1  20
Next
Number of results to display per page
 Adkins, Lee C.
 New York : John Wiley & Sons, Inc., c2011.
 Description
 Book — xii, 611 p. : ill. ; 28 cm.
 Summary

the cuttingedge study guide to Hill, Griffiths, and Lim's Principles of Econometrics, incorporates the capabilities of Stata software to practically apply the principles of econometrics. Readers will learn how to apply basic econometric tools and the Stata software to estimation, inference and forecasting in the context of real world economic problems. In order to make concepts more accessible, it also offers lucid descriptions of techniques as well as appropriate applications to today's situations. Along the way, readers will find introductions to simple economic models and questions to enhance critical thinking.
(source: Nielsen Book Data)
 Online
2. Causal inference in econometrics [2016]
 [Cham] : Springer, 2016.
 Description
 Book — 1 online resource (xi, 638 pages) : illustrations (some color).
 Summary

 Part I Fundamental Theory. Part II Applications.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
3. Metric power [2016]
 Beer, David, 1977 author.
 London : Palgrave Macmillan, [2016]
 Description
 Book — xiii, 223 pages ; 22 cm
 Summary

 Chapter 1. Introducing metric power.
 Chapter 2. Measurement.
 Chapter 3. Circulation.
 Chapter 4. Possibility.
 Chapter 5. Conclusion: The intersections and imbrications of metric power.
 Chapter 6. Coda... Metric power and the production of uncertainty.(how does metric power make us feel?).
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
 Angrist, Joshua David, author.
 Princeton, New Jersey : Princeton University Press, [2015]
 Description
 Book — xv, 282 pages : illustrations ; 22cm
 Summary

 List of Figures vii List of Tables ix Introduction xi
 1 Randomized Trials
 1 1.1 In Sickness and in Health (Insurance)
 1 1.2 The Oregon Trail
 24 Masters of 'Metrics: From Daniel to R. A. Fisher
 30 Appendix: Mastering Inference
 33
 2 Regression
 47 2.1 A Tale of Two Colleges
 47 2.2 Make Me a Match, Run Me a Regression
 55 2.3 Ceteris Paribus?
 68 Masters of 'Metrics: Galton and Yule
 79 Appendix: Regression Theory
 82
 3 Instrumental Variables
 98 3.1 The Charter Conundrum
 99 3.2 Abuse Busters
 115 3.3 The Population Bomb
 123 Masters of 'Metrics: The Remarkable Wrights
 139 Appendix: IV Theory
 142
 4 Regression Discontinuity Designs
 147 4.1 Birthdays and Funerals
 148 4.2 The Elite Illusion
 164 Masters of 'Metrics: Donald Campbell
 175
 5 DifferencesinDifferences
 178 5.1 A Mississippi Experiment
 178 5.2 Drink, Drank, ...
 191 Masters of 'Metrics: John Snow
 204 Appendix: Standard Errors for Regression DD
 205
 6 The Wages of Schooling
 209 6.1 Schooling, Experience, and Earnings
 209 6.2 Twins Double the Fun
 217 6.3 Econometricians Are Known by Their ... Instruments
 223 6.4 Rustling Sheepskin in the Lone Star State
 235 Appendix: Bias from Measurement Error
 240 Abbreviations and Acronyms
 245 Empirical Notes
 249 Acknowledgments
 269 Index 271.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
 Angrist, Joshua David, author.
 Princeton ; Oxford : Princeton University Press, [2015]
 Description
 Book — xv, 282 pages : illustrations ; 22 cm
 Summary

 Randomized trials
 Regression
 Instrumental variables
 Regression discontinuity designs
 Differencesindifferences
 The wages of schooling.
(source: Nielsen Book Data)
 Online
Law Library (Crown)
Law Library (Crown)  Status 

Find it Permanent reserve: Ask at circulation desk  
HB139 .A53984 2015  Unknown 
HB139 .A53984 2015  Unknown 
6. Econometric analysis [2012]
 Greene, William H., 1951
 7th ed.  Boston : Prentice Hall, c2012.
 Description
 Book — xxxix, 1188 p. : ill. ; 24 cm.
 Summary

