Economic growth is a tool for measuring the development and progress of countries, and technological innovation is one of the factors affecting economic growth and contributes to the development and modernization of production methods. Therefore, technological innovation is the main driver for economic growth and human progress. Spending on innovation, research and development as well as investment in innovation supports competition and progress. Accordingly, sustainable economic growth is achieved. This ensures the preservation of resources for future generations and the achievement of economic and social growth. Moreover, a sustainable educational level of the workforce, investment in research, creation of new products, and investor access to stock markets will be ensured through the development of the public and private sectors and the improvement of people’s living conditions. Our study aimed to measure the impact of technological innovation on economic growth in developing countries during the period 1990–2018. To this end, the error correction model (ECM) method has been applied. The results showed that the variables are unstable in the level and stable after taking the first difference. Co-integration was also tested using the ECM, and Granger’s causality test for the direction of causation. The test results showed that an increase in technological innovation indicators (such as spending on education, number of patents for residents and non-residents, R&D expenditures, number of researchers in R&D, high-tech exports, and scientific and technical research papers.) leads to an increase in economic growth in the short term and the long-run with a long-run and two-way causal relationship between technological innovation and GDP, and short-run causation spanning from technological innovation to GDP. The study also concluded that technological innovation has a direct impact on the sustainability of a country’s economic growth, which is why it is crucial to adopt strong policies that encourage international investors to allocate capital for development in developing countries and thus encourage more research and development.

The competitiveness of national economies is increasingly dependent on their ability to produce and use knowledge, as knowledge, education, and innovation are the main indicators of economic growth in a globalizing world. Many countries have adopted policies related to the production of knowledge and its transformation into wealth that stimulates the growth and competitiveness of their economies. Through our study, we measured some knowledge economy (KE) variables for a sample of 20 developing countries. During the period (1996–2020), using panel data, the estimate was made using three models: the cumulative regression model, the fixed-effects model, and the random-effects model. The results of the statistical tests indicated that the fixed-effects model is the appropriate model, and that the estimates of the proposed model parameters do not contradict the assumptions of economic theory, nor do they contradict the practical reality. In addition, the results showed that 93% one of the changes that occur in economic growth in the developing countries under study is due to the dependence on the knowledge economy. It became clear through the study that the use of cross-sectional time-series models increases the accuracy of statistical forecasting, because it considers the information with a time dimension in the time series, as well as the cross-sectional dimension in different units. Our study found a positive impact on economic growth of the internet and mobile phone users, control of corruption, political stability, foreign direct investment, and the total value of international trade. Additionally, spending on education, patents for residents, and trade openness had a negative impact on economic growth. Accordingly, the knowledge economy in developing countries contributed greatly to their economic growth and had a prominent role in maintaining high rates of growth for decades. Our study contributes by expanding the scope of developing countries in deciding to focus on the important indicators in the knowledge economy (KE), so that they can increase the added value of their economic growth.

Both technological innovation and foreign direct investment have received widespread attention in the literature on their role in promoting economic growth. Therefore, this study aims to test the relationship between foreign direct investment, technological innovation, and economic growth of the Egyptian economy during the period between 1990–2019 using the autoregressive distributed lag model simultaneous integration test. Our findings show of the ARDL (Autoregressive Distributed Lag) model estimation a joint complementary relationship between the rate of growth of per capita gross domestic product (GDP) in US dollars and the independent variables in the model in the long and short term, which are statistically significant results. We found a positive significant relationship between the variables of incoming foreign direct investment and share of total capital formation in economic growth. Therefore, in the long term, the rate of inflation and the innovation index had a negative impact in the long term and the speed of adjustment towards equilibrium was very large, as it was estimated at 1.5 years (1/0.651). Furthermore, the study also provides valuable lessons and a strategic vision for the Egyptian government, which aspires to advance technology and attract more foreign direct investment.

