the field of educational studies. My results indicate that short-run analyses may underestimate total skill changes. Panel VAR models can offer advantages over other approaches for specific educational questions. To the best of my knowledge, this is the first effort to apply such a model to analyze and understand dynamics within the literature on skill development. Economic modeling, however, always comes at the cost of simplification. Future research could build further on the panel VAR model from chapter 4 by incorporating more extended models. By doing so, researchers could enhance the robustness and applicability of these models. One of the strengths of this dissertation is its use of unique data that provide information on students’ skill proficiencies. However, these data unfortunately cannot be used to examine the mechanisms behind our findings, as they typically incorporate outcomes rather than the underlying processes. Therefore, future research could be devoted to mechanisms behind the development of skills. To understand these mechanisms in the skill development process, we would need to look beyond performance measures and consider other factors (e.g., cognitive processes, teaching strategies, motivations, etc.), which could shed light on how and why these skills develop in the first place. This can be accomplished by collecting additional quantitative data on these factors Or, future research could involve an analysis using qualitative data, such as interviews, case studies, or observational research. This dissertation begins by demonstrating the long-run association between early basic skills and adult satisfaction. However, it remains unclear how this relationship works, and particularly what mechanisms (beyond income and daily functioning) andpathways drive the connec145
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