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Brookings on Job Numbers

Alternative Seasonal Adjustments Confirm Slow and Steady Job Growth

There are massive seasonal patterns in employment data.  For example, in July, it is typical for the US economy to lose over a million jobs.  Adjusting for this normal seasonal variation is essential to interpreting month-to-month changes in employment.  The approach for this seasonal adjustment that is presently used by the Bureau of Labor Statistics (BLS) puts very heavy weight on the current and last two years of data in assessing what are the typical patterns for each month.

Jonathan Wright of Johns Hopkins University argues in “Unseasonal Seasonals?” that a longer window should be used to estimate seasonal effects.  He finds that using a different seasonal filter, known as the 3×9 filter, produces better results and more accurate forecasts.  The key difference in the 3×9 filter is that it spreads weight over the most recent six years in estimating seasonal patterns.  This makes the seasonal patterns more stable over time than in the current BLS seasonal adjustment method.

We calculate the month-over-month change in total nonfarm payrolls, seasonally adjusted by the 3×9 filter, for the most recent month.  The corresponding data as published by the BLS are shown for comparison purposes. According to the alternative seasonal adjustments, the economy gained 233 thousand jobs last month. The Bureau of Labor Statistics reported that the economy gained 214 thousand jobs last month. The discrepancies between the two series are explained in Dr. Wright’s BPEA paper.

Thousands of Jobs Added

BLS

Wright

2014-October

214

233

2014-September

256

249

Author

2014-August

203

207

2014-July

243

235

2014-June

267

262

2014-May

229

230

2014-April

304

309

2014-March

203

199

2014-February

222

251

2014-January

144

115

2013-December

84

90

2013-November

274

279

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