---
ticker: "USIP"
title: "U.S. Industrial Production Index"
unit: "index"
frequency: "Monthly"
source: "Fabricant (1940); Persons (1923)"
release: "Updated Monthly"
category: "Real Activity & Business Cycle"
country: "US"
language: "en"
canonical: "https://kred.dev/en/series/USIP"
license: "https://creativecommons.org/licenses/by-nc-nd/4.0/"
latest_value: 102.99
latest_date: "2026-07-01"
first_date: "1960-01-01"
observations_total: 799
observations_shown: 120
---

# U.S. Industrial Production Index

## Overview

Combines the physical output of mining, manufacturing, and utilities into a monthly index on a 2017 base.

## Key Figures

|  | Value | Date |
|---|---|---|
| Latest | 102.99 | 2026-07-01 |
| Change from previous | +0.21 | 2026-06-01 |
| Change over one year | +1.10 | 2025-07-01 |
| Highest on record | 104.10 | 2018-09-01 |
| Lowest on record | 22.13 | 1960-12-01 |
| Period covered | 1960-01-01 – 2026-07-01 |  |
| Observations | 799 |  |

## Recent observations

| Date | Value | Change |
|---|---|---|
| 2016-08-01 | 98.85 | -0.15 |
| 2016-09-01 | 98.75 | -0.10 |
| 2016-10-01 | 98.76 | +0.02 |
| 2016-11-01 | 98.35 | -0.41 |
| 2016-12-01 | 99.02 | +0.67 |
| 2017-01-01 | 98.76 | -0.26 |
| 2017-02-01 | 98.36 | -0.40 |
| 2017-03-01 | 99.01 | +0.65 |
| 2017-04-01 | 100.02 | +1.01 |
| 2017-05-01 | 100.14 | +0.12 |
| 2017-06-01 | 100.35 | +0.21 |
| 2017-07-01 | 100.11 | -0.24 |
| 2017-08-01 | 99.69 | -0.41 |
| 2017-09-01 | 99.80 | +0.10 |
| 2017-10-01 | 101.02 | +1.23 |
| 2017-11-01 | 101.27 | +0.24 |
| 2017-12-01 | 101.46 | +0.20 |
| 2018-01-01 | 101.46 | 0.00 |
| 2018-02-01 | 101.71 | +0.25 |
| 2018-03-01 | 102.21 | +0.50 |
| 2018-04-01 | 103.33 | +1.13 |
| 2018-05-01 | 102.40 | -0.93 |
| 2018-06-01 | 103.20 | +0.80 |
| 2018-07-01 | 103.36 | +0.17 |
| 2018-08-01 | 104.03 | +0.67 |
| 2018-09-01 | 104.10 | +0.07 |
| 2018-10-01 | 103.99 | -0.11 |
| 2018-11-01 | 104.07 | +0.08 |
| 2018-12-01 | 104.09 | +0.03 |
| 2019-01-01 | 103.40 | -0.69 |
| 2019-02-01 | 102.84 | -0.56 |
| 2019-03-01 | 102.88 | +0.04 |
| 2019-04-01 | 102.27 | -0.60 |
| 2019-05-01 | 102.39 | +0.12 |
| 2019-06-01 | 102.44 | +0.05 |
| 2019-07-01 | 101.94 | -0.50 |
| 2019-08-01 | 102.64 | +0.70 |
| 2019-09-01 | 102.29 | -0.35 |
| 2019-10-01 | 101.43 | -0.86 |
| 2019-11-01 | 101.94 | +0.51 |
| 2019-12-01 | 101.70 | -0.24 |
| 2020-01-01 | 101.03 | -0.67 |
| 2020-02-01 | 101.37 | +0.34 |
| 2020-03-01 | 97.41 | -3.97 |
| 2020-04-01 | 84.56 | -12.85 |
| 2020-05-01 | 85.96 | +1.40 |
| 2020-06-01 | 91.59 | +5.63 |
| 2020-07-01 | 95.03 | +3.43 |
| 2020-08-01 | 95.95 | +0.93 |
| 2020-09-01 | 95.97 | +0.01 |
| 2020-10-01 | 96.74 | +0.77 |
