"Econometrics has become such an obvious, objective - almost natural - tool that economists often forget that it has a history of its own, a complex and sometimes problematic history. Two works - Morgan (1990) and Qin (1993) - constitute the Received View of the history of econometrics. Basing our analysis on Leo Corry's methodological (and historiographical) framework of image and body of knowledge, the main purpose of this dissertation is to provide a critical account of the Received View.
Our main criticism is that historians of econometrics have a particular image of knowledge that stems from within econometrics itself, generating a problem of reflexivity. This means that historians of econometrics would evaluate econometrics and its history from an econometrician point of view, determining very specific criteria of what should be considered as "true", what should be studied or what should be the questions that the scientific community should ask.
This reflexive vision has conducted the Received View to write an internalist and funnel-shaped version of the History of Econometrics, presenting it as a lineal process progressing towards the best possible solution: Structural Econometrics and Haavelmo's Probability Approach in Econometrics (1944).
The present work suggests that a new history of econometrics is needed. A new history that would overcome the reflexivity problem yielding a certainly messier and convoluted but also richer vision of econometrics' evolution, rather than the lineal path towards progress presented by the Received View".If you have a serious interest in the history of our discipline, this is for you.
"Of all the tips that have been posted at Pedagogy Unbound since the site’s launch in August, the one that has been read the most—by far—is titled “Help your students stay awake in class.” This, it seems, is what professors are most concerned about. Not student writing. Not the plague of plagiarism. Not even students who don’t participate in discussions. No, the most pressing problem facing college teachers today is merely getting their students to stay conscious for an hour and 15 minutes.
.......The tip is one (from an associate professor who) worked as a truck driver when he was a college student and now, as a teacher, he passes on his “trucker tricks” for staying awake to his students.
......Crucially, (he) follows up these tips by inviting the students, at any time during class throughout the term, to stand up if they feel like they are getting sleepy. They can take their notebooks and stand at the back or side of the classroom. He tells them he’d much prefer a class full of standing students to one full of sleeping, or even just drowsy, students.
.......So ask your students to stand up if they feel they are in danger of falling asleep. If it turns out that a number of them take you up on the offer, you can tell yourself that you’re getting a standing ovation."
"Most people hyping data science have focused on the first word: data. They care about volume and velocity and whatever other buzzwords describe data that is too big for you to analyze in Excel. .........
But the key word in data science is not "data"; it is "science". Data science is only useful when the data are used to answer a question. That is the science part of the equation. The problem with this view of data science is that it is much harder than the view that focuses on data size or tools. It is much, much easier to calculate the size of a data set and say "My data are bigger than yours"......"Right on, Jeff!
"While writing my book (Stochastic Processes, 1953) I had an argument with Feller. He asserted that everyone said "random variable" and I asserted that everyone said "chance variable." We obviously had to use the same name in our books, so we decided the issue by a stochastic procedure. That is, we tossed for it and he won."
"As I remember, Bill X fixed my washing machine. My husband, Harry X, brought him home to talk economics after a Cambridge dinner in hall and they walked in on my frustration with the washer. I met a slight-statured, quiet man who modestly asked if he could help. He tried something with a screw-driver which may have worked - or perhaps it didn't work - and went back to talking economics'"
"I believe that these methods have a lot to offer and should be more widely known and used by economists. In fact, my standard advice to graduate students these days is 'go to the computer science department and take a class in machine learning'."
"The aim of the Association is to advance the education of the public in the subject of econometrics and its applications to a variety of fields in economics, in particular, but not exclusively, by advancing and supporting research in that field, and disseminating the results of such useful research to the public."
"It attracts attention. Often on a beach someone will say something like 'You're either a math teacher or in a really, really odd motorcycle gang.'
Why should statisticians lag behind? A bottle of champagne to the first reader who can show a permanent tattoo of Bayes' theorem - preferably on a part of the anatomy that we can decently reproduce."
"I have always considered the arguments for the use of P (p-value) absurd. They amount to saying that a hypothesis that may or may not be true is rejected because a greater departure from the trial was improbable: that is, that it has not rejected something that has not happened'"H. Jeffreys, 1980. Some general points in probability theory. In A Zellner (ed.), Bayesian Analysis in Probability and Statistics. North-Holland, Amsterdam, p. 453.
"The thing to remember about models is they’re always approximations and they will always turn out to be wrong at some point. When someone says all the models that economists use are wrong, well, in a sense that’s true. But you need to ask, are the models wrong in ways that are central to the questions, or are they wrong in ways that aren’t so central?
And so part of the task of statistical analysis is to look at models and try to figure out what the gaps are so that people will build better models in the future."
