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Course No: PA0112
This is an advanced course in Econometrics. Topics to be studied include specification, estimation, and inference in the context of models that include then extend beyond the standard linear multiple regression framework.
This course will be useful for all those who want to venture into data analysis using SAS ans is useful for following roles
- Econometric Data Analyst
- Researcher in Econometrics
- Business Analyst
- Manager
Oh Yeah! We have some pre-requisite for this course. These are not mandatory but having them will certainly be a benefit for you.
- Basic Desk top processing
- Basic Applied Statistics
- Basic Data Interpretation
- Introduction to Econometrics
- Econometrics: statistics, economics, mathematics
- Econometric modeling: understanding, prediction, control
- Modeling frameworks: Bayesian and Classical (frequentist) approaches
- Estimation and inference: Nonparametric, semiparametric, parametric
- The Classical Linear Regression Model
- Conditional mean function
- Functional form
- Least squares regression
- Fit of the regression, ANOVA, Adjusted R2
- Least squares estimator in finite samples
- Estimating the Variance of the least squares estimator
- The sampling distribution of the least squares coefficient vector
- Statistical Inference in the linear model
- The Generalized Regression Model
- Nonspherical disturbances: Implications for least squares
- Testing for nonspherical disturbances
- Generalized least squares and weighted least squares
- Two step feasible GLS estimation, familiar applications
- Seemingly Unrelated Regressions, Autocorrelation, Vector Autoregression
Panel Data
- Fixed and Random Effects
- Random Parameters and Latent Class Models
- Treatment Effects and Difference in Differences
- Heterogeneity
- Endogeneity
Nonlinear Regression Models
- Nonlinear regression and nonlinear least squares
- Partial Effects
- Nonlinear Least Squares
Methods of Estimation
- Maximum likelihood estimation
- Covariance matrix estimation
- GARCH models
- Two step estimation
- Generalized method of moments (GMM) estimation
- Bayesian Estimation
Non- and Semiparametrics
Time Series Modeling
Regular
$250
₹ 13,500 - Slides Booklet
- Tools/SW
- Lab Booklet with Code Scripts
- Class Room Demo
- Hands On Training
- Training Videos
- Cloud Lab Access
- Lifetime Support
- Deliverable On Site
- 30 Hours Class
$ 250 ₹ 13,500 DLP
$175
₹ 9,500 - Slides Booklet
- Tools/SW
- Lab Booklet with Code Scripts
- Class Room Demo
- Hands On Training
- Training Videos
- Cloud Lab Access
- Lifetime Support
- Deliverable Via Post
- 3 Months Access
$ 175 ₹ 9,500 Online
$125
₹ 6,700 - Slides Booklet
- Tools/SW
- Lab Booklet with Code Scripts
- Class Room Demo
- Hands On Training
- Training Videos
- Cloud Lab Access
- Lifetime Support
- Deliverable Via Downloads
- 3 Months Access
$ 125 ₹ 6,700 Virtual Class
$200
₹ 10,800 - Slides Booklet
- Tools/SW
- Lab Booklet with Code Scripts
- Class Room Demo
- Hands On Training
- Training Videos
- Cloud Lab Access
- Lifetime Support
- Deliverable Via Downloads
- 30 Hours Virtual Class
$ 200 ₹ 10,800
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