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Alternative seasonal adjustments suggest an even larger slowdown in jobs growth

There are massive seasonal patterns in employment data. For example, in July, it is typical for the U.S. 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.

In my paper “Unseasonal Seasonals?,” I argue that a longer window should be used to estimate seasonal effects. 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.

I 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 108,000 jobs last month. The Bureau of Labor Statistics reported that the economy gained 126, 000 jobs last month. The discrepancies between the two series are explained in my paper.

Thousands of Jobs Added

BLS

Wright

2015-March

126

108

2015-February

264

265

2015-January

201

187

2014-December

329

332

2014-November

423

455

2014-October

221

237

2014-September

250

239

2014-August

213

215

2014-July

249

223

2014-June

286

282

2014-May

236

234

2014-April

330

336