http://www.bdtd.uerj.br/handle/1/3582 Sat, 14 Mar 2026 17:18:12 GMT 2026-03-14T17:18:12Z http://www.bdtd.uerj.br/handle/1/25328 Título: Avaliação de eficiência econômica em educação inclusiva Autor: Moraes, Rosane Santuchi de Primeiro orientador: Marinho, Alexandre Abstract: This research evaluates the efficiency of inclusive infrastructure in public elementary schools across the 92 municipalities of the state of Rio de Janeiro, focusing on educational structures that ensure the right to quality education for students with disabilities. Education is conceived as a social and historical process essential to autonomy and social transformation, inspired by the theoretical contributions of Rousseau and Paulo Freire. Given that approximately 14.4 million Brazilians live with some form of disability (IBGE, 2022), assessing the allocation of public resources to foster inclusion in schools becomes imperative. Grounded in the principle of efficiency established in Article 37 of the 1988 Federal Constitution, the study applies the Data Envelopment Analysis (DEA) model to measure the relative efficiency of schools based on structural variables that directly impact educational inclusion. The analysis is conducted in three groups: all schools (TE), regular schools (ER), and specialized schools (EE), enabling comparative insights. The methodology is further enhanced with Bootstrap and the Malmquist Productivity Index, which strengthen the robustness of the evaluation. The results provide valuable evidence for more effective and equitable public policies, contributing to the advancement of inclusive education. Instituição: Universidade do Estado do Rio de Janeiro Tipo do documento: Dissertação Tue, 07 Oct 2025 00:00:00 GMT http://www.bdtd.uerj.br/handle/1/25328 2025-10-07T00:00:00Z http://www.bdtd.uerj.br/handle/1/25004 Título: A política de inovação no Brasil: uma análise comparada Autor: Silveira, Maíra Rodrigues da Primeiro orientador: Paula, Luiz Fernando Rodrigues de Abstract: The dynamics of innovation have increasingly gained global importance over the years, becoming a key competitive advantage for nations. Innovation not only boosts the efficiency and productivity of companies but also transforms and creates new consumption habits and standards. In this context, the existence of a well-structured National Innovation System (NIS) is essential for achieving more advanced stages of economic and social development, which in turn facilitates better integration into global trade. This paper aims to analyze the evolution of innovation policies in Brazil to understand the formation of its NIS. Additionally, it explores how innovation systems have developed in countries that are considered international benchmarks in this area. By comparing Brazil’s experience with that of leading countries, the study identifies both similarities and differences. The objective is to provide strategic insights that can support the improvement of Brazil’s development policies and help explain the country’s delay in advancing its innovation activities. Instituição: Universidade do Estado do Rio de Janeiro Tipo do documento: Dissertação Tue, 28 Jan 2014 00:00:00 GMT http://www.bdtd.uerj.br/handle/1/25004 2014-01-28T00:00:00Z http://www.bdtd.uerj.br/handle/1/24996 Título: Previsão da taxa de câmbio Real/Dólar norte-americano usando modelos de Deep Learning Autor: Pereira, Renan Scavone Fernandes Primeiro orientador: Aiube, Fernando Antonio Lucena Abstract: Exchange rate forecasting is one of the greatest challenges in economic and financial literature, holding strategic importance for policy formulation and decision-making aimed at efficient resource allocation. This dissertation investigates the forecasting of the Ptax exchange rate for the Brazilian Real against the US Dollar (BRL/USD) using Deep Learning (DL) models, evaluated over time horizons of 1, 10, and 20 business days ahead, and compared to the Random Walk (RW) model, which is widely recognized in the literature as a robust benchmark for exchange rate forecasting. Daily data series covering the period 2020 to 2024 were used, sequentially divided into training, validation, and test sets to simulate a practical application. The study adopted two approaches: a univariate approach, based exclusively on exchange rate data, and a multivariate approach, which incorporated economic and financial variables. For each forecast horizon and approach, DL architectures with one (1CR) or two recurrent layers (2CR) were tested. DL model selection was guided by error metrics on the validation set, followed by performance evaluation on the test set. The results show that, in the univariate approach, the predictions of the selected DL models did not outperform those of RW on the test set, a period in which the data is new to the models. Only on the 10-business-days horizon did the Modified Diebold-Mariano (DMM) test indicate statistical equivalence. However, for the 20- business-days horizon, a sharp deterioration in the performance of the selected DL models was observed, with error metrics at least 50% higher than those of the RW. On the other hand, in the multivariate approach, the DMM test, at the 10% significance level, indicated that the forecasts of the selected DL models performed statistically better than those of RWover the 20-businessdays horizon, in both architectures evaluated (1CR and 2CR). Consistently, the results of the Giacomini and Rossi (2010) fluctuation test and the Rossi and Sekhposyan (2016) rationality test indicated, respectively, in the time windows, equal or superior accuracy of the selected multivariate DL models’ forecasts, and lower bias and irrationality in errors compared to the RW. It is concluded that, although the DL models did not outperform the benchmark in the very short term, the inclusion of daily economic and financial variables provided significant gains in predictive performance over longer horizons, even in the short term. The results reinforce the potential of multivariate DL models to improve exchange rate forecasting, contributing both to the academic literature and to practical applications in the financial market. Instituição: Universidade do Estado do Rio de Janeiro Tipo do documento: Dissertação Fri, 22 Aug 2025 00:00:00 GMT http://www.bdtd.uerj.br/handle/1/24996 2025-08-22T00:00:00Z http://www.bdtd.uerj.br/handle/1/24957 Título: Avaliação de eficiência econômica no setor de turismo brasileiro Autor: Souza, Thaís Bastos de Primeiro orientador: Marinho, Alexandre Abstract: Responsible for 10.4% of the world's GDP, the tourism sector was considered crucial for sustainable development in the UN's 2030 Agenda. This study sought to evaluate the economic efficiency of the sector in Brazil in relation to the flow of international tourism and foreign exchange revenues, using the Data Envelopment (DEA) method with bias corrected by bootstrap. In the second stage, the impact of environmental variables on efficiency scores was analyzed using truncated regression (SIMAR; WILSON, 2007). The results indicate that Brazil is only 27% efficient compared to middle-income countries, receiving six million foreign tourists annually. To become efficient, the country would need to attract four times as many visitors, while maintaining the current level of government investment and jobs in the sector. It was also observed that an increase in the homicide rate decreases efficiency by 0.03, while devaluation of the exchange rate and a better airport connectivity index are positively associated with an increase in efficiency. Brazil therefore has the potential to expand its market share, provided it adopts the good practices identified in countries considered to be efficient. Instituição: Universidade do Estado do Rio de Janeiro Tipo do documento: Dissertação Tue, 18 Feb 2025 00:00:00 GMT http://www.bdtd.uerj.br/handle/1/24957 2025-02-18T00:00:00Z