introduction of econometrics

Econometrics is interesting because it provides the tools to enable us to extract useful information about important economic policy issues from the available data. Students who gain expertise in econometrics will also find that they enhance their job prospects

Econometrics is the use of statistical techniques to understand economic issues and test theories. Without evidence, economic theories are abstract and might have no bearing on reality (even if they are completely rigorous). Econometrics is a set of tools we can use to confront theory with real-world data.

If you are interested in carrying on your economics in some fashion after your first degree (whether in further study or as a professional economist in government or the private sector) econometrics can help you. Most Master's courses have compulsory, advanced econometrics components, and most employers of economists are looking for people to crunch numbers - and, crucially, interpret results.

The goal of an applied econometric study might be to test a hypothesis - for example, to determine how much of the ‘gender pay gap' can be explained by differences in education and experience. Alternatively, a study could estimate a key parameter, such as the price elasticity of demand for oil. Or econometric techniques could be used to generate forecasts, like the Bank of England uses to determine the level that the base interest rate should be set each month.

Studying econometrics builds up your human capital in two ways. The first is that it allows you to conduct applied econometric studies of your own - which can be very useful if you are also doing a dissertation. Modern econometric software greatly facilitates the process of model formulation, estimation and validation, and provides helpful graphical information as well as tables of output.

The second is that it allows to you critically assess the empirical work of others. This can be helpful when discussing the relevant academic literature in any other module - and to be able to comment on why a particular technique may or may not be appropriate can often be very impressive.

Econometrics is not an easy option. Initially many students find it dry and uninspiring. But those who persevere with it tend to be rewarded for their efforts. When you understand what you are doing, conducting an econometric study and finding something new about the world is a satisfying experience, and — dare we say it — fun.

Web Links

The Economics Networks link to different online notes on econometrics

Econometrics books

• Undergraduate textbooks
• Graduate textbooks
• Other topics:  Bayesian econometrics, bootstrap, business statistics/econometrics, count data, duration data,macroeconometrics, Monte Carlo methods, nonparametric econometrics, panel data, quantile regression, Stata, theoretical probability, theoretical statistics, time series
• Textbook price comparison                                                                                                                   
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  Introductory Econometrics
  Below is the old reading list for the reference purposes only. You should get a copy of reading list from DSE photostat shop or click here to find old/new version of original reading list as and when they will be uploaded by DSE
  • Nature and Scope of Econometrics
  • Review of Statistics
  • Classical Linear Regression Model: Two variable case
  • Classical Multiple Regression Model
  • Violations of Classical Assumptions and remedies
  • Specification Analysis
  References:
  • D. N. Gujarati and D.C. Porter, Essentials of Econometrics, 4th Edition, McGraw Hill International Edition
  • Christopher Dougherty, Introduction to Econometrics, 3rd edition, OUP,Indian edition
  • Jan Kmenta, Elements of Econometrics, Indian Reprint, Khosla Publishing House, 2008, recommended chapters for ‘Review of Statistics’