|
|
|
|
| LEADER |
05412nma a2201273 u 4500 |
| 001 |
EB002172969 |
| 003 |
EBX01000000000000001310746 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
230811 ||| eng |
| 020 |
|
|
|a books978-3-0365-7797-5
|
| 020 |
|
|
|a 9783036577975
|
| 020 |
|
|
|a 9783036577968
|
| 100 |
1 |
|
|a Gherghina, Ştefan Cristian
|
| 245 |
0 |
0 |
|a The Impact of COVID-19 on Financial Markets and the Real Economy
|h Elektronische Ressource
|
| 260 |
|
|
|a Basel
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2023
|
| 300 |
|
|
|a 1 electronic resource (346 p.)
|
| 653 |
|
|
|a Japanese model
|
| 653 |
|
|
|a market volatility
|
| 653 |
|
|
|a impulse response functions
|
| 653 |
|
|
|a COVID-19 pandemic
|
| 653 |
|
|
|a stock index
|
| 653 |
|
|
|a Latin America
|
| 653 |
|
|
|a informal labor
|
| 653 |
|
|
|a industrial sectors
|
| 653 |
|
|
|a sustainable development goal (SDG) index
|
| 653 |
|
|
|a Leontief model
|
| 653 |
|
|
|a information environment
|
| 653 |
|
|
|a n/a
|
| 653 |
|
|
|a coronavirus
|
| 653 |
|
|
|a loan restructuring policy
|
| 653 |
|
|
|a GARCH (1,1) model
|
| 653 |
|
|
|a financial time series forecasting
|
| 653 |
|
|
|a family firms
|
| 653 |
|
|
|a pandemic
|
| 653 |
|
|
|a transformation
|
| 653 |
|
|
|a forecasting methods
|
| 653 |
|
|
|a economic power
|
| 653 |
|
|
|a credit access
|
| 653 |
|
|
|a Dirichlet distribution
|
| 653 |
|
|
|a trade
|
| 653 |
|
|
|a US economy
|
| 653 |
|
|
|a the COVID-19 pandemic
|
| 653 |
|
|
|a pandemic impact
|
| 653 |
|
|
|a technical analysis
|
| 653 |
|
|
|a TRA model
|
| 653 |
|
|
|a entry mode
|
| 653 |
|
|
|a simulation
|
| 653 |
|
|
|a economic concentration
|
| 653 |
|
|
|a Vietnam
|
| 653 |
|
|
|a Chinese model
|
| 653 |
|
|
|a policy responses
|
| 653 |
|
|
|a business environment
|
| 653 |
|
|
|a monetary policy
|
| 653 |
|
|
|a urban
|
| 653 |
|
|
|a stock markets
|
| 653 |
|
|
|a COVID-19
|
| 653 |
|
|
|a impact
|
| 653 |
|
|
|a Anglo-Saxon model
|
| 653 |
|
|
|a early warning early action
|
| 653 |
|
|
|a Rhenish (German) model
|
| 653 |
|
|
|a generalized linear model (GLM)
|
| 653 |
|
|
|a banking sector
|
| 653 |
|
|
|a Economics, Finance, Business and Management / bicssc
|
| 653 |
|
|
|a socioeconomic model
|
| 653 |
|
|
|a rural
|
| 653 |
|
|
|a GDP
|
| 653 |
|
|
|a Scandinavian (Swedish) model
|
| 653 |
|
|
|a tourism
|
| 653 |
|
|
|a tourism sector
|
| 653 |
|
|
|a TAM model
|
| 653 |
|
|
|a multiplier effects
|
| 653 |
|
|
|a workforce
|
| 653 |
|
|
|a quality of life
|
| 653 |
|
|
|a corporate insolvency
|
| 653 |
|
|
|a state support measures
|
| 653 |
|
|
|a labor market
|
| 653 |
|
|
|a stock market
|
| 653 |
|
|
|a Canada
|
| 653 |
|
|
|a disaster
|
| 653 |
|
|
|a labour market
|
| 653 |
|
|
|a tourist and recreational potential
|
| 653 |
|
|
|a financial technology
|
| 653 |
|
|
|a COVID-19 outbreak
|
| 653 |
|
|
|a World Pandemic Uncertainty Index
|
| 653 |
|
|
|a mergers and acquisitions (M&As)
|
| 653 |
|
|
|a border areas
|
| 653 |
|
|
|a informational spread of coronavirus
|
| 653 |
|
|
|a uncertainty analysis
|
| 653 |
|
|
|a economy
|
| 653 |
|
|
|a economic groups
|
| 653 |
|
|
|a Ecuador
|
| 653 |
|
|
|a DSGE models
|
| 653 |
|
|
|a Stringency Index
|
| 653 |
|
|
|a system dynamics
|
| 700 |
1 |
|
|a Gherghina, Ştefan Cristian
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b DOAB
|a Directory of Open Access Books
|
| 500 |
|
|
|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
|
| 024 |
8 |
|
|a 10.3390/books978-3-0365-7797-5
|
| 856 |
4 |
0 |
|u https://www.mdpi.com/books/pdfview/book/7436
|7 0
|x Verlag
|3 Volltext
|
| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/101341
|z DOAB: description of the publication
|
| 082 |
0 |
|
|a 363
|
| 082 |
0 |
|
|a 000
|
| 082 |
0 |
|
|a 333
|
| 082 |
0 |
|
|a 380
|
| 082 |
0 |
|
|a 600
|
| 082 |
0 |
|
|a 330
|
| 520 |
|
|
|a This reprint comprises 17 papers published in the Special Issue entitled "The Impact of COVID-19 on Financial Markets and the Real Economy", centered on socioeconomic models affected by the pandemic (Vasin, 2022); the COVID-19 impact on various sectors or the economy as a whole, for instance in Canada (Singh et al., 2022), China (Habibi et al., 2022), Slovakia (Svabova et al., 2022), the United States (Rodousakis & Soklis, 2022) or Vietnam (Huynh et al., 2021; Nguyen et al., 2022); the benefits of teleworking on the continuity of operations across various sectors (Santos et al., 2022); research of the tourism and recreational possibilities of Russia and Kazakhstan's cross-border regions and the threats these areas faced during the pandemic (Tanina et al., 2022), the impact of the new coronavirus infection on the Russian labor market (Rodionov et al., 2022); the factors driving young Vietnamese people's intention to use financial technology in the context of the COVID-19 outbreak (Khuong et al., 2022) or those influencing access to credit for informal labor sector (Vu and Ho, 2022); predicting and analyzing Jordanian insurance firms' performance (Altarawneh et al., 2022) or developing an early warning system for solvency risk in the banking industry (Hidayat et al., 2022) during the COVID-19 pandemic; the impact of the pandemic on European stock markets (Keliuotyte-Staniuleniene and Kviklis, 2022); the drivers of cross-border mergers and acquisitions during the pandemic (Lee et al., 2021); examining the financial and fiscal variables of Ecuadorian economic groups (Tulcanaza-Prieto and Morocho-Cayamcela, 2021).
|