At the end of 2023, the M2 broad money supply in China amounted to over 292 trillion yuan. Broad money supply had been growing consistently over the years. However, the overall growth rate of all money supply had been decreasing.

Money is not money?

In economic theory, money supply describes the volume of currency that exists in a country. Even though it might sound counterintuitive, there are different types of money. For example, cash, saving deposits, or other liquid assets are then divided into tiers from M1 to M3. Thereby, M2 money or broad money comprised of cash and assets that can easily be converted into cash. The main application of M2 money is making payments and economic transactions. For mainstream economists, the volume of M1 and M2 money can indicate inflation.

The mysterious case of money expansion in China

The post-pandemic economic recovery has not materialized as the growth in the M2 money supply would have indicated in China. As a consequence of global anti-COVID-19 measures, China’s economic growth fell far below the country’s development targets. After another underperforming year in 2022, the M2 money supply grew by almost 13 percent in the first quarter of 2023, but the GDP increased only by 4.5 percent, which indicated that the money does not reach the real economy. Therefore, the Chinese economy could be in a liquidity trap or a balance sheet recession.

Graph and download economic data for M2 for China (MYAGM2CNM189N) from Dec 1998 to Aug 2019 about M2, China, and monetary aggregates.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Historical price and volatility data for Velocity in Chinese Yuan Renminbi across different time periods.

In 2022, the number of high-speed train carriages in China increased by about one percent. By the end of that year, the total number of high-speed train carriages in operation in the country reached 33,554.

By the end of 2023, the M1 money supply in China amounted to over 68 trillion yuan. M1 money supply includes cash and demand deposits.

Event waveforms data that detected in Changning area, China from July 6, 2019 to August 21, 2019. Folders in all_event compressed files are all named by event occurrence time. The earthquake catalog (tomoDD_mag.dat) and Velocity models are also included. Each column in the tomoDD_mag.dat represents longitude, latitude, year, month, day, magnitude, depth, hour, minute, and second.

Historical price and volatility data for Velocity in Chinese Yuan Renminbi across different time periods.

The South China Block is located on the eastern margin of the Eurasian Plate and the western margin of the Pacific Plate. The South China Block is currently in a tectonically compressed environment, while the Tibetan Plateau is moving eastward and the Philippine Sea Plate is moving westward from geodetic observations. The South China Block is an ideal place to revisit tectonic history from the Archean to Cenozoic, where its information could be well preserved in the crust. In this study, we aim to build the crustal and uppermost mantle component of the Seismological Reference Earth Model in South China (SREM-SC) to provide a background velocity model for geological interpretations and fine-scale velocity inversion. The S-wave velocity model comes from combining models inverted by ambient noise tomography and surface wave tomography. The P-wave velocity model is obtained from converted S-wave velocity and joint inversion tomography. The density model is inferred from an empirical relationship with P-wave velocity. The Moho depth is obtained by a weighted averaging scheme of previously published receiver function results. The P-wave and S-wave velocity models have a grid interval of 0.5° in both latitude and longitude, and with a vertical sampling interval of 5 km down to the 60 km depth. This work provides the 3-D crust and uppermost mantle structures and a representative reference model beneath South China.

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This dataset includes the monthly mean velocity spectrum width and turbulence dissipation rate from 0900 local standard time (LST) to 1700 LST in 2021, which are retrieved from the radar wind profiler measurements at Baoding (urban) and Zhangbei (plateau) stations. Each data file is stored in xlsx format and contains two sheets, and each sheet is a two-dimensional data, including velocity spectrum width and turbulence dissipation rate. These two variables are stored in a matrix of 30 rows and 9 columns. The row refers to the height at an interval of 120 meters, and the columns refers to time which corresponds to 0900 to 1700 LST.

The files uploaded here contain the vertical component records of earthquakes used to measure Rayleigh wave phase velocities in continental China.

This data set consists of Wavespeed models for Southern Sichuan Basin derived using data from 2019 to 2020 in the CENC, augmented by P wave data from automatic picking.

Velmodel_Weiyuan_Changning - Lat: Latitude in decimal degrees - Lon: Longitude in decimal degrees - Depth: Depth (below sea level) in kilometers - Vp: Compressional wavespeed - Vs: Shear wavespeed

4 Active Global Constant velocity universal joint parts suppliers, manufacturers list and Global Constant velocity universal joint parts exporters directory compiled from actual Global export shipments of Constant velocity universal joint parts.

Historical price and volatility data for Chinese Yuan Renminbi in Velocity across different time periods.

3D S-wave velocity model of the Tengchong volcano, China

Climate change is causing widespread boundary shifts of terrestrial plants. However, current works mainly focus on leading edges, but seldom takes a comparative study of trailing and leading edge shifts. Here, the shifts of Chinese trees were simulated along the leading and trailing edges under the maximum representative concentration path (RCP8.5). The results show that Chinese trees likely exhibit a variety of asymmetric boundary shift pattern. Synchronous northward (62.7%) dominant the trade off shift between leading and trailing edge and temperature factors have a significant positive correlation with the boundary shift distance. The other 37.3% species show a southward shift for one or two edges and this pattern could be mainly the comprehensive interaction of heat, low temperature, available water and topographic factors. The study suggest that simple view of polarward shift for leading and trailing edges is not suitable for the explanation of tree migration in China.

(1) The Terrestrial Hybrid Repeated Gravity Observation data is applied from Data Sharing Infrastructure of National Earthquake Data Center(http://data.earthquake.cn).Only Chinese language link(https://data.earthquake.cn/datashare/report.shtml?PAGEID=datasourcelist&dt=40280d0453e5add30153e5ee3dc1001f; https://data.earthquake.cn/datashare/report.shtml?PAGEID=datasourcelist&dt=40280d0453e5add30153e5f03dd10022). Data can be requested through the email application form or the offline application form.

(2) Earthquake catalog data comes from the end of China Seismic Experimental Site webpage (http://www.cses.ac.cn/sjcp/ggmx/2021/132.shtml). Click on "cata2019".
(3) ³He/⁴He release data is downloaded from the supplementary data of published article. (https://github.com/mzhangrocks/Plateau-Growth) We have cited this article in this paper.
(4) The 3-D P- and S-wave community velocity model of the crust and uppermost mantle in southwest China is downloaded from the supplementary data of published article. (https://github.com/liuyingustc/SWChinaCVM),(SWChinaCVM-1.0, DOI:10.12093/02md.02.2019.01.v1). We have cited this article in this paper.

Wind direction/velocity and current direction/velocity data were collected using current meter casts in a world wide distribution from December 6, 1970 to October 1, 1991. Data were submitted by the Japan Oceanographic Data Center (JODC).