Your empirical project must have clearly stated goals and several conclusions according to it. Its deliverable will be a short essay exposing your goals, the econometric analysis that you followed to achieve them and the conclusions.
The document should be printed with 11-12 point font, standard margins and spacing. Its structure should be as follows:
1. A cover page with: (a) the title of the work, (b) your name and a (c) brief abstract (100-200 words)
2. An Introduction, explaining the goals of the exercise.
3. A maximum of five pages explaining the analytical process. You should make a synthetically exposition, avoiding the discussion of trivial statistical results. If you cite citing a particular result (for example, a test of significance) it must relevant to justify an important decision or conclusion. Unnecessary graphics or tables should also be avoided.
4. An additional page with concluding remarks, according to the goals defined in the introduction.
Besides doing a clear and rigorous econometric analysis, it is important to document it properly. Please follow the guidelines in: Givens, G.H. and J.A. Hoeting (2002). Communicating Statistical Results, Mimeo. This very useful document can be freely downloaded from this site.
Additionally, you can use data from the following sources:
[url removed, login to view] ([url removed, login to view]) provides a wide selection of data in different areas: markets, economy, demographics, quotes…
[url removed, login to view] ([url removed, login to view]) with a philosophy and coverage similar to Quandl, but emphasizing in the generation of sophisticated graphical displays that can be embedded in web pages.
[url removed, login to view] observatory of economic complexity ([url removed, login to view]) concentrates in international commerce. It not only provides data, but also allows users to quickly compose a visual narrative about countries and the products they exchange.
[url removed, login to view] ([url removed, login to view]) provides data on various topics, including Rob Hyndman’s Time Series Data Library ([url removed, login to view]:tsdl).
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