BMET 22A54 - Introduction to Econometrics

Econometrics is the application of mathematical and statistical methods and techniques in order to: 1) understand, analyze, and interpret economic and financial data, 2) test economic and financial hypotheses/theories, and 3) make predictions about prospective changes in the economy. Econometrics is fundamentally a regression-based correlation methodology used to measure the overall strength, direction, and statistical significance between a “dependent” variable - the variable whose movement or change is to be explained - and one or more “independent” variables that will explain the movement or change in the dependent variable.

Econometrics also requires a detailed understanding of the mechanics, advantages, and limitations of the “classical” linear regression model. Thus, the first part of the course will cover the theoretical and applied statistical principles which underlie Ordinary Lest Squares (OLS) regression techniques. This part will cover the assumptions needed to obtain the Best Linear Unbiased Estimates of a regression equation – also known as the “BLUE” conditions. Particular emphasis will be placed on the assumptions regarding the distribution of a model’s error term and other BLUE conditions. We will also cover hypothesis testing, sample selection, and the critical role of the t and F-statistic in determining the statistical significance of an econometric model and its associated slope or “” parameters. The second part of the course will address the three main problems associated with the violation of a particular BLUE assumption: multicollinearity, autocorrelation, and heteroscedasticity. We will learn how to identify, address, and (hopefully) remedy each of these problems. In addition, we will take a similar approach to understanding and correcting model specification error.

Please note that this is a basic first course in econometrics. While certain advanced topics such as co-integration and error correction models will be studied toward the end of the semester, you should consider taking a more advanced econometrics class in case you have had substantial econometrics from before.

At the end of the course, the student is expected to :

• understand, analyze, and interpret economic and financial data,
• test economic and financial hypotheses/theories, and
• make predictions about prospective changes in the economy.

• The mid-term exam will be 30% and the final exam will be 30% of the final grade (all take-home).
• World bank project (see below) will be 30 % of the final grade.
• The participation will 10% of the final grade.

World Bank Project

Each student will have to replicate and critique the regressions in the following article:

Botero, Juan Carlos, Simeon Djankov, Rafael La Porta, Florencio López-de-Silanes, and Andrei Shleifer. 2004. "The Regulation of Labor." The Quarterly Journal of Economics 119 (4): 1339-1382.

This group project report is due at the end of the semester. You should submit a 5-10 page report of your assessment of Botero et al’s results. The report should include each regression output in the paper along with your assessment of each regression and the final central conclusions of the authors.

The above paper underpins the World Bank’s Doing Business project. Here is the link: http://www.doingbusiness.org/methodology. Click on "Employing Workers". The dataset used by Botero et al will be uploaded onto the class website along with the paper.

The final project report is due the final week of spring semester. The World Bank project will be 30% of the final grade.