DISCLAIMER: This entire semester was 100% online learning for FASS so the modules that I took this semester may vary from how it would be like in a regular pre-covid semester
1. EC3101: MICROECONOMIC ANALYSIS II
Lecturer/Tutor: Dr. Timothy Wong Chong Ji
Lectures: pre-recorded videos (one lecture is usually just 30 – 40 mins long)
Tutorials: weekly, by Dr. Timothy himself
– Group homework x 2 (10%)
– Midterms (23%)
– Post lecture quizzes (12%)
– Tutorial attendance and presentation (10%)
– finals (45%)
This module requires EC2101 and EC2104 as pre-requisites so you can just imagine how much knowledge is required for this mod, especially calculus. EC3101 is a ‘continuation’ of EC2101, in the sense that it picks up from where EC2101 left off. The concepts covered in EC3101 are pretty divided in the sense that there are not much direct links between topics. The main topics are monopoly, oligopoly, game theory, externalities, public good, asymmetric information.
The first half of the semester is pretty easy in my opinion. It finishes off the producer side of the market so it’s really just a firm’s cost structure, profit function etc (MR = MC, blabla). Perhaps a quick revision of EC2101 second half would help but it’s not necessary since the lecturer covers these concepts well too. Midterms test on monopoly and oligopoly. The second half of the semester is the challenge because it is all new stuff. I mean these concepts were introduced to us in EC1101E but in EC3101, we had to calculate the externalities, figure out the winning solution to game theory etc. It’s definitely a challenge, especially for game theory and asymmetric information since the questions are more on logic than mathematics/econs but I think it’s rather do-able.
Tim Wong’s homework are notorious and it takes forever to solve but it’s still do-able. Though each homework has just two questions, the solutions to each question are very tedious. One of my solution was so long i had to use five different coloured pens to show the workings for the different first order conditions lmao. But, it is not as bad as EC2101 one in my opinion. Tim Wong was also my tutor (yes, even after EC3381 in June so that’s almost from June till Nov lol) and he is great at teaching. Quite patient and friendly and the best part was his classes never dragged more than 45 mins. Tutorial presentations are by random and you would know what question you need to present a week before. Think everyone in my class presented twice in the semester.
Midterms and finals were done on Examplify. Around 6 – 8 MCQs and around 2 structured questions for midterms, and 6 structured for finals. Since it is on Examplify, we just need to type in key workings e.g. MR = MC. It’s a rather bad initiative tbh because sometimes the word count just does not allow us to write our full train of thoughts behind an answer. Was hoping it would be pen-and-paper but nah.
Overall, i still find EC3101 quite enjoyable and definitely more relevant/links to the real world e.g. game theory, asymmetric information. Tim Wong explains his concepts pretty well and lmao idk how he does it within 40 mins + but i’m not complaining, and his lecture videos often contain movie clips e.g. A Beautiful Mind (on game theory) and sitcom Friends, so it’s quite enjoyable. Bellcurve for midterm was quite bad, think average was just a pass or somewhere there then again I heard the performance for 3101 is generally bad in general because questions are tricky.
2. EC2102: MACROECONOMIC ANALYSIS I
Lecturer/Tutor: Dr. Seet Min Kok
Lectures: pre-recorded videos
Tutorials: weekly one-hour, by year 4 undergraduate
– Midterms (35%)
– Tutorial attendance and presentation (20%)
– finals (45%)
As the name suggests, this module is just about macroeconomics so it is about the representative firm, representative consumer and their interactions in the economy, and of course how government policies like monetary policy and fiscal policy affect their consumption and investment decisions. The main topics are: intertemporal model (it’s the same as EC3101 first topic), goods market, asset market, IS-LM-FE model, AD-AS model, the different school of thoughts – Keynesian and Classical – and unemployment and inflation using the Phillips curve. These topics are all interlinked and they build up on each other so if you are unclear of say, goods market then it would be very hard to catch up.
In terms of workload, it is extremely light – just weekly lecture videos and tutorials. But this also meant that midterms and finals will have a higher weightage. Class participation was ok as my TA was rather casual with us so yeah. But one thing that I really disliked about this module was how ambiguous the tutorials and even midterms/finals questions were. It was so ambiguous and open to different interpretations that when we were having our midterm review, everyone was all confused and lashing out at how they could not understand what the question really wanted. Textbooks are very important for this module because the prof takes almost everything from there, including his tutorial questions LOLOL.
