Banca de DEFESA: Renan Abrantes de Sousa

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
STUDENT : Renan Abrantes de Sousa
DATE: 21/08/2025
TIME: 14:00
LOCAL: Online
TITLE:

Unpacking Economic Complexity and Relatedness for Industrial Policy: Filtering Noise, Mapping Traps, and Framing Developmental Pathways

KEY WORDS:

economic complexity. relatedness. industrial policy. diversification. product space.

PAGES: 138
BIG AREA: Ciências Sociais Aplicadas
AREA: Economia
SUBÁREA: Economia Industrial
SPECIALTY: Organização Industrial e Estudos Industriais
SUMMARY:

ndustrial policy has re-emerged as a central pillar of development strategy, renewing longstanding debates about its design, implementation, and effectiveness. This dissertation contributes to that debate by advancing the Economic Complexity and Relatedness framework to better inform structural transformation and policy targeting. The first paper, Complexity Traps in the Product Space: Why Some Countries Get Stuck in Local Maxima, investigates how economies can become structurally constrained when certain products offer returns that are disproportionately high relative to their neighbors in the product space. These localized incentives make it more attractive to exploit products that function as local maxima—but with low complexity—than to explore nearby opportunities that would promote capability accumulation. While appealing in the short term, this pattern ultimately constrains diversification, limiting the range of activities a country can develop over time. Over the long run, such constraints give rise to persistent regions of structural stasis - complexity traps - where countries struggle to transition into more complex activities. These findings highlight the need for industrial strategies that deliberately counteract the distorting effects of local optima and promote broader diversification. The second paper, Less is More: How Relatedness Filtering Enhances Productive Upgrading Predictions, demonstrates that statistical noise in the product space can hinder accurate identification of viable diversification paths. By filtering weak and spurious connections, we significantly improve the ability to predict future productive transitions—especially for less diversified economies—offering a more precise empirical foundation for strategic industrial policy. The third paper, From Capabilities to Economic Convergence: A Structural Growth Framework Linking Economic Complexity, Institutions, and Human Capital, proposes an integrated model that explains both current income levels and future growth using a multidimensional view of capabilities. It introduces a new complexity measure based on input–output data, which captures the sophistication of production networks beyond trade flows. The results show that multidimensional complexity, institutional quality, and human capital jointly shape development trajectories, and that countries with unexpectedly high complexity relative to their income tend to grow faster. Together, the three studies offer both diagnostic and prescriptive contributions to the Economic Complexity literature, helping to identify structural bottlenecks, improve targeting of policy tools, and reframe long-run development strategies.

COMMITTEE MEMBERS:
Presidente - 1196877 - BERNARDO PINHEIRO MACHADO MUELLER
Interno - 1642911 - DANIEL OLIVEIRA CAJUEIRO
Externo à Instituição - JOÃO PRATES ROMERO - UFMG
Interno - 162391 - MAURICIO SOARES BUGARIN
Externo à Instituição - PEDRO FERNANDO DE ALMEIDA NERY FERREIRA - IDP