"This note shows that a big stock market crash, in the absence of central bank intervention, will be followed by a major recession one to four quarters later. I establish this fact by studying the forecasting ability of three models of the unemployment rate. I show that the connection between changes in the stock market and changes in the unemployment rate has remained structurally stable for seventy years. My findings demonstrate that the stock market contains significant information about future unemployment."
"...will showcase the breadth and importance of statistics and highlight the extraordinary opportunities for statistical research in the coming decade.
This invitation-only workshop will be an opportunity for presenters, all statisticians and organizers to think about where statistics should go as a discipline and the lessons learned in the past that will guide us into the future. During this unique event, statistical scientists and scientists from other disciplines will interact and chart a shared vision for the future."
Finance is an engaging and highly competitive professional field to get into. For those studying finance, the internet can offer a wealth of resources. That said, it can be hard to sift through and find the best. We hope this feature will help finance students find information about financial organizations, current economic news, financial modeling software and techniques, and the finance industry as a whole. Your site is a valuable addition to this resource.
No problem, Abigail - happy to oblige. You'll find this blog listed as site #8.We're hoping to share this article with as many finance students and professionals as possible and will be contacting our readers and followers. If you're able to post this on your website or share the article anywhere else you can think of too, I'd really appreciate it."
'Nearly two weeks before the Future of the Statistical Sciences Workshop*, the Unconference on the Future of Statistics will be staged. Organized by two of the authors of the Simply Statistics blog, the Unconference will be a virtual event hosted on Google Hangouts.
“It is a great time to be a statistician and discussing the future of our discipline is of utmost importance to us,” say Roger Peng and Jeff Leek, Unconference organizers, referring to the Future of the Statistical Sciences Workshop. “In fact, we liked the idea so much we decided to get in the game ourselves. We are super excited to announce the first ever ‘Unconference’ hosted by Simply Statistics. Our goal is to compliment and continue the discussion inspired by the Statistics 2013 Workshop.”
The Unconference, which will focus on the future of statistics from the perspective of junior statisticians, will be held October 30 from noon to 1 p.m. EST on Google Hangouts and simultaneously live-streamed on YouTube.
The event will feature several of the most exciting and innovative statistical thinkers discussing their views on the future of the field, especially those issues that affect junior statisticians the most: education, new methods, software development, collaborations with natural sciences/social sciences, and the relationship between statistics and industry.
You can sign up for the Unconference here. During the lead-up to the conference, organizers ask that you submit your thoughts on the future of statistics via Twitter using the hashtag #futureofstats. They will compile all comments and make these available along with the talks.'
Time to start tweeting!"The Fields Institute for Research in Mathematical Sciences at the University of Toronto is sponsoring a Twitter contest called “The Normal Curve”. The contest is being held in recognition of the Institute’s 20th anniversary and the International Year of Statistics. In this unique contest, the Institute poses this question to the world: “What would the world be like if the normal curve was not discovered?” To enter, tweet your answer to the question using the hashtag #WithoutTheCurve for a chance to win one of three autographed copies of Jeffrey Rosenthal’s bestselling book, Struck by Lightning. Submissions for The Normal Curve contest will be accepted beginning September 25 at 12:01a.m. EST. To be eligible for the contest, submissions must be submitted by Twitter, tagged as #WithoutTheCurve and address the contest question. The entry deadline is 11:59 p.m. EST October 15. The top entries selected by volunteers at the Fields Institute’s MathEd forum will be entered into a pool for the drawing the prizes. Winners will be randomly selected for the three prizes. Winners will be announced by the end of October. The contest is open to users internationally. Submissions not in English may be translated using Google Translate if there is no one on the judging panel who can translate the tweet."
"The 5th Lindau Meeting on Economic Sciences will provide an open exchange of economic expertise and inspire cross-cultural and inter-generational encounters among economists from all over the world. The world economic and financial crisis will surely be a central theme between the laureates and the young participants, but most likely the global central banking system or the challenges to the international free trade will also be main topics."Perhaps you know someone who deserves to be nominated to participate in this Meeting?
"New evidence is presented that Richard Price gave Thomas Bayes's famous essay a very different title from the commonly reported one. It is argued that this implies Price almost surely and Bayes not improbably embarked upon this work seeking a defensive tool to combat David Hume on an issue in theology."
"You might ask yourself, what emerges if we go through a similar analysis using the "adjusted" coefficient of determination? Is the "adjusted R2" more or less biased than R2 itself, when there is actually no linear relationship between y and the columns of X?"
“Enter each data point twice, once with the desired signs for the data, and then with the opposite signs. That is, the sample would involve ‘2n’ observations – the first ‘n’ of them would be of the form (yi, xi') and the next ‘n’ of them would be of the form (-yi , -xi'). Then fit the model (with the intercept) using all ‘2n’ observations, and the estimated slope coefficients will be the same as if the model had been fitted with just the first ‘n’ observations but no intercept.”Is your colleague's suggestion going to work?
