Wyniki wyszukiwania - Biblioteka Nauki

Nowa wersja platformy, zawierająca wyłącznie zasoby pełnotekstowe, jest już dostępna.
Przejdź na https://bibliotekanauki.pl

Ograniczanie wyników

Znaleziono wyników: 3

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: spatial Durbin model

Sortuj według:

Ogranicz wyniki do:

Wage Differences in Poland at the County Level and their Determinants

100%

Luśtyk A. , Połeć A. , Voznyuk I.

Central European Economic Journal

2024

tom 11

nr 58

447-460

This study investigates the impact of unemployment and labour productivity on relative wages in Polish counties (powiats) from 2008 to 2021. Labour productivity is measured as the ratio of sold industrial production to the number of workers. The data is sourced from the Local Data Bank of Statistics Poland. The analysis employs the Solow model of efficiency wages, the neoclassical Solow model, and the Durbin model of spatial econometrics. The results reveal that both unemployment and labour productivity are statistically significant in explaining relative wages, with unemployment having the strongest, albeit negative, effect during the study period. Notably, changes in unemployment rates or wages in a county influence wage changes in neighbouring counties. The issue of spatial wage differences at the county level in Poland has not been sufficiently explored in recent years. Although recent research has focused on regional (voivodeship-level) wage differences, there remains a gap in understanding wage differences at the county level. Given changes in the Polish labour market, particularly due to the COVID-19 pandemic, this study aims to update previous findings and provide a more detailed analysis.

The Impact of the Digital Economy on the High-Quality Development of Green Marketing in China's Manufacturing Industry: Applications of the Spatial Durbin Model

88%

Li J. , Shen Y. , Sun L. , Sun T.

Rocznik Ochrona Środowiska

2024

tom Tom 26

449--464

The digital economy provides China's manufacturing industry with a pathway to establish new national competitive advantages and is an essential driving force for the high-quality advancement of green marketing. Utilizing data from 30 Chinese provinces from 2013 to 2022, this study employs the spatial Durbin model to investigate the spatial relationship between the digital economy and the advancement of green marketing at a high quality. The findings indicate that the growth of the digital economy significantly fosters high-quality development in green marketing and exhibits positive spatial spillover effects on neighboring regions. The Application of spatial Durbin regression to multi-province areas has revealed that the more economically developed the region, significantly influences of the digital economy on the high-quality development of green marketing, with a local siphoning phenomenon currently visible in the eastern region. The western region exhibits a spatially positive spillover effect from the high-quality development of green marketing in other regions. Furthermore, developing the digital economy in neighboring regions significantly enhances the high-quality development of green marketing in this region. The findings remain stable when evaluated using the alternative variables method and the control fixed effects approach.

An empirical study on emissions trading influence for the enterprise environmental responsibility

63%

Zhao J.-X.

tom Vol. 30, nr 2

259--266

The primary objective of this paper is to address the inherent biases in the calculation of carbon emissions trading (CET) and foster the development of green innovation. By employing panel data from carbon emission trading pilots, the spatial Durbin model (SDID) is applied to assess the impact of CET on corporate environmental responsibility. By integrating CET and corporate environmental responsibility within a unified framework, this paper presents a novel analysis of the influence of environmental regulations on corporate environmental responsibility at the micro-level. Additionally, this study examines the spatial spillover effect of CET, thereby rectifying estimation biases. The model validation results indicate statistical significance below the 1 % level. The findings of this research reveal that it analyses the specific channels through which CET influences corporate environmental responsibility, providing insights that address the limitations of previous studies in mechanism analysis.