Monthly Prefecture-Level GDP in Japan
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- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015.
"Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility,"
Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
- Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2013. "Real-Time Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility," CEPR Discussion Papers 9312, C.E.P.R. Discussion Papers.
- Urasawa, Satoshi, 2014. "Real-time GDP forecasting for Japan: A dynamic factor model approach," Journal of the Japanese and International Economies, Elsevier, vol. 34(C), pages 116-134.
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This paper has been announced in the following NEP Reports:- NEP-GEO-2025-10-13 (Economic Geography)
- NEP-SEA-2025-10-13 (South East Asia)
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