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Questions tagged [regression]

In statistics, regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables (or 'predictors').

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8
votes
1answer
313 views

Alternative way of deriving OLS coefficients

In another question of mine, an answerer used the following derivation of OLS coefficient: We have a model: $$ Y = X_1 \beta + X_2 \beta_2 + Z \gamma + \varepsilon, $$ where $Z$ is unobserved. Then ...
3
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3answers
172 views

Can I use calculated data for regression

Can I use calculated data for regression analysis. case 1: first run OLS $y = \alpha+\beta x$, and get $\hat\beta$, then calculate $z = h^\hat\beta$, at last run $m = \gamma + \mu z$. case 2: follow ...
13
votes
5answers
10k views

What happens if the “control variables” are also endogenous?

I work in Political Economy, and a lot of the models include "innocent" control variables such as population, inequality, colonial legacy, etc. so that the author can claim unbiasedness on their ...
0
votes
1answer
228 views

Equilibrium Price - OLS Regression

I have asked another question related to price elasticity, which pretty much left me with this problem: I want to analyze the factors influencing the price of a product. The underlying assumption is ...
3
votes
1answer
420 views

Does it make sense to 'deflate' a sectoral price index in a regression analysis?

For instance, if one is running a regression with deflated prices for a given year and one of the independent variables is a price index for a given sector, does it make any sense to 'deflate' this ...
2
votes
2answers
77 views

Specification bias - estimated variance is biased estimator of true variance of error term

Consider the two models $ (a) y = X\beta + u $ where $X$ is $n \times K$ and (b) $y = Z\gamma + \omega $ where $Z$ is $n \times r$. Under classical assumptions (and $Z$ and $X$ are non-stochastic) if ...