An Experimental Component Index for the CPI: From Annual Computer Data to Monthly Data on Other Goods
نویسنده
چکیده
The CPI component indices are obtained from comparing price quotes at a given store in different periods. If we omit comparisons from goods in the store in the initial, but not in the comparison, period we generate a selection bias: goods that exit are disproportionately obsolete goods that have falling prices. Building on Pakes (2003), we explain why standard hedonic predictions for second-period prices of exiting goods do not account for this bias. New hedonic methods are derived, shown to have desirable properties, and applied to three CPI samples where they generate significant selection corrections.
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