 Part I: The Linear Regression Model
 Chapter 1: Econometrics
 Chapter 2: The Linear Regression Model
 Chapter 3: Least Squares
 Chapter 4: The Least Squares Estimator
 Chapter 5: Hypothesis Tests and Model Selection
 Chapter 6: Functional Form and Structural Change
 Chapter 7: Nonlinear, Semiparametric, and Nonparametric Regression Models
 Chapter 8: Endogeneity and Instrumental Variable Estimation Part II: Generalized Regression Model and Equation Systems
 Chapter 9: The Generalized Regression Model and Heteroscedasticity
 Chapter 10: Systems of Equations
 Chapter 11: Models for Panel Data Part III: Estimation Methodology
 Chapter 12: Estimation Frameworks in Econometrics
 Chapter 13: Minimum Distance Estimation and the Generalized Method of Moments
 Chapter 14: Maximum Likelihood Estimation
 Chapter 15: SimulationBased Estimation and Inference
 Chapter 16: Bayesian Estimation and Inference Part IV: Cross Sections, Panel Data, and Microeconometrics
 Chapter 17: Discrete Choice
 Chapter 18: Discrete Choices and Event Counts
 Chapter 19: Limited Dependent VariablesTruncation, Censoring, and Sample Selection Part V: Time Series and Macroeconometrics
 Chapter 20: Serial Correlation
 Chapter 21: Models with Lagged Variables
 Chapter 22: TimeSeries Models
 Chapter 23: Nonstationary Data Part VI: Appendices Appendix A: Matrix Algebra Appendix B: Probability and Distribution Theory Appendix C: Estimation and Inference Appendix D: LargeSample Distribution Theory Appendix E: Computation and Optimization Appendix F: Data Sets Used in Applications Appendix G: Statistical Tables.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
Green Library
Green Library  Status 

Find it Stacks  
HB139 .G74 2012  Unknown 
Find it Velma Denning Room (Social Science Data and Software)  
HB139 .G74 2012  Inlibrary use 
7. Econometric analysis [2012]
 Greene, William H., 1951
 7th ed.  Boston : Prentice Hall, c2012.
 Description
 Book — xxxix, 1,198 p. : ill. ; 24 cm.
 Summary

 Part I: The Linear Regression Model
 Chapter 1: Econometrics
 Chapter 2: The Linear Regression Model
 Chapter 3: Least Squares
 Chapter 4: The Least Squares Estimator
 Chapter 5: Hypothesis Tests and Model Selection
 Chapter 6: Functional Form and Structural Change
 Chapter 7: Nonlinear, Semiparametric, and Nonparametric Regression Models
 Chapter 8: Endogeneity and Instrumental Variable Estimation Part II: Generalized Regression Model and Equation Systems
 Chapter 9: The Generalized Regression Model and Heteroscedasticity
 Chapter 10: Systems of Equations
 Chapter 11: Models for Panel Data Part III: Estimation Methodology
 Chapter 12: Estimation Frameworks in Econometrics
 Chapter 13: Minimum Distance Estimation and the Generalized Method of Moments
 Chapter 14: Maximum Likelihood Estimation
 Chapter 15: SimulationBased Estimation and Inference
 Chapter 16: Bayesian Estimation and Inference Part IV: Cross Sections, Panel Data, and Microeconometrics
 Chapter 17: Discrete Choice
 Chapter 18: Discrete Choices and Event Counts
 Chapter 19: Limited Dependent VariablesTruncation, Censoring, and Sample Selection Part V: Time Series and Macroeconometrics
 Chapter 20: Serial Correlation
 Chapter 21: Models with Lagged Variables
 Chapter 22: TimeSeries Models
 Chapter 23: Nonstationary Data Part VI: Appendices Appendix A: Matrix Algebra Appendix B: Probability and Distribution Theory Appendix C: Estimation and Inference Appendix D: LargeSample Distribution Theory Appendix E: Computation and Optimization Appendix F: Data Sets Used in Applications Appendix G: Statistical Tables.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
Business Library
Business Library  Status 

