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- W3129022320 abstract "A fractionally integrated panel data model with a multi-level cross-sectional dependence is proposed. Such dependence is driven by a factor structure that captures comovements between blocks of variables through top-level factors, and within these blocks by non-pervasive factors. The model can include stationary and non-stationary variables, which makes it flexible enough to analyze relevant dynamics that are frequently found in macroeconomic and financial panels. The estimation methodology is based on fractionally differenced block-by-block cross-sectional averages. Monte Carlo simulations suggest that the procedure performs well in typical samples sizes. This methodology is applied to study the long-run relationship between energy consumption and economic growth. The main results suggest that estimates in some empirical studies may have some positive biases caused by neglecting the presence non-pervasive cross-sectional dependence and long-range dependence processes." @default.
- W3129022320 created "2021-02-15" @default.
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- W3129022320 date "2022-07-01" @default.
- W3129022320 modified "2023-09-26" @default.
- W3129022320 title "Energy consumption and GDP: a panel data analysis with multi-level cross-sectional dependence" @default.
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- W3129022320 doi "https://doi.org/10.1016/j.ecosta.2020.11.002" @default.
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