Statistical Analysis Stack Exchange
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Questions tagged [seemingly-unrelated-regressions]

SUR stands for "Seemingly Unrelated Regressions", an econometric technique for fitting several models (w/ different response variables) simultaneously. SUR may be more efficient than fitting the models separately.

SUR stands for "Seemingly Unrelated Regressions". SUR is an econometric technique for fitting several regression models (with different response variables and possibly different covariates) simultaneously using generalized least squares. The motivating idea is that the errors from each of the component regressions are correlated. SUR may be more efficient than fitting the models separately.

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Difference between SUR and Simultaneous Equation Model

Seemingly Unrelated Regression (SUR), and Simultaneous Equation Model (SEM) sound very similar to me. What is the difference between them?
Hellen
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Is the effectiveness of seemingly unrelated regression an example of Stein's paradox?

The existence of Stein's Example prima facie appears similar to seemingly unrelated regression (SUR) insofar as simultaneously estimating multiple parameters seems more effective than training them separately. In the Wikipedia articles linked above…
DifferentialPleiometry
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SUR estimation and Heckman selection model with panel data on Stata?

I'm working with unbalanced panel data using time and firms as IDs and would like to find out how to test for correlation between two panel equations that may be seemingly unrelated. The second question is about any package that allows the use of a…
user45968
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Computing BIC for SUR model

Consider the following m regression equation system: $$r^i = X^i \beta^i + \epsilon^i \;\;\; \text{for} \;i=1,2,3,..,T$$ where $r^i$ is a $(T\times 1)$ vector of the T observations of the dependent variable, $X^i$ is a $(T\times k)$ matrix of…
Mayou
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Testing if coefficients are statistically significantly different across models

I will be building two zero-inflated negative binomial (ZINB) regression models, where each model is aiming to predict different disease count outcomes based on the exact same independent variables and data. For example: $$Y_A =\beta_1^A X_1 +…
geoscience123
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The bias of Zellner estimators in dynamic SUR models

I have been playing around with a seemingly unrelated regression (SUR) estimation. However, for dynamic SUR models it is known that -- analogous to the ARIMA case -- an OLS/GLS estimate is biased. For example this article provides a correction. So…
Seb
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SUR and interaction terms

Suppose I want to determine if a simultaneous model (A) was identified: $y_1 = \beta_{10} + \beta_{11} x_1 + \beta_{12} y_2 + \epsilon_1$ $y_2 = \beta_{20} + \beta_{21} y_1 + \beta_{22} x_2 + \epsilon_2$ Where the y's are endogenous and the x's are…
RegressForward
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SEM One regressor depends on another regressor

I have the following structural model, by which one of the regressors is partially explained by another. $$ y_1= x_1+x_2+x_3+e \tag{1} $$ $$ x_1= x_2 + u \tag{2} $$ The questions are: a) Can I run equation (1) alone without getting the…
Luis
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SUR with unbalanced panel and cross equation restrictions - available software?

I would like to estimate a SUR model with an unbalanced panel and with cross equation restrictions. This does not seem possible with the standard SUR commands in Stata or R. Do you have an idea which program and or package I could use? Thx
clog14
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Books on Bayesian seemingly unrelated regression

I want to study seemingly unrelated regression using Gibbs sampling for many equations. Can someone suggest some books on Bayesian approach for seemingly unrelated regression (SUR) with R examples. I am a beginner in Bayesian statistics and learn…
Mumbo.Jumbo
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Goodness of fit of a SUR model

I know that McElroy R^2 is a measure of goodness of fit for Seemingly Unrelated Regressions (SUR models), but how can one judge that the estimated equations are well fit by using the McElroy R^2?
PaulS
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Forbidden Regression Problem?

I am quite confused about the forbidden regression problem, and unsure if I have one in this case. Stage 1: Probit Model: Prob(Distress) = Set of regressors that predict vulnerability. The predicted value "Predicted Vulnerability" is a variable of…
Kevin Smith
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What is the difference between SUR and OLS?

How is the output different in the SUR (Seemingly Unrelated Regressions) equation from the OLS? Is it still the same as Bo + B1x = y?
Hazel
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What is the difference between seemingly unrelated regression (SUR) and correcting a set of OLS results for multiple comparisons?

As I understand it, the the seemingly unrelated regressions (SUR) or seemingly unrelated regression equations (SURE) models estimate a set of Ordinary Least Squares (OLS) equations where the error terms may be correlated across equations. Correcting…
M. King
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How to compare coefficients of multivariate multiple regression models, possibly using SUR

I am trying to compare the model parameters among three multivariate multiple regressions. All three models incorporate date from the same 97 individuals and share the same 4 independent variables (age, sex, age*sex, number of missing teeth), but…
J. Joganic
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