Martin Econometrics: Econometría y Aplicaciones

INTRODUCTION.-  "Economists are far from unanimous about the definition of their subject. Here are some definitions of economics from contemporary principles of economics textbooks: "Economics is the study of economies, at both the level of individuals and of society as a whole "(Krugman and Wells, 2004, p. 2). "Economics is the study of how human beings coordinate their wants and desires, given the decision-making mechanisms, social customs, and political realities of the society" (Colander, 2006a, p. 4). "Economics is the study of how society manages its scarce resources" (Mankiw, 2001, p. 4). "[Economics is the] social science that studies the choices that individuals, businesses, governments, and entire societies make as they cope with scarcity" (Bade and Parkin, 2002, p. 5). "[E]conomics is the study of human behavior, with a particular focus on human decision making" (Gwartney, Stroup, Sobel, and MacPherson 2006, p. 5). Thus,

"What to do if your p-value is just over the arbitrary threshold for ‘significance’ of p=0.05? You don’t need to play the significance testing game – there are better methods, like quoting the effect size with a confidence interval – but if you do, the rules are simple: the result is either significant or it is not. (...)" ( Read More ) COMMENTS: A very funny post that show the many ways researchs tries to "rescue" their results, even when they are over the famous threshold (p > 0.05).

ABSTRACT: "A common heuristic for evaluating the problem of omitted variable bias in economics is to look at coefficient movements after inclusion of controls. The theory under which this is informative is one in which the selection on observables is proportional to selection on unobservables, an idea which is formalized in Altonji, Elder and Taber (2005). However, this connection is rarely made explicit and the underlying assumption is rarely tested. In this paper I first show how, under proportional selection, coefficient movements, along with movements in R-squared values, can be used to calculate a measure of omitted variable bias. I then undertake two validation exercises. First, I relate maternal behavior on child birth weight and IQ. Simple controlled regressions give misleading estimates; estimates adjusted with a proportional selection adjustment fit significantly better. Second, I match observational and randomized trial data for 29 relationships in public health. I sho