(Part 2) Top products from r/AskEconomics

So this isn’t an exact answer, but your question was kinda open-ended so I hope this a nudge in the right direction.

First off, the field of computational economics is a thing. However, it mostly is concerned with microeconomic problems that can easily be classified as “algorithmic game theory” (eg how to efficiently determine the winner of an auction). While that’s not all that’s popular in the field, that’s primarily what it is. So this might not be helpful, but I wanted to at least mention it. EDIT: actually, if you poke around that Wikipedia page enough, but might find something to help you.

Second, what you’re looking for is going to be resources about Method of Simulated Moments, Indirect Inference, and other such Econometric methods used for Structural Modeling and Computation. Now, these methods are used for estimating parameters of complex models where the parameters can’t be estimated using some kind of regression model or data is only available in aggregated form. Obviously the properties of these estimators are not what you’re concerned with. However, in order to implement these estimators, the following procedure is used: 1) guess parameters, 2) simulate the model, 3) compare the simulated data to the observed/aggregated data, 4) change the parameters you guessed and repeat until you match the simulated data to the observed data. As such, resources for implementing these estimators should cover aspects about how to efficiently simulate the model.

I bolded “should” because in actuality, there are very few good resources for this area of economics. I’ve taken some classes in the area, and I can confirm that there’s basically one textbook available and it’s not the best. I mean, simply viewing the two Wikipedia pages I included should give you a feel for how (un)popular of an area this is. (However, it is becoming more popular now that even cheap computers can run estimations of simple models). So unfortunately, the best I can tell you is good luck, and I hope I’ve given you enough keywords to help with your search. I believe u/ECTD is working on a dissertation right now that either uses these techniques or is researching them, so he/she might be able to give you some better resources.

This is my field of study, so if you have questions or comments don't hesitate to ask, but I think you need to think this through a bit. What is your goal? Are you writing a paper? Or are you just trying to understand the impact of privatization? In short, I will say that some people made their entire careers on understanding the complexities of telecom regulation. It is a dense subject with a lot of nuance that shouldn't be taken lightly.

As a general matter, then, I think you should shift the framing away from good or bad and talk about the effects for consumers or how it changed the status quo. You can make the assessment of whether or not it was good or bad after you have laid out the costs/benefits. If you need a solid read on cost-benefit analysis or public policy analysis, check this out.

A couple of words on terminology. Do you really care about the privatization OR do you care about the regulatory regime that BT was put into afterwards? The UK government owned all of the shares of BT and then one day said that they were going to put them up for sale. Is that important and if so why? A quick search turned up this paper, suggesting that the private/public distinction didn't matter much.

What did matter was the change in the regulatory regime. In the US, we didn't have a national telecom company, we had a government granted monopoly. But we did enact much of the same regime on AT&T as was enacted on BT, as did a lot of other countries. To this effect, I would check out this paper from Jerry Hausman where he talks about the effect of unbundling and such around page 33. Hausman, if you haven't taken a lot of econometrics, has a number of statistical tests named after him. He is highly respected.

As I see it, the paper entitled "Public ownership, privatisation and regulation: social welfare counterfactuals for British Telecom" is the best since it is using a counterfactual analysis. I would start there and try to understand the gist of the social effects.

Finally, a word about prices. In the US, IIRC, prices did go up for short distance calls, but long distance calls prices went down. Interestingly, the immediate effect of an increase in prices was that people talked more often using long distance and less often with a short distance. In other words, consumers budget didn't change, but how and what they consumed did. Be careful of this.

Other comments / resources:

• Another paper worth reading
  
  
• Regulation Body of Knowledge <- This web site has a lot of citations. To find out what I am saying, put the mouse over "Price Level Regulation" and then click the "Annotated Reading List." Under the "Price Regulation" subheading, click the read more link. There is a lot here to read if you want to know more about this space.
  
  
• ICT Regulation Toolkit <- This is a web site maintained by the ITU, the International Telecommunications Union.
  
  
• Jean Tirole's Nobel Prize Lecture, which touches on telecom regulation.

Now this is an interesting and difficult question, which depends on many things. For starters, if you find this process frustrating that is unfortunate, because learning how to code is usually a trail and error + revise your work process. In other words, its supposed to be both frustrating and rewarding, like a hard (text-based) video game. For me its half of the fun.

What you want to learn really depends on the context. If you are really diving into econ, Stata is still very common. More stats-heavy, new, or interdisciplinary fields tend to use R. If you work with big, live datasets, or work with computer scientists, learning Python is always a plus. But obviously start with one.

I am proficient in stata simply because I had classes in it, it is difficult for me to advice how to self study. I learned most of the basics through An Introduction to Modern Econometrics Using Stata, and later on most of my R through R for Stata Users (Statistics and Computing) . I also learned some R through Discovering Statistics Using R, but I find Field obnoxiously failing to be funny, so I wouldn't reccomend it.

