Coding for Applied Economists

Label Values (Tidy Data)

Using the World Bank’s LSMS data,

1. Define a value label set called yesno where 0 = No and 1 = Yes

2. Assign the value label set yesno to the following variables:

  • hh_shock
  • hh_primary_education
  • hh_electricity_access
  • hh_formal_education
  • nonfarm_enterprise

Defining value labels when there are just a couple options (yes/no, male/female) is fairly straightforward, especially when variables are already binary (0/1). But sometimes a variable already exists that has the information we want, just not in the form we want. In that case, we can create a new, intermediate variable, whose values are based on the existing variable. This allows us to change one form of data (strings) into another form (numeric) and then apply labels.

3. Create a variable called sector that equals 0 if urban = Rural and equals 1 if urban = Urban.

  • Label that variable “EA is rural or urban”
  • Define a value label set called sec_lbl where 0 = Rural and 1 = Urban
  • Assign the value label set sec_lbl to the variable sector
  • Drop urban and place sector after eaid (use help order if you need help with the order command)

Defining value labels in this way when there are a lot of options can become very tedious very quickly. Luckily, Stata has a decode/encode command that can sometimes creatly reduce the amount of coding you have to do to define and assign a label.

You will often have a variable which is a string that you would like to convert to a numeric. As an example, you can think of a variable called state that takes values of the name of each state in the U.S. In order to use this information in a regression, we need to convert the string to a numeric, like we did with sector. But with 50 state names, it will take a long time to 1) create a new variable that takes a unique numerical value for each state name and 2) define a label set for every value.

In this case, we can use encode to change the strings to numerical values and then use the string text as a value label for each numerical value. The syntax for the command is:

 encode varname, gen(newvar)

where varname is the name of the existing string variable and newvar is the new, numerical variable you want to create.

4. Encode the variable country so that it is a numerical variable and uses the string values as labels.

  • Call the new variable you create Country
  • Drop the old variable country
  • Rename Country as country
  • Use the command order to place country as the first variable in the data set

5. Encode the variable admin_1 so that it is a numerical variable and uses the string values as labels. Follow the same steps as in 4.4 and use order to place the new admin_1 immediately in front of admin_2.