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This paper considers testing for unit roots in Gaussian panels with crosssectional dependence generated by common factors. Within our setup we can analyze restricted versions of the two prevalent approaches in the literature, that of Moon & Perron (2004), who specify a factor model for the...
Persistent link: https://www.econbiz.de/10014357544
This paper considers a heterogeneous panel unit root model with cross-sectional dependence generated by a factor structure – the factor common to all units being an observed covariate. The model is shown to be Locally Asymptotically Mixed Normal (LAMN), with the random part of the limiting...
Persistent link: https://www.econbiz.de/10013052356
This paper considers unit-root tests in large n and large T heterogeneous panels with cross-sectional dependence generated by unobserved factors. We reconsider the two prevalent approaches in the literature, that of Moon and Perron (2004) and the PANIC setup proposed in Bai and Ng (2004). While...
Persistent link: https://www.econbiz.de/10012869636
We derive the power envelope for panel unit root tests where heterogeneous alternatives are modeled via zero-expectation random perturbations. We obtain an asymptotically UMP test and discuss how to proceed when one is agnostic about the expectation of the perturbations
Persistent link: https://www.econbiz.de/10013014914
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-valued phenomena that evolve over time. The distribution of an INAR(p) process is essentially described by two parameters: a vector of autoregression coefficients and a probability distribution on...
Persistent link: https://www.econbiz.de/10014050438
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-valued phenomena that evolve over time. The distribution of an INAR(p) process is essentially described by two parameters: a vector of autoregression coefficients and a probability distribution on...
Persistent link: https://www.econbiz.de/10014217553
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