Nber working papers api

NBER Working Papers and Data API

Overview

The National Bureau of Economic Research (NBER) is the leading U.S. economics research organization, publishing 1,200+ working papers annually by top economists. NBER papers are among the most cited in economics. The website provides structured access to working papers, researcher profiles, and macroeconomic datasets. Free metadata access; some full text requires subscription.

Working Papers Access

RSS/Atom Feeds

# Latest working papers feed
curl "https://www.nber.org/papers.rss"

# Papers by program
curl "https://www.nber.org/programs/ef/papers.rss"  # Economic Fluctuations
curl "https://www.nber.org/programs/ls/papers.rss"  # Labor Studies
curl "https://www.nber.org/programs/io/papers.rss"  # Industrial Organization

Working Paper Search

# Search via NBER website (HTML scraping needed)
curl "https://www.nber.org/api/v1/working_page_listing/contentType/working_paper/?page=1&perPage=20&q=inflation+expectations"

# Get specific paper metadata
curl "https://www.nber.org/api/v1/working_page_listing/contentType/working_paper/?page=1&perPage=1&q=w28104"

NBER Data Portal

# Macroeconomic history data
# Available at: https://data.nber.org/

# Business cycle dates
curl "https://data.nber.org/data/cycles/business_cycle_dates.json"

# CPS labor data extracts
# https://data.nber.org/cps/

NBER Programs

Code	Program	Focus
ef	Economic Fluctuations and Growth	Macro, business cycles
ls	Labor Studies	Employment, wages
io	Industrial Organization	Markets, competition
pe	Public Economics	Taxation, spending
he	Health Economics	Healthcare markets
de	Development Economics	Developing countries
if	International Finance	Exchange rates, capital flows
it	International Trade	Trade policy
me	Monetary Economics	Central banking
cf	Corporate Finance	Firm finance
ap	Asset Pricing	Financial markets
ed	Education	Education economics
ag	Aging	Demographics
ch	Children	Child welfare
le	Law and Economics	Legal institutions
env	Environment and Energy	Environmental policy
pol	Political Economy	Political institutions

Python Usage

import requests
from xml.etree import ElementTree


def get_latest_papers(program: str = None,
                      count: int = 20) -> list:
    """Get latest NBER working papers via RSS."""
    if program:
        url = f"https://www.nber.org/programs/{program}/papers.rss"
    else:
        url = "https://www.nber.org/papers.rss"

    resp = requests.get(url, timeout=30)
    resp.raise_for_status()

    root = ElementTree.fromstring(resp.content)
    papers = []
    for item in root.findall(".//item")[:count]:
        papers.append({
            "title": item.findtext("title", ""),
            "link": item.findtext("link", ""),
            "description": item.findtext("description", "")[:300],
            "pub_date": item.findtext("pubDate", ""),
        })
    return papers


def search_papers(query: str, page: int = 1,
                  per_page: int = 20) -> list:
    """Search NBER working papers."""
    resp = requests.get(
        "https://www.nber.org/api/v1/working_page_listing/"
        "contentType/working_paper/",
        params={"q": query, "page": page, "perPage": per_page},
        timeout=30,
    )
    resp.raise_for_status()
    data = resp.json()

    results = []
    for item in data.get("results", []):
        results.append({
            "title": item.get("title"),
            "authors": item.get("authors", ""),
            "number": item.get("wp_number", ""),
            "date": item.get("date", ""),
            "url": f"https://www.nber.org/papers/{item.get('wp_number', '')}",
            "abstract": item.get("description", "")[:300],
            "program": item.get("programs", []),
        })
    return results


def get_business_cycle_dates() -> list:
    """Get NBER official business cycle dates."""
    resp = requests.get(
        "https://data.nber.org/data/cycles/business_cycle_dates.json",
        timeout=30,
    )
    resp.raise_for_status()
    return resp.json()


# Example: latest macro working papers
papers = get_latest_papers(program="ef", count=5)
for p in papers:
    print(f"{p['title']}")
    print(f"  {p['link']}")

# Example: search for AI economics papers
results = search_papers("artificial intelligence labor market")
for r in results:
    print(f"[{r['number']}] {r['title']}")
    print(f"  Authors: {r['authors']}")

# Example: recession dates
cycles = get_business_cycle_dates()
for c in cycles[-3:]:
    print(f"Peak: {c.get('peak')} → Trough: {c.get('trough')}")

Key Datasets

Dataset	Description
Business Cycle Dates	Official US recession start/end dates
CPS Extracts	Current Population Survey labor data
Macrohistory Database	150 years of macro indicators
Patent Data	Patent citation and classification
Trade Data	Bilateral trade statistics

References

• NBER
• NBER Working Papers
• NBER Data
• NBER Programs