We employ a non-parametrical approach to growth accounting (Data Envelopment Analysis, DEA) to disentangle the proximate sources of labour productivity growth in 41 nations between 1929 and 1950 by decomposing productivity growth into four components: technological change, efficiency catch-up...

We describe a deep learning method to read hand-written records from the 16th century. The method consists of a combination of a segmentation module and a Handwritten Text Recognition (HTR) module. The transformer-based HTR module exploits both language and image features in reading, classifying...

We employ a non-parametrical approach to growth accounting (Data Envelopment Analysis, DEA) to disentangle the proximate sources of labour productivity growth in 41 nations between 1929 and 1950 by decomposing productivity growth into four components: technological change; efficiency catch-up...

Energy productivity is crucial for sustainable development. We use cointegration analyses to investigate the effect of electricity on energy productivity in Swedish industry from 1930 to 1990. Electricity augmented energy productivity in those industrial branches that used electricity for...

We address the issue of Western European regional productivity growth and convergence by means of Data Envelopment Analysis (DEA), decomposing labor productivity into efficiency change, technical change and capital accumulation. The decomposition shows that most regions have fallen behind the...