Overall, content was pretty manageable and very intuitive. It is similar to the macro content to EC1101E and i actually read some of it while revising for EC2102. This module is pretty content-wise and not very math-heavy but then there was this consumer optimisation problem we had to solve where no numbers were given; only greek letters alpha beta etc so yeah, the workings were super long. Not sure how to feel about that but lol ok.
3. EC2303: FOUNDATIONS OF ECONOMETRICS
Lecturer: Dr. Yogita Shamdasani
Tutorial: weekly one-hour, by year 4 undergraduate
– Tutorial attendance and presentation (15%)
– Midterms (40%)
– Finals (45%)
This module covers topics like probability distributions (Bernoulli, student’s t, normal, uniform) and sampling methods (estimators, confidence interval and hypothesis testing). It is very math-heavy and everything just builds up on one another, and there are quite a lot of proving questions to do too. I would say this is not a typical economics module since it is just integration over and over again but yeah, it is important in upper-level modules since economics uses a lot of data.
While no pre-requisites are required, it is crucial to revise integration (Double integration if possible) and there is literally no way you can escape this. Differentiation is not tested, at least for my papers. It would definitely help if you had any prior statistics knowledge before taking this module, maybe GER1000? I personally took DAO1704X (Read review) and the first half of the semester was a breeze for me. That being said, I struggled for the estimators part because it is just so abstract, like what am i even proving? Ok i know we are supposed to prove the law of large numbers but it is so abstract! But i soon realised most people do not know what really is going on too so lOL am glad.
This prof is new to NUS and I would say she’s really good at teaching! Her lectures are in bite-sized videos so it’s easy for us to watch if we don’t have enough time at one seating. Furthermore, there were many check-in questions and I felt it was quite beneficial for us to review what we have learnt before moving on to the next topic. Tutorials were quite manageable but my TA was teaching this module the first time so there were times where explanations were not very clear.
Definitely doable with EC2102, EC3101 since it is just math and not content-based.
4. GET1050: COMPUTATIONAL REASONING
Lecturer: Jonathan Sim
Tutorial: odd/even two-hours (five sessions in total), by year 4 undergraduate
– Tutorial participation (20%)
– Group project (35%)
– Individual assignments etc (20%)
– Pre-tutorials (15%)
– Final reflection paper (10%)
This module is quite heavy so I would not recommend you to overload if this module is pre-allocated to you. It is only for FASS students btw. Anyways, this module is about making critical decisions using MS Excel (why does this sound like DAO1704X again…). It attempts to teach you computation thinking e.g. decomposing etc and I quite enjoyed this module because it really taught us how sometimes algorithm can be discriminatory, and how we should be mindful when using them or analysing data. We learnt mainly VLookup, PivotTable, VBA and some pseudo code.
BUT with that being said, it is really very tedious. Every two weeks there will be two lecture videos to watch and two post-lecture quizzes. These quizzes are part of your individual assignments and each quiz has around 12 questions of which most of them are those multiple-responses ones (Which means if you selected one wrong answer your whole question is wrong). Absolutely disliked doing these quizzes though I get the importance of practicing the hard skills we learn in class. On top of that, there is a pre-tutorial assignment which is similar to a mini-project. Basically there will be a real-world problem (sort of) and a set of data. Depending on what was taught that week, you would be required to analyse the data and explain why you did things certain way. Though there were only four of them, the weightage is pretty heavy at 20%. Project was very simple and we could not choose our group mates but my group was rather bad (think they all wanted to S/U already) so the whole project was just a nightmare for me. But if your groupmates are good, this project is a breeze. The final reflection paper is just, well reflection of what you have learnt in the module but with some analysing problems to be done etc.
Overall, a rather fun module and Jonathan was extremely hyped in his lecture videos. Sometimes a little too hyped LOL.
5. GEQ1000: ASKING QUESTIONS
Lecturer: various (from six different faculties)
Tutor: Pamela Yeh Qi Ming
– Tutorial attendance and participation (36%)
– Quizzes (14%)
– Final reflection paper (14%)
– Forum (36%)
It’s gonna be a very short review for this module because I am pretty sure there are many reviews out there already. I actually enjoyed this module as some of the concepts were rather interesting. Like hey, pseudo science and deep philosophy stuff. The workload is super light and definitely manageable if you overload.
I would strongly recommend you to watch the videos and comment on the forum asap before anyone else writes pointers that you want to write (forum 1 and 2 are 36%).
That’s all for Year two semester one!