| 2020-11-01 | 97.08 | +0.34 |
| 2020-12-01 | 98.36 | +1.28 |
| 2021-01-01 | 98.88 | +0.52 |
| 2021-02-01 | 95.61 | -3.27 |
| 2021-03-01 | 98.39 | +2.77 |
| 2021-04-01 | 98.56 | +0.17 |
| 2021-05-01 | 99.43 | +0.87 |
| 2021-06-01 | 99.80 | +0.37 |
| 2021-07-01 | 100.25 | +0.45 |
| 2021-08-01 | 100.04 | -0.21 |
| 2021-09-01 | 98.86 | -1.19 |
| 2021-10-01 | 100.19 | +1.33 |
| 2021-11-01 | 100.87 | +0.68 |
| 2021-12-01 | 100.57 | -0.29 |
| 2022-01-01 | 100.19 | -0.39 |
| 2022-02-01 | 100.81 | +0.62 |
| 2022-03-01 | 101.39 | +0.58 |
| 2022-04-01 | 101.44 | +0.05 |
| 2022-05-01 | 101.33 | -0.11 |
| 2022-06-01 | 101.02 | -0.32 |
| 2022-07-01 | 101.22 | +0.20 |
| 2022-08-01 | 101.10 | -0.13 |
| 2022-09-01 | 101.29 | +0.20 |
| 2022-10-01 | 101.25 | -0.04 |
| 2022-11-01 | 100.96 | -0.30 |
| 2022-12-01 | 99.77 | -1.19 |
| 2023-01-01 | 100.50 | +0.74 |
| 2023-02-01 | 100.64 | +0.14 |
| 2023-03-01 | 101.02 | +0.38 |
| 2023-04-01 | 101.25 | +0.23 |
| 2023-05-01 | 100.93 | -0.32 |
| 2023-06-01 | 100.12 | -0.81 |
| 2023-07-01 | 100.91 | +0.79 |
| 2023-08-01 | 100.84 | -0.07 |
| 2023-09-01 | 101.02 | +0.18 |
| 2023-10-01 | 100.47 | -0.55 |
| 2023-11-01 | 100.86 | +0.39 |
| 2023-12-01 | 100.60 | -0.26 |
| 2024-01-01 | 99.22 | -1.38 |
| 2024-02-01 | 100.28 | +1.06 |
| 2024-03-01 | 100.46 | +0.17 |
| 2024-04-01 | 100.24 | -0.21 |
| 2024-05-01 | 100.86 | +0.62 |
| 2024-06-01 | 100.89 | +0.03 |
| 2024-07-01 | 99.98 | -0.92 |
| 2024-08-01 | 100.43 | +0.46 |
| 2024-09-01 | 99.81 | -0.62 |
| 2024-10-01 | 99.47 | -0.34 |
| 2024-11-01 | 99.29 | -0.18 |
| 2024-12-01 | 100.33 | +1.03 |
| 2025-01-01 | 100.06 | -0.26 |
| 2025-02-01 | 101.10 | +1.03 |
| 2025-03-01 | 101.04 | -0.06 |
| 2025-04-01 | 101.13 | +0.09 |
| 2025-05-01 | 100.97 | -0.16 |
| 2025-06-01 | 101.48 | +0.51 |
| 2025-07-01 | 101.89 | +0.42 |
| 2025-08-01 | 101.62 | -0.27 |
| 2025-09-01 | 101.67 | +0.04 |
| 2025-10-01 | 101.22 | -0.45 |
| 2025-11-01 | 101.03 | -0.19 |
| 2025-12-01 | 101.49 | +0.46 |
| 2026-01-01 | 101.04 | -0.46 |
| 2026-02-01 | 101.91 | +0.87 |
| 2026-03-01 | 101.75 | -0.15 |
| 2026-04-01 | 102.52 | +0.77 |
| 2026-05-01 | 102.51 | -0.01 |
| 2026-06-01 | 102.79 | +0.28 |
| 2026-07-01 | 102.99 | +0.21 |

## Definition

USIP is the seasonally adjusted index of industrial production recorded exactly as compiled, without transformation, and KRED ingests and stores this quantity series with no further processing. The index is the monthly index-number level (2017 = 100) of a volume index expressing the physical output of the mining, manufacturing, and utility industries, so its movements reflect changes in the quantity produced rather than in prices.