Stacks  
HB139 .G74 2012  Unknown 
 Judge, George G.
 Cambridge [U.K.] ; New York : Cambridge University Press, 2012.
 Description
 Book — xvi, 232 p. : ill. ; 23 cm.
 Summary

 Preface
 1. Econometric information recovery Part I. Traditional Parametric and Semiparametric Probability Models: Estimation and Inference:
 2. Formulation and analysis of parametric and semiparametric linear models
 3. Method of moments, GMM, and estimating equations Part II. Formulation and Solution of Stochastic Inverse Problems:
 4. A stochasticempirical likelihood inverse problem: formulation and estimation
 5. A stochasticempirical likelihood inverse problem: inference
 6. KullbackLeibler information and the maximum empirical exponential likelihood Part III. A Family of Minimum Discrepancy Estimators:
 7. The CressieRead family of divergence measures and likelihood functions
 8. CressieReadMELtype estimators in practice: evidence of estimation and inference sampling performance Part IV. Binary Discrete Choice MPDEML Econometric Models:
 9. Family of distribution functions for the binary responsechoice model
 10. Estimation and inference for the binary response model based on the MPD family of distributions Part V. Optimal Convex Divergence:
 11. Choosing the optimal divergence under quadratic loss
 12. Epilogue.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
 Wooldridge, Jeffrey M., 1960
 5th ed.  Mason, Ohio : SouthWestern Cengage Learning, ©2012.
 Description
 Book — xxv, 881 pages : illustrations ; 24 cm
 Summary

 Ch. 1. The nature of econometrics and economic data
 pt. 1. Regression analysis with crosssectional data
 Ch. 2. The simple regression model
 Ch. 3. Mutiple regression analysis: estimation
 Ch. 4. Mutiple regression analysis: inference
 Ch. 5. Mutiple regression analysis: OLS asymptotics
 Ch. 6. Mutiple regression analysis: further issues
 Ch. 7. Mutiple regression analysis with qualitative information: binary (or dummy) variables
 Ch. 8. Hetroskedasticity
 Ch. 9. More on specification and data issues
 pt. 2. Regression analysis with time series data
 Ch. 10. Basic regression analysis with time series data
 Ch. 11. Further issues in using OLS with time series data
 Ch. 12. Serial correlation and heteroskedasticity in time series regressions
 Ch. 13. Pooling cross sections across time: simple panel data methods
 Ch. 14. Advanced panel data methods
 Ch. 15. Instrumental variables estimation and two stage least squares
 Ch. 16. Simulatensous equations models
 Ch. 17. Limited dependent variable models and sample selection corrections
 Ch. 18. Advanced time series topics
 Ch. 19. Carrying out an empirical project
 Appendices.
(source: Nielsen Book Data)
 Online
 Metrolohichni ekonomichni systemy. English
 Bashni͡anyn, H. I. (Hryhoriĭ Ivanovych), 1951
 Lviv : Publishing house of Lviv Commercial Academy, 2012.
 Description
 Book — 1,149 p. : ill., col. port. ; 25 cm.
 Online
SAL3 (offcampus storage)
SAL3 (offcampus storage)  Status 

Stacks  Request 
HB139 .B3813 2012  Available 
11. Econometrics [electronic resource] [2011]
 Baltagi, Badi H. (Badi Hani)
 5th ed.  Berlin ; Heidelberg ; New York : Springer, c2011.
 Description
 Book — xv, 410 p.
 Online

 dx.doi.org SpringerLink
 Google Books (Full view)
12. Introduction to econometrics [2011]
 Stock, James H.
 3rd ed.  Boston : AddisonWesley, c2011.
 Description
 Book — xlii, 785 p. : ill. ; 24 cm.
 Summary

