we ask. The WHO (the UN’s World Health Organization) might provide clues. So if you do a little outside research, cite your sources (properly!). And … women live longer than men, on average. So if you find any countries where that isn’t the case, there is something terribly wrong going on with policies affecting women.

I’d also like to see a brief ending paragraph reflecting on the use of statistics in development—you can be critical, analytical, etc., but I’m looking for thoughtfulness. Do the existing measures we use tell us what we need to know? If not, why do we use them?

I would recommend you find someone in class to proofread anything you turn in, including this assignment. Or the online writing lab. I would hope that from this assignment you gain:

1. a better feel for the geography of gender differences and global inequalities;
2. a grasp of the concepts underlying gender and development measurement (e.g., what are the important things that will tell us if people’s / women’s lives are improving or not?);
3. a better understanding of the difficulties and complexities in trying to quantify and measure gender bias and more generally development;
4. an appreciation of the importance of measurement in trying to assess whether development is taking place—what is measured, how is it measured, does the measure actually do what it claims to do?

Keep in mind as well, that sometimes these organizations have to choose measures that are already being collected. They may know they’re not the best, but to try to collect median income instead of average income for instance would be pretty difficult, and require knowing everyone’s income and arraying them in order. And there are literally billions of people — the US president included — who don’t really want people to know how much money they make, or how much wealth they own.

As you go through these, consider possible alternative measures. For instance, ‘health/well-being’ might be measured as number of doctors per 100,000 residents (regardless of where they’re located), or life expectancy, infant mortality, total daily caloric intake, etc—all yielding different kinds of data and different conclusions. Keep in mind, measurement costs money—data have to be collected, compiled, analyzed, etc. Where does the information come from? Interviews with illiterate villagers (that is, who won’t be filling out surveys)? Official report? How hard to collect? Would possible better measures be harder to collect?

Look through these indicators for some guidance if it helps. Here’s a discussion of the HDI.

The final report should be double-spaced, no longer than 6 pages in length, due July 27.

The final version worth 50 points. Here’s a sample paper (ignore the part 2)