Data revolution is upon us. New, complex, information reach dataset are made available almost daily basis on some segments or individual agents of the economy and society. An increasing number of such datasets take the form on panels, where individuals are tracked over some time period.
The last two decades or so, the use of such panel data has become a standard in most areas of economic analysis. The available models formulations became more complex, the estimation and hypothesis testing methods more sophisticated. The interaction between economics and econometrics resulted in a huge publication output, deepening and widening immensely our knowledge and understanding in both.
Traditional panel data sets, by nature, 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 panel data sets. These arose by extending or dividing the observed individuals (like household and/or firm area data, etc.), by matching different cross sectional data (e.g., matched employer-employee, doctor-patient, etc. data), by origin destination flow type data (e.g., trade, migration, investment, etc.), by cross-sectional data grouped according to some discrete variables (e.g., new college graduates' job market offerings and wage rates for different occupations, industries, regions etc.), 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 rushed ahead of theory in this field. This book is aimed at filling this widening gap. The first ten chapters of the volume are providing the econometric foundations to deal with these new high-dimensional panel data sets. They not only synthesize our current knowledge, but mostly present new research results. Chapters 11-15 provide in-depth insights into some relevant empirical applications in this area. These chapters are a mixture of surveys and new results, always focusing on the econometric problems and feasible solutions. They deepen our understanding on how econometrics can be applied to different kinds of data and economics problems.