Merge Data (Data Management)

Using the World Bank’s LSMS data, we are going to practice merging datasets that represent different levels of aggregation (EA-level and household-level). Start by loading the ea_summary.dta file that you created in exercise 6. This will be the master file in memory.

1. Use isid to determine what variable(s) uniquely identify the data. What are these variable(s)?

Think through the structure of the EA and household data:

• In the EA summary dataset, each eaid–sector combination should appear once.
• In the household dataset, each eaid appears many times (one row per household).

This suggests a one-to-many merge: many households per EA, one EA-level summary per EA. Now merge the household data into the EA data.

2. How many matched and unmatched observations are there?

Now each household observation contains both:

• Household-level variables (e.g., totcons_USD, hh_dependency_ratio), and
• EA-level averages (mean_totcons_usd, mean_dep_ratio, etc.).

3. Create a consumption gap variable called cons_gap that is total household consumption (USD) minus mean consumption at the EA. This measures how much a household’s consumption differs from the average consumption in its EA. Is the consumption gap larger for rural households or urban households?

**Save this merged data set as household_ea.dta.

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