Macros in Stata, Why and How to Use Them

by Jeff Meyer

We finished the last article about Stata with the confusing coding of:

I admit it looks like a foreign language.  Let me explain how simple it is to understand. Let’s look at the first line from above:  local continuous educatexper wage age

Stata allows you to use a single word, such as “continuous”, to represent many other words.  In Stata this process is known as a macro.

Please note that a macro in Stata is not the same as a macro in Microsoft Excel.

Writing macros in Excel can be long and involved.

Writing a macro in Stata is very easy.

How to write a simple macro in Stata

A macro in Stata begins with the word “global” or “local”.  The command global tells Stata to store everything in the command line in its memory until you exit Stata.  If you open another data set before exiting, the global macro will still be in memory.

The command local tells Stata to keep everything in the command line in memory only until the program or do-file ends.

If you plan on analyzing only one data set then the global command shouldn’t cause you any problems.

If you will be analyzing more than one data set then you might want to consider using the local command.

If you remember from the previous article, the wages data set had four continuous variables.

In the first line of my code above, local continuous educat exper wage age, I am using the word “continuous” to represent the four variables educat, exper, wage, and age.

But why bother with a macro?

Using a macro allows me to simplify my work, which will reduce the potential for errors and keep it organized.

The code below will perform the exact same actions as the code above.

local continuous educat exper wage age
tab1 `continuous’
codebook `continuous’
summarize `continuous’

The command local tells Stata to use the word continuous to represent the variables educat, exper, wage, and age.  I then substitute the word continuous for the variable names in the the last lines.

Note that each time you use the word continuous in a command line you must begin with the forward slanting single quote key ` (to the left of the 1 key on your keyboard) and finish with the backward slanting single quote key ‘ (to the right of the ; key on your keyboard).

Using a macro to represent several variables may not seem like a big deal and why bother with it.  But wait, there is more.

For example, you might have to run numerous linear regressions, using several of the same predictor variables in each regression you run. After reviewing your results you might decide to eliminate one of the variables.

If you didn’t use a macro you will have to go back to every line of code and remove it. If you did use a macro you will only have to go back to the line of code for the macro and remove the variable from the group.

Remove it once and it is gone. Que facil!

Macros for formatting tables and graphs

Another great use for macros is for creating tables and graphs.  Unless you are Raymond (of Rain Man fame), there is no way you will remember your favorite options when creating a graph.

What are options for a graph?  To name just a few, the major and minor tick labels for the X and Y axis, the X and Y axis scale properties, whether to have a legend, placement of the legend, placement of the title, etc. etc.

It would sure be easier to use a one word macro to represent all of the above.

I suggest you create a do-file template for tables and graphs (see my previous article on creating do-file templates).

In the template you create various macros that contain the options for your tables and graphs.

Be sure to document (by using // or “*” as discussed in the previous article) in your do-file what the table or graph will look like.

Perhaps the best reason for using the macros for your table and graph formatting is it ensures consistent formatting.

If you decide you want to tweak how the tables in your research paper look, you will only need to make a change to the macro.  This saves you from having to go back to every table and change the coding.

In my next article I will show you another way to save time and effort in Stata through looping.

Jeff Meyer is a statistical consultant with The Analysis Factor, a stats mentor for Statistically Speaking membership, and a workshop instructor. Read more about Jeff here.