US non-farm payrolls data – the critical key ranges for estimates to watch

The September employment report is due from the US on Friday 4 October 2024 at 0830 US Eastern time, 1230 GMT.

Adam had a preview posted earlier:

• September non-farm payrolls preview by the numbers: Beware the seasonal pattern

And, GS:

• Goldman Sachs preview US nonfarm payroll data Friday, October 4: +165K /jobless rate 4.2%

You can see the consensus estimate in the screenshot below:

• The number in the right-most column is the ‘prior’ (previous month) result.
• The number in the column next to that, where there is a number, is the consensus median expected.

• This snapshot from the ForexLive economic data calendar, access it here.

Taking a look at the range of expectations compared to the median consensus (the ‘expected’ in the screenshot above) for the key data points:

Headline NFP number:

• 70,000 to 220,000

Unemployment rate:

• 4.1% to 4.3%

Average hourly earnings m/m:

• 0.2% to 0.4%

Average hourly earnings y/y:

• 3.7% to 3.9%

***

Why is knowledge of such ranges important?

Data results that fall outside of market low and high expectations tend to move markets more significantly for several reasons:

1. Surprise Factor: Markets often price in expectations based on forecasts and previous trends. When data significantly deviates from these expectations, it creates a surprise effect. This can lead to rapid revaluation of assets as investors and traders reassess their positions based on the new information.

2. Psychological Impact: Investors and traders are influenced by psychological factors. Extreme data points can evoke strong emotional reactions, leading to overreactions in the market. This can amplify market movements, especially in the short term.

3. Risk Reassessment: Unexpected data can lead to a reassessment of risk. If data significantly underperforms or outperforms expectations, it can change the perceived risk of certain investments. For instance, better-than-expected economic data may reduce the perceived risk of investing in equities, leading to a market rally.

4. Triggering of Automated Trading: In today’s markets, a significant portion of trading is done by algorithms. These automated systems often have pre-set conditions or thresholds that, when triggered by unexpected data, can lead to large-scale buying or selling.

5. Impact on Monetary and Fiscal Policies: Data that is significantly off from expectations can influence the policies of central banks and governments. For example, in the case of the NFP due today, a weaker jobs report will fuel speculation of more and perhaps larger Federal Open Market Committee (FOMC) rate cuts to come. A stronger report will diminish such expectations.

6. Liquidity and Market Depth: In some cases, extreme data points can affect market liquidity. If the data is unexpected enough, it might lead to a temporary imbalance in buyers and sellers, causing larger market moves until a new equilibrium is found.

7. Chain Reactions and Correlations: Financial markets are interconnected. A significant move in one market or asset class due to unexpected data can lead to correlated moves in other markets, amplifying the overall market impact.

This article was written by Eamonn Sheridan at www.forexlive.com.