I'm now in the process of learning more Python, to do some more programming work on the side. As a start I used Learn Python 3 the Hard Way recommended to me by a very proficient friend of mine. This however does not give you much of an intro to stats in python, only the very very simple basics you can use as a vantage point for further work.

If you have learned the basics, tbe hest way to learn more is just to fool around. What is your field of interest? I like a lot of macro, so I used to just go to Quandl, pick some free databases, import them, and run some fun stuff. This is the best way to learn, especially if you for example try to merge free World bank databases with a different database from Quandl, as it will give you a lot of errors whilst merging and conversion problems later on.

If you are a bit more proficient you can start using websites like upwork to get some assignments. Usually it doesn't earn you much at the start, but the experience of actual assignments is the best way to self-teach. A different manner I like to do (if you are still studying) is offering your services (for free) to a professor. Ask him/her if there are still projects they are working on for which they need some to look at. Usually you will be treated solely as someone for the code, but it generally gives you a lot of experience and the right contacts.

These are just some of my thoughts. If you could provide some more context of where exactly you want to go, I could go into more detail.

Edit: What I forgot to say is that if it is not possible to study a course, I would recommend doing at least one MOOC to get you at a basic level.

It really depends on how they are structured and who owns what.

One of the most successful partnerships, Goldman Sachs (not a coop, but the same analysis because shares were restricted) was basically forced to go public because the shares were worth so much and no one in the partnership could buy without issuing more shares. Big pay day for them.

My favorite worker-owned coop is W.L. Gore & Associates. A good book explaining corporate structures is The Enlightened Capitalists.

No matter what corporate structure is adopted, one thing is certain: everything is great if the business makes money. Once it starts losing money it doesn't really matter.

Damn... good question. Too broad to answer with any certainty though I think.

On the one hand, if it just disappeared (and the land went with it and everyone forgot it was there) then things would probably go on as normal, with a lot of new trade routes (Asia-Europe via the Mexico-Canadian sea?) and probably higher costs as a result of reduced economies of scale. I think economic climate would continue, solely on the basis that after disappearing it's like the US was never there so the world "doesn't know what it's missing" so to speak.

On the other hand, if it disappeared but everything else stayed the same, then you'd definitely have economic shocks relating to everything from debt (assuming US debt is now worthless) to commodities to services. This would probably have a lot of knock on effects such as cascading defaults, lack of liquidity, etc. in global markets. I think there'd almost certainly be war too, given the US does sort of act as a world police right now. At the very least, probably a lot more piracy and lawless regions due to destabilization.

If the US disappeared but the land remained... well that'd be an interesting one.

If you want an interesting read on this (sort of) check out a book called The Mandibles. It's fiction but the logic and economic theory in it is pretty robust. Little bit of an outlandish concept but really interesting read.

There were several Milton Friedmans.

As an academic economist, he made important contributions to business cycle theory, monetary history, and consumption theory. For an overview of Friedman's scientific contributions to economics, see here. These contributions have largely stood the test of time.

But there was another Milton Friedman: the policy advocate. In this role, we can look at his popular books like Capitalism and Freedom and Free to Choose. Whether one accepts the conclusions of his popular work is nearly orthogonal to whether one accepts the contributions of his scientific work. For a critical account, see Krugman.

If I can offer up a possible partial explanation from a non-economist with a strong interest in demography, I think a lot of the "hollowness" people feel today comes from mistaken beliefs about how well-off the typical person of 1950something was compared to the typical person of today.

A surprisingly easy way to start getting a handle on this is to look at old mail-order catalogs in one tab and using the BLS Inflation Calculator in another tab to convert historical prices to 2019 dollars. I tend to focus on electronics, specifically television sets and audio equipment. So, like, the cheapest television set available through Sears in 1957, a 21" black and white TV, sold for the equivalent of $1,539.35 in 2019 dollars. I bought a 60" 4k TV for less than half that price two years ago, so.

Also, people tend to think that strong-union manufacturing jobs were typical back then, ignoring the vast swaths of the population who lived in anti-union states, who toiled in the fields, who tried to scratch out a subsistence living in the pre-Great Society-reforms era, and who were locked out of "good" jobs because of their race. (I've tried asking around about exactly what percentage of the population held relatively-well-paying manufacturing jobs, but I've never gotten an answer.)

EDIT with data! I'm having a manic episode, so I couldn't stop digging. I found a handy breakdown of 1957 incomes, in 1957 dollars. The 1957 median income in 1957 dollars was $4,175; adjusted to 2017 dollars for comparison purposes, the 1957 median personal income was $35,492. Flashing forward, the 2016 median personal income in 2017 dollars was $31,099. So there was a pretty big decline in the median personal income between 1957 and 2016. But the median earner in 1957 could buy 21 cheap TVs, while the median earner in 2016 could buy 236 cheap TVs--an order of magnitude more. So I guess ultimately it comes down to the unsatisfying conclusion that there isn't even really a good way to compare the lifestyle of today to the lifestyle of yesteryear because there are just so many moving parts. (I'm not even addressing the increasing number of earners per household because I'm lazy like that.)

