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Monthly Archives: February 2016
21 Reasons Why You Should Never Date an Economist
Even though this list has been around for quite a while (I think inesad.edu.bo posted it first in autumn 2012), I think it just doesn’t get old. On the contrary each time I read through it, I just can’t stop … Continue reading
Posted in General
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Linear Regression in R
R presents various ways to carry out linear regressions. The most natural way is to use the lm() function, the R buildin OLS estimator. In this post I will present you how to use lm() and run OLS on the … Continue reading
Posted in Computing and Others, Econometrics
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Construct the OLS estimator as a function in R
This post shows how to manually construct the OLS estimator in R (see this post for the exact mathematical derivation of the OLS estimator). In contrary to a previous post, this post focuses on setting up the OLS estimator as a … Continue reading
Posted in Computing and Others, Econometrics
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Calculate OLS estimator manually in R
This post shows how to manually construct the OLS estimator in R (see this post for the exact mathematical derivation of the OLS estimator). The code will go through each single step of the calculation and estimate the coefficients, standard errors … Continue reading
Posted in Computing and Others, Econometrics
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CLRM – Assumption 5: Normal Distributed Error Terms in Population
Assumption 5 is often listed as a GaussMarkov assumption and refers to normally distributed error terms in the population. Overall, assumption 5 is not a GaussMarkov assumption in that sense that the OLS estimator will still be the best linear unbiased estimator (BLUE) … Continue reading
Posted in Econometrics
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Violation of CLRM – Assumption 4.1: Consequences when the expected value of the error term is nonzero
Violating assumption 4.1 of the OLS assumptions, i.e. , can affect our estimation in various ways. The exact ways a violation affects our estimates depends on the way we violate . This post looks at different cases and elaborates on … Continue reading
Posted in Econometrics
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CLRM – Assumption 4: Independent and Identically Distributed Error Terms
Assumption 4 of the four assumption required by the GaussMarkov theorem states that the error terms of the population are independent and identically distributed (iid) with an expected value of zero and a constant variance . Formally,
Posted in Econometrics
11 Comments