The index belongs to the index-number tradition founded on base-weighted and current-weighted aggregation (Laspeyres 1871; Paasche 1874). The test approach and the ideal index systematized that aggregation (Fisher 1922), and the atomistic, functional, and statistical accounts of index measurement organized it (Frisch 1936).

The industry-by-industry physical-output index gave the index of industrial production its modern form (Fabricant 1940), and many activity series are combined, detrended, and standardized into composite measures of production (Persons 1923).

This volume concept sits inside the national-income boundary (Kuznets 1941), a boundary fixed by double-entry social accounting (Stone 1947; Meade and Stone 1941), and the output index serves as the high-frequency physical-volume counterpart to the production account.

A fixed-base volume index is read against continuous-time and log-change aggregators (Divisia 1925; Törnqvist 1936), superlative index numbers refine it (Diewert 1976), and annual chain-linking updates the weights behind it (Hill 1988), the index itself being one of the activity series whose comovement defines the reference cycle (Burns and Mitchell 1946).

## Methodology

KRED applies no transformation to USIP and stores the monthly value as recorded, performing none of rescaling, deflating, smoothing, or annualizing. The underlying series is itself seasonally adjusted at compilation, so calendar and seasonal regularities are removed before the number is finalized, and the raw passthrough and the prior seasonal adjustment therefore hold together without contradiction for the same monthly figure.

The measurement basis by which the figure comes to exist is the volume index number, in which industry output relatives are weighted by base-period value shares. This weighting begins from the base-weighted definition and is complemented by the current-weighted form (Laspeyres 1871; Paasche 1874), and the true index is bounded between the two (Fisher 1922). For flexible production technologies the exact translog aggregate justifies the approach (Diewert 1976).

The physical-output index carries its own deflation and quantity-relative procedure (Fabricant 1940), and the industry quantity relatives are aggregated in the atomistic and functional manner described (Frisch 1936; Divisia 1925) and expressed in share-weighted log changes (Törnqvist 1936).

Modern compilation, anchored at 2017 = 100, follows the annual chain-linking of such volume measures, a refinement of the fixed-base scheme (Hill 1988).

The index is positioned within the production account. Consistency rules codified that account (Stone 1947; Meade and Stone 1941), reliability bounds were framed for it (Stone, Champernowne, and Meade 1942), and the index sits within the activity boundary (Kuznets 1941). KRED performs no price deflation, smoothing, rescaling, or annualization beyond what this compilation framework already embeds.

## Applications in Economics

USIP is a core coincident indicator of the production side of the cycle, and as one of the activity series that move together it is used to date the expansion and contraction phases (Burns and Mitchell 1946). Such series are folded into composite barometers of business conditions (Persons 1923; Moore 1961), individual indicators are classified as leading, coincident, or lagging (Mitchell and Burns 1938), turning points are identified by reproducible algorithm (Bry and Boschan 1971), and the measurement and timing properties of the indicator system are catalogued (Zarnowitz 1992).

The index of industrial production has long been read as the highest-frequency gauge of real output between the quarterly accounts (Fabricant 1940), and the monthly reading is treated as a current-conditions signal (Shiskin 1961).

Because it measures quantity rather than value, the index isolates volume movements inside the production boundary (Kuznets 1941), while latent-state representations treat the monthly activity series as observations on one common cycle (Stock and Watson 1989; Stock and Watson 1991).

The fixed-base volume concept lets analysts compare output across periods on a constant-quantity basis (Laspeyres 1871), yet such atheoretical measurement acquires meaning only against an explicit model (Koopmans 1947), and the figure remains an estimate carrying measurement error (Stone, Champernowne, and Meade 1942).

