17 questions linked to/from Endogeneity in forecasting
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### Are inconsistent estimators ever preferable?

Consistency is obviously a natural and important property of estimators, but are there situations where it may be better to use an inconsistent estimator rather than a consistent one? More ...
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### T-consistency vs. P-consistency

Francis Diebold has a blog post "Causality and T-Consistency vs. Correlation and P-Consistency" where he presents the notion of P-consistency, or presistency: Consider a standard linear regression ...
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### Understanding and interpreting consistency of OLS

Many econometrics textbooks (e.g. Wooldridge, "Econometric analysis...") simply write something similar to: "If the population model is $y = xB + u$ and (1) $\text{Cov}(X,U) = 0$; (2) $X'X$ is full ...
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### Minimizing bias in explanatory modeling, why? (Galit Shmueli's "To Explain or to Predict")

This question references Galit Shmueli's paper "To Explain or to Predict". Specifically, in section 1.5, "Explaining and Prediction are Different", Professor Shmueli writes: In explanatory ...
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### What is the relationship between minimizing prediction error versus parameter estimation error?

With the advent of statistical learning techniques, people are talking a lot about prediction error, while in classical statistics, one is focusing on parameter estimation error. What is the ...
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### Endogeneity testing using correlation test

I am currently testing my linear model using OLS method. The last thing I have to test is endogeneity issue. Is it enough if I test each explanatory variable for correletion with error term? Than ...
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### OLS Assumption-No correlation should be there between error term and independent variable and error term and dependent variable

My question is that does endogeneity exists if there is correlation between dependent variable and error term, but not in between error term and independent variable. So for Ex, we know there should ...
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### What is the actual definition of endogeneity?

I've been learning about endogeneity but after looking around online I've gotten more and more confused about what the definition is. Most pages say that in a model $y=X\beta+\epsilon$ the definition ...
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### endogenous regressor and correlation

In a widely cited paper by Antonakis et al. (2010), they mention: If the relation between x and y is due, in part, to other reasons, then x is endogenous, and the coefficient of x cannot be ...
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### About the meaning of ARMA parameters

I suppose that the main scope of an econometric models should be predictive or causal inference. Following this perspective it was shown that underspecified model can perform better than the correct ...
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### Models with low variance but high bias

If we have a classification/regression problem, when would we generally prefer to use families of models with high bias and low variance like multiple regression (logistic regression for ...
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### Regression: Causation vs Prediction vs Description

In my experience it seems me that the interpretation about regression, its meaning and its scope, are debatable and great confusion exist about those things. It seems me that confusions are not go ...
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### Clarification on the assumptions $E[u|x]=0$ and the $x_i$ being fixed in repeated samples in Wooldridge Introductory Econometrics

The author is writing on the assumption $E[u|x]=0$. The part of the text which is not clear to me is this (the red lines emphasize where the critical portions are located) : In the first piece I don'...
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### In regression analysis, data generate model or model generate data?

I am learning regression analysis and in starting of that I have encountered two statements: S1: model generates data S2: data generates model Given that one is correct, so I picked up S2, thinking ...
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