Exploring Time Series Techniques in Production Function Modeling: ARIMA and VECM Applications

This paper uses both used ARIMA and VECM models to analyze the production function to determine the interactions between GDP, capital and labor inputs in this analysis. The paper explores short-term dynamics as well as equilibrium behavior of these variables using annual data for the period 1984–2023. The coefficients estimated by the ARIMA (2,0,0) model indicate that current GDP depends on its past levels, and both capital and labor, although they have positive signs, are statistically insignificant. Moreover, Johsen cointegration estimates unfold one co-integrating vector; VECM result also confirms the positive association between capital and GDP but an unexpected negative relation with labor. The above study’s findings reaffirm the status of capital accumulation as a foundation for developing states’ growth policy priorities; the results of labor analysis are inconclusive and may indicate issues such as difficulty in measuring labor or the possibility of structural changes. The policy implications are for the continuous long term orientations, reform of the labor market, improving human capital, and expanding economic diversification. The paper recognizes certain limitations in the type of data and model used and recommends that future research consider non linearities, technological progress to transfer technological improvement to the production function as well as examining sectoral differences for a better understanding of growth paths in fast growing economies.