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This paper aims to present reflections and points of interest on the performance of Brazil and highlight the advances and challenges in relation to the intellectual property (IP) system; the authors highlight some scientific, economic and technological indicators on the main IP objects registered in the National Industrial Property of Brazil (INPI).

A structured literature reviews the main indicators of IP of Brazil (2013-2017), related to the scientific and economic factors more evidenced in the global scenario, with emphasis on the investment of national GDP in R&D activities, the allocation of resources from the government sector and private initiative, as in other emerging economies, such as the BRICS.

Despite Brazil’s progressive efforts to achieve greater efficiency in the public IP management system, GDP investment in R&D activities for 2019 is still below the OECD average of 2.3 per cent, and the IP indicators in the areas of patent registration, industrial designs and technology contracts have been declining.

Because of the difference between the laws of the countries on IP rights, the more incisive comparison could not be established among the emerging economies, highlighting the need for a standardization between the different international legislations.

In the scientific field, this paper allows understanding the performance of the Brazilian IP system, and the categories that require greater investments, strengthen the IP culture and stimulate integration between the international IP systems, as it is a recurrent discussion in different research studies. Originally, the paper brought together economic and scientific indicators going beyond the traditional approach that deals with IP only restricting to the quantitative of patents.

This paper aims to discuss the evolution of the Egyptian banking sector and the main trends in financial development in Egypt. The purpose of this study is to examine empirically the relationship between the development of the financial sector and economic growth in Egypt between 1980 and 2016.

The paper draws comparisons based on critical financial indicators between Egypt and selected emerging markets and developing economies. It uses a new data set of financial development indexes released by the International Monetary Fund. This paper uses econometric time series modelling of bivariate regressions for real growth per capita and measures of financial development to assess the relationship between financial development and economic growth in Egypt.

There are three specific findings based on the empirical analysis. First, there is a strong association between real growth per capita and financial development measured by money supply to GDP. Second, access to and the efficiency of banking services are not associated with real per capita income. Third, the Financial Markets Access Index – which compiles data on market capitalization outside of the top ten largest companies and the number of corporate issuers of debt – indicates a robust association with real per capita GDP.

The paper uses advanced empirical investigation techniques and new data sets available to assess the critical relationship between finance and growth in Egypt. The main policy implications of the empirical results of this paper suggest a stronger focus on promoting a more proactive role for the financial services industry in Egypt. In particular, there is a critical role for bank financing to support the private sector to maintain an inclusive growth momentum. Further development of the capital market will promote sustainability of such economic growth.

This study explores whether a new machine learning method can more accurately predict the movement of stock prices.

This study presents a novel hybrid deep learning model, Residual-CNN-Seq2Seq (RCSNet), to predict the trend of stock price movement. RCSNet integrates the autoregressive integrated moving average (ARIMA) model, convolutional neural network (CNN) and the sequence-to-sequence (Seq2Seq) long–short-term memory (LSTM) model.

The hybrid model is able to forecast both linear and non-linear time-series component of stock dataset. CNN and Seq2Seq LSTMs can be effectively combined for dynamic modeling of short- and long-term-dependent patterns in non-linear time series forecast. Experimental results show that the proposed model outperforms baseline models on S&P 500 index stock dataset from January 2000 to August 2016.

This study develops the RCSNet hybrid model to tackle the challenge by combining both linear and non-linear models. New evidence has been obtained in predicting the movement of stock market prices.

This paper aims to evaluate the impact of the “Postliteracy” program on the qualification of beneficiaries for socioeconomic integration. This qualification is achieved first through the consolidation of the achievements of individuals freed from illiteracy, and then through their support in creating income-generating activities by providing them with technical, economic, legal and institutional knowledge to ensure their conscious and responsible participation in local and regional development efforts.

