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Questions tagged [endogeneity]

Endogeneity refers to a situation where an explanatory variable in a model is correlated with the error term. Endogeneity induces biased parameter estimates. This is an important problem when working with observational data and the goal is causal inference.

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Dealing with Endogeneity in a Logit Regression when the Endogenous Regressors are Discrete

I would like to estimate a logit model in the presence of endogeneity. The dependent variable is binary (actually, it is non-binary with multiple ordinal categories, but from what I've read dealing ...
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Instrumental variable

I am exploring the impact of social media WOM on firm performance during the 8 quarters of 2014-2015 for several firms. As WOM is likely endogenous, I was thinking of using weather data as instrument. ...
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Endogeneity and Consistency

So I learned about the endogeneity problem of linear regression in class today, where E[XU] and Cov[X,U] isn't equal to zero but some random constant c times a standard basis k-element vector with 1 ...
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Including future values in a regression

If I have a variable that depends on its expected value in the future among other things (for example inflation), would it be possible to regress it on future values of the dependent variables (in a ...
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Dealing with endogeniety in an entire regression

I am using OLS to test the statistical significance of a state-wide(US states) sentiment variable that was calculated based on Twitter data. I use macro-variables(gdp, unemployment etc.) as controls. ...
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Endogenous subgroups in impact estimation

I am using RCT data to estimate the impact of a program. After doing the straightforward analysis, I decided to estimate the program impact by subgroups (treatment status*subgroup). The subgroups were ...
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Does the Heckman correction with an exclusion restriction provide causal inference?

I think I might be getting instrumental variables estimation and the Heckman correction with an exclusion restriction confused. I know that instrumental variables estimation is way to show causal ...
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Instrumental variables and GARCH

Can you use the predicted value from the first stage (as estimated using 2SLS) to replace the endogenous variable in a GARCH model? Or, what would be a different way of using instrumental variables in ...
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Is the IV approach applicable to endogenous count variable in a linear regression?

In a linear regression setting, one of the regressors (independent variables) is endogeneous. However, strictly speaking it is not continouus, but a count variable. A continouus instrumental variable ...
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Plummeting r-squared when instrumenting interaction term consisting of an endogenous variable

I've read the discussions about how to treat endogenous interaction terms when using an instrumental variable approach (2SLS) and followed the idea of Andy. However, in my case there is just one ...
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Instrumental variables - alternatives to 2SLS: not using exogenous variables in the first stage

I think that everyone knows how 2SLS works. say that we have: $y_t=a_1 +a_2X_t+a_3W^1_t+a_4W^2_t+e_t$ Let's call this equation equation (1), where $X_t$ is an endogenous ...
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Instrumental Variables for Foreign Direct Investment

I'm trying to estimate a fixed-effect regression model. Basically my Y is tertiary education enrollment (I'm trying to see the effect of FDI investment in host country, to the extent that whether ...
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How can I test for endogeneity after having used Panels Corrected Standard errors (PCSEs)?

How can I test for endogeneity after having used Panels Corrected Standard errors (PCSEs)? By endogeneity I mean the situation in which an explanatory variable is correlated with the error term. In ...
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A very basic question on ENDOGENEITY

In the regression model $Y$ = $\beta_0$ + $\beta_1X_1$ + $\beta_2X_2$ +.......+ $\beta_kX_k$ + $\epsilon$ where $\epsilon$ = $\delta_0X_2$ + $\lambda$ Will this also be the case of endogeneity ...
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Random vs Fixed variables in Linear Regression Model

Reading "Econometrics" by Fumio Hayashi, from Princenton University Press, ISBN 0-691-01018-5, in page 13 by "Fixed Regressors" subtitle, it is stated: "We have presented the classical linear ...
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auto-correlation and OLS regression

I was trying to find the OLS estimator for the model: $Y$ = $\beta_0$ + $\beta_1X_{1t}$ + $\beta_2X_{2t}$ +.......+ $\beta_5X_{5t}$ + $e$ t = 1,2,3 ......, 50 time ordered observations X is a full ...
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ARMAX for Bitcoin prediction via sentiment

I am looking for correlation between social sentiment of BTC and the financial value of BTC. My approach is to use a time-series model to predict the bitcoin value at t+1 based on multiple input ...
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Higher moments / internal IV regression

I have a set of data and am trying to look at the relative importance of two different variables in predicting an outcome: $Y \sim X_1 + X_2 + \epsilon$ but the variable $X_1$ is endogenous and ...
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Endogeneity versus multicolinearity in regressions?

