AY2014/2015, Semester 2
EC3304 Econometrics II
One of the last few cores for the major. This module taught me much more that what is being tested. The data-processing skills and methods are necessarily the most important tool that any economics student would gain from the course. For me, the optional project was the most interesting part of the module. The process of researching possible variables, trial and error in fitting different possible models and drawing past skills in MATLAB and R to run algorithms for the psuedo out-of-sample method is very different from what the usual economic modules that I would take. Dr. Fesselmeyer has also been very kind to all the emails I spammed regarding the project issues and more advanced theoretical derivations. I personally think that this module is not very intuitive and working with data really helps the understanding of the materials a lot more than just studying for the exams. There are also many materials from other universities/on the net that are related to the module, so Google also helps a lot in studying for this module. The final results is a pleasant surprise because I spent relatively less time on this module.
Grading Criteria: 20% Tutorial Participation, 30% Midterm Test, 50% Final Exam.
Grade: A+ (My first, yay)
EC3353 Health Economics I
An interesting module that looks at the dynamics in the market for health care and health insurance. Typical economics elective, main types of analyses are utility under uncertainty and comparative statics of demand and supply interactions. Prior knowledge from EC3101 would make things a lot simpler. Competition is quite stiff for the module. Mixture of MCQs, math and short essays for the final exams. Overall, the module does not require much mathematical analysis, mainly computations and intuitions.
Grading Criteria: 10% Tutorial Participation, 20% Assignments, 20% Midterm Test, 50% Final Exam.
Grade: A
EC4101 Microeconomic Analysis III
Advanced microeconomics with focus on information economics, game theory and matching markets. The first half on information economics is quite challenging. The first few chapters require understanding of both economic intuition and mathematical properties to derive the nonlinear programming problem. The solving part is mainly the usual first order condition so its straightforward. Past knowledge in EC3322 helped me breeze through adverse selection and moral hazard problems. The chapter on auction, however, is very challenging because strong statistical background is required to understand the concept and properties of conditional expectation. In the midterm test, though, derivations are not required. The second half is quite straightforward. Basically repeating everything in EC3312 with a new chapter on matching market and allocation algorithms. I thought final exam was easy but a mixture of overconfidence, lack of practice and allocating more time to PH2110/GEM2006 leads to one small mistake (misrepresented the payoffs of a simple game) in the finals end up losing a huge chunk of marks in finals. Sucks to underperform in my most confident module :( Anyway, this module is 100% math with mostly computations and some equilibrium analysis. No longer a pre-requisite for honours and honours thesis, so people who don't like math can just avoid.
Grading Criteria: 50% Midterm Test, 50% Final Exam.
Grade: A-
MA2213 Numerical Analysis I
Second time taking a highly computational module under Prof Tan, and it is moderately enjoyable. The content is interesting but the computations are just WAY TOO TEDIOUS. The general expression of the linear interpolation can easily take up to two lines, and that is just one part of a 4/5-line equation. I think this module is super useful for all sorts of quantitative applications with focus on algorithms and numerical interpolation/integration. It has quite a lot of application in quantitative finance that can be explored beyond the course, so it is quite enjoyable in this aspect. It also resharpens my MATLAB skills which I have placed aside for quite long, and this has helped my EC3304 project in some ways. However, this module remains challenging for me because I'm more for analytical solutions than numerical solutions. As usual, there is just NOT ENOUGH TIME for finals because I'm slow with punching calculators and I'm very very prone to numerical errors. Sigh. Thankfully, the results are within my expectations so not too bad.
Grading Criteria: 2% Tutorial Participation, 18% Midterm Test, 20% Assignments, 60% Final Exam.
Grade: B+
MA3110 Mathematical Analysis II
My most enjoyable, and also the most challenging, module of the semester. It deals primarily with univariate real analysis and I like to call it the "freestyle" module because you are given a bunch of results and you start thinking when you see the question. A real test of thinking on the spot, and memorizing the notes is of negligible help. It is a direct extension from MA2108 which is also taught by Prof Lee, even the notes are continuous. Forgive the math pun. This module builds on the analysis of limits from MA2108, with the continuity property being one of the main concepts that we have to know by heart from MA2108. The first half focus on the differentiability and integrability of real, univariate function while the second half focus on pointwise and uniform convergence, and how properties (continuity, differentiability and integrability) is preserved. There is also a last topic on power series, which is actually quite straightforward. Did quite badly for the midterm test but I think final exam made up for it. After this module, I'm looking forward to MA3209, the third part on real analysis!
