Stay in Touch
Not sure what course to take?
Speak with an expert curriculum consultant at 800-333-7660 or send an e-mail.Submit Your Course Requests
Want this course at another location or on a different date? Let us know your course needs.On-site Pricing
Course fee and EPTO/APTO units differ for on-site training.Introduction to Applied Econometrics
Business Knowledge Series course
|
Duration: 3.0 days Course fee: $2,175 EPTO units: 4.2 CEUs: 1.8 | ||
 |
Presented by Oral Capps, Ph.D., a full professor and holder of the Southwest Dairy Marketing Endowed Chair in the Department of Agricultural Economics at Texas A&M University as well as founder and managing partner of Forecasting and Business Analytics, LLC
This course, the first in a series of three, focuses on single-equation econometric models that enable analysts to better understand their economic/business landscape. Participants gain knowledge of the practical elements of applied econometric analysis.
Learn how to
- develop and use single-equation econometric models
- improve your ability to make sound forecasts
- sharpen your quantative, statistical, and analytical skills.
Who should attend
Academicians, forecasters, and government and business analysts
Expand All
Collapse All
Print version
Course Contents
The Nature of Applied Econometrics
- what is applied econometrics?
- course of action - development of formal quantitative models
- the nature of econometrics
- components of applied econometrics
- products of applied econometrics
- data and disciplines in applied econometrics
- the model specification phase
- generic multiple regression model
- software considerations
- importance of communication and aims for the analyst
- mathematical considerations
- statistical considerations
- the simple linear regression model
- the multiple regression model - the generic single equation econometric model
- multiple regression model - another illustration
- goodness-of-fit statistics and model selection criteria
- estimates of error variance and variances/covariances of OLS parameter estimates
- key points of econometric models
- forecasting with single-equation econometric models
- introduction: preliminary statistical elements
- basics of hypothesis testing
- tests of normality of residuals
- tests of hypotheses regarding structural parameters of econometric models
- nonlinear combinations of coefficients (x2-tests)
- intercept shifters
- slope shifters
- intercept shifters and slope shifters
- final thoughts about the use of indicator or dummy variables
- autocorrelation or serial correlation
- tests for serial correlation
- a test for serial correlation in the presence of a lagged dependent variable
- summary remarks about the issue of serial correlation
- weighted least squares (WLS)
- example of econometric analysis with heteroscedasticity
- multiplicative and additive heteroscedasticity
- common tests of heteroscedasticity
- maximum likelihood (ML) as opposed to weighted least squares (WLS)
- recommended procedures to combat heteroscedasticity
- collinearity diagnostics
- solutions to the collinearity problem
- influence diagnostics
- solutions to the problem of influential observations
- robust regression techniques
- diagnostic tests for structural change
- illustration of sequential Chow tests
- illustration of the Farley, Hinrich, and McGuire test
- illustration of recursive coefficients
- illustration of recursive residuals, CUSUM, and CUSUMSQ tests
Software
This course addresses SAS/ETS.
Course Materials
Students receive a hardcopy of the course notes and, in some courses, can choose to take home a copy of the course data.
Share Your Thoughts
Are there additional topics you'd like for this course to address?
Would you like for this course to be offered at another training facility?
Let us know by adding to our Interest List.
This page was created using SAS software.