 Economic questions and data
 Review of probability
 Review of statistics
 Linear regression with one regressor
 Regression with a single regressor : hypothesis tests and confidence intervals
 Linear regression with multiple regressors
 Hypothesis tests and confidence intervals in multiple regression
 Nonlinear regression functions
 Assessing studies based on multiple regression
 Regression with panel data
 Regression with a binary dependent variable
 Instrumental variables regression
 Experiments and quasiexperiments
 Introduction to time series regression and forecasting
 Estimation of dynamic causal effects
 Additional topics in time series regression
 The theory of linear regression with one regressor
 The theory of multiple regression.
(source: Nielsen Book Data)
 Online
Law Library (Crown)
Law Library (Crown)  Status 

Find it Permanent reserve: Ask at circulation desk  
HB139 .S765 2011  Unknown 
HB139 .S765 2011  Unknown 
HB139 .S765 2011  Unknown 
13. Introduction to econometrics [2011]
 Stock, James H.
 3rd ed.  Boston : AddisonWesley, c2011.
 Description
 Book — xlii, 785 p. : ill. ; 24 cm.
 Summary

 Part I. Introduction and Review
 Chapter 1. Economic Questions and Data
 Chapter 2. Review of Probability
 Chapter 3. Review of Statistics Part II. Fundamentals of Regression Analysis
 Chapter 4. Linear Regression with One Regressor
 Chapter 5. Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals
 Chapter 6. Linear Regression with Multiple Regressors
 Chapter 7. Hypothesis Tests and Confidence Intervals in Multiple Regression
 Chapter 8. Nonlinear Regression Functions
 Chapter 9. Assessing Studies Based on Multiple Regression Part III. Further Topics in Regression Analysis
 Chapter 10. Regression with Panel Data
 Chapter 11. Regression with a Binary Dependent Variable
 Chapter 12. Instrumental Variables Regression
 Chapter 13. Experiments and QuasiExperiments Part IV. Regression Analysis of Economic Time Series Data
 Chapter 14. Introduction to Time Series Regression and Forecasting
 Chapter 15. Estimation of Dynamic Causal Effects
 Chapter 16. Additional Topics in Time Series Regression Part V. The Econometric Theory of Regression Analysis
 Chapter 17. The Theory of Linear Regression with One Regressor
 Chapter 18. The Theory of Multiple Regression.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
 Schroeder, Douglas A.
 New York : Springer, c2010.
 Description
 Book — xxiv, 475 p.
 Online

 dx.doi.org SpringerLink
 Google Books (Full view)
15. Basic econometrics [2009]
 Gujarati, Damodar N.
 5th ed.  Boston : McGrawHill Irwin, c2009.
 Description
 Book — xx, 922 p. : ill. ; 26 cm.
 Summary

