Module review for EC3303: ECONOMETRICS I

Taken AY2015/2016 Semester 1


EC3303: ECONOMETRICS I

Description:
The major topics covered in the module includes a review of probability distributions and statistical inference, rudiments of matrix algebra, classical linear regression model with two or more variables, estimation and hypothesis testing, and violation of classical assumptions and some remedial measures. It also includes a simple introduction into using Stata to run simple regression analysis.

The first half of the semester was really boring in this module because it mainly repeats material from EC2303. This is because other modules are accepted as pre-requisites to this module. Therefore, some students may not have learnt the basics that were covered in EC2303. Although I generally don’t recommend skipping lectures, I would say that the first three lectures of the module are unnecessary; unless you think you need a refresher course in EC2303 probability distributions and simple statistics. Also, there is always the wonderful option of webcasts. In general, the lectures were quite tedious because of the nature of statistics, although Prof Kelvin Seah did try to make it more interesting with his examples. However, if you are able to understand the textbook explanation, you are more or less covered for this module.

Assessment:
The tutorials are standard format of problem set presentations in class. Assignments were a little difficult, but manageable. Prof Seah requested group work for assignments, although he did not stop us from individual submissions. For the Stata part of the assignment, you will have to go the computer lab at AS7 to use the program. Alternatively, what I and my friends did was to read the assignment question beforehand, and research and write down the commands to be typed in. We ran the regression during tutorial, saved the results and brought it home to analyze. It saved us some time, but I’m not sure if it would have worked if the regression functions had been more complicated.

Moving on, midterm was ridiculously easy. There was MCQ and short problem sums with some explanations required. I think this was because we were the first batch of students taught by Prof Seah, so he decided to go easy on us. However, this led to a really steep bell curve of mean 45 and 75th percentile 47.5 out of 50. The Final was thankfully at a more challenging standard, but still manageable.

Tutorial participation: 10%
Homework: 20%
Midterm test: 30%
Final exam: 40%


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