Does "Aggregation Bias" Explain the PPP Puzzle? / Shiu-Sheng Chen, Charles Engel.

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Chen, Shiu-Sheng

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TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w10304.Publication details: Cambridge, Mass. National Bureau of Economic Research 2004.Description: 1 online resource: illustrations (black and white)Subject(s):

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Abstract: Recently, Imbs et. al. (2002) have claimed that much of the purchasing power parity puzzle can be explained by aggregation bias'. This paper re-examines aggregation bias. First, it clarifies the meaning of aggregation bias and its applicability to the PPP puzzle. Second, the size of the bias' is shown to be much smaller than the simulations in Imbs et. al. (2002) suggest, if we rule out explosive roots in the simulations. Third, we show that the presence of non-persistent measurement error especially in the Imbs et. al. (2002) data can make price series appear less persistent than they really are. Finally, it is now standard to recognize that small-sample bias plagues estimates of speeds of convergence of PPP. After correcting small sample bias by methods proposed by Kilian (1998) and by So and Shin (1999), the half-life estimates indicate that heterogeneity and aggregation bias do not help to solve the PPP puzzle.

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February 2004.

Recently, Imbs et. al. (2002) have claimed that much of the purchasing power parity puzzle can be explained by aggregation bias'. This paper re-examines aggregation bias. First, it clarifies the meaning of aggregation bias and its applicability to the PPP puzzle. Second, the size of the bias' is shown to be much smaller than the simulations in Imbs et. al. (2002) suggest, if we rule out explosive roots in the simulations. Third, we show that the presence of non-persistent measurement error especially in the Imbs et. al. (2002) data can make price series appear less persistent than they really are. Finally, it is now standard to recognize that small-sample bias plagues estimates of speeds of convergence of PPP. After correcting small sample bias by methods proposed by Kilian (1998) and by So and Shin (1999), the half-life estimates indicate that heterogeneity and aggregation bias do not help to solve the PPP puzzle.