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APPLIED ECONOMETRICS Lecture 2 – Research Projects

APPLIED ECONOMETRICS Lecture 2 – Research Projects. COME UP WITH AN IDEA. You need an idea for your research. This should be Easy to explain - you should be able to pitch this to the class in 2 minutes Interesting – we have to want to know the answer

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APPLIED ECONOMETRICS Lecture 2 – Research Projects

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  1. APPLIED ECONOMETRICSLecture 2 – Research Projects

  2. COME UP WITH AN IDEA • You need an idea for your research. This should be • Easy to explain - you should be able to pitch this to the class in 2 minutes • Interesting – we have to want to know the answer • Feasible – you have to be able to make progress • Research – this can not be something somebody else has already done

  3. YOUR IDEA HAS FIT INTO A PROJECT • The ideas should lead to a project with the following structure: • The question • What this is • Why we should care • Empirical approach • Empirical techniques (natural experiment, IV etc..) • Data sources • Results, including some form of robustness tests • Conclusion including an answer to the question

  4. THE GOLDEN RULE OF PROJECTS (1) The golden rule is try to get a draft done early My experience as an academic, in the Treasury and managing projects with McKinsey is you rarely know future problems So best is to take a quick run-through first – i.e. pull together the data, run some regressions and write up a basic draft When you have done this you’ll know what is possible and what is not, and then can start to improve your project Never break your project up by writing intro in weeks 1 to 3, data section in weeks 4 to 6, results in weeks 7 to 9……

  5. THE GOLDEN RULE OF PROJECTS (2) • To help in this I would like: • (1) The first presentation of your ideas from Wednesday 20th January. Before you hand these in check you can do your project • Run your idea past somebody else: • Check the data exists, and if possible start using this • Check no-one else has answered it • (2) A full draft presentation from 29th January onwards • This will be marked as a draft version of the project • So you will need to show an idea, data and results, even if this is not polished.

  6. DATA SOURCES • Economists often pick their research based on data. • In principle this is not a good way to do research – ideas should drive research, not data drive research • But in practice large new datasets, if cleverly used, almost always yield interesting results • Some good places to look for data include: • NBER – www.nber.org/data/ (broad range of data • Economagic - http://www.economagic.com/ time-series data • WRDS - http://wrds.wharton.upenn.edu/ - firm-level data • You can also Google or collect your own data

  7. USE GRAPHS I also think every project should have 1 page of figures and/or graphs motivating or highlighting the work You need to get your audience interested and try to get the intuition of your work over as simply as possible The best presentation starts with a graph presenting a new-fact which people want to know more about Some examples of graphs I’ve used to follow:

  8. Monthly US stock market volatility Black Monday* 9/11 Enron Russia & LTCM Franklin National Cambodia,Kent State Gulf War II Monetary turning point JFK assassinated OPEC I Asian Crisis Afghanistan Cuban missile crisis Gulf War I OPEC II Annualized standard deviation (%) Actual Volatility Implied Volatility Note: CBOE VXO index of % implied volatility, on a hypothetical at the money S&P100 option 30 days to expiry, from 1986 to 2004. Pre 1986 the VXO index is unavailable, so actual monthly returns volatilities calculated as the monthly standard-deviation of the daily S&P500 index normalized to the same mean and variance as the VXO index when they overlap (1986-2004). Actual and implied volatility correlated at 0.874. The market was closed for 4 days after 9/11, with implied volatility levels for these 4 days interpolated using the European VX1 index, generating an average volatility of 58.2 for 9/11 until 9/14 inclusive. * For scaling purposes the monthly VOX was capped at 50 affecting the Black Monday month. Un-capped value for the Black Monday month is 58.2.

  9. European productivity had been catching up with the US for 50 years…

  10. …but since 1995 US productivity accelerated away again from Europe.

  11. - Change in annual growth in output per hour from 1990 – 95 to 1995 – 2001 % Increase in annual growth rate – from 1.2% in 1990 – 95 to U.S. EU 4.7% from 1995 Static growth – at around 2% a year – during the early and ICT - using sectors late 1990s 3.5 -0.1 ICT - producing sectors 1.9 1.6 Non - ICT sectors -0.5 -1.1 3 There was no acceleration of productivity growth in Europe in IT using sectors. Source: O’Mahony and Van Ark (2003, Gronnigen Data and European Commission)

  12. FIRM LEVEL AVERAGE MANAGEMENT SCORES France n=137 Germany n=157 UK n=154 US n=290

  13. TEMPLATE FOR NEXT WEEK • All text should be 24 point • Everyone can use 4 slides plus a cover slide with name & title • Everyone has 10 minutes to present, plus 5 minutes for Q&A • This will be strictly enforced with 2 & 1 minute warnings • I would suggest doing something like this: • Slide 1: Cover slide • Slide 2: Your idea • Slide 3: How you will pursue this – data • Slides 4 & 5: What you expect to show – identification • Bring your slides on your own PC if possible, or if not a memory stock (please check for viruses…..)

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