This study addresses the crucial question of the macroeconomic impact of investing in railroad infrastructure in Portugal. The aim is to shed light on the immediate and long-term effects of such investments on economic output, employment, and private investment, specifically focusing on interindustry variations. We employ a Vector Autoregressive (VAR) model and utilize industry-level data to estimate elasticities and marginal products on these three economic indicators. Our findings reveal a compelling positive long-term spillover effect of these investments. Specifically, every €1 million in capital spending results in a €20.84 million increase in GDP, a €17.78 million boost in private investment, and 72 new net permanent jobs. However, these gains are not immediate, as only 14.5% of the output increase and 38.8% of the investment surge occur in the first year. In contrast, job creation is nearly instantaneous, with 93% of new jobs materializing within the first year. A short-term negative impact on the trade balance is expected as new capital goods are imported. Upon industry-level analysis, the most pronounced output increases are witnessed in the real estate, construction, and wholesale and retail trade industries. The most substantial net job creation occurs in the construction, professional services, and hospitality industries. This study enriches the empirical literature by uncovering industry-specific impacts and temporal macroeconomic effects of railroad infrastructure investments. This underscores their dual advantage in bolstering long-term economic performance and counteracting job losses during downturns, thus offering valuable public policy implications. Notably, these benefits are not evenly distributed across all industries, necessitating strategic sectoral planning and awareness of employment agencies to optimize spending programs and adapt to industry shifts.

The present paper discusses the case of the Madrid Nuevo Norte Project (MNNP) in order to examine the relation of this mega-project with the city’s sustainable development. For this reason, the study used a qualitative approach using semi-structural interviews with experts (Madrid’s town hall, Madrid State, and the program management office and other external) that relayed strongly with MNNP. The expert panel requirements are split in six expertise areas: sustainability, urban development, urban planning, government or public affairs, project management or Madrid Nuevo Norte (MNN) key stakeholders. The study highlighted the vital importance of MNNP as a flagship sustainable project for the rest of Europe, that meets sustainability criteria for contributing substantially in the improvement of the quality of life of final users and for the community in general. For instance, it contributes to the regeneration of the city’s degraded area, to the interconnection of an isolated part of the city and public transportation connection, improving the external image of Madrid. Despite of it, there are some challenges that should be carefully managed such as applying sustainable solutions from other cities not properly tailored to Madrid, housing pricing accessibility increase due to the lack of terrain in Madrid and the politization of the project as discussion topic between local parties. In this context, local authorities should give particular emphasis in complying with the principles of sustainability for improving the overall performance of MNNP, ensuring social justice and prosperity for the people of Madrid.

This research focused on the design and implementation of the flipped classroom approach for higher mathematics courses in medical colleges. Out of 120 students, 60 were assigned to the experimental group and 60 to the control group. In the continuous assessment, which included homework and quizzes, the average score of the experimental group was 85.5 ± 5.5, while that of the control group was 75.2 ± 8.1 (P < 0.05). For the final examination, the average score in the experimental group was 88.3 ± 6.2, compared to 78.1 ± 7.3 in the control group (P < 0.01). The participation rate of students in the experimental group was 80.5%, significantly higher than the 50.3% in the control group (P < 0.001). Regarding autonomous learning ability, the experimental group spent an average of 3.2 hours per week on self-study, compared to 1.5 hours in the control group (P < 0.005). Other potential evaluation indicators could involve the percentage of students achieving high scores (90% or above) in problem-solving tasks (25.8% in the experimental group vs. 10.3% in the control group, P < 0.05), and the improvement in retention of key concepts after one month (70.2% in the experimental group vs. 40.5% in the control group, P < 0.01). In conclusion, the flipped classroom approach holds substantial promise in elevating the learning efficacy of higher mathematics courses within medical colleges, offering valuable insights for educational innovation and improvement.

