Programa de Pós-Graduação em Economia http://repositorio.ufc.br/handle/riufc/584 2026-08-11T22:23:40Z 2026-08-11T22:23:40Z Oliveira, Bruno Marinho Cavalcante de http://repositorio.ufc.br/handle/riufc/87430 2026-08-07T18:34:55Z 2026-01-01T00:00:00Z

Título: Investimentos educacionais e arrecadação tributária por bairro em Fortaleza, análise para o período de 2015-2022 Autor(es): Oliveira, Bruno Marinho Cavalcante de Abstract: This study examines the effects of place-based public investments in educational infrastructure, namely Early Childhood Education Centers and Full-Time Schools, on neighborhood-level tax revenues from the services tax and the tourism-related value-added tax in Fortaleza from 2015 to 2022. The empirical strategy combines an event-study difference-in-differences design with matching on pre-treatment outcome trajectories, building an explicit counterfactual for each treated neighborhood and recovering dynamic effects around investment implementation. The main results show a large and short-lived response for the services tax, with sizable increases at the implementation quarter and in the subsequent quarter, and additional evidence up to roughly one year depending on specification. Robustness checks re-estimate the design under progressively stricter matching vectors that incorporate 2010 Census covariates capturing socioeconomic gradients and urban pressure, confirming the stability of the services-tax dynamics. For the tourism-related value-added tax, the evidence is markedly weaker, with no clearly persistent post-implementation path and higher sensitivity to specification. The findings suggest that localized urban investments can generate short-run fiscal externalities in territorially anchored service tax bases, while effects on more aggregated tax bases appear limited and less tightly linked to the immediate neighborhood environment. Tipo: Dissertação

2026-01-01T00:00:00Z Moura, Yure Revélles da Silva http://repositorio.ufc.br/handle/riufc/87420 2026-08-06T19:12:09Z 2026-01-01T00:00:00Z

Título: Ensaios sobre modelos de machine learning aplicados à econômia Autor(es): Moura, Yure Revélles da Silva Abstract: This study brings together three empirical essays that focus on the application of machine learning models to economic forecasting at both the national and regional levels, seeking to evaluate the extent to which these approaches can complement traditional econometric methods. Despite the recent advances in these techniques, important limitations still remain regarding the economic interpretability of the models, the incorporation of regional heterogeneities, and the comparison with structural approaches. The choice of the sample period is justified by its coverage of major consolidations in the Brazilian macroeconomic environment, particularly the adoption of the inflation-targeting regime, while also encompassing distinct economic regimes, episodes of instability, and changes in the conduct of economic policy. In addition, the temporal delimitation was defined according to the availability, compatibility, and standardization of the databases employed throughout the essays. In this context, the first essay presents a national inflation forecasting exercise based on an extensive set of macroeconomic variables. Additionally, the study aims to identify the key predictors of inflation across multiple forecasting horizons. To this end, machine learning models are employed as the main approach and compared with benchmark models. The empirical findings suggest that machine learning models outperform benchmark models across different forecasting horizons. Furthermore, the results provide evidence of the relevance of production and fiscal sectors, labor market conditions, energy costs, and expectations in explaining inflation forecasts over different periods. The second essay proposes a regional inflation forecasting exercise based on an implicit hierarchical structure, incorporating regional elements into the forecasting process. Furthermore, a dynamic decomposition of inflation predictors is performed across regions and forecasting horizons. The results indicate the presence of significant regional heterogeneity across the states of Northeastern Brazil. The dynamic decomposition also reveals that the determinants of regional inflation gradually change over time, exhibiting patterns consistent with economic and political events at both the national and regional levels. The third essay proposes the use of multivariate neural network models to generate dynamic counterfactuals for Brazilian macroeconomic variables based on shocks applied to selected variables. The simulated trajectories are then compared with the dynamic responses obtained from a structural model, allowing an assessment of the extent to which machine learning-based methods can reproduce propagation and persistence patterns commonly found in traditional econometric models. The findings indicate that the multivariate model responds to shocks in a more moderate manner and in closer alignment with the macroeconomic literature. In particular, the model is able to reproduce propagation patterns similar to those generated by the structural model, although such responses arise from statistical relationships learned from the data rather than from explicitly modeled causal mechanisms. In this sense, the estimated counterfactuals exhibited smaller and more gradual responses at the onset of the shock for all variables when compared with the structural model. Taken together, the results reinforce the potential of machine learning methods not only as forecasting tools, but also as complementary instruments to traditional econometric approaches for analyzing dynamic and complex phenomena, especially in environments characterized by high macroeconomic instability. Tipo: Tese

