闪电代写 -代写CS作业_CS代写_Finance代写_Economic代写_Statistics代写_代码代做_IT代写_加急帮助

Introduction to Econometrics (ECON-UA 266)

Summer 2021 – Session 1

Syllabus

1. Organization

Instructor: Francesco Furno [email protected]

Lectures: Mo/Tu/We/Th Zoom - 10:00-11:35am

Office Hour: Zoom – TBD

Teaching Assistant: Matheus Silva [email protected]

Recitation Group 1: Th Zoom - 11:45am-1:15pm

Recitation Group 2: Fr Zoom - 11:45am-1:20pm

Office Hour: Th/Fr Zoom - 1:30-2:30pm

Piazza Website: piazza.com/nyu/summer2021/econua266/home

Zoom Format: Lectures, recitations and office hours will be held on NYU Zoom

2. General Description

This course introduces econometric methods used to estimate economic models and test economic theories. Economic theory is used to formulate the model and properly recognize which variables are endogenous (i.e. determined as the outcome of an equilibrium) and which are not. Data are combined and manipulated from various sources. Statistical theory is used to perform statistical tests in a scientific manner. Parameter estimates and statistical tests are interpreted within the context of the underlying economic theory.

We will start with a basic review of probability and statistics. Our first topic will be the linear regression model, covering estimation, hypothesis testing, heterogeneous/dependent data, measurement error, and specification testing. Later in the course we will introduce instrumental variables estimation which is used, among other things, for causal inference. We will then move on to panel data and, finally, if time permits, we will discuss extensions to time-series models and forecasting.

2.1 Course Outline

The following outline is tentative and may be revised as the course proceeds. SW denotes recommended readings from the textbook by Stock and Watson (updated Edition 4).

• Week 1: Probability/Statistics Review (SW 1,2,3) + Simple Regression (SW 4,5,18)

• Week 2: Simple Regression (SW 4,5,18) + Multiple Regression (SW 6,7,19)

• Week 3: More on Multiple Regressions (SW 8, 9, 11) + Experiments (SW 13) + Midterm

• Week 4: Instrumental Variables (SW 12)

• Week 5: Panel Data (SW 10) + Intro to Time-Series (SW 14)

• Week 6: Review + Final

2.2 Course Prerequisites

ECON-UA 18 or ECON-UA 20 and MATH-UA 212 or MATH-UA 122 or MATH-UA-123.

This class requires a solid command of basic probability and statistics. In particular: marginal distributions, joint distributions, conditional distributions, expectations, conditional expectations, variances and covariances, conditional variances and covariances, stochastic independence, central limit theorem, convergence in probability, estimators and sampling distributions, unbiasedness, consistency, test of hypothesis. Please make sure you are familiar with most of these topics before the course starts because we will have only time for a quick review.

2.3 E-Mail Policy and Piazza

Questions regarding the material covered in class should be asked every day after class, or during office hours. For anything else feel free to e-mail me.

For questions regarding doubts, empirical applications and the problem sets you can always reach out to your TA Matheus Silva ([email protected]). Matheus also holds regular office hours, and you are encouraged to ask questions in that occasion rather than via e-mail if you can.

For questions regarding R, a Piazza forum has been created where you can communicate with each other. The advantage of R over e-mails is that answers are shared with everyone so that you can learn from each other. Please enroll in the Piazza forum at this link: piazza.com/nyu/summer2021/econua266/home. To encourage active participation, the four students who contributes the most to the Piazza forum will be rewarded with an extra +5% score.

3. Course Schedule and Grading Policy

Grading: participation (10%), problem sets (20%), midterm exam (20%), final exam (50%). There will also be an extra 5% bonus for those who contribute the most to Piazza.

This is the calendar with problem sets and exam dates:

Week 1	PS 1
Week 2	PS 2
Week 3	Midterm Exam
Week 4	PS 3
Week 5	PS 4
Week 6	Take-Home Final Exam

During week 3 you will be assigned some practice problems that will help you prepare for the midterm. They will not be graded.

3.1 Problem Sets

There will be 4 problem set. Problem sets will be a combination of theoretical exercises and computational/simulation exercises which you will do in the programming language R. Problem sets are an essential element in learning the course content and preparing for the exams. Further, I strongly encourage to use the problem sets as a device for learning R (if you don't already). R is increasingly used in economics, finance and data science in both the academic and private sectors. It is free and open source and very adaptable. Putting in a small amount of effort to learn R should serve you well.

Problem sets will be assigned one week ahead and must be submitted through NYU Classes. Late submissions will not be accepted, and you will get a 0 score. Problem sets will be given a score equal to either 1, 2 or 3:

• Score of 1: Insufficient

• Score of 2: Sufficient/Ok

• Score of 3: Good/Excellent

A score of 2 or 3 means you are doing fine. A score of 1 means you are expected to put more effort if you want to pass the class. Your lowest score on the problem sets will not be counted. Therefore, students who are not able to complete a problem set for a legitimate reason will not be adversely affected. You can work in groups (no more than 4 people) and hand in just one solution.

3.2 Exams

There will be a midterm and a final exam. The exam content will be cumulative, but with an emphasis on the most recent material. All material discussed in the course is examinable unless stated otherwise.

• The midterm exam will take place towards the end of Week 3.

• The final exam will be from Thursday, July 1 08:00am to Friday July 2 08:00am.

No make-up exams will be given. The usual university polices on academic honesty apply and will be applied strictly. Do not cheat or you will be failed.

Exam View: You will be given the chance to ask clarifications about your exam score in Matheus’ first office hours after the scores are released.

3.3 Participation

Students who actively participate to the course will be rewarded for their participation. Participation can take many forms (as simple as being active on Piazza). Logging into the lectures/recitations and walk away from the computer will not count towards active participation. If you log into a class, I expect you to be active. Otherwise, just do not log in.

3.3 Missed exams

Attendance of the final exam is mandatory. If you miss a midterm due to a medical emergency (for which you must provide a doctor's note within one week of the exam) I will appropriately re-weight your scores from the remaining exams.

3.4 Regrading

You may ask for a regrade within one week after the exam was distributed if you think your exam was graded incorrectly. If you ask for a regrade, you must email me explaining what specifically you view as having been graded incorrectly. I will then regrade your entire exam. This means that your score could go up or down upon regrading.

4. Materials

The recommended textbook is:1