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Data Analysis for Competition Policy: an Introduction to Econometrics

Data Analysis for Competition Policy: an Introduction to Econometrics. Katie Curry Senior Economist, OFT. Outline. What is econometrics? Why is it useful? Example Defining the relevant market in a recent merger case. What is econometrics?. Statistical modelling of economic relationships

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Data Analysis for Competition Policy: an Introduction to Econometrics

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  1. Data Analysis for Competition Policy: an Introduction to Econometrics Katie Curry Senior Economist, OFT

  2. Outline • What is econometrics? • Why is it useful? • Example • Defining the relevant market in a recent merger case

  3. What is econometrics? • Statistical modelling of economic relationships • e.g. how consumers respond to price changes • A commonly used technique is called regression analysis • Regression analysis uses actual data to assess how one variable of interest (e.g. quantity consumed) is related to possible explanatory factors (e.g. price)

  4. Error term. Variable trying to explain. Average value of Y. X is the explanatory factor. b measures the average increase in Y caused by an increase in X. What is econometrics? ctd. • Allows for the fact we don’t have data on all possible influences by including an error term • Use data to estimate equation of the form: Y = a + bX + e

  5. Y b a X What is econometrics? ctd.

  6. Why use econometrics? • It allows us to analyse a large amount of information in a systematic way • Suppose we have data on the price of ice cream and the quantity of ice cream eaten and we are interested in how consumer demand responds to changes in price • We could look at what happened to ice cream sales every time the price changed • But if there are lots of observations this could take a long time- and if we only look at one or two instances our conclusions could be unrepresentative • Regression analysis can handle millions of observations easily

  7. Why use econometrics? ctd. • Can give more meaningful results than simple statistics • We could look at the average price of ice cream and the average quantity eaten in a large dataset very easily • Knowing that a 5% price increase leads to a 1% reduction in demand could be much more helpful than simply knowing the average level of each

  8. Why use econometrics? ctd. • Controls for effect of more than one variable • We could use our data to make a chart, showing how quantity is related to price • However there may be many other factors affecting quantity demanded that obscure this relationship (e.g. more ice cream in the summer) • Econometrics can control for these other factors, allowing us to focus on the relationship we are interested in

  9. Example of econometrics in practice

  10. Example of econometrics in practice • Used to define relevant market in a merger • Merging parties overlapped in manufacture and supply of specific types of soft cheese (Brie, Camembert and goat’s cheese) • Parties submitted that British cheese was in a separate market from French cheese so there was no overlap

  11. Econometrics results used for market definition • Used an econometric model to estimate how demand for one cheese changes when its own price and the price of a potential substitute changes • The elasticity estimates obtained in this way were used to conduct a critical loss analysis • Critical loss analysis uses data on profit margins and elasticities to calculate whether a 5% price increase would be profitable • Starts with narrowest market- if not profitable, then move to broader market

  12. Almost Ideal Demand System • Useful way of estimating demand when there are many brands that can be grouped together in segments • Assumes customers decide how much to spend on one segment (e.g. camembert) and then decide which brand to buy • Demand for each brand can be estimated as a function of the prices of all of the brands in the same segment

  13. The ideal model

  14. What we actually did

  15. Illustrative results

  16. Questions?

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