mw. J. (Joan) van Heijster


  • Faculteit der Maatschappij- en Gedragswetenschappen
    Programmagroep: Political Economy and Transnational Governance
  • Bezoekadres
    REC BC
  • J.vanHeijster@uva.nl

The Politics of Macroeconomic Measurement in China and India

This project focuses on the politics of macroeconomic measurements in China and India. The research traces the history of the Gross Domestic Product (GDP) indicator and tries to understand how developments in the Chinese and Indian political economy drive the changes in the measurement and use of GDP. Tthe construction of macroeconomic indicators is linked to the politics around economic planning.

Joan van Heijster has a background in International Relations with a focus on Asian political economy and the BRICS countries.
Key Words: Global Political Economy; Macroeconomic Measurements; GDP; China; India; Emerging Economies

 

Project Description - Background Information

China and India have become powerful countries in the global economy. But their enormous transformation during the past decades makes it hard to grasp the evolving shape of their economies. The formulas and measurements that OECD countries use are ambiguous already; in the case of China and India, it is even less clear what gets measured in official indicators, and why.To be sure, both countries have signed up to many international standards, for example the System of National Accounts. But as so often, the devil is in the detail, and real measurement decisions are made at the national level. So how do these countries measure their economies? And what are the political dynamics behind the choices they have made in this respect? 

India's rich statistical tradition

China and India have much to offer as stand-alone cases. On the one hand, India has a long colonial history with the United Kingdom. On the other hand, it has a long tradition of eminent statisticians, notably including Prasanta Chandra Mahalanobis, one of the two “developing country” representatives at the Nuclear Statistical Commission (the forerunner of the United Nations Statistical Office that first met in 1946), and the only one to play a leading role in subsequent years. Indeed, the development of statistics in India long precedes colonial times and, as a branch of applied mathematics, is well documented. In contrast, there is a dearth of scholarship on how India has historically measured its economy. How has the economic liberalization of the past decades filtered through India's complex political system into its national statistics?

'Is Chinese economic steering also visible in macroeconomic indicators?'

China, for its part, has a tradition of heavy government intervention in the economy, which survives despite gradual and highly selective liberalization. It is an open question to what extent government steering is also visible in the formulas underlying economic measurement. Debate of Chinese statistics has concentrated on the plausibility of GDP and growth figures. Similar questions have been raised about unemployment data. In addition to their value as stand-alone cases, China and India make an exciting comparison. To what degree have their liberalization trajectories led them to similar outcomes? Have national idiosyncrasies disappeared, or have they been strengthened?

Map measures in India and China

The goal of this project is threefold. First, they will map the evolution of measurement formulas in China and India for economic growth during the post-war period. In this largely descriptive endeavour, this project can draw on the insights from the other projects within the Fickle Formulas research project, which can provide pointers to the most contentious issues and important moments of international harmonization. In a second step, this project tests to what degree the dynamics found in the other subprojects - for example on the influence of expert groups or stakeholders like unions - also hold in China and India and if not, what explains these differences. In a third step, we can then gauge the influence of idiosyncratic factors per country.

 

 

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