Grading Criteria: 20% Assignment, 20% Midterm Test, 60% Final Exam.
Grade: B+
PH2110/GEK2006 Logic
Crazy module. I have a love-hate relationship in this module. Took this module with a bunch of intellectual friends, and spending hours arguing over walk and talk is mixture of fun and frustration, illustrating the hedonistic concept of pain and pleasure to its very best. The module is about the laws of truth, and how should we translate statements into algebraic expressions for a framework of analysis. The focus is on the validity and soundness of statements, translation of statements and analysis using either a logic table or a logic tree. People without mathematics, computer science or philosophy will be in for an unpleasant surprise, and no, its nothing like Cheryl's birthday problem. Everything seems to go well until some ambiguity arise in the final quiz and we totally flunk everything. Prof Blumson acknowledges the ambiguity but sadly the marks are computerized and there's not much to be done. Final exam was a disaster. LOL. I got a pathetic 4/10 but I have to say it is the most unique final exam experience ever. 10 MCQs for two hours and I only manage to properly solve 4/10 questions, and hell, out of the 6 questions that I randomly picked, I got none of them correct. Damn suay, that's like a 17.8% probability...Yes, I'm so lost in the exam that I calculated this probability lol. This module is only for people that are willing to spend hours thinking about (ridiculous) logical problems, otherwise it would be an excruciating journey.
Grading Criteria: 50% Online Quiz, 50% Final Exam.
Grade: B- (took this module hoping to get above B+ sigh)
Ending Note
SAP 4.26, a 0.36 drop from last sem. That being said, it is still a decent semester. CAP crawled from 3.87 to 3.94, another step closer. Felt a little distracted towards the end of the sem, not sure why. Maybe its the fatigue from chionging academics in the past 4 semesters, maybe my winter holiday was to beautiful that it broke the momentum, or maybe because there is one less reason for me to push myself so hard anymore. Whatever it is, the exam period this semester was wayyy to chill for my own good, but on the brighter side, I'm recharged enough to juggle research work with my 7 modules next sem!
One of the last few cores for the major. This module taught me much more that what is being tested. The data-processing skills and methods are necessarily the most important tool that any economics student would gain from the course. For me, the optional project was the most interesting part of the module. The process of researching possible variables, trial and error in fitting different possible models and drawing past skills in MATLAB and R to run algorithms for the psuedo out-of-sample method is very different from what the usual economic modules that I would take. Dr. Fesselmeyer has also been very kind to all the emails I spammed regarding the project issues and more advanced theoretical derivations. I personally think that this module is not very intuitive and working with data really helps the understanding of the materials a lot more than just studying for the exams. There are also many materials from other universities/on the net that are related to the module, so Google also helps a lot in studying for this module. The final results is a pleasant surprise because I spent relatively less time on this module.
Grading Criteria: 20% Tutorial Participation, 30% Midterm Test, 50% Final Exam.
Grade: A+ (My first, yay)
EC3353 Health Economics I
An interesting module that looks at the dynamics in the market for health care and health insurance. Typical economics elective, main types of analyses are utility under uncertainty and comparative statics of demand and supply interactions. Prior knowledge from EC3101 would make things a lot simpler. Competition is quite stiff for the module. Mixture of MCQs, math and short essays for the final exams. Overall, the module does not require much mathematical analysis, mainly computations and intuitions.
Grading Criteria: 10% Tutorial Participation, 20% Assignments, 20% Midterm Test, 50% Final Exam.
Grade: A
EC4101 Microeconomic Analysis III
Advanced microeconomics with focus on information economics, game theory and matching markets. The first half on information economics is quite challenging. The first few chapters require understanding of both economic intuition and mathematical properties to derive the nonlinear programming problem. The solving part is mainly the usual first order condition so its straightforward. Past knowledge in EC3322 helped me breeze through adverse selection and moral hazard problems. The chapter on auction, however, is very challenging because strong statistical background is required to understand the concept and properties of conditional expectation. In the midterm test, though, derivations are not required. The second half is quite straightforward. Basically repeating everything in EC3312 with a new chapter on matching market and allocation algorithms. I thought final exam was easy but a mixture of overconfidence, lack of practice and allocating more time to PH2110/GEM2006 leads to one small mistake (misrepresented the payoffs of a simple game) in the finals end up losing a huge chunk of marks in finals. Sucks to underperform in my most confident module :( Anyway, this module is 100% math with mostly computations and some equilibrium analysis. No longer a pre-requisite for honours and honours thesis, so people who don't like math can just avoid.