 Part I: SingleEquation Regression Model
 Chapter 1: The Nature of Regression Analysis
 Chapter 2: TwoVariable Regression Analysis: Some Basic Ideas
 Chapter 3: Two Variable Regression Model: The Problem of Estimation
 Chapter 4: Classical Normal Linear Regression Model (CNLRM)
 Chapter 5: TwoVariable Regression: Interval Estimation and Hypothesis Testing
 Chapter 6: Extensions of the TwoVariable Linear Regression Model
 Chapter 7: Multiple Regression Analysis: The Problem of Estimation
 Chapter 8: Multiple Regression Analysis: The Problem of Inference
 Chapter 9: Dummy Variable Regression Models Part II: Relaxing the Assumptions of the Classical Model
 Chapter 10: Multicollinearity: What happens if the Regressor are Correlated
 Chapter 11: Heteroscedasticity: What Happens if the Error Variance is Nonconstant?
 Chapter 12: Autocorrelation: What Happens if the Error Terms are Correlated
 Chapter 13: Econometric Modeling: Model Specification and Diagnostic Testing Part III: Topics in Econometrics
 Chapter 14: Nonlinear Regression Models
 Chapter 15: Qualitative Response Regression Models
 Chapter 16: Panel Data Regression Models
 Chapter 17: Dynamic Econometric Model: Autoregressive and DistributedLag Models. Part IV: SimultaneousEquation Models
 Chapter 18: SimultaneousEquation Models.
 Chapter 19: The Identification Problem.
 Chapter 20: SimultaneousEquation Methods.
 Chapter 21: Time Series Econometrics: Some Basic Concepts
 Chapter 22: Time Series Econometrics: Forecasting Appendix A: Review of Some Statistical Concepts Appendix B: Rudiments of Matrix Algebra Appendix C: The Matrix Approach to Linear Regression Model Appendix D: Statistical Tables Appendix E: Computer Output of EViews, MINITAB, Excel, and STATA Appendix F: Economic Data on the World Wide Web.
 (source: Nielsen Book Data)
 Part I: SingleEquation Regression Model
 1: The Nature of Regression Analysis
 2: TwoVariable Regression Analysis: Some Basic Ideas
 3: Two Variable Regression Model: The Problem of Estimation
 4: Classical Normal Linear Regression Model (CNLRM)
 5: TwoVariable Regression: Interval Estimation and Hypothesis Testing
 6: Extensions of the TwoVariable Linear Regression Model
 7: Multiple Regression Analysis: The Problem of Estimation
 8: Multiple Regression Analysis: The Problem of Inference
 9: Dummy Variable Regression Models Part II: Relaxing the Assumptions of the Classical Model
 10: Multicollinearity: What happens if the Regressor are Correlated
 11: Heteroscedasticity: What Happens if the Error Variance is Nonconstant?
 12: Autocorrelation: What Happens if the Error Terms are Correlated
 Chapter 13: Econometric Modeling: Model Specification and Diagnostic Testing Part III: Topics in Econometrics
 14: Nonlinear Regression Models
 15: Qualitative Response Regression Models
 16: Panel Data Regression Models
 17: Dynamic Econometric Model: Autoregressive and DistributedLag Models. Part IV: SimultaneousEquation Models
 18: SimultaneousEquation Models.
 19: The Identification Problem.
 20: SimultaneousEquation Methods.
 21: Time Series Econometrics: Some Basic Concepts
 22: Time Series Econometrics: Forecasting Appendix A: Review of Some Statistical Concepts Appendix B: Rudiments of Matrix Algebra Appendix C: The Matrix Approach to Linear Regression Model Appendix D: Statistical Tables Appendix E: Computer Output of EViews, MINITAB, Excel, and STATA Appendix F: Economic Data on the World Wide Web.
 (source: Nielsen Book Data)
 Online
Law Library (Crown)
Law Library (Crown)  Status 

Find it Basement  
HB139 .G84 2009  Unknown 
HB139 .G84 2009  Unknown 
Find it Permanent reserve: Ask at circulation desk  
HB139 .G84 2009  Unknown 
16. Econometric theory and methods [2009]
 Davidson, Russell.
 International ed.  New York : Oxford University Press, 2009.
 Description
 Book — xviii, 750 p. : ill. ; 24 cm.
 Summary

Econometric Theory and Methods International Edition provides a unified treatment of modern econometric theory and practical econometric methods. The geometrical approach to least squares is emphasized, as is the method of moments, which is used to motivate a wide variety of estimators and tests. Simulation methods, including the bootstrap, are introduced early and used extensively. The book deals with a large number of modern topics. In addition to bootstrap and Monte Carlo tests, these include sandwich covariance matrix estimators, artificial regressions, estimating functions and the generalized method of moments, indirect inference, and kernel estimation. Every chapter incorporates numerous exercises, some theoretical, some empirical, and many involving simulation.
(source: Nielsen Book Data)
 Online
 Wooldridge, Jeffrey M., 1960
 4th ed.  Mason, OH : SouthWestern/Cengage Learning, c2009.
 Description
 Book — xx, 865 p. : ill. ; 25 cm.
 Summary

 Regression analysis with crosssectional data
 Regression analysis with time series data
 Advanced topics.
(source: Nielsen Book Data)
 Online
Law Library (Crown)
Law Library (Crown)  Status 

