Questions tagged [endogeneity]

Question 1

Given the model: $y = a + bx + u$, and that $x$ is endogenous, This implies that $E(u|x)\neq 0$. I believe this implies that there are no values for $a$ and $b$ that exist that can make $E(u|x)=0$? So ...

Question 2

We are given the following regression specification and terms, which I believe are fairly standard. The regression model is written as shown below. \begin{align} \boldsymbol{y} & =\boldsymbol{X\...

Question 3

I'm working with dyadic panel data and estimating a Poisson Pseudo Maximum Likelihood (PPML) gravity model. Two variables I suspect to be endogenous (let's call them var1 and var2) are initially ...

Question 4

I’m investigating the question: How does childbearing (specifically, transitioning from two to three children) affect mothers’ and fathers’ labor supply, particularly in rural versus urban settings? ...

Question 5

I’m investigating the question: How does childbearing (specifically, transitioning from two to three children) affect mothers’ and fathers’ labor supply, particularly in rural versus urban settings? ...

Question 6

I was confused by the usual definition of endogeneity, in which it is described as regressors being correlated with residuals. I could not come up with code that generates data with such a feature. I ...

Question 7

I'm reading Challenges and Opportunities in Media Mix Modeling, and the author raises the following point regarding funnel-effect selection bias: A broader problem is that many important variables ...

Question 8

I have a multivariate dataset consisting of household level variables such as education, location of the household, occupation, income, consumption etc. The regressand variable is number of social ...

Question 9

I am currently fitting a model where the sales of a company (Y) are explained by the company's investment in advertising (X), plus many other marketing variables. The estimated B for the the ...

Question 10

Suppose a linear model estimated by OLS. Suppose X1 is the study variable and is strictly exogenous. Now, suppose control variables X2 and X3 are added. Suppose X2 and X3 are correlated with the error ...

Question 11

I am running an experiment using a lottery setup where participants are presented with information about risk and reward. The design includes two factors: Condition: In one condition (free sequence), ...

Question 12

As is in the title, I'm doing a research project that investigate the relationship between X (the dependent variable) and Y (the independent variable). Both of them are continuous variables and Y is ...

Question 13

So if I want to estimate the effect of x on y, however, I also know that y has an effect on x (in other words, reverse causality is present). I have a panel data for both variables, and I know there ...

Question 14

How can there be Ommited Variable Bias (OVB) in OLS? Can't all regressions be computed without endogeneity? For introduction, this is Greene (Econometric Analysis, 8th edition)'s entry on OVB: ...

Question 15

Here is my set up (longitudinal mixed effects): Time periods: $t = 1,...,T$ Clusters: $j = 1,...,J$ Variables: $z_{jt}$, $x_{jt}$, $y_{jt}$ Initially, I wanted to make the following model (current ...

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Questions tagged [endogeneity]

Does endogeneity in a linear model imply a non-linear conditional mean?

Statistical Test for Endogeneity Condition: Statistical Test for Correlation of Error Term with Independent Variables

How to handle potential endogeneity in a ppml gravity using orthogonal residuals and lagged instruments?

Rural and Urban subgroup analysis and potential endogeneity

Does statistical significance at 10% undermine the credibility of an IV estimate?

Is endogeneity only a problem for explanation, and not a problem for forecasting?

Does including variables like price in a media mix model always lead to bias if they're partially influenced by upstream ad decisions? [closed]

How to model Endogeneity in a Zero-Inflated process

Biased beta in regression model - Multicollinearity or Endogeneity?

Endogenous Control Variables

Is it valid to analyze a design where one condition involves endogenous and another exogenous assignment?

Condition the effect of X on Y on the indicator of Y

Is this a correct understanding of why the Anderson-Hsaio estimator removes bias introduced by reverse causality in a estimator of an causal effect

How can there be omitted variable bias in OLS? Shouldn't OLS always eliminate endogeneity?

A model to deal with endogeneity and simultaneity in panel data

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