# How Reliable Are Initial US Nonfarm Payrolls: Standard Chartered Analysis Highlights Major Revision Gaps

> A study by Standard Chartered economist Dan Pan reveals that initial US NFP releases in April and November are the most accurate, whereas January and May suffer from the largest subsequent revisions.

**Type:** article · **Category:** Market · **Published:** 2026-10-07 · **Source:** TrendKia
**Canonical:** https://trendkia.com/en/market/us-nonfarm-payrolls-ke-shuruati-ankare-kitane-bharosemnda-standard-chartered-ke-shodha-men-bare-antara-ka-khulasa-44659 · **Language:** English
**Tags:** Nonfarm Payrolls, US Dollar, Standard Chartered, Interest Rates, Crude Oil, Gold, finance

Financial markets across the globe treat the US Nonfarm Payrolls (NFP) report as the gold standard for judging the underlying momentum of the world's largest economy. Whether determining the trajectory of Federal Reserve interest rate policy, charting the course of the US Dollar, or setting the benchmark for Treasury yields, the monthly jobs report consistently sparks significant volatility. However, the initial figures released on the first Friday of each month often undergo substantial revisions in later benchmark updates. Dan Pan, an economist at Standard Chartered, examined the reliability of preliminary NFP figures across the calendar year to identify which months offer the truest signals and which ones warrant heavy caution.

## April and November Deliver the Most Accurate Initial Signals
By comparing initial releases with subsequent benchmark revisions using mean absolute error (MAE) metrics, Dan Pan identified clear seasonal differences in data reliability. April and November emerged as the standout performers, delivering initial estimates closest to the final reality. On a single-month basis, April recorded the lowest MAE of any month on the calendar. Furthermore, when evaluated on a three-month moving average (3mma) basis, April still maintained the second-lowest MAE overall.

November also demonstrated a low MAE on a single-month basis, although its measurement accuracy has shown some degradation in the post-pandemic period. As Dan Pan noted, when evaluating which months feature preliminary numbers that match final estimates most closely, April and November stand out. These months provide relatively clean readings where seasonal noise and reporting distortions remain contained, allowing market participants to take initial prints with greater confidence.

## January, September, March, and May Face Severe Revision Risks
In stark contrast to the stability seen in spring and late autumn, several months consistently produce preliminary reports that diverge dramatically from final benchmarked figures. Dan Pan found that January, September, March, and May register the largest revisions across the board. The divergence is substantial, with the least reliable months recording MAEs that are nearly twice as high as those found in the most dependable months.

Dan Pan highlighted this gap directly, warning investors that trading on early surprises during these volatile months carries substantial risk. Seasonal adjustments around the turn of the year, corporate hiring cycles, and back-to-school employment shifts often inject significant measurement noise into early data collections. Consequently, trading aggressively on knee-jerk surprises in January or May frequently leads to miscalculations once the comprehensive benchmark revisions are applied.

## Three-Month Moving Averages Still Carry Built-In Biases
To smooth out single-month noise, market participants frequently turn to three-month moving averages. Dan Pan confirmed that MAEs are indeed lower on a 3mma basis than on a single-month basis, largely because statistical errors occurring in one month tend to cancel out in the subsequent release. Nevertheless, substantial disparities between specific calendar windows persist even under smoothed measures.

On a 3mma basis, April, July, and October present the highest degree of reliability, while January, May, and September rank as the least dependable. The analytical spread between the top and bottom tiers remains wide. Dan Pan observed that the three-month moving averages for January and May often overstate the true employment trend because they absorb upward biases accumulated over preceding reporting periods. While pre-pandemic NFP releases frequently understated employment growth, an overstatement bias has become increasingly common in the post-pandemic era.

## Surging Treasury Yields Propel the US Dollar Across Forex Pairs
Beyond employment data methodology, currency and debt markets continue to digest broader macroeconomic pressures. A fresh advance in US Treasury yields has revived appetite for the US Dollar, drawing dip-buyers into the greenback amid lingering geopolitical uncertainties. This dynamic has weighed heavily on the Australian Dollar, with AUD/USD struggling to extend its recent recovery and trading with a negative bias below 0.7000 during Wednesday's Asian session. Firm expectations surrounding a hawkish Reserve Bank of Australia (RBA) have failed to counter the broader strength of the US Dollar, leaving traders waiting on the upcoming FOMC Minutes.

Concurrently, USD/JPY hovered near a one-and-a-half-week peak around 158.50 during Asian trading on Wednesday. The currency pair has been bolstered by a combination of dovish signals from Bank of Japan (BoJ) officials and renewed US Dollar purchases driven by rising US bond yields. Bullish traders are closely monitoring the 200-day Simple Moving Average (SMA) hurdle to gauge whether conditions support further gains ahead of the FOMC Minutes release.

