AY2015-2016 Semester 1 Module Review

I am very grateful that I got over 30 MCs with results that isn't too far from my expectations. Actually, 30 MCs wasn't as bad as I thought especially after I submitted my thesis. Since I only have 15 MCs to do a review for, I shall try to be even more detailed this time round.

EC4103 Singapore Economy: Practice and Policy

I have much grievances over this module. It is nothing but a burden. Ask me to name anything I learnt from it and I won't even be able to think of a single thing. Probably how to follow instructions and carry out the commands in Stata? Right, so this module was introduced this semester as many employers have given feedback that NUS EC graduates can only regurgitate theory but aren't so well-versed when it comes to knowledge of the Singapore economy. Although this may be true to a certain extent, this module is definitely not gonna help much in that aspect. I honestly think the way the module is taught needs to undergo some serious revisions.

How does this module work? There are 5 lecturers and each of them assesses 20% of the course. Depending on the lecturer, there could be 2 or 3 reports to hand up over that 2 or 3 weeks. If not, presentations had to be made. Occasionally, presentation slides had to be submitted as well. This cycle continued and I think there were about 8 written assignments in total over the entire semester. Every assignment had to be presented and so on top of the additional presentations, there were a total of about 10 presentations. Initially, the module started out slow and steady with the report having a page limit of two sides. Then it became worse with each lecturer, with the last lecturer allowing a page limit of 5 to 7 pages. There were 5 themes in total. Aamir Hashmi took the first one and it was, in summary, on the macroeconomics of Singapore i.e. the characteristics of its economy etc. Danny Quah was next and took the part on growth if I didn't remember wrongly. Then came Ivan Png who taught Singapore productivity. Up next was Jessica Pan who taught income inequality. Last was Chia Ngee Choon who took the aspect of Singapore budget policies. Or was it taxation? I can't really remember but it was something along those lines. 

The bottomline is this: lectures are pretty much useless if you're talking about scoring for this module. Actually, even for the purposes of learning, the lectures still remain useless. The thing is the assignments had absolutely nothing to do with what was taught in lectures. The only thing that you need to know is how to surf the net and look for relevant information. So it wasn't surprising that the turnout for the lectures was just getting more and more pathetic by the week. I did not attend lectures at all but still managed to get away with a decent grade. The assignments by the first two lecturers started off as generic essay-based questions so you could say that it's pretty much a test of general knowledge. Then they became Stata-based with the next two lecturers. And the last lecturer's was simply basic calculations using Excel. Needless to say, the assignments of these three lecturers required students to obtain the correct results as well as to analyze the results. For Ivan Png's, all we had to do was simply to follow the step-by-step instructions in the assignment using Stata and then analyze the regression results. Jessica Pan's part was a lot harder in comparison as hers was not so straightforward so a lot of people had difficulties. But the tutor (Kelvin Seah) was always ready to help and you can actually check with him if the graphs and results you got were correct. And this was important as correctness is a major determinant of your score for Jessica Pan's segment as is the case for Ivan Png's as well as Chia Ngee Choon's parts though the other two lecturers weren't so flexible with the validation of answers.

This module consumed a lot of my time every week but really, I got nothing out of it. It came to a point that the workload was so heavy that I found the completion of assignments and preparation for presentations becoming increasingly burdensome. Among all the 5 themes, I picked up pretty much zero stuff. Before I took this module, I know so much about Singapore. After completing this module, I still know as much about Singapore. That's how helpful the module had been. By the way, this module is fully groupwork. After being assigned a tutorial group, you will be assigned to your groups. You don't get to choose your group members. So if you and your friends are in the same tutorial group but do not have different starting letters for your names, then you don't have to think of being in the same project group. Cos how they assigned the groups was a no-brainer. They simply went by alphabetical order and grouped say, ABCD together in one group, EFCG in another and so on. Anyway, this is pretty crucial. Your grade is highly determined by peer review as much as I thought it didn't play a big role. After submission of each report, your group members are supposed to rate you and not to worry, it's confidential. I gave high ratings for my group members but it ended up that two (out of three) of them got a grade lower than me.

