NA310G Applied econometrics in Stata

NA310G · Örebro University · Autumn 2026

From a research question to results you can defend

Magnus Lodefalk’s part of Economics Research and Communication: the practical application of econometrics in Stata. Two lectures, three computer labs and an individual empirical report on how AI relates to Swedish firms and jobs, on a twin of the research data behind it: firm accounts from Serrano, job ads and AI-exposure measures.

Every number in your report should come from a do-file that anyone can rerun. That is the standard in economics journals, and it is the standard here.

Schedule for this part

Date Time · Room What
Tue 13 Oct 10:15–12:00 · Zoom Lecture: Regression analysis with time-series data (Wooldridge ch. 10–12). Slides as a self-test: handout (PDF)
Tue 20 Oct 09:15–13:15 · digital exam hall Written exam (Daniela Andrén’s part of the module)
Thu 22 Oct 09:15–15:00 · L149 Lab 1
Mon 26 Oct 09:15–10:00 · T135 Lecture: Instrumental variables and two-stage least squares (Wooldridge ch. 15). This term the lecture comes after the written exam, so it serves the report
Mon 26 Oct 10:15–15:00 · T135 Lab 2
Wed 28 Oct 09:15–15:00 · F103 Lab 3: a short lab lecture, then work on the report with help in the room
23 Oct – 6 Nov see Help desk Help desk, in N4008 and on Zoom
Sun 8 Nov 16:00 Deadline: individual report

Times and rooms come from the official schedule (schema.oru.se), which always takes precedence for times and rooms. (Kronox labels the sessions differently: the 13 Oct slot is the time-series lecture and the Mon 26 Oct afternoon is Lab 2.) Daniela Andrén’s lectures, the self-assessment tests and the exam are in the course guide on Blackboard.

What this part examines

The written exam (A005, 4 credits) is Daniela Andrén’s; see the course guide on Blackboard.

Grades for the report: Fail (U), Pass (G) or Pass with Distinction (VG); exchange students also get an ECTS grade (A–F). You get written feedback after the deadline. A report graded conditionally passed can be revised: one major and one minor revision.

Course documents

Before Lab 1 (Thu 22 Oct): five steps, about two hours

  1. Install Stata (free for students at the School of Business), start it once and make sure it is up to date. The licence and the installation instructions are on Blackboard; the same information was e-mailed to all School of Business students earlier this year. For technical problems, e-mail itsupport@oru.se.
  2. Watch the five videos (about 75 minutes in all): 1. Welcome, and how to pass the report; 2. setting up Stata, the project folder and master.do; 3. your first do-file; 4. append and merge; 5. reading regress output. Videos 4 and 5 (and 6 to 8 later) run on their own small example data, not on the do-files in the project folder, so you only need to watch them. In the labs we do the same steps on the course data.
  3. Read the instructions for the report, so you know in Lab 1 what the labs build towards. The rules for using AI apply from Lab 1.
  4. Download the project folder (one zip) and unzip it into Documents, not OneDrive, Dropbox or iCloud. This is where all your lab and report work lives.
  5. Download the data, unzip, and put the files themselves (not the folders they come in), unchanged, in the folder data/raw/ inside your project folder; never edit them there. For the labs: the course dataset. For the report: your own dataset and research question, with your personal code from Blackboard, on the page Your data.

Bring your laptop with Stata and the project folder to Lab 1. Fall behind or miss part of a lab? The project folder has a folder lab1-catchup with the lab’s code. If you downloaded the project folder before 21 October, download the Lab 1 catch-up, unzip it and put the folder lab1-catchup at the top of your project folder, next to master.do. The data page explains the course data, and how to get Serrano free for your thesis.

Before Lab 2 and Lab 3: four more videos

Questions

Come to the help desk, or e-mail magnus.lodefalk@oru.se with NA310G in the subject line.