Questions tagged [sur]

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

Filter by
Sorted by
Tagged with
0
votes
0answers
9 views

Why use iterated SUR (ISUR) over regular (one-step) SUR?

Stata, a statistical package, offers the possibility to estimate a system of equations using Zellner’s seemingly unrelated regression (SUR) in either one-step or using an iterated SUR (ISUR) method ...
0
votes
0answers
15 views

Model selection criteria for Seemingly Unrelated Regressions - same as OLS?

If there are two SUR models, each containing two equations, and the only differences between them is the exclusion of a dummy variable in the second set (or say, the intercept term) what measures ...
3
votes
1answer
105 views

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 ...
0
votes
0answers
16 views

SUR and cross equation restrictions in SAS

I am estimating a system of three equations using the option SUR in syslin procedure. Code: ...
0
votes
0answers
96 views

Weighted Seemingly Unrelated Regression in R

I am using the systemfit package in R to estimate a system of three equations using the seemingly unrelated regression approahk ...
0
votes
0answers
38 views

Is there any benefit of using GLS when the regressors are identical

I am reading Greene, Econometric Analysis, 7th Addition, I am seeking a point of clarrification. "The case of identical regressors is quite common [think a VAR mode].... In this special case, ...
1
vote
1answer
740 views

Find (or calculate) log-likelihood value, AIC, and BIC for SUR model (for each equation) with systemfit

I have estimated SUR model with systemfit (R package). With the estimated results, I am trying to get logLik, AIC and BIC for ...
3
votes
1answer
96 views

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 + \...
2
votes
0answers
215 views

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 ...
2
votes
0answers
83 views

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 (...
2
votes
0answers
190 views

Solving SUR with (N-1) Equations

Problem I'm estimating a seemingly unrelated regression (SUR) with identical regressors where my dependent variable, $y_{cit}$, is a share of total across $c$, such that, $\sum_{c=1}^5 y_{cit}$ = 1. ...
3
votes
1answer
61 views

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 ...
1
vote
0answers
124 views

Are multivariate probit models with the same set of explanatory variables for each outcome more efficient that piecewise probit regressions?

I understand that multivariate probit models are analogous to SUR models. In the SUR case, there's no efficiency gain by fitting a SUR model over several independent OLS regressions when the model ...
3
votes
0answers
164 views

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 ...
1
vote
0answers
26 views

testing hypothesis in spatial sure models

I have estimated spatial sur models (lag and error) using the spse program, spseml function. I want to test some restrictions about the coefficients in this model and I have not been able to do it ...
0
votes
0answers
91 views

CAPM Model - SUR Model -

We know that the CAPM regression (for a asset i) is given by $\ z_i = α_i1_T +$ $\beta_iz_m + ε_i = X∗θ_i + ε_i$ How can I show that the estimator of $\hat\alpha$ has the following distribution $\...
1
vote
1answer
324 views

Why are individual fixed effects from a “within” and from a dummy variable panel model different?

I am working on a long panel data set with N=34 and T=132. I need to extract fixed effects from plm (within) model and estimation of the same model but including dummies for individuals (N-1) in OLS. ...
1
vote
0answers
252 views

Multiple impute multilevel data and postestimation tests

I want to do the following three things but am not sure how/whether they can be done: multiple impute multilevel data. I would be ok with just accounting for clusters, but I need to somehow account ...
1
vote
1answer
70 views

Significant effect of control variable on the concerned determinant

I have a regression where I find the effect of x on y while controlling for z: y = x + z Theoretically, Both x and z have an effect on y. z has an effect on x. ...
3
votes
2answers
509 views

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 ...
0
votes
1answer
187 views

A model similar to vector autoregressive (VAR) model with different explanatory variables

VAR models do not allow the flexibility of having different explanatory variables in each equation. Are there any alternative models which allow this flexibility and written in a VAR form?
1
vote
2answers
88 views

Why the inverse of the covariance matrix is equal to the original covariance matrix in Seemingly Unrelated Regression?

In Zellner 1962 p350-351, you may see (2.4) & (2.6), and you can also verify that the Sigma(c)=Sigma(c)^-1. Why the inverse of the covariance matrix is equal to the original covariance matrix in ...
2
votes
0answers
752 views

How to perform a SUR with Panel Data?

To do a sureg in Stata I was thinking of reg healthy x1 x2 ... i.year i.country ...
2
votes
1answer
2k views

Difference between SUTSE (Seemingly Unrelated Time Series Equations) and SUR (Seemingly Unrelated Regressions)

I am studying time-series econometrics and in particular Dynamic Linear Models for multivariate time-series. Someone can help me in understanding which is the difference between SUTSE (Seemingly ...
2
votes
1answer
633 views

Test on SUR model

I have a SUR model with 22 equations, where each equation has the same 7 factors. I want to test if a coefficient (b3 in equation 1) is significantly different from another coefficient in another ...
2
votes
0answers
847 views

Seemingly Unrelated Regression with the same dependent variables

I am analyzing the effect of foreign aid on governance. Foreign aid consists of six categories and I want to know each effect. Governance is measured by one indicator. I made six regression equations ...
4
votes
1answer
3k views

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?
3
votes
1answer
677 views

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 ...
3
votes
1answer
149 views

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 ...