A Guide to a Painless Undergrad Econometrics Project

A Guide to a Painless Undergrad Econometrics Project 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  Okuns law  to create an econometrics project. Okuns law refers to how the nations output- its  gross domestic product- is related to employment and unemployment. For this econometrics project guide, youll test whether Okuns law holds true in America. Note that this is just an example project- youll 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 youre testing by doing a   t-test. To do so, use the  following function:   Yt 1 - 0.4 Xt Where:Yt  is the change in the unemployment rate in percentage pointsXt  is the change in the percentage growth rate in real output, as measured by real GDP So you will be estimating the model:  Yt b1 b2 Xt Where:Yt is the change in the unemployment rate in percentage pointsXt is the change in the percentage growth rate in real output, as measured by real GDPb1 and b2 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 youve done everything correctly, you should see something that looks like this  fact sheet  from the BEA, containing quarterly GDP results. Once youve downloaded the data, open it in a spreadsheet program, such as Excel. Finding the Y and X Variables Now that youve 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 Youve 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. Youre 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 Xts 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 youve 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 youll have to  install it. You cannot do regression analysis in Excel without the Data Analysis ToolPak installed. Once youve selected  Data Analysis  from the  tools  menu, youll see a menu of choices such as Covariance and F-Test Two-Sample for Variances. On that menu, select Regression. Once there, youll 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 youll 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 youve gotten the intercept coefficient between 0 and 1, and the x variable coefficient between 0 and -1, youve 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 Okuns Law, you can use this same kind of methodology to create just about any econometrics project.