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008			211107s9999 000 0 eng
020			_cRs.725.00 ; Acc.no.-83077-Rs.799.00 _a9788131524657
020			_cRs.725.00 ; Acc.no.-83077-Rs.799.00 _a8131524655
020			_cRs. 1099.00 _a9789355731074
041			_aeng
082			_a330.015195 _bW913In
100			_aWooldridge, Jeffrey M.
245	1	0	_aIntroductory econometrics _ba modern approach _cJeffrey M. Wooldridge
250			_a5th ed. ,
250			_a7th ed.
260			_aDelhi _bCengage Learning India Pvt. Ltd. _c2013 ; Acc.no.-83077-2016 rep. _cc2020, _c2024
300			_axxvii, 831 p. : illus. ; 25cm.
300			_a826 p.
500			_aGain an understanding of how econometrics can answer today's questions in business, policy evaluation and forecasting with Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 7E. Unlike traditional texts, this book's practical, yet professional, approach demonstrates how econometrics has moved beyond a set of abstract tools to become genuinely useful for answering questions across a variety of disciplines. The author has organized the book's presentation around the type of data being analyzed with a systematic approach that only introduces assumptions as they are needed. This makes the material easier to understand and, ultimately, leads to better econometric practices. Packed with relevant applications, the text incorporates more than 100 data sets in different formats. Updates introduce the latest developments in the field, including the recent advances in the so-called “causal effects” or “treatment effects," to provide a complete understanding of the impact and importance of econometrics today.
505			_a1. The Nature of Econometrics and Economic Data. Part I: REGRESSION ANALYSIS WITH CROSS-SECTIONAL DATA. 2. The Simple Regression Model. 3. Multiple Regression Analysis: Estimation. 4. Multiple Regression Analysis: Inference. 5. Multiple Regression Analysis: OLS Asymptotics. 6. Multiple Regression Analysis: Further Issues. 7. Multiple Regression Analysis with Qualitative Information. 8. Heteroskedasticity. 9. More on Specification and Data Problems. Part II: REGRESSION ANALYSIS WITH TIME SERIES DATA. 10. Basic Regression Analysis with Time Series Data. 11. Further Issues in Using OLS with Time Series Data. 12. Serial Correlation and Heteroskedasticity in Time Series Regressions. Part III: ADVANCED TOPICS. 13. Pooling Cross Sections Across Time: Simple Panel Data Methods. 14. Advanced Panel Data Methods. 15. Instrumental Variables Estimation and Two Stage Least Squares. 16. Simultaneous Equations Models. 17. Limited Dependent Variable Models and Sample Selection Corrections. 18. Advanced Time Series Topics. 19. Carrying Out an Empirical Project. Math Refresher A: Basic Mathematical Tools. Math Refresher B: Fundamentals of Probability. Math Refresher C: Fundamentals of Mathematical Statistics. Math Refresher D: Summary of Matrix Algebra. Math Refresher E: The Linear Regression Model in Matrix Form. Answers to Exploring Further Chapter Exercises. Statistical Tables. References. Glossary. Index.
650			_aEconomics
650			_aEconometrics
650			_aEconometrics—Mathematical models
650			_aStatistical methods—Economics
650			_aRegression analysis
650			_aEconomic forecasting
942			_cBK _2ddc
999			_c19797 _d19797