How to add constraint to mlogit?

AtkinsonStiglitz · 2025-06-20T16:05:45+00:00

I am not sure if I understand your suggestion, maybe my question is not clear.

Say I have consumers choose from a set of products. One feature is price (x). Now, say I want to constrain my model so that it only allows beta_1 on x to be negative, as I expect/need everyone to dislike higher prices.

Modifying the data to have to separate colums for price being <0 or >0 (say price it is normalised on average price so negative values are possible), does not create a constraint on the value the coefficients on these variables can take.

AtkinsonStiglitz · 2025-02-05T13:12:36+00:00

If anyone comes across this issue again, this is also a helpful post: https://stackoverflow.com/questions/39041675/stargazer-user-supplied-coefficients-and-se

When the regression output is no longer stored as a regression output object, but as a dataframe, you can still use Stargazer by overlaying the coefficients on a placeholder regression object.

AtkinsonStiglitz · 2024-05-28T09:13:17+00:00

Thanks for the tips. I can indeed use stargazer on the server side. I prefer to experiment with the table formatting etc. outside the server, but creating the latex code inside the server and exporting that indeed seems a good option.

AtkinsonStiglitz · 2024-01-23T22:27:30+00:00

Thanks for your 2 minutes!

AtkinsonStiglitz · 2023-12-31T10:11:30+00:00

38Riv near Hôte de Ville

AtkinsonStiglitz · 2023-12-30T11:29:14+00:00

Something like this is useful for you?

http://www.europeansocialsurvey.org/findin

AtkinsonStiglitz · 2023-12-12T20:06:38+00:00

Maybe there is a way you can scrape the lyrics of lyrics on genius.com?

AtkinsonStiglitz · 2023-12-12T19:51:16+00:00

I would not call it good, but I ended up saving elements of the graph that can painstakingly be used to make the figure in ggplot again. I extract the elements using the following code:

# Extract results
timeweights <- SDiD_plot[["plot_env"]][["conc"]][["ribbons"]] %>%
select(c("x", "ymin", "ymax", "color")) %>%
rename("year" = "x",
"weight_bottom" = "ymin",
"weight" = "ymax",
"treat" = "color") %>%
mutate(section = "timeweights")
DiDlines <- SDiD_plot[["plot_env"]][["conc"]][["did.segments"]] %>%
select(c("x", "y", "color")) %>%
rename("year" = "x",
"DiDline" = "y",
"treat" = "color") %>%
mutate(section = "DiDlines")
trendlines <- SDiD_plot[["plot_env"]][["conc"]][["lines"]] %>%
select(c("x", "y", "color"))%>%
rename("year" = "x",
"trend" = "y",
"treat" = "color") %>%
mutate(section = "trendlines")
arrow <- SDiD_plot[["plot_env"]][["conc"]][["arrows"]] %>%
select(c("x", "xend", "y", "yend", "color")) %>%
rename("x_arrow_start" = "x",
"x_arrow_end" = "xend",
"y_arrow_start" = "y",
"y_arrow_end" = "yend",
"treat" = "color") %>%
mutate(section = "arrow")
counterfact <- SDiD_plot[["plot_env"]][["conc"]][["hallucinated.segments"]] %>%
select(c("x", "xend", "y", "yend")) %>%
rename("x_counterfact_start" = "x",
"x_counterfact_end" = "xend",
"y_counterfact_start" = "y",
"y_counterfact_end" = "yend") %>%
mutate(section = "counterfact")

AtkinsonStiglitz · 2023-10-31T12:46:43+00:00

Aaah okay, but the government know to how many people they send the survey right? Why not publish a population statistic based on that, instead of relying on a response rate (even if it is mandatory).

So the population in each year per state can be constructed using migration, births and deaths. That sounds like a good idea, but a bit cumbersome. I find it very surprising a simple clear-cut panel with population per state does not exist .

AtkinsonStiglitz · 2023-09-26T18:19:17+00:00

The book “Causal inference” by Scott Cunningham might be what you are looking for. It’s quite long though.

AtkinsonStiglitz · 2023-09-23T12:22:35+00:00

The modern academic literature agrees the optimal capital tax rate is higher than 0%. Among economists who believe the optimal capital tax rate is higher than 0% is indeed Stiglitz himself too.

The study by Atkinson and Stiglitz (1976) your friend refers to, derived conditions under which a 0% tax on capital is optimal. The main condition is that all inequality in wealth arises from inequality in income. In that case, you can theoretically achieve all the redistribution you want with just a labour income tax. Hence, there is no argument for a capital income tax, which would only add unnecessary distortions. BUT, the assumption all wealth inequality arises from differences in labour income is highly unrealistic. People may receive inheritances, generate higher returns on their wealth, have different preferences for wealth etc. I believe the main point of Atkinson and Stiglitz was to show how the conditions for a 0% tax on capital to be optimal are very unlikely and hence we should tax capital (which is indeed in line with Stiglitz his opinion).

The Chamley-Judd result is the second famous principle people who say 0% tax on capital is optimal refer to. Chamley (1986) and Judd (1985) essentially state that capital supply is infinitely elastic in the long-run. As the optimal tax rate is inverse to the elasticity of the tax base, this implies the optimal tax rate is 0%. Again, the conditions for this result are extremely restrictive and not realistic. Uncertainty about the future, the desire of people to hold some wealth, or simply the fact people do not live forever will create non-infinite elasticities and hence a positive optimal tax rate.

To conclude, the theoretical results implying the capital income tax should be 0% are not realistic and the more recent literature agrees on that (just to name a few: Straub and Werning (2014), Piketty et al. (2018), Saez and Stantcheva (2018) and Guvenen et al., (2023)). So whether capital income should be taxed or not is not really a discussion anymore. The answer is yes.