This study aimed to analyze the impact of the digital economy and artificial intelligence (AI) on GDP growth in 10 developed and developing countries during the period 2010–2024. It was based on the hypothesis that increased digitalization and AI investments promote sustainable economic growth by improving national productivity and efficiency, in accordance with modern technological growth theory, which links digital innovation to economic development. The study used tablet data comprising 150 observations, which were analyzed using fixed- and random-effects models, controlling for traditional variables such as employment, human capital, and investment. The results showed that the Digitalization Indicators (DIGI) had a significant positive impact on growth (fixed: 0.003479, p < 0.01; random: 0.003325, p < 0.01), and that investment in AI also had a significant positive impact (fixed: 0.063695, p < 0.05; random: 0.066548, p < 0.05). In contrast, workforce size had a limited impact, while education and human capital emerged as key drivers of sustainable growth (Constant: 0.003257, p < 0.01; Random: 0.003264, p < 0.01). The inclusion of dummy variables further differentiated between developed and developing countries in the random-effects model, reinforcing the economic interpretation of the findings. The study suggests that integrating digitalization, education, and investment in artificial intelligence is an effective strategy for promoting sustainable economic growth, while emphasizing the importance of workforce skills development to maximize its impact.

Purpose: Our study aimed to verify the role of the digital economy in economic growth in Egypt and the availability of the technological capabilities of the business sector for digital transformation, based on the negative impact of the epidemic on all economic sectors in the world in general and Egypt in particular. Design/methodology/approach: This was verified based on the standard Error correction package modeling (VECM) study and analysis using Xlstat 2023 and EViews 10. Findings: The results of the study conducted during the period (1996–2022) showed that there is a co-integration relationship in the short and long term between the impact of the digital economy and economic growth. We found a positive, statistically significant relationship between the variables of mobile phone subscriptions and Internet use that had a strong positive effect. At the same time, trade openness hurt economic growth in the short term. In the long run, both mobile phone subscriptions and trade openness had a significant positive effect, and the speed of adjustment toward equilibrium was very severe, estimated at 4.7 years (1/0.21). Research limitations/implications: The work is limited to the economies of Egypt, which is part of Africa. We suggest conducting further research on evidence from other emerging and developed economies. Practical implications: The results are of great importance to policymakers in Egypt as an African country, as the estimation results were positive between the digital economy and economic growth in the Egyptian economy, and this is consistent with the endogenous growth model of economic growth, which assumes that knowledge is the main driver of economic growth. Social implications: The paper documents the importance of the digital economy in boosting economic growth, which impacts social life more than the traditional digital economy, especially in times of crisis. Originality/value: Based on the existing literature, this paper identified various research gaps. First, no consensus has been reached on the concept of the digital economy, and its index system is inadequate. While existing literature concentrates on examining the influence of ICT on economic development in terms of the number of Internet users, fixed broadband Internet users and mobile subscribers. These measures cannot adequately capture the broader implications of the digital economy. Furthermore, research has largely investigated the significance of digitalization in economic development and reached ambiguous conclusions.

This study examines the dynamic relationship between illiteracy and poverty in Egypt over the period 1990–2023 using annual time-series data. The analysis applies both a simple linear regression model and the Autoregressive Distributed Lag (ARDL) framework to distinguish between short-run dynamics and potential long-run relationships. While the linear regression results indicate a statistically significant association between illiteracy and poverty, the ARDL (1,2) specification provides a more appropriate framework for capturing temporal adjustments and dynamic interactions. The ARDL bounds test yields inconclusive evidence regarding long-run cointegration, suggesting that the existence of a stable long-run equilibrium relationship cannot be confirmed with certainty. Consequently, long-run estimates are interpreted as indicative of potential sustained effects rather than definitive equilibrium outcomes. In contrast, the short-run results reveal statistically significant and cumulative effects of illiteracy on poverty. The error correction term is negative and statistically significant (ECM (− 1) = − 0.199), indicating that approximately 19.9% of short-term deviations from the long-run path are corrected each year. Diagnostic and stability tests confirm the robustness and validity of the estimated model. Overall, the findings highlight the importance of short-run dynamics and emphasize education as a critical policy instrument for poverty reduction and sustainable development in Egypt. By focusing on illiteracy as a key determinant, this study provides new empirical insights into the dynamic education–poverty nexus in a developing country context.