Questions tagged [omitted-variable-bias]

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Homoskedasticity

Suppose we have the following: $$Y=X_1'\beta_1+X_2'\beta_2+e$$ $$E[e|X_1,X_2]=0$$ $$E[e^2|X_1,X_2]=\sigma^2$$ $$E[X_2|X_1]=\Gamma X_1$$ We will assume $\Gamma\neq0$ and $\beta_1$ is of interest. We ...
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VAR model variable selection

I'm required to use two time series models in my exam project. I want to use a stock price of an energy company, and then explain it first using ARIMA, and then adding other variables and using VAR. ...
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2answers
24 views

Is omitted variable bias possible with a perfectly correlated dependent and independent variable?

Suppose $X$ and $Y$ are perfectly correlated, and we fit a model $Y=a+bX+\epsilon$. Is it possible that there would be omitted variable bias in this situation? Intuitively, I think so, but I'm ...
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1answer
87 views

How to test whether OVB by examining two regressors (X_1, X_2) using hypothesis test with null hypothesis H0: corr(X_1,X_2) = 0

Suppose you have an i.i.d. sample {(π‘Œ , 𝑋 , 𝑋 ): 𝑖 = 1, ... , 𝑛}. You want to estimate the causal effect of 𝑋1 on π‘Œ. You first run a regression π‘Œ = 𝛼0 + 𝛼1𝑋i + 𝑒i and get the following ...
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109 views

Difference Omitted Variable Bias and Confounding?

Is there a difference between omitted variable bias and confounding bias in linear models? To my knowledge, when investigating the causal effect of $X$ on $Y$, a confounder is a variable $Z$ that is ...
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1answer
21 views

Endogeneity coming from omitted variable vs measurement error

Can someone explain more clearly what is a measurement error and how is it different from omitted variable. I know the theoretical implications, but I don't really know how to tell which problem I'm ...
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1answer
285 views

Omitted Variable Bias (OVB) and multicollinearity

In a linear regression model, the reason we control for variables is to prevent the omitted variable bias (OVB). That is, suppose we are trying to fit the model $$ Y = \beta_{0} + \beta_{1}X_{1} + \...
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Variable significance very sensitive to specification of non-correlated second variable

IΒ΄m doing research on a political science topic and my models leave me behind with a big questionmark at this point. I have a dataset containing 79 observations on a number of variables and trying and ...
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Question about regression and deriving omitted variables

usually when I see derivations of ommited variable bias, I see something of the sort: from y=xb + $\eta$, and looking at the for formula for the slope estimate: $cov(x,y)$$/var(x)$ $cov(x,xb+\eta )$$/...
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Using an IV when there is more than one omitted variable

I am trying to estimate the following model: $$y=B_0 + B_1x_1 + B_2x_2 + B_3x_3 + e$$ However, I have an omitted variable bias because $x_2$ and $x_3$ are not observed. Situation 1 If I have an (...
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2k views

Can a confounding factor hide a possible causal relationship? (as opposed to find a spurious one)

I'm a rookie with statistics, and I'm struggling to understand this: it is well known that a confounding factor can cause a spurious association, leading to rejecting a true null hypothesis (i.e. due ...
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1answer
75 views

Does confounding always imply endogeneity?

I'm a bit confused with the definitions regarding causal inference. My question is whether we can call measured confounding an endogeneity problem?
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Are coefficients that are zero omitted variable bias?

If a regression coefficient is essentially zero, doesn't that imply that there is (massive) omitted variable bias? That is, the change must then exist in the error term. The classic definition of OVB ...
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50 views

omitted variable bias

I have a question about omitted variables and there is a big problem about omitted issues for me. Please can you help me. Suppose that the true model is $π‘Œ_{t} = \beta_{0} + \beta_{1}𝑋_{1,t} + \...
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612 views

Omitted variable bias vs. Multicollinearity

There's seems to be a bit like catch 22: suppose I am doing linear regression, and I have 2 variables that are highly correlated. If I use both in my model, I will suffer from multicollinearity, but ...