Matyas Edits Volume on Big Data “The Econometrics of Multi-dimensional Panels” Published by Springer

Data revolution is upon us. New, complex, information rich, very large datasets are made available almost on a daily basis on some events, items, segments or individual agents of the economy and society. An increasing number of such data take the form of panels, where these are tracked over time.

In the course of the last two decades or so, the use of such panel data has become standard in most areas of economic analysis. The available model formulations have become more complex, estimation and hypothesis testing methods are more sophisticated. The interaction between economics and econometrics has resulted in a huge publication output, immensely deepening and widening our knowledge and understanding of both.

By nature, traditional panel data are two-dimensional. Lately, however, as part of the big data revolution, there has been a rapid emergence of three, four and even higher dimensional panels. This has happened by extending or dividing up the individuals observed (e.g. household and/or firm data), by matching different cross sectional data (e.g., matched employer-employee or doctor-patient data), by origin destination flow type data (e.g., trade, migration and investment), by cross-sectional data grouped according to some discrete variables (e.g., new college graduates' job market offerings or wage rates for different occupations, industries and regions),  by  multi-dimensional interactive data (e.g., social networking data with a large number of social groups and group members), and so on.

Oddly, applications have rushed ahead of theory. This book is aimed at filling the resulting widening gap in the field. The first ten chapters of the volume provide the econometric foundations to deal with these new high-dimensional panel data sets. Not only do they synthesize our current knowledge, but also present a wide range of new research results. Chapters 11-15 provide in-depth insights into some relevant empirical applications in the area. These chapters are a mixture of surveys and new studies, always focusing on the econometric problems and feasible solutions. They deepen our understanding of how econometrics can be applied to different kinds of data and economics problems.

The publication can be accessed here: http://www.springer.com/gp/book/9783319607825