 Nonstationary Panel DataGebhard Kirchgässner, Juergen Wolters and Uwe Hassler Chapter 7 in Introduction to Modern Time Series Analysis, 2013, pp 251-279 from Springer Abstract: Abstract In Chapter 4 we introduced an approach to analyse vectors of stationary time series, while Chapter 6 was devoted to the nonstationary case. With yth we denote the ith component at time t, t = 1, …, T. In typical time series applications the dimension of the vector is small (for instance equal to 3 in Examples 4.4. or 6.8), while the time dimension is rather large (T > 100). In a panel situation the number of components or units, denoted by N, is large as well, i = 1, …, N. There may be N price indices, N exchange rates or generally N countries or units. The unrestricted VAR(p) model from equation (4.1) allows each component to depend on its own lagged values and on the past of all other components. Hence, (4.1) includes p•N2 + N parameters when modelling time series from N units, a number growing fast with the dimension N. Already with N = 10 there would be hundreds of parameters to estimate. Therefore, the VAR approach is not applicable unless the cross-sectional dimension is rather small. Keywords: Panel Data; Unit Root; Percent Level; Unit Root Test; Generalise Little Square (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-3-642-33436-8_7 Ordering information: This item can be ordered from DOI: 10.1007/978-3-642-33436-8_7 Access Statistics for this chapter More chapters in Springer Texts in Business and Economics from Springer |
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