Chances of getting onto the LSE MSc Economics program?

I'm currently a second year economics student at Warwick University and I have just closed the year out with an average of 79%, with my core modules of macroeconomics, microeconomics and econometrics each scoring 88%, 74%, and 74% respectively. Unfortunately my internship applications have not been successful this year and I was too late to apply for any undergraduate research scheme.

For what it's worth, I am currently trying to learn how to perform data analysis with what I've learned in econometrics using python and eventually start learning R with the aim of using python to perform the data analyses needed to write my dissertation both as a proof of competence and a challenge to myself.

Does LSE value any python skills on an economics student as an additional method to apply econometrics knowledge? How difficult would it be for me to get a spot on the program?

Personally I wouldn't overthink it too much. Postgraduate economics programs place little emphasis on work/internship experience as it's completely different to what they're interested in (i.e. theoretical and some applied Econ skills). Only exception is some third year RA experience, working over the summer in a research centre or financial/international institution with a heavy economic research focus (e.g. Central Banks and IMF/BIS). Unlike what most think, they really don't care if you've worked for a bank, asset manager, fund, brokerage, etc etc - it's irrelevant to academic economics which is what they care about.

With respect to the software/languages for econometrics, typically universities aren't super picky. They value good grades from strong economics undergraduate degrees and research experience as the most sought after things. They recognise that students' programming knowledge is simply a function of their course modules and what the lecturers on those courses decided to teach, rather than using it as a barometer to compare the quality of applicants.

I did my MSc and PhD at LSE and in the MSc there wasn't a huge applied econometrics component to be honest. Obviously this was a few years ago so some of the modules may have changed slightly, but typically there's a much greater emphasis on calculus, linear algebra and mathematical statistics than there is on applied econometrics (i.e. where python/R skills is useful). So it's likely to be more useful for your end of course research project (LSE normally uses a 6k word research project rather than a full dissertation), than in the modules. And while programming skills are good and might help on the margins with your application, they're certainly no game changer or substitute for good grades, research experience, good reference letters and mathematics/stats ability.

Given that I only have about a month or two till LSE opens it's application process for the 2024/25 entry for the MSc Economics program, I don't see a lot of chances for me to boost my application with a research assistant role aside from maybe starting to work on a small project while reading up on papers that might interest me? I think my favourite specialization is probably in developmental or financial economics so my reading will probably be on those two sub-fields if that's any useful information?

Since learning Python independently wouldn't really help my application, should I instead aim to take the 2 optional econometrics modules my course offers in the third year as there is no more compulsory econometrics module? The 2 optional econometrics modules include a module focused on a deeper dive into cross-sectional methods (causal inference and regression, DiD and synthetic control etc.) as well as time series (models like GARCH, VECM, VAR, and even deeper dive into cointegration). This might sound a bit short sighted but I am on the fence about these modules because I know they will absolutely pull down my average and I really wanted to graduate with an 80 and not just a high first, if knowing these will definitely help with the applications however I will be happy to take them.

How much econometrics am I expected to know to apply to LSE? I have attached a list of what I've learned so far so if you're interested you could take a look.

Are my chances of getting into LSE low? If you have any other suggestions of what I could do now to boost my application, please let me know.

Thank you very much for taking the time to help me!

Helloo I am also an economics undergrad considering applying to LSE - I will be starting my final year soon!

I have had a look over your syllabus and it looks pretty much like the standard econometrics I've seen in most courses (including my own) so I honestly do not think you will have a problem in terms of how much you must know prior to entering the MSc course at LSE. I don't know if there are many econ undergrad courses which focus heavily on any programming, but mine does include some Stata and (on an optional basis) R so I don't think it would hurt to become familiar with something like that. That being said, I know people from universities who did 0 programming and they are now completing their 1 year masters at LSE so I don't think it is vital

Worth a shot. LSE place a heavy emphasis on programming languages like Stata/ Python, so it does look good on your app.

Cool, I'm also doing R now so ideally by the time I apply and graduate I'll have learned the trinity (Stata, Python, R) so here's hoping I could get in.
I would also like a second opinion on the issue of quantitative modules however, how much micro-econometrics and time-series knowledge would I require to apply to LSE? I am curious about where LSE stops with teaching econometrics to their BSc students as compulsory knowledge of the course in comparison to my course's content that I've listed above. Would I need to know stuff like synthetic controls and GARCH models or am I fine without them? There is kind of a trade-off to me takin the more quantitative modules as my grades would likely go from possible 80% to mid 70's so I'm pretty concerned and have been very deliberate with my module choices. Thank you!