the paper presents an analysis of both energy intensity and energy demand for the italianindustrial sector. the aim of the paper is twofold: making a decomposition of energy intensity at the aggregate level and modeling energy demand at the firm level. the decomposition of energy intensity shows different patterns for the different sub-sectors in the period of interest. in the micro approach, p...

We argue that the welfare inferences drawn from answers to subjective-qualitative survey questions are clouded by concerns over the structure of measurement errors and how latent psychological factors influence observed respondent characteristics. We propose a panel data model that allows more robust tests and we estimate the model on a high-quality survey for Russia. We find significant income...

Hellinger distance has been successfully used as a tree splitting criterion in Hellinger Distance Decision Trees [10] (HDDT) for unbalanced static datasets. In unbalanced data streams, state-of-the-art techniques use instance propagation and standard decision trees to cope with the unbalanced problem. However it is not always possible to revisit/store old instances of a stream. We solve this pr...

the paper presents an analysis of both energy intensity and energy demand for the italianindustrial sector. the aim of the paper is twofold: making a decomposition of energy intensity at the aggregate level and modeling energy demand at the firm level. the decomposition of energy intensity shows different patterns for the different sub-sectors in the period of interest. in the micro approach, p...

The objective of this study is to investigate the factors affecting firm competitiveness in an emerging market—Turkey. In the paper, competitiveness is proxied by a firm’s financial performance. The empirical analysis is based on firms listed on Borsa Istanbul and covers the period between 2005 and 2014. Results from a firm-level panel data model indicate that return on assets is positively rel...