Spurious seasonal patterns and excess smoothness in the BLS local area unemployment
AbstractState level unemployment statistics are some of the most important and widely used data sources for local analysts and public officials to gauge the health of their state’s economy. We find statistically significant seasonal patterns in the state level seasonally adjusted Local Area Unemployment Statistics (LAUS) released by the U.S. Bureau of Labor Statistics (BLS). We find that the pro-rata factors used in the benchmarking process can invoke spurious seasonal patterns in this data. We also find that the Henderson 13 filter used by the BLS to smooth the seasonally adjusted data may reduce monthly volatility too much in the sense that the aggregated state data is much smoother than the independently estimated national data. To reduce these problems, we suggest that the BLS use seasonally adjusted data when benchmarking regions to national totals.
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Bibliographic InfoPaper provided by Federal Reserve Bank of Dallas in its series Working Papers with number 1305.
Date of creation: 2013
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