Linked Questions

34
votes
4answers
2k views

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 ...
8
votes
2answers
23k views

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 ...
10
votes
3answers
863 views

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 ...
19
votes
2answers
442 views

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 ...
7
votes
2answers
381 views

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 ...
2
votes
2answers
757 views

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 ...
0
votes
1answer
586 views

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 ...
2
votes
3answers
228 views

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 ...
1
vote
3answers
270 views

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 ...
3
votes
0answers
344 views

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 ...
2
votes
1answer
155 views

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 ...
3
votes
2answers
115 views

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 ...
2
votes
2answers
99 views

Neural Network vs regression in prediction

I collected a sample of 600 observation (time series data) with 100 predictors variables in order to predict another one. I want to use some prediction models but I know that, unfortunately, ...
1
vote
1answer
73 views

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'...
1
vote
0answers
144 views

Machine Learning with few observations

Is common to say that Machine Learning techniques represent are purely data driven methods, and them are effective only if we have a large amount of data. I focused here on supervised/predictive ...

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