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This paper analyses the rapidly emerging discourse of a green economy based on green growth. It highlights inherent conflicts and contradictions of this discourse such as the myth of decoupling growth from the environment, pollution generations and resource consumption. Using key theoretical constructs of both Gramsci and Polanyi, the paper argues that the green economy/growth discourse can be seen as a Gramscian ‘passive revolution’ whereby the dominant sustainable development discourse, subsumed by capitalist hegemony, is protected in the context of global environmental, economic and development crises. The ‘neoliberalising of nature’, or in other words, the privatisation, marketisation and commodification of nature, akin to Polanyi's fictitious commodities, continues and intensifies with green economy/growth strategies. Greening the economy and associated strategies of green growth divert attention from the social and political dimensions of sustainability and issues of social and international justice. In this way, the inexorable march or ‘sustainable development’ of neoliberal capitalism is maintained. This paper goes on to argue that contesting the claims of green economy/growth discourse through political struggles by civil society against the neoliberalisation of nature is a sign of a slowly emerging counter-hegemonic ‘double movement’ which challenges capitalist hegemony and the commodification of society–nature relations.  相似文献   
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Recent work on the effects of currency unions (CUs) on trade stresses the importance of using many countries and years in order to obtain reliable estimates. However, for large samples, computational issues associated with the three‐way (exporter‐time, importer‐time, and country pair) fixed effects currently recommended in the gravity literature have heretofore limited the choice of estimator, leaving an important methodological gap. To address this gap, we introduce an iterative poisson pseudo‐maximum likelihood (PPML) estimation procedure that facilitates the inclusion of these fixed effects for large data sets and also allows for correlated errors across countries and time. When applied to a comprehensive sample with more than 200 countries trading over 65 years, these innovations flip the conclusions of an otherwise rigorously specified linear model. Most importantly, our estimates for both the overall CU effect and the Euro effect specifically are economically small and statistically insignificant. We also document that linear and PPML estimates of the Euro effect increasingly diverge as the sample size grows.  相似文献   
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