Selected work

Representative Papers

Sovereign Stress Avalanches and Network Amplification in Latin America

Jun 08, 2026

This study investigates the clustering of sovereign stress episodes—referred to as “avalanches”—in Latin American credit markets and their amplification through network dynamics. Leveraging EMBI spread data from eleven countries over 2007–2026, the authors develop an innovative threshold-based method to identify country-level stress events and employ heavy-tailed distribution tests, permutation controls, and dynamic network analysis to disentangle common-factor-driven co-movements from conditional dependence in regional contagion channels. Proposing a finite-size criticality framework to characterize emerging market fragility, the study finds that avalanche sizes follow a power-law distribution with exponent 1.77, and exhibit significantly higher synchronicity than random benchmarks (p<0.001). Large avalanches coincide with denser contemporaneous correlation networks, though partial correlation networks show no such pattern, suggesting that network metrics capture real-time stress conditions rather than serve as leading early-warning signals.

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Hall-Like Transversal Stress and Sandpile Criticality on Real Production Networks

May 02, 2026

This study investigates how economic shocks propagate through real-world production networks via transverse stress mechanisms, leading to systemic instability. Drawing an innovative analogy to the physical Hall effect, the authors develop a cascading failure model that integrates transverse exposure-driven dynamics with sandpile-like threshold behavior, thereby avoiding artificial near-criticality induced by row-stochastic operators. Leveraging real input–output data from the World Input–Output Database (WIOD), the framework combines discrete toppling rules, multiplicative transfer functions, and Monte Carlo simulations to identify four distinct dynamical regimes—stable absorption, latent fragility, critical transition, and avalanche—across multiple propagation normalizations. The findings reveal that both avalanche magnitude and systemic risk increase concomitantly with field strength and redundancy stress, yet no universal power-law criticality is observed, challenging the prevailing assumption of self-organized criticality in economic networks.

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Sandpile Economics: Theory, Identification, and Evidence

Apr 15, 2026

This study addresses why minor shocks often trigger disproportionately large macroeconomic crises by introducing Forman–Ricci curvature from graph theory into macroeconomics to characterize local substitutability within evolving production networks under supply-chain disruptions. The framework reveals how increasing specialization drives economies toward a critical state prone to cascading failures, thereby establishing a non-ergodic, path-dependent theory of crisis generation that transcends the limitations of representative-agent models. Empirical analysis demonstrates that the global input–output network has persistently exhibited negative curvature, which significantly predicts three-year-ahead output growth and outperforms conventional network metrics in explaining cross-country differences in economic resilience.

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Identification and Inference in Nonlinear Dynamic Network Models

Apr 03, 2026

This study addresses the challenge of structural unidentifiability and inference difficulty in nonlinear dynamic systems operating on unknown interaction networks. The authors propose an identification framework based on an implicit dependence matrix, establishing necessary and sufficient conditions for network identifiability by revealing its reliance on the spectral heterogeneity of the interaction matrix. The framework characterizes observational equivalence classes and overcomes the limitation of conventional approaches that erroneously conflate network dependencies with common shocks. Methodologically, it integrates semiparametric estimation, spectral analysis, and asymptotic theory to construct estimators with desirable asymptotic properties and develops a test for network dependence whose power is governed by spectral characteristics. The proposed framework demonstrates broad applicability across economic systems, including production networks and contagion models.

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Invited to Develop: Institutional Belonging and the Counterfactual Architecture of Development

Nov 26, 2025

This study investigates the institutional roots underlying the divergent developmental trajectories of Spain and Uruguay—two countries with similar historical endowments but markedly different growth paths since the 1960s. It asks: How does an actor’s structural position within transnational institutional networks shape long-term development through “institutional belonging”? Method: We develop a generative counterfactual framework, introducing a novel Wasserstein GAN–based simulation method integrated with the Economic Complexity Index and a path-dependent institutional model to quantify institutional embedding effects (1960–2020). Contribution/Results: We propose the Expected Developmental Shift (EDS) metric, demonstrating that institutional belonging is a pivotal structural determinant of divergence. Counterfactual analysis reveals that Spain would have experienced significant decline had it been embedded in Latin American institutional architectures, whereas Uruguay would have achieved higher economic complexity and systemic resilience by joining European institutional frameworks. The findings establish institutional belonging as a core structural variable explaining cross-national development divergence.

