Simplifying a Complicated Global Economy

CAMBRIDGE – The global economy this year is full of puzzling surprises. Japan’s GDP growth is currently surpassing that of China, and July retail sales in the United States were double the consensus forecast, despite the US Federal Reserve pursuing one of the most concentrated rate-hiking cycles in decades.

In the United Kingdom, wage growth has risen to an annualized rate of 7.8% and core inflation has remained high, even after 14 consecutive rate hikes by the Bank of England (with more to come). Meanwhile, Brazil and Chile have both cut interest rates, diverging from market expectations that the Fed will keep rates high for a prolonged period.

These oddities are just a few of many, and adding to the complexity are the uncertain implications of significant structural shifts on the horizon. These include the necessary transition to zero-carbon energy, the artificial-intelligence revolution, and various other innovation-driven changes. Add in geopolitical tensions and the retreat from economic and financial globalization, and a wide range of potential scenarios opens up.

With so many moving pieces, and under such unconventional (and in many cases unprecedented) conditions, navigating this landscape would be challenging for anyone. That is when I find it particularly useful to return to a simple analytical framework that I learned early in my career as an economist. It is an extreme version of a “reduced-form equation” that economists use to focus on just a handful of key factors for predicting outcomes. These factors may not fully explain a phenomenon, but this strategy is better than relying on an impractically large and unwieldy set of factors.

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