Reference no: EM13157281

The basic purpose of this course is to prepare students to carry out their own econometric study. Students will be asked to formulate an original econometric model, collect data relevant to the model, use econometric techniques to estimate the model, and interpret the results of the estimation. Econometrics is best learned by actually doing an econometric study. Only then will the "uninitiated" learn the power as well as the pitfalls of econometrics. This handout will outline the steps to writing an econometrics paper.

I. The Model

The model and the data are the starting points of an econometric project. The first step in formulating a model is to select a topic of interest and to consider the model's scope and purpose. In particular thought should be given to the objectives of the study, what boundaries to place on the topic, what hypotheses might be tested, what variables might be predicted, and what policies might be evaluated. Close attention must be paid, however, to the availability of adequate data. In particular the model must involve causal relations among measurable variables.

These papers are generally interested in the impact of some independent variable X on a dependent variable Y. But since there are many variables X that have influence on the variable Y, it is important to include all those variables on the right hand side of the equation.

To ensure that the model is both interesting and manageable, it should contain at least four to five independent variables on the right hand side. The model should be formulated as an algebraic, linear, stochastic equation along with a corresponding verbal statement of the meaning of the equation. The expected signs of all the coefficients should be considered. All relevant multipliers, short-run and long-run, should be identified and considered.

Remember that these ideas above are merely examples of reasonable topics. You should be original and follow your own interests. Perhaps the best choice of a topic is one in which you have prior experience or knowledge. Did you take a course on economic development or do you like to watch basketball games? You will have a head start in these areas because you are already familiar with the basic issues. If you feel particularly uninspired, take a look at Bernt, The Practice of Econometrics, Addison-Wesley, 1991. In any case, you will have to identify and study the previous literature on the subject. Good sources are professors, EconLit, and the Honnold Library On Line Catalog. The relevant literature should indicate, or at least suggest, a model and also hypotheses to be tested, variables to be forecast, and/or policies to be evaluated. It can also be a useful guide to the relevant data.

II. The Data

Data form an essential ingredient in any econometric study, and obtaining an adequate and relevant set of data is an important and often critical part of the econometric project. Data must be available for all the variables in the model.

National Statistical Abstracts, Statistical Yearbooks, or Statistical Handbooks, published annually by most major countries provide both summary statistics and references to primary sources. For the United States, the best starting point for the acquisition of relevant data is the Statistical Abstract of the United States which is published annually.

The appendix to the annual Economic Report of the President contains information on fewer variables than the Statistical Abstract, but has a longer times series for these variables. It includes series on income, employment and production. The U.S. Department of Commerce, Bureau of Economic Analysis publishes the Survey of Current Business each month. Business Statistics, the biennial supplement to the Survey provides historical data and methodological notes for approximately 2,100 series. Depending on the series, the data are published on a monthly, quarterly, and or annual basis. Some series are seasonally adjusted. Numerous private agencies also collect economic data. Economagic.com provides access to over 200,000 economic times series. The Conference Board collects data on several economic variables, as does the Institute of Social Research at the University of Michigan.

For financial data, there are several primary sources. The Center for Research in Securities Prices (CRSP) dataset contains data on market prices and quarterly dividends for every firm listed on the New York Stock Exchange (NYSE) since 1926. The ILS dataset, produced by Interactive Data Corporation (IDC), contains daily stock-trading volume, prices, quarterly dividends, and earnings for all NYSE and AMEX securities, and some OTC securities. The Compustat dataset, produced by Investors Management Sciences, Inc. (IMSI), contain over 20 years of annual data for more than 3,500 stocks.

For international data, the United Nations Statistical Yearbook provides a wealth of data on member countries, as do statistical yearbooks of other international organizations like the OECD. The Federal Reserve Bank of St. Louis puts out International Economic Conditions which gives comparative data for Canada, France, Germany, Italy, Japan, Netherlands, Switzerland, United Kingdom, and the U.S. Various almanacs, sources on the WWW like www.census.gov, and other reference works also abound in statistics. Take a look at the course homepage and the economics department homepage. All of these sources contain data on so many topics that they may suggest a topic for the econometric project. You should also talk to librarians and other professors and just keep your eyes open.

Data can be either time-series or cross-section. For this project it is probably best not to pool data of the two types. Also it is best to avoid data sets which are too small, say less than thirty observations. The data should be examined, and if necessary, refined to make them suitable for the purposes of the model. For time-series data it may be necessary to use seasonal adjustments or perhaps to eliminate certain trends. For both time-series and cross-section consideration should be given to whether to divide the data into separate samples or perhaps exclude certain observations. Thus in time-series data it may (or may not) be appropriate to exclude war years or years of a recession. In a cross-section of nations it may be inappropriate to include all countries that are UN members. The developed countries might be treated as one group and the developing countries as another group. Dividing the data this way into subsamples not only leads to more homogenous data sets but also facilitates the study by allowing comparative analyses.

III. The Estimation

After both the model and data have been developed, the next step is to utilize econometric techniques to estimate the model. Your final paper is expected to use multiple regression analysis to estimate your multivariate model and test relevant hypotheses. You need to use STATA 11. For this project it is best if the dependent variable is a quantitative variable. Do make sure that you have enough observations for all the variables and that the dependent and independent variables show some variation over the observations. You should not be estimating any identities, or using the dependent variable on the right hand side of the equation unless it is lagged.

IV. The Write-Up

The paper should be approximately 10-15 pages in length. If it is much shorter, it should be very good. If it is much longer, it should be very important. Unless there are reasons for doing otherwise, the best style to use in the final write-up of the econometric project is that of an article in a scholarly journal, a style that is both clear and brief, though never sacrificing clarity for the sake of brevity. The following outline is suggested for your paper:

I. Title Page

II. Introduction 
Discuss the nature and objectives of the topic, provide a general description of the scope of the model, and the hypotheses to be tested and/or policies to be evaluated. Here you should motivate your paper by explaining why the issues you are studying are important.

III. Review of Previous Literature 
Discuss the approaches and results of previous studies of this topic or related topics. Explain why your paper is better than the previous literature.

IV. Specification of the Model 
Define and discuss the specification of your model. What variables are included in the model? Explain why you chose those variables and the role they play in the model. Have you included all the important variables in the model? What are the expected signs of all the coefficients? Explain the stochastic and other assumptions being made in the model.

V. Data Description

Provide complete descriptions of all the data, their sources, refinements used, and their possible biases or other possible weaknesses.

VI. Results 
Present the estimates of the model and its related statistics such as standard errors, t statistics and the R2. Discuss which coefficients are significant at the 5% and 1% levels. If relevant, a discussion of possible serial correlation and its correction; a discussion of possible heteroscedasticity and its correction; and a discussion of possible multicollinearity and its correction. Estimate alternative models to test the robustness of the results.

VII. Discussion 
Discuss the signs and magnitudes of the estimated coefficients and their comparisons to predicted or theoretical signs and magnitudes. What have we learned? Consider how the model might be reformulated in future studies, and implications for future econometric research.

VIII. Conclusions 
Sum up the major results of your study.

IX. Bibliography 
Include complete citations of all items referred to in the paper.