Result: A-

I was surprised by this grade as it exceeded my prediction of a B+ or worse. I am really thankful to my group members for giving me good reviews (as they said). Of course, that comes with a price as I was doing a lot of the work. Then again, I thought we allocated the work quite well as everyone was doing what they're good at. This is not to say that I think A- was deserving of the work we had put in. Seriously, considering how much effort this module requires, I think I should have gotten an A in return. But this module is the sort that you put in 10 times more effort than what you get in return. Hopefully there will be some changes to this module for the next batch as I don't think the majority would like to experience what the Year 4s had just gone through.

EC4301 Microeconomic Analysis III

This is supposed to be a level 4000 module. It is also supposed to be a core module initially. Something wrong must have happened midway which caused it to become so unworthy of a level 4000 module in terms of both workload and content. Anyone who has gone through both EC4101 and EC4102 will definitely tell you that EC4101 is nothing compared to EC4102. And true enough, EC4301 is pretty much peanuts compared to EC4302. This module was taken by Chen Yi Chun this semester. And it's not that he can't teach difficult stuff but that he wants to tone down the difficulty due to past bad experiences. He's a pretty good lecturer and I think his lessons are surprisingly not mundane even though the content may be. The module started off hard as we were taught all the abstract stuff in consumer theory. Actually, abstract may be too strong a word for some. It won't actually be if you have been exposed to MA modules. Then when everyone thought they were done for for this module, the lecturer's announcement that midterms and finals weren't gonna test all these proofs came as a huge relief.

Topics
1.   Preference and Utility
2.   Utility-Maximizing Problem and Its Solution
3.   Utility-Maximizing Problem and Expenditure-Minimizing Problem
4.   Law of Demand, Exchange Economies, Pareto Efficiency
5.   Core and Competitive Equilibrium
6.   Welfare Theorems and Existence of Competitive Equilibrium
7.   Choice under Risk
8.   Externality
9.   Asymmetric Information
10. Modelling Strategic Behaviours I
11. Modelling Strategic Behaviours II
12. Incomplete Information and Efficient Mechanism

Weightage

Homework: 20%

Midterms: 30%

Finals: 50%

The homework was given out on a weekly basis and they were to be completed in groups of four or maximum, five. It wasn't graded based on correctness but rather, completeness. So I should expect that no one lost any marks from this component. There was also only one tutorial presentation per group. So the workload for this module was real light.

Midterms was tested up to Topic 5. Topic 6 was covered but not tested and its lecture was conducted during the recess week. Although this topic wasn't compulsory, it turned out to be useful for midterms. If you had attended the lecture or studied the notes on your own, it would help in scoring for your midterms. So take it with a pinch of salt when the lecturer says it's not tested. I disliked the topics after midterms especially Topics 8 and 9. They were way too simplistic for a level 4000 module and it wasn't value-adding in any way especially Asymmetric Information. Up till now, I still haven't been exposed to proper modelling of asymmetric information. All I understand are the implications of asymmetric information. Topics 10 and 11 are on game theory. Topic 12 was centered around mechanism design but its basis came from game theory. Mechanism design was a real interesting topic but too bad, it had to be so brief in this module. I scored 95 for my midterms. Average was 85? I can't recall exactly. The highest was 98 out of 100. I scored 95 probably cos I was pretty good at the first half of this module. Edgeworth Box was covered for Topics 4 and 5 but of course it wasn't as lame as what was taught in EC3101. Then again, I attribute the 95 I got mainly to the lecturer. I actually made many mistakes but he was amazingly lenient with his marking. As long as you showed some understanding of the concepts, he will give you credit. So keep this in mind if you're taking the module under Chen Yi Chun: do not leave anything blank. Actually, midterms was rather insignificant as it was upon 100 and when you convert the marks to 30%, it becomes negligible. The lecturer said it himself that people who scored well for midterms usually didn't score well eventually whereas those who didn't score well for midterms are the ones who fared well eventually. As much as there may be some truth to that statement, I personally think that midterms are such that you should get at least slightly above average if you are looking to get an A- or above. Nonetheless, I don't dispute the fact that finals is the determining factor and my grade is an affirmation of that as well. By the way, both midterms and finals were open-book though it wouldn't have helped much.

It was claimed that finals is cumulative but trust him not. On the whole, finals was easy. I got screwed up thanks to the steep bell curve and mistakes I shouldn't have made at all. As the second part had three chapters on game theory, it was no surprise that there was one entire question dedicated to game theory in the finals. Even though having taken EC3312 may be a plus, it wasn't as much help as I thought. Basically, game theory in this module was a lot more simplistic than in EC3312. Anyway, as with EC2101 and EC3101, the questions in the finals are such that it carries an overly high weightage. For instance, I could be given 10 marks for just a three-liner solution so it was pretty hard to gauge what was required of me especially when certain questions were quite open-ended.

