Monitoring Demand and Supply in Asia: An Industry Level Approach

IMF Working Papers, October 17, 2023

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Decomposition of GDP and its deflator into demand- and supply-driven components for 12 Asian countries, the US and Europe, following the forecast error-based methodology of Shapiro (2022).
Extensions to Shapiro (2022) methodology:
- Consideration of a wide range of statistical forecasting models and selection of the optimal model for each country.
- Provision of a measure of idiosyncratic demand and supply movements to distinguish aggregate demand-driven inflation from inflation driven by large shocks in a small number of sectors.

Lockdowns in 2020:
- Explained by a mix of demand and supply shocks in Asia.
- Idiosyncratic demand shocks played a significant role in some countries.
Post-COVID recovery dynamics:
- Supply factors played an important role primarily in 2021.
- Demand factors became more important in 2022.
Inflation surge in 2021-22:
- Mix of shocks differs by country.
- Large and advanced economies generally experienced more supply shocks: China, Australia, Korea.
- Emerging markets experienced significant demand pressures pushing up prices: Indonesia, Malaysia, Philippines, Vietnam, Thailand.

Keynesian supply shocks:
- Investigation of whether industry supply shocks created demand-like movements in aggregate prices and quantities.
- Evidence found for this mechanism in a minority of countries in the Asia sample, and also for Europe and the USA.
- These results are driven by the COVID-19 event.
Cross-country growth spillovers:
- Use of granular industry-level idiosyncratic shocks to construct country-level GDP shocks.
- Analysis of cross-country growth spillovers for the three large economic units in the sample: China, Europe and the US.

Subject: COVID-19, Deflation, Economic theory, Financial sector policy and analysis, Health, Inflation, Prices, Spillovers, Supply shocks
Keywords: Asia and Pacific, COVID-19, Deflation, Demand, demand and supply movement, demand and supply shock, Europe, GDP shock, Global, growth spillover, Inflation, inflation decomposition, Machine Learning, Spillovers, Supply, Supply shocks