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EFB222 Assessment item 2: Portfolio 55%

· Quizzes 10% (for details, see Bb)

· Report 35% (for details, see below)

· Reflection 10% (for details, see Bb)

Report 35%

The task is to address an economic issue and use data to describe and analyse it.

The criteria for a successful portfolio task are primarily focused on the econometrics, the correct and appropriate use of the methods, and observations that are concerned of the econometric issues. The topic itself does not need to be solidly grounded in an economic theory, it could be something exploratory, however, do keep in mind that you will need to interpret and discuss the model and findings in terms of the economic problem you are looking at.

The portfolio will be combined of data description and 3 separate tasks. Each task builds on the previous, and the techniques to be exemplified in each will relate to the text book chapters 5-7. The complete report is submitted in one piece at the end of the portfolio task, and it will be assessed against the expected style and knowledge covered by that time.

The data should be cross-sectional (no time series, no panels). Some suggestions for places to go to find data are:

· RBA: https://www.rba.gov.au/

· ABS: https://www.abs.gov.au/, also census

· OECD: https://data.oecd.org/, browse by topic; https://stats.oecd.org/

· DataHub: https://datahub.io/collections/economic-data

· FRED: https://fred.stlouisfed.org/

· The World Bank: https://data.worldbank.org/

· IMF: https://www.imf.org/en/Data

Data description (5%)

Preliminaries: Choose a topic. Collect data, bring it into Stata, and make sure you can estimate some reasonable model with at least two explanatory variables (you may add more later). It may be better to leave the writing of the data description until the three tasks are completed, in case you decide to change or modify the data set.

Report: Data description. 1 page

For each of the three tasks:

Preliminaries: Make a task list of what econometric techniques / issues to address / exemplify, draft out some ideas on how to do that. Get together with your group and start working with your data.

Report: Describe the technique/issue, provide demonstration and explanation, and a brief interpretation in the context of your data/application. 1 page / task

Task 1 (10%)

Chapter 5 – address the following topics:

· Interpret regression equation

· Goodness-of-fit

· Assumptions MLR.1-5

Task 2 (10%)

Chapter 6 – choose 4 topics from:

· t-test of a single population parameter

· Confidence interval

· t-test of a single linear combination of parameters

· F-test of exclusion restrictions or for model significance

· Prediction and confidence interval

Task 3 (10%)

Chapter 7 – choose 4 topics from:

· Logarithmic transformations

· Quadratic, and interaction terms

· Irrelevant variables

· Omitted variables

· Functional form misspecification test

· Multicollinearity