Challenge 3 (Data Management)

Using the household_ea.dta data set that you created in exercise 8, we are going to dig a bit more into the consumption gap between households in rural and urban EAs. We will walk through a number of steps that require you to use the concepts and commands from earlier in Assignment 3.

• Start by using gen to create a variable called gap that equals 1 if the household’s consumption gap is negative. Then replace the value of gap so that it equals 0 if the household’s consumption gap is positive.
  • Hint: there are a number of households with missing values because either the household or EA data was missing. For reasons that are not important, Stata treates a missing value (the sysmis .) as positive infinity. So if you were to just type replace gen = 0 if cons_gap > 0 Stata will assign a 0 to household above the mean consumption but also to all households with missing values. So you need to add an additional conditional about cons_gap not equalling .
• Label the variable as Indicator for sign of consumption gap. Also define a value label called gap_lbl where 0 is Positive Gap and 1 is Negative Gap. Assign this value label to the gap variable.
• Use egen to create a variable called below that totals up all households with gap = 1. Do this by eaid and sector. Label the variable Number of households below mean consumption.
• Use egen to create a variable called above that totals up all households with gap = 0. Do this by eaid and sector. Label the variable Number of households above mean consumption.
  • Hint: when having Stata total up households with a positive gap, you need to explicitly tell Stata to count the households where gap == 0.
• Use egen to create a variable called tot_hh that counts up all households in an EA and sector. Label the variable Total number of households in EA.
• Use gen to create a variable called share_below that is the percentage of households with a negative consumption gap within an EA and sector. Label the variable Percentage of households in EA below mean consumption.

Now that we have all these variables created and labeled, we can ask questions about where the gap is most negative or most positive using bys in combination with sum.

1. Is the share of households with a negative consumption gap greater in urban or rural EAs?
2. Which country has the largest share of households with a negative consumption gap?
3. Which country has the smallest share of households with a negative consumption gap?

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