Grading Criteria: 50% Midterm Test, 50% Final Exam.
Grade: A-
MA2213 Numerical Analysis I
Second time taking a highly computational module under Prof Tan, and it is moderately enjoyable. The content is interesting but the computations are just WAY TOO TEDIOUS. The general expression of the linear interpolation can easily take up to two lines, and that is just one part of a 4/5-line equation. I think this module is super useful for all sorts of quantitative applications with focus on algorithms and numerical interpolation/integration. It has quite a lot of application in quantitative finance that can be explored beyond the course, so it is quite enjoyable in this aspect. It also resharpens my MATLAB skills which I have placed aside for quite long, and this has helped my EC3304 project in some ways. However, this module remains challenging for me because I'm more for analytical solutions than numerical solutions. As usual, there is just NOT ENOUGH TIME for finals because I'm slow with punching calculators and I'm very very prone to numerical errors. Sigh. Thankfully, the results are within my expectations so not too bad.
Grading Criteria: 2% Tutorial Participation, 18% Midterm Test, 20% Assignments, 60% Final Exam.
Grade: B+
MA3110 Mathematical Analysis II
My most enjoyable, and also the most challenging, module of the semester. It deals primarily with univariate real analysis and I like to call it the "freestyle" module because you are given a bunch of results and you start thinking when you see the question. A real test of thinking on the spot, and memorizing the notes is of negligible help. It is a direct extension from MA2108 which is also taught by Prof Lee, even the notes are continuous. Forgive the math pun. This module builds on the analysis of limits from MA2108, with the continuity property being one of the main concepts that we have to know by heart from MA2108. The first half focus on the differentiability and integrability of real, univariate function while the second half focus on pointwise and uniform convergence, and how properties (continuity, differentiability and integrability) is preserved. There is also a last topic on power series, which is actually quite straightforward. Did quite badly for the midterm test but I think final exam made up for it. After this module, I'm looking forward to MA3209, the third part on real analysis!
Grading Criteria: 20% Assignment, 20% Midterm Test, 60% Final Exam.
Grade: B+
PH2110/GEK2006 Logic
Crazy module. I have a love-hate relationship in this module. Took this module with a bunch of intellectual friends, and spending hours arguing over walk and talk is mixture of fun and frustration, illustrating the hedonistic concept of pain and pleasure to its very best. The module is about the laws of truth, and how should we translate statements into algebraic expressions for a framework of analysis. The focus is on the validity and soundness of statements, translation of statements and analysis using either a logic table or a logic tree. People without mathematics, computer science or philosophy will be in for an unpleasant surprise, and no, its nothing like Cheryl's birthday problem. Everything seems to go well until some ambiguity arise in the final quiz and we totally flunk everything. Prof Blumson acknowledges the ambiguity but sadly the marks are computerized and there's not much to be done. Final exam was a disaster. LOL. I got a pathetic 4/10 but I have to say it is the most unique final exam experience ever. 10 MCQs for two hours and I only manage to properly solve 4/10 questions, and hell, out of the 6 questions that I randomly picked, I got none of them correct. Damn suay, that's like a 17.8% probability...Yes, I'm so lost in the exam that I calculated this probability lol. This module is only for people that are willing to spend hours thinking about (ridiculous) logical problems, otherwise it would be an excruciating journey.
Grading Criteria: 50% Online Quiz, 50% Final Exam.
Grade: B- (took this module hoping to get above B+ sigh)
Ending Note
SAP 4.26, a 0.36 drop from last sem. That being said, it is still a decent semester. CAP crawled from 3.87 to 3.94, another step closer. Felt a little distracted towards the end of the sem, not sure why. Maybe its the fatigue from chionging academics in the past 4 semesters, maybe my winter holiday was to beautiful that it broke the momentum, or maybe because there is one less reason for me to push myself so hard anymore. Whatever it is, the exam period this semester was wayyy to chill for my own good, but on the brighter side, I'm recharged enough to juggle research work with my 7 modules next sem!