Curated Measure
1,106
208

Political Risk and Sentiment

Last updated Jan 12, 2026 9 series in this Curated Measure

At a glance:

Political Risk and Sentiment

Coverage

Public firms, 80+ countries, 2002-present.

Methodology and data

Granularity

Earnings-call level (firm-panel export: one row per call).

Source

LSEG earnings-call transcripts (English).

Update schedule
Last updated Jan 12, 2026. Update frequency:

Quarterly

Export shape

Time-series aggregates; firm-panel call-level rows.

Access

Free preview; exports depend on plan.

Access details Pricing

Overview

Political Risk (PRisk) and Sentiment (PSentiment) tracks when companies discuss political issues as a source of uncertainty -- and whether they frame those political developments as net positive or net negative.

The Curated Measure contains two core signals:

  • PRisk: how intensely call participants discuss political matters in the context of risk or uncertainty. Higher PRisk means more of the conversation is devoted to political risks that could affect the firm.
  • PSentiment: the net tone of political discussion (positive vs. negative) in those same political passages. Positive values indicate a more favorable framing; negative values indicate a more adverse framing.

In addition to the overall series, we provide topic-based PRisk that decomposes political risk into eight policy areas: Economy, Trade, Tax, Security, Institutions, Health, Environment, and Technology.

Common applications include:

  • Identifying which firms are most exposed to political uncertainty at a point in time (and how that changes).
  • Studying how political risk relates to investment, hiring, guidance, or volatility.
  • Separating "politics is uncertain" (PRisk) from "politics is good/bad for us" (PSentiment).
  • Pinpointing what kind of political risk is driving attention (e.g., trade vs. tax vs. regulation/institutions).
  • Building sector- or country-level aggregates from firm-level signals while preserving firm heterogeneity.

Why it matters

Political events often matter most through firm-specific channels -- regulatory exposure, procurement dependence, licensing, cross-border supply chains, and industry-specific policy. Traditional measures tend to be slow-moving or too aggregate to reveal which firms are actually affected.

This dataset captures political risk as expressed by decision-makers and analysts in real time, namely what they choose to talk about when discussing outlook, operations, and constraints.

Explore the data

This measure includes 9 related series. Use the filter to find a series, select it to update the chart, and open Details for full query and methodology notes.

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over time

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Mean number of sentences per earnings call containing a query keyword and a synonym for risk. Smoothed with a 4-period moving average.

How to read this chart

This time-series chart shows the mean number of sentences per earnings call containing a query keyword and a synonym for risk. Smoothed with a 4-period moving average.

Interpretation:

  • Higher values mean call participants devoted more discussion to the topic.
  • The chart is best for timing and directional monitoring.
  • Use exports for statistical modeling, replication, and firm-level analysis.

How to access?

Preview: Browse all series and view charts without an account. Downloads require sign-in .

Free plan

  • series: time-series + panel included.
  • Other series: 1 unlocks panel + time-series.

Standard plan

  • Time-series: included for all series.
  • Panel: series included; other series require 1 panel export credit .

Research / Enterprise

  • Time-series: included for all series.
  • Panel: included for all series.

Methodology and data

Methodology (conceptual)

This Curated Measure is based on the approach in Firm-Level Political Risk: Measurement and Effects by Hassan, Hollander, van Lent, and Tahoun and published in the Quarterly Journal of Economics in 2019:

  1. Identify political language. We use a political-language classifier derived from training libraries to identify phrases -- weighted by an associated tf*idf score ** strongly associated with political discussion.

  2. Construct PRisk (political risk). Political risk is measured by counting political-language instances that occur in conjunction with synonyms for risk or uncertainty, producing a firm-by-quarter (and call-level) measure of political risk intensity.

  3. Construct PSentiment (political sentiment). Political sentiment measures the net tone (positive vs. negative) of political discussion, computed within the same political passages used for PRisk.

  4. Topic decomposition. Topic-specific PRisk applies the same logic within eight political domains: Economy, Environment, Health, Institutions, Security, Tax, Technology, and Trade.

Note: Hassan et al. (2019) measure political phrases and associated risk terms in a sliding +/- 10 word window. We measure it at the sentence level.

Data

  • Earnings-call transcripts (English), 2002–present
  • Public firms across 80+ countries
  • Source: LSEG transcripts
  • Exports: time-series aggregates and firm-panel call-level rows

References

Hassan, T. & Hollander, S. & van Lent, L. & Tahoun, A., "Firm-Level Political Risk: Measurement and Effects," The Quarterly Journal of Economics, 134(4) (2019)

NL Analytics. (2026). Political Risk and Sentiment [Data set]. NL Analytics. https://apps.nlanalytics.tech/curated-measures/political-risk/