Tóm tắt:
Nghiên cứu này nhằm đánh giá vai trò của vốn nhân lực (VNL) đối với tiến bộ công nghệ tại các quốc gia ASEAN giai đoạn 1971-2019. Bằng việc sử dụng thuật toán Markov chain Monte Carlo (MCMC) trong khuôn khổ cách tiếp cận hiệu ứng hỗn hợp Bayes, kết quả cho thấy nguồn nhân lực trình độ trung học đóng góp nhiều hơn cho tiến bộ công nghệ so với trình độ đại học. Ngoài ra, hoạt động du nhập và hấp thụ công nghệ nước ngoài đóng góp nhiều hơn cho tăng trưởng công nghệ tại các nước ASEAN. Các phát hiện phù hợp với dự báo của mô hình Nelson-Phelps. Dựa trên kết quả nghiên cứu, nhóm tác giả đề xuất bốn nhóm giải pháp nhằm phát triển nhanh VNL góp phần thúc đẩy tiến bộ công nghệ tại Cộng đồng ASEAN.
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Abstract:
The study aims to assess the role of human capital in technological advancement in ASEAN countries during the period 1971–2019. Using the Markov Chain Monte Carlo (MCMC) algorithm within a Bayesian mixed-effects framework, the results indicate that secondary-level human capital contributes more to technological progress than tertiary-level human capital. Additionally, the adoption and absorption of foreign technology play a more significant role in driving technological growth in ASEAN countries. These findings align with the predictions of the Nelson-Phelps model. Based on the research results, the author proposes four solutions to rapidly develop.