Find it Permanent reserve: Ask at circulation desk  
HB139 .W665 2009  Unknown 
 Wooldridge, Jeffrey M., 1960
 4e.  Mason, OH : SouthWestern, Cengage Learning, c2009.
 Description
 Book — xx, 865 p. : ill. ; 25 cm. + 1 access code card.
 Summary

Practical and professional, this text bridges the gap between how undergraduate econometrics has traditionally been taught and how empirical researchers actually think about and apply econometric methods. The text's unique approach reflects how econometric instruction has evolved from simply describing a set of abstract recipes to showing how econometrics can be used to empirically study questions across a variety of disciplines. The systematic approach, where assumptions are introduced only as they are needed to obtain a certain result, makes the material easier for students, and leads to better econometric practice. It is organised around the type of data being analysed  an approach that simplifies the exposition and allows a more careful discussion of assumptions. Packed with relevant applications and a wealth of interesting data sets, the text emphasises examples that have implications for policy or provide evidence for or against economic theories.
(source: Nielsen Book Data)
 Online
19. Econometric analysis [2008]
 Greene, William H., 1951
 6th ed.  Upper Saddle River, N.J. : Pearson/Prentice Hall, c2008.
 Description
 Book — xxxvii, 1,178 p. : ill ; 25 cm.
 Summary

 Preface
 Chapter 1  Introduction
 Chapter 2  The Classical Multiple Linear Regression Model
 Chapter 3  Least Squares
 Chapter 4  Statistical Properties of the Least Squares Estimator
 Chapter 5  Inference and Prediction
 Chapter 6  Functional Form and Structural Change
 Chapter 7  Specification Analysis and Model Selection
 Chapter 8  Generalized Regression Model and Heteroscedasticity
 Chapter 9  Models for Panel Data
 Chapter 10 Systems of Regression Equations
 Chapter 11  Nonlinear Regression Models
 Chapter 12  Instrumental Variables Estimation
 Chapter 13  SimultaneousEquations Model
 Chapter 14  Estimation Frameworks in Econometrics
 Chapter 15  Minimum Distance Estimation and the Generalized Method of Moments
 Chapter 16  Maximum Likelihood Estimation
 Chapter 17  Simulation Based Estimation and Inference
 Chapter 18  Bayesian Estimation and Inference
 Chapter 19  Serial Correlation
 Chapter 20  Models With Lagged Variables
 Chapter 21  TimeSeries Models
 Chapter 22  Nonstationary Data
 Chapter 23  Models for Discrete Choice
 Chapter 24  Truncation, Censoring and Sample Selection
 Chapter 25  Models for Event Counts and Duration Appendix A: Matrix Algebra Appendix B: Probability and Distribution Theory Appendix C: Estimation and Inference Appendix D: Large Sample Distribution Theory Appendix E: Computation and Optimization Appendix F: Data Sets Used in Applications Appendix G: Statistical Tables References Author Index Subject Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
Business Library
Business Library  Status 

Stacks  
HB139 .G74 2008  Unknown 
HB139 .G74 2008  Unknown 
20. Econometrics [2008]
 Baltagi, Badi H. (Badi Hani)
 4th ed.  Berlin : Springer, c2008.
 Description
 Book — xv, 392 p. : ill. ; 26 cm.
 Summary

 Preface  Part I: What Is Econometrics? Basic Statistical Concepts. Simple Linear Regression. Multiple Regression Analysis. Violations of the Classical Assumptions. Distributed Lags and Dynamic Models. Part II: The General Linear Model: The Basics. Regression Diagnostics and Specification Tests. Generalized Least Squares. Seemingly Unrelated Regressions. Simultaneous Equations Model. Pooling TimeSeries of CrossSection Data. Limited Dependent Variables. TimeSeries Analysis. Appendix. Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
Teaches some of the basic econometric methods and the underlying assumptions behind them. This book includes a simple and concise treatment of advanced topics in spatial correlation, panel data, limited dependent variables, regression diagnostics, specification testing and time series analysis.
(source: Nielsen Book Data)
 Online

 dx.doi.org SpringerLink
 Google Books (Full view)
Articles+
Journal articles, ebooks, & other eresources
 Articles+ results include