The Unassuming Economist

John H. Cochrane, Senior Fellow at the Hoover Institution (Stanford University) writes about the inflationary impact of pent-up demand in the post-pandemic period in his blog, The Grumpy Economist. He writes:

“Milton Friedman once said that if you want inflation, you can just drop money from helicopters. That is basically what the US government has done. But this US inflation is ultimately fiscal, not monetary. People do not have an excess of money relative to bonds; rather, people have extra savings and extra apparent wealth to spend. Had the government borrowed the entire $5 trillion to write the same checks, we likely would have the same inflation.”

In the subsequent sections, he discusses reasons why the Covid-19 related fiscal stimulus produce inflation when previous stimulus efforts from 2008 to 2020 fizzled.

Click here to read the full blog.

In a column for VoxEU CEPR, Majed Dodin and Sebastian Findeisen of the University of Manheim, Lukas Henkel of the European Central Bank, Dominik Sachs of the University of St. Gallen, and Paul Schüle of the University of Munich write about social mobility in Germany.

“According to the OECD, social mobility in Germany is lower than in most other developed economies, reigniting a debate on equality of opportunity and shortcomings of the education system. This column discusses how census data can be used to obtain high-quality mobility statistics for Germany. Using the Abitur educational qualification as a measure of opportunity, it suggests that relative mobility has remained constant for recent birth cohorts but points to substantial geographic variation in mobility measures across regions in the country.”

Click here to read the full blog.

The recently published book, India’s Industrial Policy and Performance (2021), by Dr. Nitya Nanda (Director, Council for Social Development- a New Delhi-based think tank) assesses the performance of Indian industries from the perspectives of trade, investment, policy, and development incentives. Excerpts from its abstract:

“The book examines India’s key policy initiatives and economic and institutional plans through many decades and examines their short and long-term effects on industrial environment and performance. It measures India’s strategic policies and efforts to promote industrialization against similar initiatives in countries like Germany, Japan, South Korea, and Taiwan. The volume also contextualizes the performance of different sectors of industry such as automobiles, electronics and information technology, and pharmaceuticals, among others, within the larger framework of global economic scenario and competition.”

It also discusses issues like the benefit foreign direct investment brings to developing countries (Loungani and Razin, 2001), changes in foreign equity norms in India and their role in shaping industrial policy, etc.

Click here to access the full book online.

The IMF’s major book on policies to achieve inclusive growth was just published. The book is available here. 

This and the book, Confronting Inequality: How Societies Can Choose Inclusive Growth (Ostry, Loungani, Berg; 2019) together make a compelling case for why inequality matters for efficiency and what policies can foster inclusive growth. 

New paper by Jennifer L. Castle , Jurgen A. Doornik and David F. Hendry

“By its emissions of greenhouse gases, economic activity is the source of climate change which affects pandemics that in turn can impact badly on economies. Across the three highly interacting disciplines in our title, time-series observations are measured at vastly different data frequencies: very low frequency at 1000-year intervals for paleoclimate, through annual, monthly to intra-daily for current climate; weekly and daily for pandemic data; annual, quarterly and monthly for economic data, and seconds or nano-seconds in finance. Nevertheless, there are important commonalities to economic, climate and pandemic time series. First, time series in all three disciplines are subject to non-stationarities from evolving stochastic trends and sudden distributional shifts, as well as data revisions and changes to data measurement systems. Next, all three have imperfect and incomplete knowledge of their data generating processes from changing human behaviour, so must search for reasonable empirical modeling approximations. Finally, all three need forecasts of likely future outcomes to plan and adapt as events unfold, albeit again over very different horizons. We consider how these features shape the formulation and selection of forecasting models to tackle their common data features yet distinct problems.”

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