2026-01-01T00:00:00Z Melo, Antonio Lucas de Abreu http://repositorio.ufc.br/handle/riufc/87279 2026-07-27T19:23:47Z 2026-01-01T00:00:00Z

Título: Análises em economia da educação: avaliação das escolas estaduais de educação profissional do Ceará. Autor(es): Melo, Antonio Lucas de Abreu Abstract: This thesis, situated within the field of Economics of Education, analyzes the policy of creating State Schools of Professional Education (EEEP) in the state of Ceará, Brazil, combining theoretical and impact assessment evaluations of its effects on socioeconomic development. Starting from a context marked by inequality, low workforce qualification, and difficulties in youth labor market insertion, the study investigates the extent to which vocational education can contribute to employability, income, and the reduction of social externalities such as youthcrime. The research is structured into three complementary essays. The first reconstructs the policy logic through Program Theory and the Logical Framework, highlighting internal consistency between diagnosis, objectives, instruments, and expected outcomes, with emphasis on mechanisms such as the integration of general and technical education, extended school hours, and linkages with the productive sector. The second essay evaluates the impacts of the policy on income and employability of young individuals aged 15 to 29 across municipalities in Ceará from 2008 to 2024, using a Differences-in-Differences approach following Callaway and Sant’Anna (2021), finding no statistically significant aggregate effects, althoughheterogeneous impacts are observed at the sectoral level. The third essay investigates the effects of the policy on homicide rates among young males aged 15 to 19, employing the sameDifferences-in-Differences methodology, and finds no statistically significant impacts. Overall, the results indicate that, despite its theoretical consistency and localized effects, the policy hasnot produced significant aggregate changes, highlighting the importance of expanding access,targeting vulnerable groups, and coordinating with other public policies to enhance itseffectiveness. Tipo: Tese

2026-01-01T00:00:00Z Firmiano, Marília Rodrigues http://repositorio.ufc.br/handle/riufc/87278 2026-07-27T19:02:30Z 2026-01-01T00:00:00Z

Título: Desmatamento no bioma amazônia: evidências empíricas a partir de imóveis rurais Autor(es): Firmiano, Marília Rodrigues Abstract: This thesis comprises two articles that investigate deforestation on rural properties in the Amazon biome. In the first chapter, the causal impact of municipalities’ inclusion in the List of Priority Municipalities (LPM) on deforestation associated with rural properties is analyzed, using geospatial data from the Rural Environmental Registry (CAR), combined with deforestation data and socioeconomic variables, covering the period from 2010 to 2022. The empirical strategy is based on the Generalized Synthetic Control method, which allows for handling staggered policy adoption and unobserved heterogeneity. The results indicate that the LPM was effective in reducing deforestation, with effects that consolidate over time and exhibit significant spatial heterogeneity across municipalities that benefited from the policy. In the second chapter, the relationship between rural credit and deforestation is investigated, as well as how this relationship behaves under different policy contexts: in 2008, when Central Bank Resolution No. 3,545 was enacted and the Soy Moratorium was implemented; in 2014, when the CAR was introduced; and in 2019, when environmental enforcement policies were relaxed in Brazil. Using a dataset containing deforestation and socioeconomic variables for the period from 2008 to 2019, a continuous treatment approach based on the Generalized Propensity Score (GPS) and semiparametric estimators is employed. The results reveal a positive, non-linear relationship between credit and deforestation, indicating that higher levels of financing are associated with larger increases in deforestation. Additionally, the quantile analysis reveals heterogeneity across the distribution, with more pronounced effects in the upper quantiles, suggesting that areas with higher deforestation intensity respond more strongly to credit expansion, while no significant effects are observed in contexts of low anthropogenic pressure. Taken together, the results indicate that deforestation arises from the interaction between public policy instruments operating through distinct mechanisms. While command-and-control policies, such as the LPM, help reduce deforestation, economic instruments, such as rural credit, may—if not properly conditioned—amplify incentives for land-use conversion. Thus, this thesis contributes to the literature by shifting the analysis to the level of rural properties and by providing robust empirical evidence on the mechanisms through which different policy instruments shape deforestation dynamics, offering relevant insights for improving the design and coordination of environmental policies in the Amazon context. Tipo: Tese

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