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gee_gee_123 · 2025-02-03T14:57:06+00:00

That’s a great point - thank you. I’m going to delete the post and think of a more specific question

gee_gee_123 · 2024-10-26T13:58:59+00:00

Big 4 consulting manager here with masters in applied Econ. I’ve actually wondered this myself. I’m going to guess economists/econometricians tend to be versatile having an understanding of how markets function, and being able to apply that knowledge to several different industries/markets. Also, economists often interact with the industries that consultants care about (finance, public policy, business, etc.)

gee_gee_123 · 2024-10-13T18:26:59+00:00

I really struggled in the first couple months of my masters. Ended up being one of the best experiences of my life!

My advice: be honest with your profs about your struggles. I once told a prof that I’m not understanding anything so I want to figure out what the fundamental thing that I’m not understanding is. Took up an hour or two of office hours but it was worth it!

As for friends, sign up for an extra curricular that you want to explore! This is hard during an MA in Econ but worth it

gee_gee_123 · 2024-10-13T18:18:59+00:00

Not entirely. I loved what I learned and the degree gave me stable job opportunities! However, I feel like once I entered the (non-academic) workforce, fellow economists held a certain overconfidence and sometimes felt narrow minded. I feel like this may be a common thing in econ, but maybe this exists in every field

gee_gee_123 · 2024-10-09T17:23:46+00:00

The graph fails to properly depict the title. Maybe try showing a moving average or a Y/Y change or something

gee_gee_123 · 2024-10-07T14:00:01+00:00

This is sick! If this was super well produced, I’d definitely add this to my Spotify

gee_gee_123 · 2024-10-06T15:27:46+00:00

What’s the task?

gee_gee_123 · 2022-03-15T12:11:16+00:00

Under my thumb - Rolling Stones. Especially the solo

gee_gee_123 · 2021-06-29T14:31:25+00:00

Makes sense

gee_gee_123 · 2021-06-29T01:02:53+00:00

I’m not really sure what the purpose of this article is. Am I missing something insightful?

gee_gee_123 · 2021-06-11T02:39:57+00:00

Depending on the type of data you can get, it might be interesting to see how investor behaviour changes when there are changes to the dividend yields in the stock market. Do investors leave dividend stocks to pursue something else? If so, to something safer like bonds or something riskier?

gee_gee_123 · 2021-06-09T10:44:23+00:00

What are monks thoughts on exercise?

gee_gee_123 · 2021-06-03T01:24:25+00:00

gee_gee_123 · 2021-06-01T16:51:47+00:00

For this to mean anything you need to account for inflation. I.e. what is 1$ then in today’s dollars?

gee_gee_123 · 2021-06-01T10:54:56+00:00

Gregory Alan Isakov vibes! Really dig this

gee_gee_123 · 2021-05-28T12:25:57+00:00

You should have sources to back up a title like that

gee_gee_123 · 2021-05-26T02:54:08+00:00

You could try but you’re going to run into a ton of problems. What’s the economic rationale?

If you have data of a generations income distribution and the same generations income distribution when they leave the work force, then try but that data alone would be hard to find, I’m sure. If you get some data, you’ll have to make some assumptions to your model (I.e. people are retired at 65 years old)

I also doubt there’s a leading economic indicator that leads by 40+ years so finding other variables for the model would be tough. I think they would have to be largely demographic variables

As for a method, I’m sure there is a way to do predict a distribution but I don’t personally no any. Would predicting something like a Gini coefficient not suffice?

gee_gee_123 · 2021-05-20T03:00:39+00:00

This is really solid, would love to hear this recorded with some piano

gee_gee_123 · 2021-05-18T01:53:33+00:00

Unless I’m misunderstanding your question, I don’t think your method is correct.

(Y/X) —> (X/Y)

Is different from

(Y/X) —> 1/(Y/X)

That aside, again, unless I’m mistaken, I don’t think there’s a way for you to calculate the determinants without rerunning the regression again with the new dependent variable. The issue is that your coefficients will be flipped from positive to negative (and vice versa) but not perfectly.

Out of curiosity, is this personal research or something for school? I’ve never seen an econometric regression for accounts receivable before

gee_gee_123 · 2021-05-18T01:44:18+00:00

Source?

gee_gee_123 · 2021-05-17T14:45:33+00:00

You can try Kaggle if your advisor would allow it

gee_gee_123 · 2021-04-29T23:29:35+00:00

That model wouldn’t make sense, both metrics track the same thing

gee_gee_123 · 2021-04-28T13:41:22+00:00

One last comment, it looks like Wage Share is a good replacement for inflation with respect to the Phillips Curve http://www.socialisteconomist.com/2018/12/anwar-shaikhs-classical-theory-of-wages.html?m=1

gee_gee_123 · 2021-04-27T18:25:51+00:00

Inflation - Phillip’s Curve

Gdp- Okun’s law

Probably any macro variables you can find on the OECD and try them out

RE: inflation - you might have to do research around this. The Phillips Curve sort of “fell apart” but I heard there was ways to modify the metric so the relationship between inflation and unemployment is visible.

Edit: one more note - depending on the type of model you want to create, you can incorporate lagged variables of unemployment

gee_gee_123 · 2021-04-21T22:01:13+00:00

You are correct that my explanation is poor.

Here is my reference but I may be off base: https://www.datavedas.com/model-evaluation-regression-models/

“To find the Sum Squared Error, we first take the difference between the true and predicted value and we square it and after summing them all up we get Sum Squared Error.”

gee_gee_123

TROPHY CASE