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Is Equipment Price Deflation a Statistical Artifact? Bart Hobijn FRBNY

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What is an Artifact? Artifact: An inaccurate observation, effect, or result, especially one from the technology used in scientific investigation or from experimental error.The apparent pattern in the data was an artifact of the collection method American Heritage Dictionary of the English Language

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Example: PC microprocessor prices Price per MHz increasing in speed of processor !

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Hypothesis Measured equipment price deflation overstated because statistical methods do not take into account imperfect competition in equipment markets

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Outline Step 2 (real world): Positive correlation between markup and quality biases measures of equipment price deflation. –Notation –Measures of equipment price deflation –Example: PC microprocessors Step 1 (my world): Imperfect competition causes markups to be positively correlated with the quality of the machine. –Model market for machines –Equilibrium outcome How do real world methods do in my world? –numerical example Conclusion and big picture

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Stylized example Suppose quality of MPU is proportional to clock speed

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Notation timet vintage indicatorv efficiency units embodied in vA v price of vintage v at time tP t,v vintage age =t-v number of v machines sold at time tX t,v One vintage introduced in each period Technological progress: A v >A v-1

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Vintage price schedules Modus operandi –Relative prices reflect relative qualities –Implicit: No markups and production costs constant per quality unit.

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Vintage price schedules Modus operandi I will argue –market power is higher for newer vintages t,v > t,v-1 –market power decreases as vintage ages t,v > t+1,v –note: t,v =1 gives back conventional schedule

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Matched model method Set of vintages in market today and yesterday, M. Measured equipment price inflation, t Apply measure to vintage price schedule with markups

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Matched model method Vintage price schedule: Measured equipment price inflation, t Measured deflation captures price decrease as well as market power erosion

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Stylized example revisited (1)

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Hedonic price method Vintage price schedule Quantify part of price determined by quality using regression Apply measure to vintage price schedule with markups

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Hedonic price method Vintage price schedule Estimate regression –Omitted variable bias: lnQ v is correlated with the omitted markup variable. –Too big a part of price changes attributed to quality differences! –Too little attributed to price increases!

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Stylized example revisited (2)

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Conclusion Imperfect competition leads to markups being positively correlated with quality positive correlation between markups and quality bias measures of equipment price deflation equipment price deflation overestimated Important aggregate implications

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