If you're interested in economics then I'd recommend. It gives a comprehensive overview of the titular economic models and their historical-societal contexts.
I don't know how hours of reading can be avoided. One book I've found very valuable is Richard Wolf's Contending Economic theories. https://www.amazon.ca/Contending-Economic-Theories-Neoclassical-Keynesian/dp/0262517833
As far as left economics it really only deals with Marxist style socialism. But it does so by contrasting it with Keynesian and Neoclassical theory in such a way that you come out the other end with a pretty good picture of the entire economic horizon (at least in the minds of the most influential thinkers in economics today). From there I'd look for books on other variants of post-capitalist economics.
He co-authored a pretty decent book on Economics. I've been reading it, pretty dry tbh.
Other than that, I think he's just been busy doing his political activism, which probably leads to some marginalization by the academic community.
Here are two graduate-level textbooks on econometrics:
You can flip through the table of contents to get an overview of the topics covered.
Prerequisites include multivariable calculus, linear algebra, probability theory, and mathematical statistics. In a typical first-year PhD econometrics sequence, some fraction of the first semester is devoted to a review of probability and statistics.
A book that is not as much critiques but a primer on neo, Keynesian and Marxian is this:
https://www.amazon.com/Contending-Economic-Theories-Neoclassical-Keynesian/dp/0262517833
My library had a copy. It was pretty good. The Marxism chapter is a little long but it’s good. But again not really criticism, just discussion about how the three differ.
If you want to bookend your sleep I'd recommend Contending Economic Theories. It'll have you sleeping like a baby in minutes.
I also wrote my thesis on GARCH models! I used Tsay (2010) a lot. Also I'd recommend looking into the papers of Engle and Bollerslev. Else I'd just go off the references in Tsay, as he covers much of the immediate methodology.
Seems like a generic selection-on-observables design (explanation). But they don’t seem to have any discussion of what those observables actually are or what drives propensity to play violent video games. In short: I wouldn’t put much stock in it.
I had a Probability and Statistics course during my CS degree and I was working on exercises from this book: https://www.amazon.com/Thousand-Exercises-Probability-Geoffrey-Grimmett/dp/0198572212
It probably won't cover as many subjects as you listed, but I found it helpful and interesting.
Sorry dude, but Ceaușescu's choice to ban abortion, while faltering in providing food and labor opportunity, only intensified his regime's problems. Obviously, it's not the sole factor that lead Romania to revolution, but it's an important factor when compared to how other revolutions went down. Also, the foster kids weren't just kids when the revolution happened; they were of fighting age.
If you want an in-depth analysis of how someone came to the conclusion, a partnership of an economist and a journalist coming together wrote a book called Freakonomics. Here's also an analysis after the fact, a revisiting if you will.
It's not just about abortion and Ceaușescu's downfall, but they make a connection in how the legalization of abortion helped the US' crime rate to go down. Again, it’s not the sole factor, but an important point of time to point out: from a time where abortion wasn't publicly allowed, to a time where abortion was legal.
Contending Economic Theories: Neoclassical, Keynsian, and Marxism by Ricahrd D. Wolff and Steven Resnik
Paul Cockshott's YouTube Channel
Peter Kennedy's "A Guide to Econometrics" is a clear and intuitive textbook. It is a good start and also a good supplement to other textbooks.
Greene's Econometric Analysis is kind of an encyclopedia of econometric techniques. Not as much informal discussion as you'll find in Mostly Harmless, but it covers an immense amount of material.
I'm a PhD econ student as well, if you have any more info on the type of work he does (time series, geospatial data, etc.) I could perhaps suggest something more specific!
>Mutta tuo linkkaamasi tutkimus ei kyllä sano etteikö asumistuki vaikuttaisi vuokriin, vaan että tietyn alueen sisällä tarkasteltuna ihmiset eivät muuta korkeamman vuokran alueelle saadakseen enemmän asumistukea.
En väittänyt, että asumistuki ei vaikuta vuokratasoon. Varmasti vaikuttaa ja vaikutus on positiivinen, mutta valitettavasti sitä vaikutusta on mahdoton estimoida.
Jos keksit tavan sen estimointiin, sillä varmaan pokaat jo tenuroidun professuurin ulkomailta itsellesi.
Tutkimusasetelma on käytännössä RDD, joten tämä vaikutus itseasiassa on arvioitu asumistuen kausaalivaikutus marginaalilla. Lisää aiheesta tässä klassikossa.
>Tutkimus on tämän kysymyksen kannalta merkityksetön koska vertailututkimusta jossa asumistukea ei ole koskaan ollut olemassa ei ole saatavilla.
Ei ole. Tutkimus antaa estimaatin marginaalivaikutukselle. Käytännössä näiden tulosten perusteella voidaan sanoa, ettei asumistuen leikkaaminen todennäköisesti laske vuokratasoa, jos leikkaus ei ole "liian suuri".
Suosittelen petraamaan vähän tutkimuskirjallisuuden tulkintaa. Eerolan ja Lyytikäinen bloggauksia löytyy VATT:in sivuilta.
So I think I get what you’re asking: is there a word, term or concept for the every day ebb and flow of certain occurrences in a given area, category, or around a certain activity. Are these things related, and why do they seem to happen in groups all at once instead of a steady trickle.
That’s a really interesting and abstract thought. One I think many people have but don’t know how to voice. I don’t know the answer, but as far as I know the closest thing you’ll find about the subject is economics and statistics.
As for why you’re seeing these patterns: You’re most likely just experiencing a thing called confirmation bias. Our brains are really good at recognizing patterns, but sometimes it causes us to categorize things into patterns when there really isn’t one there.