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Recent publications

Latest Papers

Sovereign Stress Avalanches and Network Amplification in Latin America

Jun 08, 2026

This study investigates the clustering of sovereign stress episodes—referred to as “avalanches”—in Latin American credit markets and their amplification through network dynamics. Leveraging EMBI spread data from eleven countries over 2007–2026, the authors develop an innovative threshold-based method to identify country-level stress events and employ heavy-tailed distribution tests, permutation controls, and dynamic network analysis to disentangle common-factor-driven co-movements from conditional dependence in regional contagion channels. Proposing a finite-size criticality framework to characterize emerging market fragility, the study finds that avalanche sizes follow a power-law distribution with exponent 1.77, and exhibit significantly higher synchronicity than random benchmarks (p<0.001). Large avalanches coincide with denser contemporaneous correlation networks, though partial correlation networks show no such pattern, suggesting that network metrics capture real-time stress conditions rather than serve as leading early-warning signals.

0 citationsRead paper

Hall-Like Transversal Stress and Sandpile Criticality on Real Production Networks

May 02, 2026

This study investigates how economic shocks propagate through real-world production networks via transverse stress mechanisms, leading to systemic instability. Drawing an innovative analogy to the physical Hall effect, the authors develop a cascading failure model that integrates transverse exposure-driven dynamics with sandpile-like threshold behavior, thereby avoiding artificial near-criticality induced by row-stochastic operators. Leveraging real input–output data from the World Input–Output Database (WIOD), the framework combines discrete toppling rules, multiplicative transfer functions, and Monte Carlo simulations to identify four distinct dynamical regimes—stable absorption, latent fragility, critical transition, and avalanche—across multiple propagation normalizations. The findings reveal that both avalanche magnitude and systemic risk increase concomitantly with field strength and redundancy stress, yet no universal power-law criticality is observed, challenging the prevailing assumption of self-organized criticality in economic networks.

0 citationsRead paper

Sandpile Economics: Theory, Identification, and Evidence

Apr 15, 2026

This study addresses why minor shocks often trigger disproportionately large macroeconomic crises by introducing Forman–Ricci curvature from graph theory into macroeconomics to characterize local substitutability within evolving production networks under supply-chain disruptions. The framework reveals how increasing specialization drives economies toward a critical state prone to cascading failures, thereby establishing a non-ergodic, path-dependent theory of crisis generation that transcends the limitations of representative-agent models. Empirical analysis demonstrates that the global input–output network has persistently exhibited negative curvature, which significantly predicts three-year-ahead output growth and outperforms conventional network metrics in explaining cross-country differences in economic resilience.

0 citationsRead paper

Identification and Inference in Nonlinear Dynamic Network Models

Apr 03, 2026

This study addresses the challenge of structural unidentifiability and inference difficulty in nonlinear dynamic systems operating on unknown interaction networks. The authors propose an identification framework based on an implicit dependence matrix, establishing necessary and sufficient conditions for network identifiability by revealing its reliance on the spectral heterogeneity of the interaction matrix. The framework characterizes observational equivalence classes and overcomes the limitation of conventional approaches that erroneously conflate network dependencies with common shocks. Methodologically, it integrates semiparametric estimation, spectral analysis, and asymptotic theory to construct estimators with desirable asymptotic properties and develops a test for network dependence whose power is governed by spectral characteristics. The proposed framework demonstrates broad applicability across economic systems, including production networks and contagion models.

0 citationsRead paper

Invited to Develop: Institutional Belonging and the Counterfactual Architecture of Development

Nov 26, 2025

This study investigates the institutional roots underlying the divergent developmental trajectories of Spain and Uruguay—two countries with similar historical endowments but markedly different growth paths since the 1960s. It asks: How does an actor’s structural position within transnational institutional networks shape long-term development through “institutional belonging”? Method: We develop a generative counterfactual framework, introducing a novel Wasserstein GAN–based simulation method integrated with the Economic Complexity Index and a path-dependent institutional model to quantify institutional embedding effects (1960–2020). Contribution/Results: We propose the Expected Developmental Shift (EDS) metric, demonstrating that institutional belonging is a pivotal structural determinant of divergence. Counterfactual analysis reveals that Spain would have experienced significant decline had it been embedded in Latin American institutional architectures, whereas Uruguay would have achieved higher economic complexity and systemic resilience by joining European institutional frameworks. The findings establish institutional belonging as a core structural variable explaining cross-national development divergence.

0 citationsRead paper