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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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slide2

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
slide3

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
slide4

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……

slide5

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.
slide6

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
slide7

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:

slide8

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.

there was no acceleration of productivity growth in europe in it using sectors

-

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)

slide12

FIRM LEVEL AVERAGE MANAGEMENT SCORES

France

n=137

Germany

n=157

UK

n=154

US

n=290

slide13

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…..)