This paper provides a comprehensive review of equity trading simulators, focusing on their performance in assuring pre-trade compliance and portfolio investment management. A systematic search was conducted that covered the period of January 2000 to May 2023 and used keywords related to equity trade simulators, portfolio management, pre-trade compliance, online trading, and artificial intelligence. Studies demonstrating the use of simulators and online platforms specific to portfolio investment management, written in English, and matching the specified query were included. Abstracts, commentaries, editorials, and studies unrelated to finance and investments were excluded. The data extraction process included data related to challenges in modern portfolio trading, online stock trading strategies, the utilization of deep learning, the features of equity trade simulators, and examples of equity trade simulators. A total of 32 studies were included in the systematic review and were approved for qualitative analysis. The challenges identified for portfolio trading included the subjective nature of the inputs, variations in the return distributions, the complexity of blending different investments, considerations of liquidity, trading illiquid securities, optimal portfolio execution, clustering and classification, the handling of special trading days, the real-time pricing of derivatives, and transaction cost models (TCMs). Portfolio optimization techniques have evolved to maximize portfolio returns and minimize risk through optimal asset allocation. Equity trade simulators have become vital tools for portfolio managers, enabling them to assess investment strategies, ensure pre-trade compliance, and mitigate risks. Through simulations, portfolio managers can test investment scenarios, identify potential hazards, and improve their decision-making process.

This paper uses Public Choice analysis to examine the case for and experience with Public-Private Partnerships (PPPs). A PPP is a contractual platform which connects a governmental body and a private entity. The goal is to provide a public sector program, service, or asset that would normally be provided exclusively by a public sector entity. This paper focuses on PPPs in developed countries, but it also draws on studies of PPPs in developing countries. The economics literature generally defines PPPs as long-term contractual arrangements between a public authority (local or central government) and a private supplier for the delivery of services. The private sector supplier takes responsibility for building infrastructure components, securing financing of the investment, and then managing and maintaining this facility.

However, in addition to those formed through contracts, PPPs may take other forms such as those developed in response to tax subvention or coercion, as in the case of regulatory mandates. A key element of PPP is that the private partner takes on a significant portion of the risk through a schedule of specified remuneration, contingency payments, and provision for dispute resolution. PPPs typically are long-term arrangements and involve large corporations on the private side, but may also be limited to specific phases of a project.

The types of PPPs discussed in this paper exclude arrangements which may result from government mandates such as the statutory emission mandates imposed on automobile manufacturers and industrial facilities (e.g., power plants). It also excludes PPP-like organizations resulting from US section 501(c)(3) of the Internal Revenue Code, which provides tax subsidies for certain public charities, scientific research organizations, and organizations whose goals are to prevent cruelty to animals or erect public monuments at no expense to the government. This paper concludes that an array of Public Choice tools are applicable to understanding the emergence, success, or failure of PPPs. Several short case studies are provided to illustrate the practicalities of PPPs. 

The purpose of this study is to predict the frequency of mortality from urban traffic injuries for the most vulnerable road users before, during and after the confinement caused by COVID-19 in Santiago de Cali, Colombia. Descriptive statistical methods were applied to the frequency of traffic crash frequency to identify vulnerable road users. Spatial georeferencing was carried out to analyze the distribution of road crashes in the three moments, before, during, and after confinement, subsequently, the behavior of the most vulnerable road users at those three moments was predicted within the framework of the probabilistic random walk. The statistical results showed that the most vulnerable road user was the cyclist, followed by motorcyclist, motorcycle passenger, and pedestrian. Spatial georeferencing between the years 2019 and 2020 showed a change in the behavior of the crash density, while in 2021 a trend like the distribution of 2019 was observed. The predictions of the daily crash frequencies of these road users in the three moments were very close to the reported crash frequency. The predictions were strengthened by considering a descriptive analysis of a range of values that may indicate the possibility of underreporting in cases registered in the city’s official agency. These results provide new elements for policy makers to develop and implement preventive measures, allocate emergency resources, analyze the establishment of policies, plans and strategies aimed at the prevention and control of crashes due to traffic injuries in the face of extraordinary situations such as the COVID-19 pandemic or other similar events.