Change Variables (Data Management)

Before undertaking this exercise, make sure you save the household-level version of that data that is currently in Stata’s memory. Save the file into your data folder and call it household_all.dta. Make sure you use the option replace so that when you run the .do file again it writes over any pre-existing versions of the data.

Using the World Bank’s LSMS data, use collapse to create an EA-level dataset (grouped by eaid and sector) that contains the following EA-level variables:

• Mean household size: based on hh_size
• Share of households with electricity: based on hh_electricity_access
• Share of households with a nonfarm enterprise: based on nonfarm_enterprise
• Mean total consumption in USD: based on totcons_USD

After the collapse, rename these variables as

• ea_hh_size
• ea_electricity_access
• ea_nonfarm_enterprise
• ea_totcons_USD

1. What is the average EA-level household size in urban and rural areas?

2. What percentage of urban households, on average, have electricity access? What percentage of rural households, on average, have electricity access?

3. What percentage of urban households, on average, have a non-farm enterprise? What percentage of rural households, on average, have a non-farm enterprise?

4. Is average EA-level consumption (mean_totcons_usd) higher in urban or rural areas?

Save this EA-level file as ea_summary.dta.

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