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AbstractIn this paper, we developed the recursive unit root tests to identify the beginning and end of potential speculative bubbles in the Chinese housing price cycles during 2006–2013 for the 70 major cities of China. The method is best suited for a practical implementation with a time series and delivers a consistent date‐stamping strategy for the origination and termination of multiple bubbles. Simulations demonstrate that the test significantly improves discriminatory power and leads to distinct power gains when multiple bubbles occur. Overall, the results indicate that the speculative housing price bubbles in China are not bursting, and they indicate that the stationarity of the housing price level varies across the different city sizes. Between the cities, approximately one‐fourth of the bubbles have burst up to December 2013, while the first‐tier city bubble may not burst due to the urbanization process.

Spatial sampling is widely used in environmental and social research. In this paper we consider the situation where instead of a single global estimate of the mean of an attribute for an area, estimates are required for each of many geographically defined reporting units (such as counties or grid cells) because their means cannot be assumed to be the same as the global figure. Not only may survey costs greatly increase if sample size has to be a function of the number of reporting units, estimator sampling error tends to be large if the population attribute of each reporting unit can be estimated by using only those samples actually lying inside the unit itself. This study proposes a computationally simple approach to multi-unit reporting by using analysis of variance and incorporating 'twice-stratified' statistics. We assume that, although the area is heterogeneous (the mean varies across the area), it can be zoned (or stratified) into homogeneous subareas (the mean is constant within each subarea) and, in addition, that it is possible to acquire prior knowledge about this partition. This zoning of the study area is independent of the reporting units. The zone estimates are transferred to the reporting units. We call the methodology sandwich estimation and we report two contrasting empirical studies to demonstrate the application of the methodology and to compare its performance against some other existing methods for tackling this problem. Our study shows that sandwich estimation performs well against two other frequently used, probabilistic, model-based approaches to multi-unit reporting on stratified heterogeneous surfaces whilst having the advantage of computational simplicity. We suggest those situations where sandwich estimation might be expected to do well.

Prestellar cores are self-gravitating dense and cold structures within molecular clouds where future stars are born. They are expected, at the stage of transitioning to the protostellar phase, to harbor centrally concentrated dense (sub)structures that will seed the formation of a new star or the binary/multiple stellar systems. Characterizing this critical stage of evolution is key to our understanding of star formation. In this work, we report the detection of high-density (sub)structures on the thousand-astronomical-unit (au) scale in a sample of dense prestellar cores. Through our recent ALMA observations toward the Orion Planck Galactic Cold Clumps, we have found five extremely dense prestellar cores, which have centrally concentrated regions of similar to 2000 au in size, and several 10(7) cm(-3) in average density. Masses of these centrally dense regions are in the range of 0.30 to 6.89 M. For the first time, our higher resolution observations (0.8 '' similar to 320 au) further reveal that one of the cores shows clear signatures of fragmentation; such individual substructures/fragments have sizes of 800-1700 au, masses of 0.08 to 0.84 M, densities of 2 - 8 x 10(7) cm(-3), and separations of similar to 1200 au. The substructures are massive enough (greater than or similar to 0.1 M) to form young stellar objects and are likely examples of the earliest stage of stellar embryos that can lead to widely (similar to 1200 au) separated multiple systems. ; Ministry of Science and Technology, China 108-2112-M-001-048- 108-2112-M-001-052- international partnership program of the Chinese Academy of Sciences 114231KYSB20200009 National Natural Science Foundation of China (NSFC) 12073061 Shanghai Pujiang Program 20PJ1415500 ANID AFB 170002 AFB-170002 National Natural Science Foundation of China (NSFC) U1631237 NRC Canada Natural Sciences and Engineering Research Council of Canada (NSERC) Spanish Government AYA2017-88754-P State Agency for Research of the Spanish Ministry of Science and Innovation through the "Unit of Excellence Maria de Maeztu 2020-2023" award CEX2019-000918-M Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education, Science and Technology NRF-2019R1A2C1010851 National Science Foundation (NSF) AST-1715876 National Natural Science Foundation of China (NSFC) 11911530226 11725313 11873086 Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research (KAKENHI) 20H05645 Yunnan Province of China 2017HC018 Chinese Academy of Sciences MoST 108-2112-M-001-017 MoST 109-2112-M-001-023 ; Versión publicada - versión final del editor