## Applications in Financial Markets

In markets USIP serves as a real-time read on the manufacturing cycle, feeding cyclical asset allocation, earnings expectations for industrial and export sectors, and the growth leg of monetary-policy expectations. Traders use the index as a turning-point signal, grounded in the reference-cycle framework and the composite-indicator tradition (Burns and Mitchell 1946; Moore 1961; Zarnowitz 1992), given a reproducible form by turning-point algorithms (Bry and Boschan 1971), with the monthly construction filling the gap between the quarterly accounts (Shiskin 1961).

As a volume measure in the index-number sense the figure can be compared cleanly across data vintages (Laspeyres 1871; Paasche 1874; Fisher 1922), a comparability underpinned by superlative refinement and chain-linking (Diewert 1976; Hill 1988), which matters when positioning around data releases.

The physical-output composition makes the series sensitive to industrial demand (Fabricant 1940), and because that output sits inside the production account, fixed-income and equity desks connect the print to the wider growth picture (Kuznets 1941), while single-index representations translate the same reading into one cycle variable (Stock and Watson 1991).

The form most relevant to trading is the period-on-period output growth rate, and the log-change aggregation and continuous-time view frame how that growth rate is read off the level index (Törnqvist 1936; Divisia 1925).

## Statistical Tests

USIP is a seasonally-adjusted-at-source industrial-production index, and its published level is the statistical object. The sample is 796 monthly observations spanning 1960-01 to 2026-04, and the unit-root triplet is fitted on the level with a constant and trend.

The augmented Dickey-Fuller regression of Dickey and Fuller (1979), in the lag-augmented form of Said and Dickey (1984), fails to reject the unit root at p = 0.5345, the nonparametric test of Phillips and Perron (1988) concurs at p = 0.6939, and the stationarity-null test rejects trend stationarity at p < 0.01 (Kwiatkowski et al. 1992), so all three procedures agree on a clean I(1) classification. The GLS-detrended escalation of Elliott, Rothenberg, and Stock (1996) and the modified-criterion lag selection of Ng and Perron (2001) are reserved for ambiguous outcomes under the house protocol and are not invoked on this clean reading.

Because the level is I(1), the portmanteau and the break search are run on its first difference, since a level portmanteau reads the near-unit autocorrelation of a stochastic trend and a level mean-break search spuriously segments it (Perron 1989; Hamilton 2018; Bai and Perron 1998). The portmanteau statistic of Ljung and Box (1978), refining the form of Box and Pierce (1970), rejects the white-noise null on the differenced series with Q = 73.5759 at twelve lags and Q = 90.607 at twenty-four lags, both at p = 0.000, while the multiple-break procedure of Bai and Perron (1998), computed by the dynamic-programming algorithm of Bai and Perron (2003), finds no break in the mean of the differenced series.

The seasonal battery is run with the interpretation that any seasonal reading reflects the adjustment applied at source rather than a property KRED identifies. The seasonal-unit-root test of Hylleberg et al. (1990), with the monthly mechanics of Beaulieu and Miron (1993), rejects unit roots at the seasonal frequencies with a statistic of 1351.5342 at p = 0.000, so no stochastic seasonality remains, and the seasonal dummies on the first difference are not jointly significant with F = 0.7792 at p = 0.661172, so no deterministic seasonal mean survives. The seasonal-lag portmanteau on the first difference nonetheless rejects with a statistic of 90.607 at p = 0.000, so autocorrelation at the seasonal lags of the differenced series remains, and because that statistic is the same one the twenty-four-lag portmanteau reports it does not isolate a specifically seasonal channel. The joint reading therefore differs from the seasonally adjusted designation carried at source and is reported as a property of that adjustment rather than as a seasonal pattern KRED identifies, read alongside the stationary-seasonality frame of Canova and Hansen (1995) and the seasonal-adjustment literature (Ghysels and Osborn 2001).

## Frequently Asked Questions

### What do the US business cycle indicators cover?

United States real output, industrial production, the published unemployment-gap rule reading and the published business conditions index, all carried as released.

### Is the US ADS business conditions index a KRED estimate?

No. It is a passthrough of the index its original authors publish. KRED separately estimates business conditions for Korea, but the two are distinct series produced by different parties for different economies.

### Does KRED process the US industrial production index further?

None. Several of these are seasonally adjusted at source and KRED applies no further treatment to any of them.