tools available to governments and central banks

Even now, governments and central banks have various control instruments at their disposal to manage the surge in inflation without causing other collateral damage, a few of which are contextualized below:

what if inflation controls overshoot?

While demand-driven inflation is easier to address through money markets, supply-driven inflation that stems from inadequate production, low productivity, long time-to-market, lagging infrastructure and trade barriers, entails longer turnaround times. Most markets faced supply issues once the Russia-Ukraine conflict was underway and during the China lockdowns. The overhang for 2023 stems from the fact that the global supply of everything from oil to manufactured goods and food grains was massively disrupted and fixing the supply chain to restore production is taking longer than hoped.

Coordinated global action too can only be limited in scope and reach. We are more likely to see a flurry of activity from central banks in an attempt to clamp down on demand pressure. Yet these measures, easier to implement and “fail fast” as they are, run the risk of slowing down economic growth, leading to unemployment, recessions and pushing the poorest into greater misery – ingredients of the perfect storm.

The trade-offs for central banks and governments are difficult, and how policies navigate these headwinds in the coming months remains to be seen.

peer-reviewed

Carl Densem

by

Author

Tanushree Datta

Tanushree Datta is a Senior Director at Capgemini USA. She has 19 years of experience and leads AI Solutions for Banking and Capital Markets. In addition to an economics undergraduate degree, Tanushree has earned an MBA, a PG in International Trade Law, along with over 80 certifications across risk, strategy, finance, econometrics, programming and AI/ML.

Synopsis

This article presents an analysis of the impact of asset price bubbles on the markets for cryptocurrencies and considers the standard risk management measure Value-at-Risk (“VaR”). It applies the theory of local martingales, presents a styled model of asset price bubbles in continuous time and performs a simulation experiment featuring one- and two-dimensional Stochastic Differential Equation (“SDE”) systems for asset values through a Constant Elasticity of Variance (“CEV”) process that can detect bubble behavior. It summarizes a working research paper that is available from the author upon request, containing mathematical details, complete results and references1 .

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