include monte carlo for R

The Technology of Skill Formation

"Since Edward Leamer's memorable 1983 paper, "Let's Take the Con out of Econometrics," empirical microeconomics has experienced a credibility revolution. While Leamer's suggested remedy, sensitivity analysis, has played a role in this, we argue that the primary engine driving improvement has been a focus on the quality of empirical research designs. The advantages of a good research design are perhaps most easily apparent in research using random assignment. We begin with an overview of Leamer's 1983 critique and his proposed remedies. We then turn to the key factors we see contributing to improved empirical work, including the availability of more and better data, along with advances in theoretical econometric understanding, but especially the fact that research design has moved front and center in much of empirical micro. We offer a brief digression into macroeconomics and industrial organization, where progress -- by our lights -- is less dramatic, although there is work in both fields that we find encouraging. Finally, we discuss the view that the design pendulum has swung too far. Critics of design-driven studies argue that in pursuit of clean and credible research designs, researchers seek good answers instead of good questions. We briefly respond to this concern, which worries us little."

IV / natural experiment proponents revisiting Leamer's critique.

This review is a primer for those who wish to familiarize themselves with nonparametric econometrics. Though the underlying theory for many of these methods can be daunting for some practitioners, this article will demonstrate how a range of nonparametric methods can in fact be deployed in a fairly straightforward manner. Rather than aiming for encyclopedic coverage of the field, we shall restrict attention to a set of touchstone topics while making liberal use of examples for illustrative purposes. We will emphasize settings in which the user may wish to model a dataset comprised of continuous, discrete, or categorical data (nominal or ordinal), or any combination thereof. We shall also consider recent developments in which some of the variables involved may in fact be irrelevant, which alters the behavior of the estimators and optimal bandwidths in a manner that deviates substantially from conventional approaches.

"Financial econometrics has become an increasingly popular research field. In this paper we review a few parametric and nonparametric models and methods used in this area. After introducing several widely used continuous-time and discrete-time models, we study in detail dependence structures of discrete samples, including Markovian property, hidden Markovian structure, contaminated observations, and random samples. We then discuss several popular parametric and nonparametric estimation methods. To avoid model mis-specification, model validation plays a key role in financial modeling. We discuss several model validation techniques, including pseudo-likelihood ratio test, nonparametric curve regression based test, residuals based test, generalized likelihood ratio test, simultaneous confidence band construction, and density based test. Finally, we briefly touch on tools for studying large sample properties."

The government of North Korea regards economic statistics as state secrets, which makes the country's economy difficult to study. I do careful survey research on the North Korean economy by surveying defectors, Chinese enterprises, and South Korean firms. Still, North Korea is so opaque that when I am asked where I get my data, I normally reply, "I make it up." And I'm only half-joking. Others seem less than half-serious. Last month, the South Korean news agency Yonhap ran a story about a report from a major South Korean think tank stating that North Korea's GDP grew 4.7 percent in 2011. That think tank, the Hyundai Research Institute, used a combination of United Nations infant mortality data for 198 countries over the 2000-2008 period and North Korean crop data to estimate annual North Korean per capita income. While infant mortality and food availability correlate with income, one cannot meaningfully estimate year-to-year income changes with these two pieces of information alone ...

But even such an apparently simple exercise is fraught. Every year some country around the world reports an amazing spike in trade or investment with North Korea, consisting mostly of North Korean cell phones and automobiles. Has Apple opened an iPhone factory in Pyongyang? No, someone in the bowels of some national statistical agency has confused North and South Korea. Both Mexico and Austria have done so in the past; Denmark confused the two in its 2009 outward investment data. The disparity in the magnitudes of North and South Korean trade volumes is so vast, with North Korea trading very little and South Korea trading very much, that a single such instance of misidentification can completely distort North Korea's trade statistics. Our best-guess estimate for North Korea's total trade in 2010 is about $7 billion. Mexican trade with South Korea is $15 billion. So if a major trading country confuses the two Koreas, the misreporting can swamp reality.

Read it online: http://www.mediamused.blogspot.com/2012/02/econometricians-are-modern-day.html?m=1

What to do when "experiments" can not be controlled (not much, but indoctrination helps) - predates current IV methodology?