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Wyszukujesz frazę "Zhu, Kai" wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Paths to low-carbon development in China: The role of government environmental target constraints
Autorzy:
Bai, Tingting
Xu, Dong
Yang, Qianyi
Dudás Piroska, Vargáné
Dénes Dávid, Lóránt
Zhu, Kai
Powiązania:
https://bibliotekanauki.pl/articles/39830406.pdf
Data publikacji:
2023
Wydawca:
Instytut Badań Gospodarczych
Tematy:
government environmental target constraints
carbon emissions
energy consumption
industrial structure optimization
green technology innovation
Opis:
Research background: To achieve the targets for carbon peak and air quality improvement, local governments should propose environmental targets and develop realization paths that are tailored to their unique local conditions. They then promote low-carbon development through the implementation of multiple measures. Purpose of the article: As the government performance appraisal system im-proves, the question arises as to whether governments take the initiative to com-bine environmental policies with government target constraints to reduce carbon emissions. Methods: The announcement of environmental target constraints by local governments in government work reports is considered a quasi-natural experiment. This study examines the effect of government environmental target constraints (GETC) on carbon emissions (CEs) using differences-in-differences (DID), propensity score matching-DID (PSM-DID), and spatial-DID (SDID) with data from 241 Chinese cities from 2003 to 2019. Findings & value added: The results demonstrate that GETC can effectively reduce local CEs, with the inhibitory effect being most effective in the first two years after setting environmental targets, but diminishing in the third year. GETC can reduce local CEs through three paths: reducing energy consumption, promoting industrial structure optimization, and encouraging green technology innovation. Spatial spillover effects show that GETC reduces local CEs while exacerbating CEs in neighboring cities, indicating a beggar-thy-neighbor effect in conventional environmental regulation policy. This effect is observed mainly in the geographic matrix and the economic-geographic matrix, but not in the economic matrix. According to heterogeneity analysis, GETC in the eastern and central cities can significantly reduce CEs. The inhibitory effect of GETC on local CEs is stronger in cities where secretaries and mayors have longer tenures and higher levels of education. The paper's theoretical value lies in exploring the reduction of CEs through the combination of government self-restraint and environmental policies, providing a new solution for local governments to achieve CEs reduction. Furthermore, it offers practical insights into the improvement of the Chinese government assessment system.
Źródło:
Oeconomia Copernicana; 2023, 14, 4; 1139-1173
2083-1277
Pojawia się w:
Oeconomia Copernicana
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Google and Apple mobility data as predictors for European tourism during the COVID-19 pandemic: A neural network approach
Autorzy:
Nagy, Benedek
Gabor, Manuela Rozalia
Bacoș, Ioan Bogdan
Kabil, Moaaz
Zhu, Kai
Dávid, Lóránt Dénes
Powiązania:
https://bibliotekanauki.pl/articles/22402532.pdf
Data publikacji:
2023
Wydawca:
Instytut Badań Gospodarczych
Tematy:
Mobility
Tourism
Google Mobility data
Apple mobility data
Europe
COVID-19 pandemic
Opis:
Research background: The COVID-19 pandemic has caused unprecedented disruptions to the global tourism industry, resulting in significant impacts on both human and economic activities. Travel restrictions, border closures, and quarantine measures have led to a sharp decline in tourism demand, causing businesses to shut down, jobs to be lost, and economies to suffer. Purpose of the article: This study aims to examine the correlation and causal relationship between real-time mobility data and statistical data on tourism, specifically tourism overnights, across eleven European countries during the first 14 months of the pandemic. We analyzed the short longitudinal connections between two dimensions of tourism and related activities. Methods: Our method is to use Google and Apple's observational data to link with tourism statistical data, enabling the development of early predictive models and econometric models for tourism overnights (or other tourism indices). This approach leverages the more timely and more reliable mobility data from Google and Apple, which is published with less delay than tourism statistical data. Findings & value added: Our findings indicate statistically significant correlations between specific mobility dimensions, such as recreation and retail, parks, and tourism statistical data, but poor or insignificant relations with workplace and transit dimensions. We have identified that leisure and recreation have a much stronger influence on tourism than the domestic and routine-named dimensions. Additionally, our neural network analysis revealed that Google Mobility Parks and Google Mobility Retail & Recreation are the best predictors for tourism, while Apple Driving and Apple Walking also show significant correlations with tourism data. The main added value of our research is that it combines observational data with statistical data, demonstrates that Google and Apple location data can be used to model tourism phenomena, and identifies specific methods to determine the extent, direction, and intensity of the relationship between mobility and tourism flows.
Źródło:
Equilibrium. Quarterly Journal of Economics and Economic Policy; 2023, 18, 2; 419-459
1689-765X
2353-3293
Pojawia się w:
Equilibrium. Quarterly Journal of Economics and Economic Policy
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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