Empire State Manufacturing Survey: New orders: Current (increase vs decrease; diffusion index; percentage points; seasonally unadjusted) - United States - NY FED - Monthly
This series is part of the dataset: Empire State Manufacturing Survey (NY FED)
Download Full Dataset (.xlsx)Latest updates. According to survey data about NY-based manufacturers, the seasonally unadjusted diffusion index for new orders (share of CEOs seeing a recent increase minus share reporting a decrease) was -9.8 in September 2025, versus 7.3 in August 2025.
Sample. This montly series has 291 records in total. The time period covered by the series extends from July 2001 to September 2025.
History. Have a look at a few statistics we calculated on the full sample: the diffusion index recorded a bottom of -60.6 in April 2020; it recorded a maximum of 48.3 in May 2004; it was equal on average to 5.9.
Latest values
| Date | Value - Percentage points |
|---|---|
| 2025-07-31 | -2.8 |
| 2025-08-31 | 7.3 |
| 2025-09-30 | -9.8 |
Tip. Our metadata often comprise links to the original sources of the data we provide. You can use these links to find more details.
Not for investment purposes. Any data released on this web site are not intended for investment purposes or any other financial decision. Users should consult expert advice and do independent analysis before pledging money to any investment.
Series Metadata
| Field | Value |
|---|---|
| Description | Diffusion index for the question: Did new orders increase or decrease in the past month? |
| Country | United States |
| Economic concept | Business survey response |
| Data type | Coincident indicator of the business cycle |
| Deflation method | Not applicable |
| Seasonally adjusted | No |
| Rescaling | None |
| Frequency | Montly |
| Unit | Percentage points |
| Source | Federal Reserve Bank of New York |
| Source type | Central bank |
| Data licence | Free use subject to conditions |
| Measure type | Diffusion index (share of respondents reporting an increase minus share reporting a decrease) |
Series in the same data set
Discover the other time series included in this data set.