Result: A-

I don't know what to make of this grade. After midterms, I was aiming for an A. After finals, I was realistically expecting a B+. I guess knowing your concepts well is the key to scoring for this module.

EC4303 Econometrics III

First and foremost, this module isn't as difficult as most may imagine it to be. There was more breadth than depth. Honestly, I question the use of econometrics exams at times. Here's the thing. You don't actually have to know how to prove theorems. All you need to understand are the concepts and properties of the theorems as well as how to go about applying them. But unfortunately, and I don't blame the lecturer for this, econometrics exams usually involve quite senseless questions. Anyway, this module was taken by Tatsushi Oka and he takes the definition of politeness to the next level. The topics covered for this module were quite impromptu in the sense that the later topics were chosen only because some of us were doing on these topics for our term paper.

Topics
1.   Ordinary Least Squares Estimation
2.   Linear Probability Model / Maximum Likelihood Estimation
3.   Nonparametric Regression
4.   Quantile Regression
5.   ARMA model
6.   GARCH model
7.   LASSO
8.   Panel Data Models
9.   Program Evaluation I: DID Estimation
10. Program Evaluation II: IV Regression
11. Program Evaluation III: Regression Discontinuity
12. Classification and Regression Tree

Weightage

Problem Sets: 20%
Term Paper and Presentation: 20%
Book Presentation: 10%
Participation: 10%
Finals: 40%

There were 3 problem sets and all of them were easy. They were graded based on effort and correctness. Most people scored 100 or at worst, 99 so this component wasn't gonna make any distinction among the students.

The term paper was to be done in groups of 3. You get to choose your groups. Basically, you had to find an existing paper, replicate the results and extend the paper. There were 2 presentations for this component. The first one was a 5-minutes presentation and it only involved presenting about the existing paper as in the type of dataset etc., the results your group had replicated and lastly, an outline of the extensions. The second one was a 10-minutes presentation and you had to present on the extensions your group had come up with. The report was only limited to 3 pages excluding appendices and all so it was pretty slack. The draft was due sometime during the middle of the semester whereas the final one including probably the last one and a quarter page on extensions was due sometime in Week 12 or 13.

Book presentation. This is probably the one and only useless component of this module. First, we were assigned a textbook, Statistical Learning from a Regression Perspective by Richard Berk and this textbook is considered pretty advanced for undergraduates. All the equations inside weren't what you normally see in an econometrics textbook. Second, this textbook was taught with students making presentations in their groups so every week, there would be one presentation until all 8 presentations were done. The chapter that you present on was decided by drawing lots. So some got the earlier chapters which were easier while those who got the later ones might need to spend a bit of time understanding the earlier ones before they could do their presentation slides. The presentation was up to 25 minutes and all 3 group members would present a section. I think during this weekly presentation, everyone was just shutting off their ears and that included me. The thing is some presentations were so poor that you could tell they didn't really understand the content themselves which I perfectly understand why. I really question the use of this component as the presentations not only consumed time but also, the book chosen is a bit too advanced for self-studying as its content is very different from what you usually see in econometrics.

Don't worry about the component on participation. You can get it just by attending all the lessons.

I actually only realized finals is 40% as I typed the weightage. But finals is the determining factor to your grade for this module. Oka was very generous with the 60% CA component as he said that everyone would probably get full credit for it. Finals was open book and there were some questions that we could directly refer to assignment solutions or lecture notes to get the marks. Then again, I thought the differentiating factor came in in the last 2 questions which added up to a total of 16 marks. I probably screwed up more than half of that 16 marks but judging from my grade, I believe most people did as well.

Result: A
This grade came as a big surprise as I was expecting at most an A-. Even though this module was more of breadth and it was a lot less rigorous than I thought, I think it's pretty much a must-take if you're looking to go into specialized economics jobs. Anyway, knowing more econometrics models is always a good thing for someone studying economics. This is not to say that you should take it if you're afraid of screwing up your CAP. I think I just managed to scrape through an A as it was really competitive with the cohort size of 20.