Most economics departments require second- or third-year undergraduate students to complete an econometrics project and write a paper on their findings. Many students find that choosing a research topic for their required econometrics project is just as difficult as the project itself. Econometrics is the application of statistical and mathematical theories and perhaps some computer science to economic data.

The example below shows how to use Okun's law to create an econometrics project. Okun's law refers to how the nation's output—its gross domestic product—is related to employment and unemployment. For this econometrics project guide, you'll test whether Okun's law holds true in America. Note that this is just an example project—you'll need to chose your own topic—but the explanation shows how you can create a painless, yet informative, project using a basic statistical test, data that you can easily obtain from the U.S. government, and a computer spreadsheet program to compile the data.

### Gather Background Information

With your topic chosen, start by gathering background information about the theory you're testing by doing a t-test. To do so, use the following function:

**Y _{t} = 1 - 0.4 X_{t}**

Where:

Yt is the change in the unemployment rate in percentage points

Xt is the change in the percentage growth rate in real output, as measured by real GDP

So you will be estimating the model: **Y _{t} = b_{1} + b_{2} X_{t}**

Where:

Y_{t} is the change in the unemployment rate in percentage points

X_{t} is the change in the percentage growth rate in real output, as measured by real GDP

b_{1} and b_{2} are the parameters you are trying to estimate.

To estimate your parameters, you will need data.

Use quarterly economic data compiled by the Bureau of Economic Analysis, which is part of the U.S. Department of Commerce. To use this information, save each of the files individually. If you've done everything correctly, you should see something that looks like this fact sheet from the BEA, containing quarterly GDP results.

Once you've downloaded the data, open it in a spreadsheet program, such as Excel.

### Finding the Y and X Variables

Now that you've got the data file open, start to look for what you need. Locate the data for your Y variable. Recall that Yt is the change in the unemployment rate in percentage points. The change in the unemployment rate in percentage points is in the column labeled UNRATE(chg), which is column I. By looking at column A, you see that the quarterly unemployment rate change data runs from April 1947 to October 2002 in cells G24-G242, according to Bureau of Labor Statistics figures.

Next, find your X variables. In your model, you only have one X variable, Xt, which is the change in the percentage growth rate in real output as measured by real GDP. You see that this variable is in the column marked GDPC96(%chg), which is in Column E. This data runs from April 1947 to October 2002 in cells E20-E242.

### Setting Up Excel

You've identified the data you need, so you can compute the regression coefficients using Excel. Excel is missing a lot of the features of more sophisticated econometrics packages, but for doing a simple linear regression, it is a useful tool. You're also much more likely to use Excel when you enter the real world than you are to use an econometrics package, so being proficient in Excel is a useful skill.

Your Yt data is in cells G24-G242 and your Xt data is in cells E20-E242. When doing a linear regression, you need to have an associated X entry for every Yt entry and vice-versa. The Xt's in cells E20-E23 do not have an associated Yt entry, so you will not use them. Instead, you will use only the Yt data in cells G24-G242 and your Xt data in cells E24-E242. Next, calculate your regression coefficients (your b1 and b2).

Before continuing, save your work under a different filename so that at any time, you can revert back to your original data.

Once you've downloaded the data and opened Excel, you can calculate your regression coefficients.

### Setting Excel Up for Data Analysis

To set up Excel for data analysis, go to the tools menu on the top of the screen and find "Data Analysis." If Data Analysis is not there, then you'll have to install it. You cannot do regression analysis in Excel without the Data Analysis ToolPak installed.

Once you've selected Data Analysis from the tools menu, you'll see a menu of choices such as "Covariance" and "F-Test Two-Sample for Variances." On that menu, select "Regression." Once there, you'll see a form, which you need to fill in.

Start by filling in the field that says "Input Y Range." This is your unemployment rate data in cells G24-G242. Choose these cells by typing "$G$24:$G$242" into the little white box next to Input Y Range or by clicking on the icon next to that white box then selecting those cells with your mouse. The second field you'll need to fill in is the "Input X Range." This is the percent change in GDP data in cells E24-E242. You can choose these cells by typing "$E$24:$E$242" into the little white box next to Input X Range or by clicking on the icon next to that white box then selecting those cells with your mouse.

Lastly, you will have to name the page that will contain your regression results. Make sure you have "New Worksheet Ply" selected, and in the white field beside it, type in a name like "Regression." Click OK.

### Using the Regression Results

You should see a tab at the bottom of your screen called Regression (or whatever you named it) and some regression results. If you've gotten the intercept coefficient between 0 and 1, and the x variable coefficient between 0 and -1, you've likely done it correctly. With this data, you have all of the information you need for analysis including R Square, coefficients, and standard errors.

Remember that you were attempting to estimate the intercept coefficient b1 and the X coefficient b2. The intercept coefficient b1 is located in the row named "Intercept" and in the column named "Coefficient." Your slope coefficient b2 is located in the row named "X variable 1" and in the column named "Coefficient." It will likely have a value, such as "BBB" and the associated standard error "DDD." (Your values may differ.) Jot these figures down (or print them out) as you will need them for analysis.

Analyze your regression results for your term paper by doing hypothesis testing on this sample t-test. Though this project focused on Okun's Law, you can use this same kind of methodology to create just about any econometrics project.