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Werner Hernani-Limarino — Development economist specializing in poverty measurement, machine learning for social protection, inequality, intergenerational mobility, and informality in Bolivia and Latin America. Tools for poverty mapping, proxy means tests, and distributional analysis.

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Werner L. Hernani-Limarino

Development economist · Poverty measurement · Distributional analysis · Intergenerational mobility

Development economist specializing in poverty measurement, distributional analysis, and intergenerational mobility in Latin America and the Caribbean. Over 20 years of experience producing applied research, building measurement tools, and advising governments and international organizations on poverty targeting, social protection design, and evidence-based policy. Founding partner of IA Analytics; former founding executive director of Fundación ARU (ranked Top 10 independent think tank in LAC). Work experience with the World Bank, IDB, ILO, and IPEA across 20+ countries.

What’s New

LIVE DASHBOARD

Bolivia P2P Dollar — Early Warning System

The Bolivian boliviano is under stress. Dollar shortages, parallel exchange rates, and P2P crypto markets have become a daily reality for millions of Bolivians. This live dashboard tracks the emerging parallel economy in real time — exchange rate spreads, stablecoin flows, and early warning signals updated daily.

Do you want to know when the next shock is coming before it hits?

INTERACTIVE TEST

Do you discriminate against indigenous people — without knowing it?

Most people believe they treat everyone equally. The evidence says otherwise. The Implicit Association Test measures the split-second associations your brain makes before your conscious mind has time to intervene. It takes 7 minutes.

Across Latin America, we find strong implicit bias against indigenous names and faces — even among respondents who explicitly reject discrimination. The gap between what we believe and what we do is where inequality hides.

NEW RESULTS — 2024

Where is poverty in Bolivia? Municipality-level estimates for 339 communities

Bolivia’s national poverty rate tells you almost nothing about where poor people actually live. Using the 2024 census, a Distributional Random Forest, Bayesian spatial smoothing, and Optimal Transport calibration, we now have poverty estimates for every one of Bolivia’s 339 municipalities — the first such map since 2012.

Potosí, Oruro, and the northern altiplano remain the hardest hit. But the map reveals pockets of extreme deprivation hidden inside otherwise prosperous departments. Child malnutrition follows a different geography than income poverty — and both differ from what targeting systems currently assume.

Current Research Program

Six active themes producing working papers and submitted manuscripts:

  1. Income Measurement and the Invisible Firm — correcting self-employment income mis-measurement via ML and structural methods
  2. Optimal Poverty Targeting — augmented ML methods for PMT and poverty maps that work in the distribution tails
  3. Distributional Incidence Analysis — real-time monitoring tools for welfare impacts between survey rounds
  4. Structural Poverty and Informality — distinguishing structurally trapped workers from the transitory poor
  5. Intergenerational Mobility — Mobility Frontier framework; schooling lag methodology; 18 LAC countries
  6. Gender, Adaptive Preferences, and Social Norms — endogenous preferences and the limits of redistribution

Affiliations

IA Analytics Founding Partner, 2025–present
Fundación ARU Founding Executive Director 2006–2018; Distinguished Research Fellow 2018–2020
LACEA Network of Inequality and Poverty Network Head 2018–2022; Research Co-Director RIDGE-LACEA 2022–2025
Bolivian Academy of Sciences Académico de Número (Full Academician), since 2013
Universidad Católica Boliviana — IISEC Research Fellow, since 2018