To evaluate the impact of the “Postliteracy” program, this paper uses quasi-experimental methods with a control group (participants of the “Literacy” program 2020 / 2021) and a treatment group (participants of the “Postliteracy” program 2021 / 2022). Skill acquisition is measured through pretest and posttest evaluations using a questionnaire aligned with the National Agency for the Fight Against Illiteracy (ANLCA)-adopted curriculum. The survey occurred at the beginning and at the end of the program, providing sufficient time for skill development. The questionnaire includes three sections covering socioprofessional characteristics, technical and economic domains and legal and institutional aspects. These sections contribute to a score reflecting the acquired skills for successful socioeconomic integration.

The results of the study demonstrate that the “Postliteracy” program has a positive impact on the acquisition of competences necessary for improved socioeconomic integration of the beneficiaries. The various matching techniques reveal a score difference ranging from 12 to 14 points in favor of program participants compared to those who did not participate. The Difference-in-Differences method confirms the positive and significant impact of the program.

The findings highlight the importance of the “Postliteracy” program in national literacy policy, underlining the need to further strengthen its presence within the programs deployed by ANLCA, notably by increasing the number of beneficiaries targeted by this program. To achieve this, it would be advisable to increase the funds allocated to it within ANLCA's budget.

The originality of this work is a unique research of the case of Morocco based on a microeconometric study for which the authors evaluate the impact of adult education by applying impact evaluation methods in the field of adult literacy.

This study examines the relevance of information and communication technologies in the effect of gender economic inclusion on environmental sustainability.

The focus is on a panel of 42 sub-Saharan African countries over the period 2005–2020. The empirical evidence is based on generalized method of moments. The environmental sustainability indicator used is CO2 emissions per capita. Three indicators of women’s economic inclusion are considered: female labour force participation, female employment and female unemployment. The chosen ICT indicators are mobile phone penetration, Internet penetration and fixed broadband subscriptions.

The results show that: (1) fixed broadband subscriptions represent the most relevant ICT moderator of gender economic inclusion for an effect on CO2 emissions; (2) negative net effects are apparent for the most part with fixed broadband subscriptions (3) both positive ICT thresholds (i.e., critical levels for complementary policies) and negative ICT thresholds (i.e., minimum ICT levels for negative net effects) are provided; (4) ICT synergy effects are apparent for female unemployment, but not for female employment. In general, the joint effect of ICTs or their synergies and economic inclusion should be a concern for policymakers in order to better ensure sustainable development. Moreover, the relevant ICT policy thresholds and mobile phone threshold for complementary policy are essential in promoting a green economy.

The study complements the extant literature by assessing linkages between information technology, gender economic inclusion and environmental sustainability.

A promising solution to meet the challenge of sustainability and ensure the protection of the environment consists in acting considerably on the adoption and use of new information and communication technologies. The latter can act on the protection of the environment; completely change manufacturing processes into energy-efficient, eco-friendly techniques or influence institutions and governance. The article attempts to cover shortcomings in the literature by providing a couple of theoretical frameworks and grounded empirical proofs for the dissemination of green technologies and the interaction of the latter with institutional quality.

The sample is made up of 43 African countries covering the period 2000–2020 and a panel VAR modeling approach is employed.

Our results show that an attenuation of CO2 emissions amplifies the diffusion of digital technologies (mobile telephones and Internet). Efficiency in the institutional quality of African countries is mandatory for environmental preservation. Moreover, the provision of a favorable institutional framework in favor of renewable energy helps to stimulate environmental performance in African states.

This study complements the extant literature by assessing nexuses between green technology and CO2 emissions in environmental sustainability.

This study empirically investigates the relationship between goodwill assets and capital structure (i.e. debt ratio) of firms and the moderating effect of financial market development on the relationship between goodwill assets and capital structure.

This research applied a quantitative method. The article collects large samples of listed firms from 23 developing and nine developed countries and applied the panel data techniques. This research used firm-level data from the DataStream database for both developed and developing countries. The study uses 4,912 firm-level data from 23 developing countries and 4,303 firm-level data from nine developed countries.