(I limit myself to two explanatory variables to keep it simple) So as I understand it, when an explanatory variable is highly correlated with another variable then it becomes difficult to distinguish ...
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Exogeneity Assumption within or across observations

Suppose we have a linear regression model: $$ y_{i}=x_{i}\beta+\epsilon_{i} $$ Where $i$ is an index for individuals $i=1...N.$ Now, the requirement for unbiased estimation of $\beta$ via OLS ...
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Instrument only relevant for endogenous subsample

I have a panel of person-year observations and I run the following regression reg y x where y is some measure of a person's performance in a certain project in a ...
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2SLS Multiple versus Single Instrumental Variable

To address endogeneity, I was wondering whether it may be easier to find many instrumental variables that predict a single instrumental variable, rather than finding a single instrumental variable. ...
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Can I Scale my dependent variable by one of the independent ones and still use the independent one as a feature?

I would like to predict $y_i$ (my variable at time step $i$) but find some merit in instead taking $y_i$ as percentage difference of a feature at that same step e.g $b_i$. So that I instead use $(y_i-...
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Quandt (1958) Endogenous vs Exogenous Breakpoint

I would like to explain why an endogenous breakpoint is a problem when testing for a difference in the mean between two subperiods in a time-series. Here are my questions. The breakpoint cannot ever ...
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How to motivate a POLS?

How would you justify the usage of Pooled OLS regression instead of Fixed effects? If I am calculating just correlation between two phenomena, may I get rid of these fixed effects? May I choose to ...
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2SLS - With the same X's and Z's but 3 different Y's, Over-identification and Hausman tests give different results

Dear Stack Exchange users, Let's say that my independent variable of interest is expected to be endogenous and that I want to investigate its effect on 3 separate outcomes. I run separate 2SLS's (one ...
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Is it ok to include endogenous explanatory variables in control function approach?

I am using control function approach (Woolridge 2010, 128-29) with the goal of correctly estimating the effect of my endogenous explanatory variable y2 on the outcome variable y1. Because y1 is a ...
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2SLS: Residual in first stage to handle a unique endogeity problem?

I am interested in the following model: $y = f(x)\beta + e$, where $x = x'+x''$, $f()$ is a nonlinear transformation, and $cov(x,e) \neq 0$. Suppose I have an instrument $z$ that satisfies the ...
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How is endogenous and exogenous variables defined in time series?

According to this site, endogenous variables "have values that are determined by other variables in the system (these “other” variables are called exogenous variables)". I thought that it should be ...
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Interpreting the coefficient of the interaction between 2 (binary) endogenous variables

I have the following outcome (second-stage) equation: $$y = \beta_0 + \beta_1w + \beta_2x + \beta_3w x + \cdots$$ $y$, $w$ and $x$ are all binary. Both $w$ and $x$ are endogenous, but I have an ...
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GMM Distance and/or Davidson-Mackinson endogeneity test in R

I'm looking for alternative Durbin-Wu-Hausman test of endogeneity in R for triangulation purposes. I have found GMM distance test in ivreg2 package in Stata (http://fmwww.bc.edu/ec-p/wp667.pdf) but ...
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Interpretation of correlation in endogenous regression model

Suppose you have a linear regression with an endogenous regressor $x$ that can be represented as follows: $x = z'\delta + \epsilon_1$ $y = \beta x + w'\gamma + \epsilon_2$ where $\begin{pmatrix}\...
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Is there a collinearity issue when using: x, dummy indicating extreme negative value of x and their interaction?

