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Midastar : Threshold Autoregression with Data Sampled at Mixed Frequencies
Motegi, Kaiji; Dennis, Jay - 2022
We propose Midastar models by combining the Mixed Data Sampling (MIDAS) and the threshold autoregression (TAR). The Midastar model of the first kind is designed for a low frequency target variable and a high frequency threshold variable. The proposed model can detect threshold effects...
Persistent link: https://www.econbiz.de/10014240508
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Beyond parametric bounds : exploring regional unemployment patterns using semiparametric spatial autoregression
Furková, Andrea; Knížat, Peter - In: Business systems research : a system view accross … 15 (2024) 2, pp. 48-66
explain the dynamics of the European Union's regional unemployment. Conclusions The results show that regional unemployment …
Persistent link: https://www.econbiz.de/10015108406
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The natural rate of unemployment : a regionally disaggregated approach
Burns, Andrew - 1990
Persistent link: https://www.econbiz.de/10000803565
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Can Google data help predict French youth unemployment?
Fondeur, Yannick; Karamé, Frédéric - In: Economic modelling 30 (2013), pp. 117-125
Persistent link: https://www.econbiz.de/10009703714
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Minimum distance estimation of the spatial panel autoregressive model
Azomahou, Théophile - In: Cliometrica : journal of historical economics and … 2 (2008) 1, pp. 49-83
Persistent link: https://www.econbiz.de/10003664278
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Estimating and forecasting with a dynamic spatial panel data model
Baltagi, Badi H.; Fingleton, Bernard; Pirotte, Alain - 2011
Persistent link: https://www.econbiz.de/10009546961
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Estimating and forecasting with a dynamic spatial panel data model
Baltagi, Badi H.; Fingleton, Bernard; Pirotte, Alain - In: Oxford bulletin of economics and statistics 76 (2014) 1, pp. 112-138
Persistent link: https://www.econbiz.de/10010439610
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Biases on variances estimated on large data-sets
Gardes, François - 2021
Persistent link: https://www.econbiz.de/10012668335
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Parameter estimation in spatial econometric models with non-random missing data
Seya, Hajime; Tomari, Masashi; Uno, Shohei - In: Applied economics letters 28 (2021) 6, pp. 440-446
Persistent link: https://www.econbiz.de/10012485047