Introduction to econometrics 3rd edition by christopher dougherty

Subscribe to our mailing list. We put a lot of effort and resources to keep the materials you enjoy in LearnClax free. Consider making a donation. On Telegram. Home Leaderboard. Optional filter - Choose an institution first. Linear algebra matrix algebra is not used in this text. This is not a serious impediment to acquiring a sound knowledge of econometrics at this level. Although it means that, for the purpose of theoretical analysis, we have to restrict the analysis to models with no more than two explanatory variables, this is not a major constraint.

We can still investigate nearly everything that we wish, and greater complexity would add very little. Appendix A, Matrix Algebra, of Greene's Econometric Analysis is an excellent resource, giving you just what you need to know for econometrics. Statistics: You must have a clear understanding of what is meant by the sampling distribution of an estimator and of the principies of statistical inference and hypothesis testing. This is absolutely essential. In my experience, most problems that students have with an introductory econometrics course are not econometric problems at al!

There are no short cuts. If you do not have this background, you should put your study of econometrics on hold and study statistics first.

Otherwise there will be core parts of the econometrics syllabus that you do not begin to understand. In addition, it would be helpful if you have some knowledge of economics. However, although the examples and exercises in this text relate to economics, most of them are so straightforward that a previous study of economics is not a requirernent.

Additional resources There are two additional major resources that you should check out as soon as you begin to use this text: the slideshows and the study guide. Roth are available, at no cost and with no restrictions, in the Online Resource Centre at www. Slideshows: The PowerPoint slideshows systematicaily cover all of the topics treated in the text, typically with greater graphical detail.

They are not intended as a substituta for the text, but they should provide substantial support. Study guide: This provides answers to the starred exercises in the text and addi- tional exercises, also with solutions. It was commissioned by the University of London International Programmes as an additional resource for distance-learning students, and the organizers of the External Negree have kindly allowed it to be available to anyone who is interested in using it.

The Online Resource Centre also gives unrestricted access to ah l of the data sets used in the examples and exercises in the text. With little variation, they al! Many of the tables in this text reproduce output from Stata or EViews, mainly because the format is compact and tidy. Output from other applications looks very similar.

If you do not have access to one of these -commercial applications, then download gretl and use that instead. Go to the Online Resource Centre, find the link, and follow the instructions. There you will also find a downloadable manual that tells you how to use gretl to do the exercises in this tcxt. You should not try to use an inferior substitute.

In particular, you should not try to use the regression engine built into a spreadsheet application such as Microsoft Excel. Excel and other spreadsheets are invaluable applications, but they are not intended or designed for serious econometrics use. You need a dedicated application, and gretl is an excellent one. The aims of this text have been stated abo y e. There is one further aim, or at least, hope.

That is that you will find the study of econometrics intellectually satisfying. By the time that you approach the end of this text, you will find that, although the material in each chapter is new, the sane themes and concerns keep reappearing, especially those related to the properties of estimators. When you begin to recognize this, you will be well on your way to becoming a proper econometrician, and not just someone mechanically handling data and performing tests.

And, of course, when the time comes for you to fit your own modeis with your own data, it is hoped that you will find the practice of econometrics enjoyable too. Amemiya, Takeshi Qualitative response models: a survey. Journal of Economic Literature 19 4 : Tobit models: a survey. Journal of Econometrics 24 1 : Baltagi, Badi H. Econometric Analysis of Panel Data 5th edn. Chichester: Wiley.

Box, George E. Cox An analysis of transformations. Draper Jenkins Time Series Analysis: Forecasting and Control. San Francisco: Holden Day. Jenkins, and Gregory C.

Reinsel Time Series Analysis: Forecasting and Control 3rd edn. Breusch, Trevor S. Testing for autocorrelation in dynamic linear models. Australian Economic Papers 17 31 : Brown, T. Habit persistence and lags in consumer behaviour. Econometrica 20 3 : Card, David Using geographic variation in college proximity to estimate the return to schooling. In Louis N. Christofides, E.

Toronto: University of Toronto Press. Chow, Gregory C. Tests of equality between sets of coefficients in two linear regressions. Econometrica 28 3 : Cobb, Charles W.

Douglas A theory of production. American Economic Review 18 1, Suppl. Cooper, Ronald L. The predictive performance of quarterly econometric models of the United States. In Bert G. Hickman ed. New York: Columbia University Press. Court, Andrew T. Hedonic price indexes with automotive examples. New York: General Motors Corporation. Davidson, James E. Econometric Theory. Oxford: Blackwell. Davidson, Russell, and James G. MacKinnon Estimation and Inference in Econometrics. New York: Oxford University Press.

L1 Bibliography Dickey, David A. Fuller Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74 : Dickey, David A. Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 49 4 : Diebold, Francis X. The past, present, and future of macroeconomic forecasting. Journal of Economic Perspectives 12 2 : Elements of Forecasting 2nd edn.

Cincinnati, OH: South-Western. Durbin, James Errors in variables. Review of the International Statistical Institute 22 1 : Testing for serial correlation in least-squares regression when some of the regressors are lagged dependent variables. Econometrica 38 3 : Durbin, James, and G. Watson Testing for serial correlation in least-squares regression I.

Biometrika 37 : Durlauf, Steven N. Phillips Trends versus random walks in time series analysis. Quantity: 3. US Soft Cover Edition. Book may have heavy wear on cover, corners, or spine. Some pages may have creases or bends. May contain highlighting or underlining on some pages. May have tape on parts of the book.

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