The research question centers on understanding the dynamic interplay between digitalization and human capital development in Vietnam from 1996 to 2019. This study is crucial because Vietnam has actively pursued digital transformation through policy and significant investment in R&D. Unlike some countries that mandate digital adoption, Vietnam’s approach emphasizes incentivizing businesses, making it a valuable case study in understanding the impact of incentivized digital innovation on human capital. The research uses Vietnam as a case study because of its proactive policies supporting digital transformation and human capital development, coupled with a substantial financial commitment to R&D. The government's focus on incentivizing businesses rather than mandating digital adoption provides a unique context to explore the relationship between digitalization and human capital. Understanding this dynamic is critical for policymakers to design effective policies that support both short-term and long-term economic growth. A failure to account for the interplay between digitalization and human capital development can result in ineffective or even counterproductive policies.

The study grounds its theoretical framework in human capital theory, tracing its evolution from classical economists like Adam Smith and Karl Marx to the neoclassical contributions of Becker, Schultz, and Mincer. These economists highlighted the role of education and skills in boosting productivity and economic growth. The paper acknowledges the challenges in measuring human capital, noting the lack of a universally accepted method due to its multifaceted nature. It discusses different levels of human capital assessment (micro, meso, macro, mega) and various evaluation methods (investment, return on investment, and natural indicators). This review sets the stage for the empirical analysis, highlighting the complexity of the human capital concept and the need for sophisticated econometric techniques.

This study employs a novel econometric approach to analyze the complex relationship between digitalization and human capital development in Vietnam. The researchers utilize the extended joint connectedness method (TVPVAR-EJC) in conjunction with a parameter vector autoregression with time-varying parameters. This innovative technique allows them to account for the dynamic and interconnected nature of the variables involved, overcoming limitations of traditional methods in handling scarce data. The variables considered include: * **INU (Index of Network Use):** A measure of digitalization penetration. * **MOBSUB (Number of Mobile Subscribers):** Reflecting mobile technology adoption. * **CO2 Emissions:** Representing environmental impact and possibly indirect effects on economic growth. * **Human Capital Index:** A composite indicator capturing the quality of human resources. The TVPVAR-EJC model is carefully specified, and the lag length is determined using the Bayesian information criterion (BIC). The model captures time-varying parameters, which is crucial given the dynamic nature of the relationship between digitalization and human capital. This model also addresses the issue of varying variance-covariance matrices over time, a characteristic frequently observed in economic time series data. The model is transformed into a TVP-VMA (Vector Moving Average) model to facilitate the analysis of impulse response functions and spillover effects. The generalized forecast error variance decomposition (GFEVD) is used to quantify the impact of shocks in one variable on others. The generalized spillover index is calculated to measure the overall connectedness between the variables. Finally, the concept of net pairwise directional spillover is utilized to understand the direction and magnitude of influence between individual pairs of variables. This comprehensive approach allows for a nuanced understanding of the dynamic interplay between these variables and provides a framework for policy analysis.

The empirical results, derived from the TVPVAR-EJC analysis, reveal a complex and dynamic relationship between digitalization and human capital in Vietnam. The study presents time-series graphs depicting fluctuations in the variables from 1996 to 2019, which are consistent with the historical policies and development milestones of the country. The analysis shows the existence of significant spillover effects between the different indicators, suggesting that changes in one variable can have considerable impact on the others. The GFEVD reveals the varying contributions of different variables to the overall forecast error variance, providing insights into the relative importance of each factor in the system. The generalized spillover index highlights periods of high and low connectedness among the variables across time, providing a measure of the overall dynamic interdependence within the system. Further analysis using net pairwise directional spillovers identifies specific relationships between pairs of indicators. The study provides a detailed time-varying analysis of these relationships, which changes significantly depending on the specific period analyzed, showing that policy interventions that occur during the sample significantly impact the observed connectedness. Specific numerical results from the GFEVD and spillover index calculations would be included in the full paper, along with detailed visualizations of the time-varying connectedness.

The findings demonstrate a complex and dynamic relationship between digitalization and human capital development in Vietnam. The strong interconnectedness revealed by the TVPVAR-EJC model suggests that policies aimed at promoting one aspect (e.g., digital infrastructure) can have significant ripple effects on others (e.g., human capital development). The time-varying nature of the relationships underscores the need for flexible and adaptive policies. The results support the importance of considering both short-term and long-term impacts of digitalization initiatives. The study's contribution lies in its methodological innovation and its specific application to the Vietnamese context, offering valuable insights for policymakers. The empirical findings provide a data-driven basis for informing policies aimed at optimizing the development and utilization of human capital in the digital age.

This research provides valuable insights into the dynamic relationship between digitalization and human capital development in Vietnam. The use of the TVPVAR-EJC model offers a significant methodological advancement in analyzing complex, time-varying relationships in the context of limited data. The findings underscore the importance of considering the interconnectedness of factors when designing policies related to digitalization and human capital. Future research could explore the role of specific digital technologies, further disaggregate human capital components, or investigate the impact of digitalization on different socio-economic groups.

One limitation is the availability of data. While the study utilizes innovative econometric techniques to overcome data scarcity, the availability of more comprehensive and granular data could enhance the analysis. The focus on Vietnam might limit the generalizability of findings to other contexts. Further research is needed to investigate potential causality beyond correlation and to explore the potential influence of unobserved variables.