The aim of this paper is to introduce a practical nonlinear generalization of PCA that captures nonlinear forms of dependence and delivers truly independent factors. The output of the method is a low-dimensional curvilinear coordinate system that tracks the important features of the data. The...

Governments around the world want to develop their ICT and digital industries. Policymakers thus need a clear sense of the size and characteristics of digital businesses, but this is hard to do with conventional datasets and industry codes. This paper uses innovative 'big data' resources to...

This paper investigated the usage of artificial intelligence and text mining techniques for classification of court judgments and discussed potential alternative applications in formulation and evaluation of public policies. Besides, we built a survey of studies related to Jurimetry based on the...

The use of "Big Data" to explain fluctuations in the broader economy or guide the business decisions of a firm is now so commonplace that in some instances it has even begun to rival more traditional government statistics and business analytics. Big data sources can very often provide advantages...

We investigate the macroeconomic impacts of mothballed businesses-those that closed temporarily-on sectoral equilibrium prices after a negative demand shock. First, we introduce a new establishment-level dataset derived from Google Places. We confirm the importance of temporary closures during...