Things might not actually be happening in big chunks and then not at all, it’s just that you don’t bother remembering the times when it doesn’t line up with the pattern.
Ask yourself this: Do you have better days when you roll down the windows in your car during your commute?
If you think about it for long enough you might see a pattern because our brains are really good at making connections between seemingly disconnected things. Doesn’t mean it’s actually a pattern, it just means you can make a connection.
the book freakenomics has some good examples of trying to find cause and effect for mundane, everyday patterns. Worth a read or a skim.
I'm a big fan of Casella and Berger's Statistical Inference. My college professor taught from that even though it wasn't our university's chosen text, but I liked it a lot better than the chosen text.
Edit: I know it used to be available for free on Google docs, because while I ordered my copy off Amazon my classmates found a free electronic copy.
Edit: Since it's not mentioned here, Tsay's Analysis of Financial Time Series.
Edit: Lol definitely start first on the appendices to Christensen's Plane Answers book. Good news is those appendices are a wonderful resource, like a book within a book, if you ever need to refresh or re-teach yourself those topics.
I found this book and going by it, they say it is a classic and a good thing is that it does not start from the Gaussian distribution of returns assumption. I hope it helps you.
https://www.amazon.de/Analysis-Financial-Wiley-Probability-Statistics/dp/0470414359
I don't understand how my example of spurious correlation among randomly generated numbers doesn't already meet that burden. That's a data generating process that is not causal by design but produces your preferred observed signal.
Your additions of "repeated", "different times" and "different places" only reduce likelihood of finding a set with your preferred signal (or similarly require checking more pairs). There's literally a cottage industry around finding these funny noncausal relationships http://tylervigen.com/page?page=1
If you're imagining something more elaborate about what it means to move "reliably" together, Mostly Harmless Econometrics walks through how every single thing you might be thinking of is really just trying to get back to Rubin style randomized treatment assignment https://www.amazon.com/Mostly-Harmless-Econometrics-Empiricists-Companion/dp/0691120358
I went through just a few parts of the book in the link below and implemented some of the ideas in python. I downloaded free financial time series and then had a web front end where i displayed some of the data and the resulting calculations. I didn't have a lot of programming experience at the time so it's definitely doable even if you're not advanced as a developer. Let me know if you have any questions about how to start.
https://www.amazon.com/Analysis-Financial-Time-Ruey-Tsay/dp/0470414359/
There's a couple ways to do it. Heckman selection is a popular two-stage solution. Alternatively you could use a simultaneous regression where you assume the covariance between error terms is non-zero (like a system of SUR) but this can be computationally difficult especially if it isn't solvable analytically. Chapter 18 (pp. 808-810 specifically) of Greene's Econometric Analysis as suggested above covers a nested logit model as well.
Richard Wolff's "Contending Economic Theories" would probably be a better start. It compares the three major economic schools, neoclassical, Keynesian, and Marxian, and studies each economic model in depth. It even gives the mathematical models used by economists in each school (but in no way is it math heavy at all). After it looks into each school in depth it analyzes late neoclassical thought, oscillations in the systems, and some of the philosophical premises behind each system. Wolff is a prominent Marxian economist, and the book undoubtedly spends the most time with and favors Marxian economics, but it's a great source to gain an extensive knowledge of each system.
I did well in both Econometrics courses (399,497), and would say definitely check this text book out. You should be able to find a PDF somewhere. In my section with Fossati there was some really basic coding (Shazam), and the stats/maths were very introductory. Understanding basic calculus (multivariate inc.) as well as introductory stats (distributions, expected values, hypothesis testing) is most the course imo.
They're also both a lot of fun. :) If you're looking for interesting Econ courses, those specific 400 level ones are pretty interesting, since you typically get directed to read papers with substantial findings and get a good taste of that particular field. Labor Economics and Urban Economics are both great.
Also a really good companion book to any econometrics text -- it's been my reference throughout my PhD program and it's better than google most of the time :)
For econometrics, the best thing you can do is get a copy of Kennedy's A guide to Econometrics: http://www.amazon.com/A-Guide-Econometrics-Peter-Kennedy/dp/1405182571
It explains the intuition behind lots of econometrics concepts without getting bogged down in formulas. Not to say that the formulas are not important, but if you are going through another rigorous econometrics text, this is handy to have as a supplement so that you can get the big picture and intuition of what you are doing. This book seriously should be mandatory for anyone starting a masters or phd.
> When I want to know about string theory I look for actual science and not anecdotes made by physicists. Not everything that comes out of mouth of educated person is science.
>You made ignorant claim and attempted to support it with an anecdote made by some supposedly respectable economist. That's extremely poor reasoning.
Er..I wasn't aware economic analysis was an anecdote. Besides, my analogy I admit actually wasn't the absolute best, because economics is a soft science, since human beings have conflicting interests. It's that pesky "class" issue.
>Sources you gave me offers no analysis. It's social commentary.
All economics is social commentary, this particular commentary just happens to be backed by fact.
Why don't you provide something that adequately refutes basic economics, instead of stupidly telling me to just go "google it".
>As I said you need to open an actual textbook.
You mean like the textbook he's citing? http://www.amazon.com/Contending-Economic-Theories-Neoclassical-Keynesian/dp/0262517833
Ironically Wikipedia just redirects "Supply and Demand" to Capitalism, that's basically all one needs to know how flawed that idea is.
Come back to me with more than "nu uh, I didn't watch da youtube video". Next you're going to tell me "free markets" actually exist :P
How about One Thousand Exercises in Probability?
It's the partner book to Probability and Random Processes - both good books, but only the "Exercises" one has solutions.