Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff

By Thomas C. Herndon, M. Ash, R. Pollin. 2014

1,062 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/7d21785bcb2c316a9207ac2f1c38becb3c29d4e4

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Citations in the corpus

Fides: Towards a Platform for Responsible Data Science (2017, background): “For example, Reinhart and Rogoff omitted values in a spreadsheet from their analysis that motivated a global economic policy in austerity; inclusion of the missing values changed the conclusions [21].”
Open Access to Data: An Ideal Professed but Not Practised (2014, background): “Besides fraud, the debate surrounding the coding error by two eading economists on the negative relation between debt and rowth, which has been used to justify austerity programmes round the world, has also advanced the debate on data-sharing nd replication (Herndon et al., 2013; Reinhart and Rogoff”
Verifiable differential privacy (2015, background): “Mistakes can and do occur (even when the author is a Nobel prize winner [23]), and there have been cases where researchers appear to have fabricated or manipulated data to support their favorite hypothesis [6, 12, 27]; this is why reproducibility is a key principle of the scientific method.”
Exploration and Explanation in Computational Notebooks (2018, neutral): “Insights are sensitive to the methods used to produce them; small changes in how data are collected, cleaned, or processed can lead to vastly different results [13].”
The Politics of Public Debt: Neoliberalism, Capitalist Development and the Restructuring of the State (2014, neutral): “of sample construction in Reinhart and Rogoff’s 2010 study (Herndon et al., 2013), what should”
The influence of hidden researcher decisions in applied microeconomics (2020, critical): “The most well-known example of the latter is likely the attempt by (Herndon et al., 2014) to replicate Reinhart and Rogoff (2010), which uncovered a coding error in the original study.”
A Hierarchy of Limitations in Machine Learning (2020, methodology): “Documented examples of mistakes in scientific results mostly have to do with data handling, prior to going into software that does analysis and model-building (Miller, 2006; Karraker and Latham, 2015), especially when Excel is involved (Panko, 1998; Hutson, 2010; Herndon et al., 2013).”
The Meaning of Failed Replications: A Review and Proposal (2015, positive): “To take a famous example, Herndon et al. (2014) present a replication test of Reinhart and Rogoff (2010), in that they discuss what is indisputably an error (specifically, it is a verification test).”
Public debt and economic growth in advanced economies: A survey (2013, background): “7 This article was written before the release of Herndon et al.’s (2013) critique to Reinhart and Rogoff (2010).”