Energy intensity, economic structure, and capital goods imports in upper-middle income countries: Insights from HDBSCAN clustering.

In recent years, there have been substantial efforts to improve the efficiency of production resources, including energy use, to reduce the human footprint from economic activities. Increasing production capacity and incorporating new technologies that improve energy efficiency in the production process are two primary challenges faced by developing countries, where capital goods imports could play a key role in addressing both challenges. This paper contributes to the empirical literature by examining the relationship between energy intensity, economic structure, and capital goods imports in a set of 36 upper-middle income economies in the period 2000-2019. The empirical strategy recognizes the existing heterogeneity among the broad group of countries in the sample by implementing the Hierarchical Density-Based Spatial Clustering of Applications with Noise algorithm, a state-of-the-art unsupervised machine learning technique which allows identification of clusters of countries and years. The results show the existence of ten clusters, where energy intensity has the most relevant positive associations with industry share, trade openness, and merchandise imports. Improvements in regulatory quality are associated with lower energy intensity. The direction and strength of the relationship between energy intensity and capital goods imports depend on the cluster; nonetheless, it is usually a weak relationship. Policy implications are discussed.

Tracking temporal trend breaks of anthropogenic change in Mussel Watch (MW) databases.

The potential for structural changes in time trend concentrations of mercury (Hg), lead (Pb), cadmium (Cd), zinc (Zn), and copper (Cu) in the Mediterranean mussel, Mytilus galloprovincialis, was examined in Mussel Watch (MW) databases of metal pollution at eighteen coastal stations over a decadal period, from 1992 to 2007. Simultaneously, by using two statistical methods representing both the classical hypothesis-testing and the Bayesian approaches, we found single and multiple trend breaks for Hg (28% of the stations), Cd (17%), and Pb (11%) within trends in connection with anthropogenic and subtle natural environmental changes. Also called change point problems, if not accounted for, these could bias time trend investigations and interpretations. We calculated trend rate differences of 39% and switches up to 1 order of magnitude from classical linear trend assessments. We discuss sampling, analytical, and environmental (both natural and anthropogenic) sources of data set variabilities, showing that, in practice, the overall 16-year analytical performance could be as elevated as the yearly sampling reproducibility. We demonstrate that environmental time trend interpretations benefit from undertaking prior structural change analysis. After decades of MW marine chemical pollution assessments these have proven extremely useful, although the occurrence of trend breaks directly affects the long-term marine environmental monitoring strategies. Our results suggest a broader concept to design monitoring programs in agreement with rapid global anthropogenic and environmental changes.