Problem set 3
You must submit all assignments as a PDF document. Answer all questions carefully and neatly. Use section headings to distinguish what question you are answering. Be neat. If the question involves a graph, copy/paste the graph into your document and make sure the graph has a title.
Task 1: Land Invasions in Brazil
Let’s look at this data on land invasions in Brazilian municipalities (similar to a US district) between 1988 and 2004. This data covers all of Brazil, not just rural areas.
|ext_pov||Extreme Poverty (Percent) 1991|
|occs||Land Invasions 1988-2004|
|logarea||Logged (Land Area)|
|logfam||Logged (Families Involved in Land Invasions) 1988-2004|
|logpop||Logged (Population) 1991|
- Look at one or two of the municipalities with the highest rates of land invasions. Look them up online, and also see if you can find any reference to invasions happening there (OK if you don’t); what are these places like? Where are they within Brazil? What stands out about them?
- Calculate and report the following across the sample: a) average percent of extreme poverty; b) average Gini coefficent (Google to learn what this is); c) the sum of all land occupations; d) the maximum number of families involved in a land invasion. Note that number of families is logged; to “unlog” you need to exponentiate the number and round. Briefly discuss the magnitude of these four statistics; are they surprising? Larger or smaller than expected?
Task 2: Measuring Wealth
Measuring wealth is hard. You can simply ask people how much they make each month, but their incomes might vary a lot from month to month. Some may not know, exactly, how much they make. And two people with the same monthly income may have very different levels of wealth.
We’re going to try to measure wealth using data on household assets from Honduras in 2018. Each of the
r columns tells you whether or not a household has a particular asset (e.g., fridge, cell phone, etc.). If a household has the asset, the cell = 1, otherwise = 0.
- Calculate the proportion of households who own an asset, for 5 assets of your choosing separately for urban and rural areas. Note: if you take the average of a variable that only takes on values of 0 or 1, the result is a proportion. Easiest way to do this is with a pivot table, putting the asset on “value” and
uron “rows”. Report the proportions for your assets. Are you surprised by the results? How different are urban and rural household ownership rates of these?
- Pick a set of 5 assets that you think would help distinguish people who are wealthier from people who are poorer. Make up reasonable prices (USD) for each of the assets. Now, create a new variable called
wealththat tells you how much “wealth” a person owns, in dollars, based on their ownership of these assets. The video I sent will be helpful here.
- Plot the distribution (histogram chart) of
wealthin the data. Do they fit what you’d expect? How skewed are they? What stands out about them?
- You’ve just created a measure of wealth based on household assets. Let’s see how well these measures capture wealth Using a pivot table, take the average of two non-asset variables you think should be related to wealth for each level of “wealth”. Then, plot “wealth” on the x-axis and these averages on the y-axis in two new plots. What does the relationship look like? Would you say the measure you created captures wealth well, or not?
|ed||Years of Schooling|
|q10new_18||Monthly Household Income|
|r1||Television in Home|
|r3||Refrigerator in Home|
|r4||Landline in Home|
|r4a||Cellular Telephone in Home|
|r5||Number of Vehicles at the House|
|r6||Washing Machine in Home|
|r7||Microwave Oven in Home|
|r12||Drinking water in Home|
|r14||Indoor Bathroom in Home|
|r15||Computer in Home|
|r16||Flat Panel TV in Home|
|r18||Internet Service in Home|
|q14||Intends to Live or Work Abroad|
|fs2||Has Run Out of Food in the Last 3 Months (1 = yes)|
|fs8||Has Gone without Meals in the Last 3 Months (1 = yes)|
|wf1||Receives Government Assistance (1 = yes)|