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Microeconometrics using Stata

By: Contributor(s): Material type: TextTextPublication details: College Station, Tex. : Stata Press, ©2010.Edition: Revised EditionDescription: xlii, 706 pages : illustrationsISBN:
  • 9781597180733
  • 1597180734
Subject(s): DDC classification:
  • 338.5015195 CAM
Contents:
1. Stata basics -- 2. Data management and graphics -- 3. Linear regression basics -- 4. Simulation -- 5. GLS regression -- 6. Linear instrumental-variables regression -- 7. Quantile regression -- 8. Linear panel-data models: basics -- 9. Linear panel-data models: extensions -- 10. Nonlinear regression methods -- 11. Nonlinear optimization methods -- 12. Testing methods -- 13. Bootstrap methods -- 14. Binary outcome models -- 15. Multinomial models -- 16. Tobit and selection models -- 17. Count-data models -- 18. Nonlinear panel models -- A. Programming in Stata -- B. Mata.
Summary: This text presents an introduction to microeconometrics and how to do microeconometric research using Stata. The authors address each topic with an in-depth Stata example and demonstrate how to use Stata's programming features to implement methods for which Stata does not have a specific command.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Lending Books Lending Books Main Library Stacks REF 338.5015195 CAM (Browse shelf(Opens below)) Available 013371
Total holds: 0

Includes index

1. Stata basics --
2. Data management and graphics --
3. Linear regression basics --
4. Simulation --
5. GLS regression --
6. Linear instrumental-variables regression --
7. Quantile regression --
8. Linear panel-data models: basics --
9. Linear panel-data models: extensions --
10. Nonlinear regression methods --
11. Nonlinear optimization methods --
12. Testing methods --
13. Bootstrap methods --
14. Binary outcome models --
15. Multinomial models --
16. Tobit and selection models --
17. Count-data models --
18. Nonlinear panel models --
A. Programming in Stata --
B. Mata.


This text presents an introduction to microeconometrics and how to do microeconometric research using Stata. The authors address each topic with an in-depth Stata example and demonstrate how to use Stata's programming features to implement methods for which Stata does not have a specific command.

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