I was wondering whether I can build my baseline model using the following variables without incurring in any multicollinearity issue: $X_1$= Net capital flows over GDP (which may be positive and ...
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Endogeneity - Omitted variable bias in OLS

If a have a true model $y = \beta_0 + \beta_1 x_1 + \beta_2 x_2 + \beta_3 x_3 + \epsilon$ but $x_3$ is unobservable. What are the consequences of having a unobservable variable which correlates ...
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Endogenous controls in linear regression - Alternative approach?

I have a cross-section of $x$, $y_1$, and $y_2$. These are individual level data used in labor economics. I have random variation in $x$ and I'm interested in the effect of $x$ on $y_1$. It is well ...
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Testing endogeneity in a Logit vs Probit model

I'm completely new with logit/probit models and I am confused. While I read in some books/papers that endogeneity would be a major issue in a probit model, I cannot find any references regarding logit ...
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When and why should we use Tobit Regression model?

I am trying to find out determinants of corporate cash holdings for a panel dataset of 1696 firms over a period of 21 years. The dependent variable is the ratio of 'Cash and Cash Equivalents' to '...
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Reverse causality

I have 4 time series, $y, x_1, x_2$ and $x_3$, and I'm running the following reduced form VAR: $ \Delta y_{t} = A_1 \,x_{1,\,t-1} + A_2 \,x_{2,\,t-1} + A_3 \,x_{3,\,t-1} + \varepsilon_t$ Is there ...
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IV regression: endogenous variable is sum of exogenous and endogenous

Suppose I construct the variable $U_i = S_i + T_i $, and I want to estimate the equation $$ Y_i = \alpha + \beta U_i + \gamma X_i + \epsilon _i $$ Suppose $X_i$ and $S_i$ are exogenous, but $T_i$ is ...
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Using granger causality test with dummy variable

I have a question whether Granger causality test can be performed if one of the variables is a dummy. I have two variables one continuous variable and then a dummy for an event that is 1 during the ...
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How to interpret an interaction between an endogenous and an exogenous variable

Consider the following model for a regression : $y = \beta_0 + \beta_1 x_1 + \beta_2 x_2+ \beta_3 x_1 x_2 + u$. Suppose $x_1$ is exogenous and $x_2$ is endogenous. Endogeneity precludes me from ...
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Panel data: Does a lagged independent variable as a regressor violates strict exogeneity?

A dynamic panel data model is considered in the sense that it contains (at least) one lagged dependent variable. Including a lagged dependent variable as a regressor violates strict exogeneity, ...
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Proof that predictions are unbiased in in endogenous linear model

Problem Statement Suppose we have a linear model given by $$y = X\beta + \varepsilon,$$ where $\varepsilon\sim N(0, \sigma^2 I)$ and $E[\varepsilon|X]\neq0$ (i.e., explanatory variables are ...
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When is it justifiable to ignore explanatory variable endogeneity in a regression model?

I have three related questions: Is there a way to conduct a back of the envelop calculation that informs the reader on the degree of endogeneity we should have to bias the OLS estimates in a ...
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Econometrics: What are the assumptions of logistic regression for causal inference?

I'm trying to understand what are the assumptions for logistic regression when you intend to interpret the parameter as causal? The assumptions for causal OLS regressions is well-known but I can't ...
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Endogeneity and variable development

Basic endogeneity question here: I'm estimating a standard migration model, with the household ($i$)'s decision to migrate ($m_{iv}$) as a binary dependent variable , using cross-sectional data: $...
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Endogeneity bias - does it spread?

Here's an example: If I estimate a model WAGE = b1 + b2*EDUC + b3*EXPER and we assume that EDUC (years of education) is endogenous while EXPER (years of work exerpience) is exogenous, will my ...
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Endogeneity bias in cross sectional data

My supervisor asked to use 2SLS in thesis titled : Does Women's Autonomy affect child health survival" I used stata and found women's autonomy as endogenous variable, while women's education was ...
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Difference-in-Differences without an exogenous shock?

First time post! In any case, I'm struggling to solve the endogeneity problem in one of my studies. I have found a series of top papers (in accounting, finance, and economics) that utilize a rather ...
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Endogenity in logistic regression

Consider a logistic regression model built to assess female work participation with household income included as an explanatory variable. Would household income be an endogenous variable in this ...