Category: Economics

State-space models in Stan

Michael Ziedalski writes: For the past few months I have been delving into Bayesian statistics and have (without hyperbole) finally found statistics intuitive and exciting. Recently I have gone into Bayesian time series methods; however, I have found no libraries to use that can implement those models. Happily, I found Stan because it seemed among […]

All statistical conclusions require assumptions.

Mark Palko points us to this 2009 article by Itzhak Gilboa, Andrew Postlewaite, and David Schmeidler, which begins: This note argues that, under some circumstances, it is more rational not to behave in accordance with a Bayesian prior than to do so. The starting point is that in the absence of information, choosing a prior […]

All statistical conclusions require assumptions.

Mark Palko points us to this 2009 article by Itzhak Gilboa, Andrew Postlewaite, and David Schmeidler, which begins: This note argues that, under some circumstances, it is more rational not to behave in accordance with a Bayesian prior than to do so. The starting point is that in the absence of information, choosing a prior […]

“Heckman curve” update: The data don’t seem to support the claim that human capital investments are most effective when targeted at younger ages.

David Rea and Tony Burton write: The Heckman Curve describes the rate of return to public investments in human capital for the disadvantaged as rapidly diminishing with age. Investments early in the life course are characterised as providing significantly higher rates of return compared to investments targeted at young people and adults. This paper uses […]

Most Americans like big business.

Tyler Cowen asks: Why is there so much suspicion of big business? Perhaps in part because we cannot do without business, so many people hate or resent business, and they love to criticize it, mock it, and lower its status. Business just bugs them. . . . The short answer is, No, I don’t think […]

Economics, power laws, and hacking

Increasing costs impact some players more than others. Those who know about power laws and know how to prioritize are impacted less than those who naively believe everything is equally important. This post will look at economics and power laws in the context of password cracking. Increasing the cost of verifying a password does not […]

Moneyball for evaluating community colleges

From an interesting statistics-laden piece by Dean Dad: Far more community college students transfer prior to completing the Associate’s degree than actually complete first. According to a new report from the National Student Clearinghouse Research Center, about 350,000 transfer before completion, compared to about 60,000 who complete first. That matters in several ways. Most basically, […]

This is one offer I can refuse

OK, so this came in the email today: Dear Contributor, ADVANCES IN POLITICAL METHODOLOGY [978 1 78347 485 1] Regular price: $455.00 Special Contributor price: $113.75 (plus shipping) We are pleased to announce the publication of the above title. Due to the limited print run of this collection and the high number of contributing authors, […]

Zak David expresses critical views of some published research in empirical quantitative finance

In honor of Ebenezer Scrooge, what better time than Christmas Eve to discuss the topic of liquidity in capital markets . . . A journalist asked, “I just wanted to know how bad the problem of data mining is in capital markets compared to other fields, and whether the reasons for false postives in finance […]

The post Zak David expresses critical views of some published research in empirical quantitative finance appeared first on Statistical Modeling, Causal Inference, and Social Science.

Zak David expresses critical views of some published research in empirical quantitative finance

In honor of Ebenezer Scrooge, what better time than Christmas Eve to discuss the topic of liquidity in capital markets . . . A journalist asked, “I just wanted to know how bad the problem of data mining is in capital markets compared to other fields, and whether the reasons for false postives in finance […]

The post Zak David expresses critical views of some published research in empirical quantitative finance appeared first on Statistical Modeling, Causal Inference, and Social Science.

“When Both Men and Women Drop Out of the Labor Force, Why Do Economists Only Ask About Men?”

Dean Baker points to this column, where Gregory Mankiw writes: With unemployment at 3.8 percent, its lowest level in many years, the labor market seems healthy. But that number hides a perplexing anomaly: The percentage of men who are neither working nor looking for work has risen substantially over the past several decades. . . […]

The post “When Both Men and Women Drop Out of the Labor Force, Why Do Economists Only Ask About Men?” appeared first on Statistical Modeling, Causal Inference, and Social Science.

“When Both Men and Women Drop Out of the Labor Force, Why Do Economists Only Ask About Men?”

Dean Baker points to this column, where Gregory Mankiw writes: With unemployment at 3.8 percent, its lowest level in many years, the labor market seems healthy. But that number hides a perplexing anomaly: The percentage of men who are neither working nor looking for work has risen substantially over the past several decades. . . […]

The post “When Both Men and Women Drop Out of the Labor Force, Why Do Economists Only Ask About Men?” appeared first on Statistical Modeling, Causal Inference, and Social Science.

Oh, I hate it when work is criticized (or, in this case, fails in attempted replications) and then the original researchers don’t even consider the possibility that maybe in their original work they were inadvertently just finding patterns in noise.

I have a sad story for you today. Jason Collins tells it: In The (Honest) Truth About Dishonesty, Dan Ariely describes an experiment to determine how much people cheat . . . The question then becomes how to reduce cheating. Ariely describes one idea: We took a group of 450 participants and split them into […]

The post Oh, I hate it when work is criticized (or, in this case, fails in attempted replications) and then the original researchers don’t even consider the possibility that maybe in their original work they were inadvertently just finding patterns in noise. appeared first on Statistical Modeling, Causal Inference, and Social Science.

Oh, I hate it when work is criticized (or, in this case, fails in attempted replications) and then the original researchers don’t even consider the possibility that maybe in their original work they were inadvertently just finding patterns in noise.

I have a sad story for you today. Jason Collins tells it: In The (Honest) Truth About Dishonesty, Dan Ariely describes an experiment to determine how much people cheat . . . The question then becomes how to reduce cheating. Ariely describes one idea: We took a group of 450 participants and split them into […]

The post Oh, I hate it when work is criticized (or, in this case, fails in attempted replications) and then the original researchers don’t even consider the possibility that maybe in their original work they were inadvertently just finding patterns in noise. appeared first on Statistical Modeling, Causal Inference, and Social Science.

“Economic predictions with big data” using partial pooling

Tom Daula points us to this post, “Economic Predictions with Big Data: The Illusion of Sparsity,” by Domenico Giannone, Michele Lenza, and Giorgio Primiceri, and writes: The paper wants to distinguish between variable selection (sparse models) and shrinkage/regularization (dense models) for forecasting with Big Data. “We then conduct Bayesian inference on these two crucial parameters—model […]

The post “Economic predictions with big data” using partial pooling appeared first on Statistical Modeling, Causal Inference, and Social Science.

“She also observed that results from smaller studies conducted by NGOs – often pilot studies – would often look promising. But when governments tried to implement scaled-up versions of those programs, their performance would drop considerably.”

Robert Wiblin writes: If we have a study on the impact of a social program in a particular place and time, how confident can we be that we’ll get a similar result if we study the same program again somewhere else? Dr Eva Vivalt . . . compiled a huge database of impact evaluations in […]

The post “She also observed that results from smaller studies conducted by NGOs – often pilot studies – would often look promising. But when governments tried to implement scaled-up versions of those programs, their performance would drop considerably.” appeared first on Statistical Modeling, Causal Inference, and Social Science.