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Every month, the Bureau of Labor Statistics (BLS) releases employment data that frequently moves markets and shapes policy. Recently, the discussion of non-traditional or “alternative” economic or financial data has increased, especially after government shutdowns disrupted data collection. Many alternative datasets from the private sector may offer more depth and higher frequency reporting than government data.

 

Why does this matter? Jobs data provides critical insight into consumer spending, which accounts for roughly two-thirds of U.S. economic activity. It also offers a glimpse into potential future corporate earnings and the broader economic landscape. The ripple effects touch everything from Federal Reserve policy decisions to movements in currencies, equities and commodities.

Enter ADP: The Private Alternative

When considering alternative data, ADP's National Employment Report (NER) frequently appears on economic calendars and receives significant financial press attention. This raises the question: how does ADP's NER compare with the BLS Nonfarm Payroll (NFP) monthly employment updates?

ADP's advantage: As a global human capital management company, ADP gathers real-time payroll data from more than 500,000 firms covering over 26 million employees – approximately 20% of U.S. private employment. This aggregated data covers nonfarm private employment and is typically released two days before the BLS report, offering an early read on employment trends.

BLS's breadth: The BLS approach is survey-based, including approximately 121,000 private firms and government agencies ranging from small businesses to large corporations. Notably, firms with fewer than 20 employees represent about 45% of the BLS establishment survey, capturing small business hiring that larger payroll processors might miss.

Comparing the Data

Ultimately, both datasets are asking the same question: is the U.S. economy experiencing job expansion or contraction?

Despite different methodologies and data, the BLS and ADP data tend to trend in the same direction over the longer term – even when monthly reports diverge. 

Here's a distinction many overlook: The BLS publishes two datasets. One includes both private and government jobs (the headline number typically cited in the press) capturing about 22 million more workers on average than ADP. The second covers private sector jobs only. When comparing BLS private sector payrolls to ADP – a more logical "apples to apples" comparison – the gap shrinks significantly. On average, the second series captures only 1.26 million more workers thus allowing for a better comparison. 

The relationship between these datasets becomes clearer when examining rolling correlations over different time horizons. For example, a six-month rolling correlation shows significant variance, cycling between positive and negative correlations. This reflects the monthly noise that tends to generate conflicting headlines. In contrast, a five-year rolling correlation removes this noise and reveals a relatively consistent positive correlation over the longer term.

Viewing these rolling correlations through box-and-whisker plots illustrates the range of correlation values, along with their respective averages (X) and medians (line) for each time series. The pattern is clear: longer rolling correlations produce higher averages and medians with smaller variance.

The Takeaway

When paired with other employment metrics – such as the U3 unemployment rate (standard unemployment) or U6 (broader underemployment) – these datasets offer complementary economic insights valuable for understanding interest rates, Federal Reserve policy and potential market direction across equities, commodities and forex markets. 


 

 

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