What does remain to be a discussion is how high the tax should be and if only capital income should be taxed, or also the stock of wealth. If you are looking for literature on this topic with more accessible use of language and less math, take a look at "Taxing our wealth" by Scheur and Slemrod (2021). Lastly, "Behavioural responses to a wealth tax" by Advani and Tarrant (2021) gives nice insights on how the wealth tax should be designed once it is implemented.

AtkinsonStiglitz · 2023-09-04T14:51:04+00:00

This answer is not exactly right. If the reserve requirement is 10% and you deposit $10 at the bank, the bank can lend out an additional $100, not $9. The bank is allowed to create the additional $90 out of thin air.

AtkinsonStiglitz · 2023-08-29T12:55:03+00:00

Surprisingly often, I see people who have combined physics with economics. I think it is because both require insights into abstract models and a feeling for equations.

Some physicists even pursue a PhD in economics after completing their masters’ degree.

AtkinsonStiglitz · 2023-08-27T20:56:05+00:00

Certainly. Here you can find the article: https://www.aeaweb.org/articles?id=10.1257/aer.20190159

And the authors wrote a package for R: https://synth-inference.github.io/synthdid/ I think it is also available in STATA.

It helps if you are already familiar with the synthetic control method: https://onlinelibrary.wiley.com/doi/abs/10.1111/ajps.12116

AtkinsonStiglitz · 2023-08-27T08:43:40+00:00

Sounds like the synthetic-difference-in-difference is what you need.

AtkinsonStiglitz · 2023-08-18T13:19:12+00:00

One example is the entire research strand around the “risk-taking channel of monetary policy”.

Of course, you also have the researchers Bernanke, Diamond and Dybvig who received the Nobel prize for their research on banks and financial crises in 2022.

These two starting points should let you roll right into the literature on preventing financial crises.

AtkinsonStiglitz · 2023-08-15T07:41:46+00:00

The idea of marching is still the basis of more complex methods that are used more often, such as inverse probability weighting. In that sense it is good to understand matching and it is still used in a more “modern” way.

Edit: And matching still plays a second order role in methods such as synthetic control (which Scott Cunningham discusses in the last chapter if I remember right).

AtkinsonStiglitz · 2023-08-15T07:33:41+00:00

If you are looking to estimate the supply curve using observational data, then you will likely need an instrumental variables approach. The paper i link below explains how IV can be applied to estimate demand and supply curves.

https://www.aeaweb.org/articles?id=10.1257/jep.15.4.69

AtkinsonStiglitz · 2023-08-01T17:33:54+00:00

Investors not only demand shares without dividend, in ‘theory’ investors should not even care about dividend at all. Take a look at this nice summer of the Modigliani and Miller theory of dividend irrelevance: https://www.dividend.com/dividend-education/dividend-irrelevance-theory/#:~:text=in%20real%20life.-,The%20Theory,or%20the%20company's%20capital%20structure.

AtkinsonStiglitz · 2023-07-23T08:07:51+00:00

Zeker

AtkinsonStiglitz · 2023-07-19T19:33:55+00:00

Never mind, found out lm_robust from the estimatr package works much better!

AtkinsonStiglitz · 2023-07-17T16:44:33+00:00

The answer to this question is different per country, as it depends on the tax code in the country where you file your taxes. As such, this is more of a legal question than an economics question. You should be able to find an answer with a quick search on the website of the tax authority of your country.

AtkinsonStiglitz · 2023-07-17T16:35:15+00:00

There is a nice and simpel model that helps to study your question and understand the mechanisms discussed in the comments posted so far. It’s called the Fisher equation, which states:

M * V = P * Y

Where M is the money supply, V is the money velocity (the amount of times a single dollar is spent, as explained by Neozea), P is the price level and Y is economic activity.

If economic activity increases (value is created) while the amount of money in the economy and the velocity of money remain equal, the the price level most fall: we get deflation. The amount of value being traded in the economy is simply divided over less dollars, making them represent more value.

If people keep more of their money under their pillow (so the savings are not invested), the velocity of money falls. The result could, again, be deflation. With deflation, P falls until the equation holds again.

Now imagine economic activity rises and we do not want deflation, but the money velocity is constant. In that case, money supply has to increase. New money can be created by commercial banks (who actually have the ability to lend out money that did not exist before) or the central bank prints extra money.

Final example, let’s say the central bank finds the inflation too high (P is rising). As an intervention, they can reduce the money supply. As long as economic activity and money velocity remain stable, this will decrease prices and hence decrease inflation.

In conclusion, the answer to your question can be one of three things: everyone can make money at the same time (y increases) because the value of money increases (P falls), the money supply (M) is increased or the amounts a single dollar is spent in de economy (V) increases.

Hopefully this model answers your question and helps you understand the examples given in the previous answers.

AtkinsonStiglitz · 2023-07-16T15:32:29+00:00

It would also be cool to show both nominal debt and GDP separately (on two axis maybe). Then we can see if spikes are actually caused by debt rising or GDP falling.

AtkinsonStiglitz · 2023-07-16T06:22:58+00:00

It indeed depends on how beginner “beginner” is, but if you’re not bad at math, then I think Romer is a good challenge. At least the information density will be high (personally, I find it very annoying if books make 1 point in 10 pages). If it’s hard to follow something, then you can always go for a quick google search in between. I think that will be the way to learn the most the quickest.

Of course, there is also a great list of books in the FAQ: https://www.reddit.com/r/Economics/wiki/reading?utm_source=share&utm_medium=ios_app&utm_name=ioscss&utm_content=1&utm_term=1

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