--- license: other license_name: public-domain-source-us-government pretty_name: "US Macro Data: Productivity" language: - en tags: - finance - economics - macroeconomics - time-series - fred - productivity - quant - backtesting size_categories: - n<1K configs: - config_name: long data_files: data/long.parquet default: true - config_name: wide_quarterly data_files: data/wide_quarterly.parquet --- # US macro data: Productivity (137 series) 137 productivity series from US government sources, cleaned into one consistent format and ready for pandas. This free package holds the **last 12 months** (2025-11-03 on) of each series' latest values. It is refreshed weekly. ```python import pandas as pd df = pd.read_parquet("hf://datasets/FinzData/macro-productivity/data/long.parquet") # series_id, date, value wide = pd.read_parquet("hf://datasets/FinzData/macro-productivity/data/wide_quarterly.parquet") # one column per series ``` or `datasets.load_dataset("FinzData/macro-productivity")`. Wide tables by frequency: `wide_quarterly` (137 series). `series.csv` lists every series with its title, units, frequency and how far back the full history goes. ## The full history, point in time, through one API The FinzData API serves every series back to its first observation, **every revision** (what was known on any past date, so backtests do not peek at later revisions), and **daily updates**, in the same format: ```python import finzdata as fz # pip install finzdata c = fz.Client() # free API key: https://api.finzdata.com/ c.macro("PRS85006152") # full history, latest values c.macro("PRS85006152", vintage="first") # as first released c.macro("PRS85006152", as_of="2020-03-01") # exactly what was known on that date c.macro_series(category="productivity") # the catalogue for this category ``` ## Most-watched series in this package | ID | Title | Units | Frequency | Full history from | |---|---|---|---|---| | `PRS85006152` | Nonfarm Business Sector: Real Hourly Compensation for All Workers | Percent Change at Annual Rate | Quarterly | 1947 | | `RPSGENAITSIND10` | Generative Artificial Intelligence, Time Savings: Finance and Insurance | Percent | Quarterly | 2024 | | `PRS85006101` | Nonfarm Business Sector: Hourly Compensation for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1948 | | `PRS85006151` | Nonfarm Business Sector: Real Hourly Compensation for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1948 | | `PRS84006032` | Business Sector: Hours Worked for All Workers | Percent Change at Annual Rate | Quarterly | 1947 | | `PRS30006032` | Manufacturing Sector: Hours Worked for All Workers | Percent Change at Annual Rate | Quarterly | 1987 | | `PRS84006092` | Business Sector: Labor Productivity (Output per Hour) for All Workers | Percent Change at Annual Rate | Quarterly | 1947 | | `PRS85006102` | Nonfarm Business Sector: Hourly Compensation for All Workers | Percent Change at Annual Rate | Quarterly | 1947 | | `PRS30006151` | Manufacturing Sector: Real Hourly Compensation for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1988 | | `PRS84006162` | Business Sector: Output per Worker for All Workers | Percent Change at Annual Rate | Quarterly | 1947 | | `PRS85006161` | Nonfarm Business Sector: Output per Worker for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1948 | | `RPSGENAITSIND4` | Generative Artificial Intelligence, Time Savings: Manufacturing | Percent | Quarterly | 2024 | | `RPSGENAITSIND9` | Generative Artificial Intelligence, Time Savings: Information | Percent | Quarterly | 2024 | | `RPSGENAITSOCC3` | Generative Artificial Intelligence, Time Savings: Computer and Mathematical Occupations | Percent | Quarterly | 2024 | | `PRS30006011` | Manufacturing Sector: Employment for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1988 | | `PRS30006021` | Manufacturing Sector: Average Weekly Hours for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1988 | | `PRS31006011` | Manufacturing, Durable Goods Sector: Employment for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1988 | | `PRS85006162` | Nonfarm Business Sector: Output per Worker for All Workers | Percent Change at Annual Rate | Quarterly | 1947 | | `PRS88003091` | Nonfinancial Corporations Sector: Labor Productivity (Output per Hour) for Employees | Percent Change from Quarter One Year Ago | Quarterly | 1948 | | `RPSGENAITSIND12` | Generative Artificial Intelligence, Time Savings: Professional, Scientific, and Technical Services | Percent | Quarterly | 2024 | | `PRS30006161` | Manufacturing Sector: Output per Worker for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1988 | | `PRS30006162` | Manufacturing Sector: Output per Worker for All Workers | Percent Change at Annual Rate | Quarterly | 1987 | | `PRS84006102` | Business Sector: Hourly Compensation for All Workers | Percent Change at Annual Rate | Quarterly | 1947 | | `PRS84006151` | Business Sector: Real Hourly Compensation for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1948 | | `PRS84006152` | Business Sector: Real Hourly Compensation for All Workers | Percent Change at Annual Rate | Quarterly | 1947 | All 137 series: `series.csv`. Browse them at https://finzdata.com/macro/category/productivity. ## More from FinzData - Every macro category: https://huggingface.co/FinzData ยท index on GitHub: https://github.com/FinzData/macro-data - Survivorship-free US stock prices since 2000, COT positioning, 13F holdings, insider trades, short interest - Pricing (history bundles from $195 once): https://finzdata.com/pricing - Python client (open source): https://github.com/FinzData/finzdata-python Source: U.S. government agencies via FRED/ALFRED (Federal Reserve Bank of St. Louis). Compiled by FinzData. Data for research, not investment advice.