# Point Estimation in Stata

Updated: Mar 16, 2020

After fitting a model and obtaining estimates for the coefficients, you may want to view the predicted average of the dependent variable with specific values of covariates. Today, we want to show you how to do this in three different ways.

I will use automobile dataset as an example. The linear regression I fit is shown below, with **mpg **being the dependent variable and **weight **being the independent variable. Stata also gives us the estimated value of the coefficient:

**Method 1: Using lincom command**

**lincom** stands for linear combinations of estimators. **lincom** can display estimates for any linear combination of coefficients. However, **lincom **will not work on non-linear combinations of coefficients. In the example below, I will show you how to use **lincom** to obtain the predicted average of **mpg** given the value of **weight **equals 3000. To do this, I would type:

The result is:

Note: When you type **weight**, **lincom** knows that you mean the coefficient of **weight**. The formal syntax for referencing this coefficient is **_b[weight]**, or alternatively, **_coef[weight]**. Thus, more formally, I would have typed:

**Method 2: Using display command**

The use of **display** command is similar to using **lincom** command, however, you will need to use the formal syntax to reference the coefficient. Thus, instead of typing **weight**, I would type **_b[weight]**:

**Method 3: Using margins command**

The **margins** command estimates margins of responses for specified values of covariates and presents the results as a table. To use **margins** command, you will need to specify a value of the covariate using the **at** option if it is a continuous variable. The **at **option specifies values for covariates to be treated as fixed. For example, to obtain the margins of **mpg** for weight values equals 3,000, I would type:

The result in Stata is: