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Spurious seasonal patterns and excess smoothness in the BLS local area unemployment

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Listed:
  • Keith R. Phillips
  • Jianguo Wang

Abstract

State 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.

Suggested Citation

  • Keith R. Phillips & Jianguo Wang, 2013. "Spurious seasonal patterns and excess smoothness in the BLS local area unemployment," Working Papers 1305, Federal Reserve Bank of Dallas.
  • Handle: RePEc:fip:feddwp:1305
    DOI: 10.24149/wp1305
    Note: Published as: Phillips, Keith and Jianguo Wang (2014), "A note on spurious seasonal patterns and other distortions in the BLS local area unemployment statistics," Journal of Economic and Social Measurement 39 (3): 145-152.
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    File URL: http://www.dallasfed.org/assets/documents/research/papers/2013/wp1305.pdf
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    Keywords

    Business; cycles;

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