Here is the list  of courses I wish to teach next year at Chiang Mai School of Economics, not so sure about the demand there! Undergraduate (B.Econ.) ECON 304: Economics Statistics (with R) ECON 408: Research Design in Economics ECON 417: Managerial Economics ECON 419: Economic Theory and Entrepreneurship ECON 443: Industrial Economics ECON 4... [Read more...]

Visualization is a key to success in regression analysis. This is one of the (many) reasons I am also suspicious when I read an article with a quantitative (econometric) analysis without any graph. Consider for instance the following dataset, obtai... [Read more...]

In econometrics course we always say to our students that "if you fit a linear model with no constant, then you might have trouble. For instance, you might have a negative R-squared". So I tried to find databases on the internet such that, when we ... [Read more...]

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Check them out. Here are thirty homoskedastic ones: __ homo.wiener for (j in 1:30) {  for (i in 2:length(homo.wiener)) {          homo.wiener[i,j] for (j in 1:30) {        plot( homo.wiener[,j],           type = "l", col = rgb(.1,.... [Read more...]

“My interpretation of [Leland Wilkinson’s] grammar [of statistical graphics]: —Data is the most important thing, and the thing that you bring to the table. —Geometric objects … what you actually see on the plot: points, lines, polygons, etc. ... [Read more...]

“My interpretation of [Leland Wilkinson’s] grammar [of statistical graphics]: —Data is the most important thing, and the thing that you bring to the table. —Geometric objects … what you actually see on the plot: points, lines, polygons, etc. ... [Read more...]

Consider a random pair of binary responses, i.e. with taking values 1 or 2. Assume that probability can be function of some covariates . The Gaussian vector latent structure A standard model is based a latent Gaussian structure, i.e. there exi... [Read more...]

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cumsum ( rnorm(50), lend="butt", lwd=12, type="h" ) Cumulative sum of 50 draws from a normal distribution. File this under mysteries of the Central Limit Theorem. [Read more...]

Central Limit Theorem A nice illustration of the Central Limit Theorem by convolution.in R: Heaviside 0,1,0) }HH [Read more...]

Here is how to improve your charts, graphs, maps, and plots: Erase non-data ink. Erase redundant data ink. Maximize the ratio of data to ink. Show data variation, not design variation. The surface area of graphical elements should be directly proportio... [Read more...]

extrapolation and interpolation The most important lesson I learned from this book:  regression is reliable for interpolation, but not for extrapolation.  Even further, your observations really need to cover the whole gamut of causal variables, inter... [Read more...]