## Gold Slides by 1.20% as Brent Crude Crosses $102
The resumption of the rally in the US Dollar and Treasury yields exerted immediate pressure on traditional safe havens. Gold prices declined by nearly 1.20%, with investors cutting exposure while awaiting the FOMC Minutes for clear hints regarding whether policymakers will deliver another interest rate increase before the year concludes. Broad risk sentiment weakened progressively through Wednesday, reflected in deepening sell-offs across European equity indices.

Energy markets moved higher against this backdrop of geopolitical anxiety, with Brent crude oil pushing above $102 per barrel. Looking at live market data for US Crude Oil (CL=F), the commodity trades at $90.12, marking a gain of 0.76% from its previous close of $89.44, within a 52-week trading range of $54.98 to $119.48. Its 14-day RSI sits at 46 and the MACD stands at -0.21 against a signal line of 0.91. Immediate technical levels place primary resistance at $90.71 and $91.30, while key support zones are situated at $89.43 and $88.74.

## Digital Assets Face Pullbacks While the ECB Confronts Policy Dilemmas
The cryptocurrency space has similarly experienced a broad retreat. Bitcoin entered a corrective phase following heavy selling pressure and supply resistance near the $87,200 threshold. Other major tokens followed suit, with Ethereum edging down toward key support around $2,600, while Ripple extended its downward leg into the $1.45 demand territory.

Meanwhile, monetary officials in Europe confront an increasingly thorny environment. Under normal economic conditions, the European Central Bank (ECB) would counter inflation running at nearly double its target through straightforward interest rate hikes. However, recent developments in fixed-income markets have complicated that equation. The bond market has effectively enacted a portion of the policy tightening on its own through higher yields, leaving the ECB navigating a precarious policy dilemma between taming price pressures and avoiding unnecessary economic strain.

## What this means for you
Significant revisions in US employment data and the resurgence of the US Dollar directly influence currency valuations, global commodity costs, and investment portfolios.

- **Currency and Import Expenses:** Renewed strength in the US Dollar puts downward pressure on foreign currencies worldwide. This dynamic can raise the cost of dollar-denominated imports, overseas education, and foreign travel for households.
- **Gold and Jewellery Consumers:** Rising US bond yields and a firmer greenback have triggered a pullback in precious metals. If bullion remains subdued, domestic buyers and retail jewellery consumers could see more favourable price levels.
- **Energy and Fuel Costs:** Brent crude climbing above $102 per barrel threatens to lift transportation and manufacturing expenses globally. Sustained elevated energy prices typically filter into higher domestic logistics and retail fuel costs over time.
- **Equity and Crypto Investors:** Trading aggressively on preliminary jobs data during high-revision months like January and May carries substantial downside risk. Market participants should wait for benchmark confirmations before repositioning large allocations.

## Why this happened
Discrepancies in preliminary payroll data stem from sampling response lags, evolving seasonal adjustments, and statistical biases inherent in real-time economic reporting.

- **Survey Reporting Lags:** Initial NFP figures released on the first Friday of each month rely on incomplete establishment sample returns. As comprehensive payroll data trickles in from employers over subsequent weeks, government statisticians must issue large benchmark revisions.
- **Seasonal Adjustments and Accumulated Bias:** Months like January and May coincide with major shifts in seasonal hiring, holiday transitions, and workforce turnover. Accumulated upward biases from previous months often lead moving averages to overstate the underlying labour strength.
- **Bond Yield Momentum and Policy Divergence:** A fresh surge in US Treasury yields alongside geopolitical friction has channeled international capital into the US Dollar. Dovish stances from the Bank of Japan and tightening dilemmas at the European Central Bank have further reinforced dollar dominance.

## Questions & Answers

### 1. Which NFP months provide the most accurate initial figures according to Standard Chartered?
According to the analysis, April and November deliver the most dependable initial releases, recording the lowest mean absolute errors relative to benchmark data.

### 2. Which months experience the largest revisions in US employment data?
January, September, March, and May see the largest subsequent revisions, with error rates nearly double those of the most reliable months.

### 3. Which months are most reliable on a three-month moving average basis?
On a three-month moving average basis, April, July, and October prove to be the most accurate, whereas January, May, and September rank lowest.

### 4. What is driving the renewed advance in the US Dollar?
The US Dollar has been supported by a fresh leg up in Treasury yields alongside safe-haven demand stemming from geopolitical uncertainty.

### 5. How have crude oil and gold prices reacted to recent market shifts?
Brent crude climbed above $102 per barrel, while gold dropped nearly 1.20% under pressure from rising US yields and a stronger greenback.

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