Tuesday, October 30, 2012

Wind Visual

An amazing visualization of the wind. The screen capture below is from the morning after hurrican Sandy made land.

Sunday, October 21, 2012

Ugly Graphs

This website is painful. It burns my eyes. It contains a plethora of hideous graphs, nearly all 3-d. Its hard to pick the worst, but the one below has to be a front runner.

Learning R

I'm in the process of learning R. This post nails my reaction to finally learning a real programming language.

Stata seems to have been designed to make sense to social scientists and if this makes it confusing to programmers, then so be it. A simple example of this is that Stata uses the word “variable” in the sense meant by social scientists. More broadly, Stata is pretty bold about defaults so as to make things easy for beginners. It presumes that anything you’re doing applies to the dataset (aka the master data) – which is always a flat-file database. Other things that might be held in memory have a secondary status and beginning users don’t even know that they’re there. Likewise, commands distinguish between the important arguments (usually variables) and the secondary arguments, which Stata calls “options”. There’s also the very sensible assumptions about what to report and what to put in ephemeral data objects that can be accessed immediately after the primary command (but need not be stored as part of the original command, as they would in most other languages).
Note, I’m not complaining about any of this. Very few of Stata’s quirks are pointlessly arbitrary. (The only arbitrary deviation I can think of is using “*” instead of “#” for commenting). Most of Stata’s quirks are necessary in order to make it so user-friendly to social scientists. In a lot of ways R is a more conventional language than Stata, but most social scientists find Stata much easier to learn. In part because Stata is willing to deviate from the conventions of general purpose programming languages, running and interpreting a regression in Stata looks like this “reg y x” instead of this “summary(lm(y~x))” and loading a dataset looks like this “use mydata, clear” instead of this “data <- read.table(mydata.txt)”. Stata has some pretty complicated syntax (e.g., the entire Mata language) but you can get a lot done with just a handful of simple commands like “use,” “gen,” and “reg”.

Wednesday, October 17, 2012

ECO 712: Week 7 Readings

This week readings from Paige:

Olive Oil Prices: Drizzle and drought.

Here is another that will be useful to think about after the lecture: IS-LMentary.

Friday, October 05, 2012

Stimulus


Here is an excellent compendium of the recent recent on the effects of stimulus spending.

In this post, I’ve pulled together my summaries of the original nine papers, and added sections on the six new additions to the literature. The critical issue in these studies concerns the “fiscal multiplier” — that is, how much bang the government gets for its stimulus buck. For example, if each dollar spent on a particular kind of tax cut results in a $1 increase in GDP, the multiplier for that tax cut is 1. Any multiplier that is greater than zero indicates a program is stimulative, but the higher the multiplier, the more effective stimulus spending is.
Here a a reply of sorts. It points out the limitations of the research, by noting the following:

Stimulus Advocates Largely Ignore the Public Choice Problems with Implementing Stimulus.

Stimulus Advocates Often Brush Past Long Run / Short Run Distinctions.

Bias in Polls


Wednesday, October 03, 2012

ECO 712: Week 5 readings

Here are the readings for this week:

Counterfeit goods becoming more dangerous.
From tequila crisis to sunrise.

Note: I will likely let class out early so you can all have your popcorn popped and ready to go for the 8pm Presidential Debate. The debate is scheduled to cover domestic policy. Given we are still at an level of employment below the level of December of 2007, you can bet that Jobs will be something you hear often.Take notes. We will discuss their proposals the following week after the exam.