The findings reveal a significant positive relationship between goodwill assets and capital structure in developing countries, but goodwill assets have a significant negative relationship with capital structure in developed countries. Moreover, financial market development positively moderates the relationship between goodwill assets and the capital structure of firms in developing countries. The results inform firm managers that goodwill assets serve as additional collateral to secure debt financing. Moreover, policymakers should formulate a debt market policy that recognizes goodwill assets as additional collateral for the purpose of obtaining debt capital.

The study has several implications. First, goodwill assets are identified as a factor of capital structure in this study. Fixed assets have been identified as one of the drivers of capital structure in previous research, although goodwill assets are seldom included. Second, this article shows that along with demand-side determinants, supply-side determinants also play an important role in terms of the firms' choice about the capital structure. Therefore, firms should take both the demand-side and supply-side factors into consideration when sourcing for external financing (i.e. debt capital).

The study considered goodwill as a component of capital structure. The study analysis includes a large sample of enterprises, including 4,912 big firms from 23 developing countries and 4,303 large firms from nine industrialized or developed countries, which adds to the current capital structure information. Furthermore, a large sample size increases the results' robustness and generalizability.

The article aims to establish whether the degree of aversion to inflation and the responsiveness to deviations from potential output have changed over time.

This paper assesses time variation in monetary policy rules by applying a time-varying parameter generalised methods of moments (TVP-GMM) framework.

Using monthly data until December 2022 for five inflation targeting countries (the UK, Canada, Australia, New Zealand, Sweden) and five countries with alternative monetary regimes (the US, Japan, Denmark, the Euro Area, Switzerland), we find that monetary policy has become more averse to inflation and more responsive to the output gap in both sets of countries over time. In particular, there has been a clear shift in inflation targeting countries towards a more hawkish stance on inflation since the adoption of this regime and a greater response to both inflation and the output gap in most countries after the global financial crisis, which indicates a stronger reliance on monetary rules to stabilise the economy in recent years. It also appears that inflation targeting countries pay greater attention to the exchange rate pass-through channel when setting interest rates. Finally, monetary surprises do not seem to be an important determinant of the evolution over time of the Taylor rule parameters, which suggests a high degree of monetary policy transparency in the countries under examination.

It provides new evidence on changes over time in monetary policy rules.

The author investigates whether investors’ online information demand measured by Google search query and the changes in the numbers of Wikipedia page view can explain and predict stock return, trading volume and volatility dynamics of companies listed on the Nigerian Stock Exchange.

The multiple regression model which encompasses both the univariate and multivariate regression framework was employed as the research methodology. As part of our pre-analysis, we test for multicollinearity and applied the Wu/Hausman specification test to detect whether endogeneity exist in the regression model.

We provide novel and robust evidence that Google searches neither explain the contemporaneous nor predict stock return, trading volume and volatility dynamics. Similarly, results also indicate that trading volume and volatility dynamics have no relationship with changes in the numbers of Wikipedia pages view related to stock activities.

This study opens new strand of empirical literature of “investors' attention” in the context of African stock markets as empirical evidence. No evidence from previous studies on investors' attention exist, whether in Google search query or Wikipedia page view, with respect to African stock markets, particularly the Nigerian stock market. This study seeks to bridge these knowledge gaps by examining these relations.

There is abundant literature analyzing the determinants of banks’ profitability through its main component: the net interest margin. Some of these determinants are suggested by seminal theoretical models and subsequent expansions. Others are ad-hoc selections. Up to now, there are no studies assessing these models from a Bayesian model uncertainty perspective. This paper aims to analyze this issue for the EU-15 countries for the period 2008-2014, which mainly corresponds to the Great Recession years.

It follows a Bayesian variable selection approach to analyze, in a first step, which variables of those suggested by the literature are actually good predictors of banks’ net interest margin. In a second step, using a model selection approach, the authors select the model with the best fit. Finally, the paper provides inference and quantifies the economic impact of the variables selected as good candidates.

The results widely support the validity of the determinants proposed by the seminal models, with only minor discrepancies, reinforcing their capacity to explain net interest margin disparities also during the recent period of restructuring of the banking industry.

The paper is, to the best of the knowledge, the first one following a Bayesian variable selection approach in this field of the literature.