EmergingWelfare SIGNED

Project "EmergingWelfare" data sheet

The following table provides information about the project.

 Partnership

Take a look of project's partnership.

Map

 Project objective

This research project aims to identify a new welfare regime in emerging market economies and explain why it has emerged. The project will compare Brazil, China, India, Indonesia, Mexico, South Africa and Turkey to test two hypotheses: (i) emerging market economies are forming a new welfare regime that differs from liberal, corporatist and social democratic welfare regimes of the global north on the basis of extensive and decommodifying social assistance programmes, (ii) the new welfare regime emerges principally as a response to the growing political power of the poor as a dual source of threat and support for governments. Based on a comparative and interdisciplinary perspective, the project follows a multi-method strategy that combines state-of-the-art computer-based protest event data collection techniques, macro-historical methods, quantitative data analyses and qualitative content analysis. The project will radically expand the literatures on welfare regimes, welfare state development and contentious politics, by challenging the existing paradigms dominated by structuralist perspectives, a myopic focus on Western countries, and limited data collection and analysis techniques. This project is genuinely innovative, unprecedented, ground-breaking, ambitious and high-risk/high-gain in three ways: (i) it re-shapes the welfare regimes literatures as the first study to classify and explain welfare systems of emerging markets as a new welfare regime and (ii) the project demonstrates a causal link between changes in grassroots politics and welfare policies and challenge the structuralist preponderance in the existing welfare state development literature (iii) it makes a prodigious contribution to our empirical knowledge on contentious politics in emerging markets by creating the first cross-national databases on protest event, employing state-of-the art computer methods, such as natural language processing and machine learning, on newspaper archives.

 Publications