If you're interested in all of that, you should start by reading up on mechanism design, which you can find in any good microeconomics or game theory textbook. I like Fudenberg and Tirole.

• Fudeberg and Tirole - Game Theory
  
  I mainly see Krishna's book used for auctions. Menezes and Monteiro is also good. There are also books by Paul Klemperer and Paul Milgrom which are less textbook like.
  
  
• Auction Theory - Vijay Krishna
  
  
• Menezes and Monteiro - An Introduction to Auction Theory
  
  For matching, the guide to the "classical" theory is Roth & Sotomayor, but it's getting pretty old. There's a new "Handbook of Market Design" but I haven't read it and can't vouch for it.
  
  
• Roth and Sotomayor - Two-Sided Matching
  
  For bargaining, you can't go wrong with Osbourne and Rubinstein.
  
  
• Osbourne and Rubinstein - Bargaining and Markets
  
  Sadly, I don't know of a good voting textbook. Much of the recent work in voting has moved out of economics into computer science, political science, etc., so I would look there for current work on voting.

Abel and Bernanke's Macroeconomics is standard mainstream intermediate macroeconomics. Williamson's Macroeconomics introduces new classical Real Business Cycle type modelling. It's useful if you intend to go on to graduate work, especially a PhD in Economics, but I wouldn't recommend it if you just want to build up your economic intuition on how the economy ticks. If you don't want to go on to graduate work, I would recommend Blanchard's Macroeconomics instead of Williamson.

https://www.amazon.com/Macroeconomics-7th-Olivier-Blanchard/dp/0133780589/

It shouldn't be overwhelming if you prepare properly. Try to at least get your hands on intermediate level micro / macro texts and read through them to understand the basics. For an econ MA you don't need a ton of math. I usually suggest this Schaum's outline because it covers the needed areas up to differential equations and it has a lot of problems to help you learn the material. Add any decent introduction to econometrics, e.g. Stock / Watson, and you should be set.

Keep in mind you don't need to know everything in those textbooks, so don't worry too much if it looks like a ton of material. What you might want to do is try to get copies of the syllabi for the undergrad courses in econ at the universities you're applying to for an MA. That way you can see which textbooks they use, what material they focus on, etc.

I recommend this book https://www.amazon.co.uk/Principles-Microeconomics-Robert-H-Frank/dp/007110657X
Is the one that I use in my microeconomics class. First semester

So I usually tell my MBA students to just read books, not textbooks. Here are a few of my general suggestions:

Nudge, Thaler and Sunstein

Misbehaving Thaler

Superforecasting Tetlock and Gardner

Zombie Economics Quiggin

If you need more suggestions or want to discuss any of the ideas in these books, don't hesitate to ask.

For that I recommend Mishkin's Money Banking and Financial markets 100x over a general intro econ textbook. Its understandable by a layman, imo. You can get a fairly recent edition here used hardcover for under $20

Here is the table of contents from an older edition to give you an idea of the type of stuff covered in the book

If I were you I would read the last part of the book (the last few chapters which covers general macroeconomics) before reading the rest, but its up to you

You can't go wrong with Krugman, Obstfeld, and Melitz. These guys "wrote the book" on trade, literally and figuratively.

MWG is the bible of microeconomics, but it's almost entirely unreadable. If you want a step up from Mankiw I'd start with Blanchard's Macroeconomics and Varian's Intermediate Microeconomics. These are the books I use when I teach intermediate macro/micro. The math is straight-forward (nothing beyond calculus), but you're going to be swimming in MWG or Stockey and Lucas unless you have the fundamentals down first.

Math econ isn't a sub-field of, it's a set of mathematical tools used in econ. You can't specialize in math econ in grad school.

Chiang and Wainright and Simon and Blume are what you want to at least cover the basics. Although most if not all of it will be review which is the intention.

it depends on the way they experience assymetric shocks deriving from assynchronised bussiness cycles and how governments handle these.

in theory there is no problem with taking away the 3 tools of monetary policy assuming that (i) money is neutral in the long run and (ii) fiscal policies can be done in the short run.

there are obvious benefits to sharing a currency with trade partners (are they trading a lot with each other? i got no idea).

here's a good book at the ugrad level: https://www.amazon.co.uk/Economics-Monetary-Union-Paul-Grauwe/dp/0199563233

My health econ professor for undergrad made us use folland's health econ book. I'm not sure how good it is though compared to other textbooks.

If you want an understanding of Marxian crisis theory, Wolff has a paper [here](https://journals.sagepub.com/doi/pdf/10.1177/048661347801000103), this is from Mandel's [book](https://www.ernestmandel.org/en/works/txt/1990/karlmarx/9.htm) & Shaikh writes about it quite a bit in his [book](https://www.amazon.com/Capitalism-Competition-Conflict-Anwar-Shaikh/dp/0199390630). There is a more ecologically focused book elsewhere (though the leftcoms despise it).