The Role of Government Expenditure and Economic Indicators in Mathematics Achievement: A Longitudinal Bayesian SEM Analysis of TIMSS in Jordan

In this study, 8th-grade performance records for the Trend International Mathematics and Science Study (TIMSS) for the period between the years 1999 and 2023 was used as a secondary source of data. Investigating these trends requires long-term analysis, as substantial changes on the system level are rarely observed regarding student outcomes in short periods. The study is grounded in several theoretical perspectives, including Human Capital Theory, Socioeconomic Status and Educational Outcomes, Educational Policy and Reform Theory, and Systems Theory in Education. These perspectives provide a comprehensive lens through which the interplay between economic factors, educational policies, and student achievement can be analyzed. Bayesian Structural Equation Model (SEM) was implemented to adequately take care of the sampling estimation Employing item response theory, we perform a concurrent calibration of item parameters was perform to link the eight studies onto a common scale spanning the period from 2019 to 2024 using data from empirical research. The results from the analysis yielded a strong association between Wage_and_Salaried_Workers and GDP. The regression loading of Wage_and_Salaried_Workers on its latent variable was estimated at 3.351 with a posterior standard deviation of 0.330, indicating a robust and highly significant association. However, the estimated covariances between the latent variable associated with economic factors (GDP and wage_and_salaried_workers) and other endogenous variables like Gov_Exp_Secondary and TIMSS_Achievement were notably low (Estimates of -0.008 and -0.277 respectively). These findings imply that while each construct significantly impacts its respective domain, their interactions are limited, indicating potential independence in their effects within the model structure. Overall, TIMSS results shows that the quality of education in Jordan is relatively low compared to the international landscape.