00-0: Logistics

Logistics

Fall 2026

Instructors

  • Instructor : Taro Mieno (Office: 209, E-mail: tmieno2@unl.edu)
  • Teaching Assistant :
    • Mona Mosavi (E-mail: mmousavi2@huskers.unl.edu)

Goals of the course

  • Learn modern introductory econometric theory
  • Apply econometric theories to real economic problems
  • Learn how to use statistical software (R) so you can conduct research independently (without technical help from your advisor)
    • manage data
    • visualize data
    • run regressions
    • interpret results

Text Books

Recommended: Wooldridge, Jeffrey M. 2013. Introductory Econometrics: A Modern Approach (5th edition). Mason, OH: South-Western Cengage Learning.

Course Schedule

  • Lectures (MW): 3:00-4:30pm
  • Lab sessions (F): 1:00-2:30pm

All dates, holidays, and deadlines: course calendar

Grading

  • Problem sets (3 assignments): 30%
  • Small-size midterms (2): 30%
  • Paper: 40%

Assignments

Problem sets

  • Most questions are from the required text book
  • Some questions come from what we cover in lab sessions

Use Quarto to write and submit your problem sets

  • You are required to present your R codes
  • You learn how to compile your assignment with your R code written in a document using Quarto , which will be covered in the second lab session

Caution

  • 2nd year students have answers to all the questions I will assign (I will use exactly the same problems because they are really good to learn econometrics)
  • You are free to copy and paste (or rephrase) the answers for your assignment. I won’t bother to try to tell if you have copied and pasted answers.
  • However, you are simply doing dis-service to yourself by depriving yourself of learning opportunities
  • Moreover, your lack of understanding of the material will be clearly manifested on your performance at midterms and final paper

Midterms

In-class open-book midterms

  • Midterm 1: Oct 7 (Wed), 2026
  • Midterm 2: Nov 18 (Wed), 2026

Final Paper

In this assignment,

  • you write a paper with a particular emphasis on econometric analysis using a real world data set
  • you are encouraged to use the data set you are using for your masters thesis (talk with your advisor)
  • you need to ensure that you use a panel dataset
  • No presentation of your final paper

Time line

  • Oct 16 (Fri) : identify a research topic and the data set you will be using, and get approval from the instructor
  • Oct 23 (Fri) : paper proposal
  • Dec 18 (Fri) : final paper

Paper Proposal

Introduction

  • clear identification of what you are trying to find out (research question)
  • why the research question is worthwhile answering

Simple Model

  • dependent variable (the variable to be explained)
  • explanatory variables (the variables used to explain it)

Data Source

  • where you get data

Final Paper

Introduction

  • clear identification of what you are trying to find out (research question) [1 point]
  • why the research question is worthwhile answering [1 point]

Data description

  • the nature of the data with summary statistics table [1 point]
  • visualize a few key variables in a meaningful way [3 points]

Econometric Methods

The process of how you end up with the final econometric models and methods. [40 points ( or more )]

  • justification of your choice of independent variables
  • potential endogeneity problems
  • what did you do to address the endogeneity problems?
  • justification of econometric model(s) and method(s)
  • identify appropriate standard error estimation methods

Results, Discussions, and Conclusions

  • interpret and describe the results [2 points]
  • implications of the results [1 point]
  • conclusions [1 point]