ECONS205 EMPIRICAL GROUP PROJECT GUIDELINES Due by: Sunday 7 June 2020, 23:59 (NZ Time)
To strengthen both team work and communication skills, students will work in a group of two, three or four students (but no more than four students) and collaboratively identify, describe, model and analyse practical real-world problem using the data analytics techniques you have learned from this class. Students will form their own groups. Students may work alone if they wish. The project will involve testing some Economics/Finance proposition using either data that you have gathered (such as a survey) or data that you have obtained from source (see below for some suggestions on data resources). You can choose to work on either Regression Analysis Related Project or Optimisation Modelling Project.
Each group is required to prepare a short written report in a 3-page paper. Your report should cover at least the following:
For Regression Analysis Related Project:
1. Introduction in which you state the importance and the purpose of your research
2. Short data description. What is the source of the data? Is the data cross-section or time series?
Summary Statistics of the data. What are the data problems, if any?
3. The story – what is the primary hypothesis tested?
4. Short description of empirical method
5. Presentation of the empirical results
6. Conclusions and implication
For Optimisation Modelling Related Project:
1. Introduction: Describe your problem in words and explain why it is interesting
2. Model Formulation: Describe your problem as a mathematical model, state your model assumptions, and clearly define all its sets, variables and data parameters
3. Short data description. What is the source of the data? Summary Statistics of the data. What are the data problems, if any?
4. Analysis: Solve your model and remember that that its purpose is insight not numbers. In your analysis, you might also want to include sensitivity analysis.
5. Conclusion and implications
We want to reward data visualization skills and so for the paper you need to format any table professionally rather than just doing a cut and paste from Excel. If you want examples, check empirical papers that we posted on Moodle.
The report is three pages, all-inclusive (so no appendices). The text size should be 12 point and in Times New Roman font with 1 inch margins and 1.5 line spacing. Therefore, the word count may be somewhere about 1,800 words maximum. The reason for these length restrictions is to reward skill in summarizing data effectively and efficiently.
A good basis for structuring your report is to look at the section of the sample research posters on Moodle The poster presentation format forces you to concentrate on the main findings in a short and informative way.
Listed below are some of the topics from past students:
• Does the soil type affect the costs to reduce nitrogen leaching?
• The Pink Tax: Do women pay more?
• What makes diamonds so expensive?
• Wider effects of hosting international sporting events
• What factors influence healthcare expenditure?
• How the price of oil affects the prices of energy stocks within New Zealand?
• Relationship between Final Grade and Tutorial Attendance
• Which month should directors release their films to earn the most revenue?
• Which statistic is getting NBA players paid?
• Does the Phillips curve exist in New Zealand?
There are a large number of data sources that are useful for conducting Economic and Finance analysis. The following websites are comprehensive sources for economist. They contain links to lots of data sources as well as to other sites of interest to empirical economists. In addition, on the next pages we have listed other sources and made notes about the nature of the data available from them.
Waikato University also has several databases available for students with interests in Finance, which include:
• NZX Company Research (formerly NZX Deep Archive), which provides historical information on New Zealand Companies
• Datastream which provides key data sets from both developed and emerging markets. Current and historical data is available variables such as - equities, market indices, company accounts, economic indicators, bonds, foreign exchange, interest rates, commodities and derivatives.
Other Data Sources
This is an University of Auckland library site with links to a wide range of official statistical sources from around the world.
You can browse by country, by region of the world and by subject. The subjects include both economic and non-economic ones.
Federal Reserve Economic Data is a database maintained by the St. Louis Federal Reserve and has over 750,000 time series on financial and macro data especially for the US, but also Australia, China, Canada etc. If you install the FRED Add-in, you can download data directly into Excel.
This site has US, Australian, Chinese (new), ECB and Japanese data, plus LIBOR data in various currencies. The site allows you to manipulate the data: e.g. convert monthly data to quarterly or annual data (see Transform this series); copy data into Excel spreadsheets; and graph the data.
Data Market https://datamarket.com/topic/list/countries/
This site has a consistent means of searching, comparing, visualising and downloading quantitative data from a wide variety of international sources. You can explore data by country, by industry, or by data provider (such as IMF, World Bank, the UN etc). Any data that is open and free from the source site is still available free on the DataMarket site – some 125 million time series from about 16 thousand data sets.
Quandl has indexed over 7 million time-series datasets from over 400 sources. All of Quandl's datasets are open and free. You can download any Quandl dataset in any format that you want. You can also visualize, save, share, authenticate, validate, upload, index, merge and transform data.
A reasonable guide to carrying out a research project is:
Ramu Ramanathan, Introductory Econometrics with Applications, 5th edition, South-Western, 2002. Chapter 14: Carrying Out an Empirical Project [accessible through Moodle]. Note however that your project is smaller, and has a more focused presentation than the sort of project described by Ramanathan.