The Role of the Green Economy in Supporting Sustainable Economic Development in Iraq: An Analytical Study (2000-2024)
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Abstract
This study examines the interplay between [dependent variable] and the explanatory factors—VAA, CRE, and CDE using annual data from 2000 to 2024. The researchers adopted the Autoregressive Distributed Lag (ARDL) approach, which is actually pretty well-suited for capturing both immediate and lagged responses among variables in a time series. The ARDL bounds test pointed to Cointegration, so there’s clearly a stable, long-term equilibrium tying these variables together. When you look at the long-run estimates, it’s clear: lagged values of VAA and CRE have significant positive effects. CDE, though, is a bit of a mixed bag showing a positive influence in the short term, but then turning negative as time goes on. As for the short-run dynamics, the negative and statistically significant error correction term indicates that any deviation from equilibrium tends to get corrected fairly quickly. On the diagnostics front, the model didn’t trip any alarms no serial correlation, no heteroscedasticity, and the residuals look pretty normal. All things considered, the findings underscore the importance of tracking both short-term changes and long-term trends in policy or strategic planning. The evidence here isn’t just theoretical; it’s grounded in actual data, making for more informed decision-making.
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