Ep76 “How Should You Deal with Uncertainty in Today's World?” with Nick Bloom

The podcast discusses various ways to measure uncertainty, focusing on economic growth volatility, stock market volatility (VIX), and text-based measures derived from news articles. The hosts and guest, Professor Nick Bloom, explore the discrepancies between these measures and their implications for economic decision-making. One measure of uncertainty is the volatility of economic growth, typically measured by GDP growth. A low-volatility economy experiences consistent growth rates, while a high-volatility economy sees significant booms and recessions. However, short-term GDP volatility measures may not capture long-term economic outlooks, especially during periods of significant technological change like the AI revolution. A second measure is the VIX, a forward-looking indicator of stock market volatility. The stock market, representing a stream of future economic activity and profits, can reflect long-run economic volatility. The VIX is based on option prices and offers a real-time measure of volatility, unlike GDP data which has a time lag. The VIX typically averages 18% annually but can spike to 60-70% during crises, while also experiencing long periods of low volatility around 10%. The third, more recent, measure of uncertainty is text-based. With the advent of large language models and AI, text from sources like newspapers can be quantified to gauge uncertainty. This method, pioneered by Professor Nick Bloom, analyzes the frequency of words related to uncertainty in major news outlets. Like the VIX, text-based measures can provide real-time insights into perceived uncertainty. A significant puzzle has emerged in recent years: the divergence between these uncertainty measures. Historically, the VIX, text-based indices, and business surveys moved in tandem. However, in the last two to three years, particularly during the Trump administration, text-based measures of uncertainty have "exploded," reaching two to three times their levels from the 2000s or 2010s. In contrast, market measures like the VIX and survey-based uncertainty remain around average levels. This presents a conundrum: is uncertainty truly a "10 out of 10" as suggested by text, or a "five out of 10" as indicated by markets and surveys? Professor Bloom offers two hypotheses for this divergence. One is that the media, particularly mainstream newspapers, might be overly focused on specific political figures like Trump, leading to an exaggeration of uncertainty. This is supported by the observation that national newspapers show a much higher spike in uncertainty compared to local U.S. newspapers, which tend to focus more on local business. This suggests that the actual level of uncertainty might be somewhere in between the high text-based readings and the more moderate market and survey indicators. The second hypothesis is that genuine, real, and longer-term uncertainties, such as changes in the U.S. political system, geopolitical conflicts, and shifts in trading arrangements, are not adequately captured by short-term market fluctuations or firm surveys. Markets, for instance, are heavily weighted towards certain sectors like tech and finance and primarily focus on earnings, potentially overlooking broader political or societal uncertainties that don't immediately impact profitability. Markets also tend to be more sensitive to negative news, reflecting higher volatility during adverse events but remaining flat during positive, even if significant, events like the fall of the Berlin Wall. The discussion also touches on the "Chicken Little" phenomenon, where the media's incentive to cover "bad news" ("if it bleeds, it reads") might contribute to elevated text-based uncertainty. Research shows a significant increase in the negativity of news reporting since 1970, with 2020 being the most negatively reported year since 1850. This trend could be driven by the competitive landscape of journalism, where sensationalism helps attract readers and online engagement. However, even if media reporting exaggerates, if businesses and households read these reports and become stressed, it can still lead to real economic outcomes, such as reduced hiring and investment. Another potential explanation for the market's subdued volatility, despite high text-based uncertainty, is the "Greenspan put" effect, where central banks or governments intervene to stabilize markets during crises. If markets believe that policymakers, including figures like Trump, will step in to mitigate negative outcomes, this could suppress perceived volatility in financial markets, even if underlying political and geopolitical risks are high. Regarding the impact of uncertainty, Professor Bloom's research indicates that increased uncertainty leads to a drop in hiring and, more significantly, in investment, especially long-term projects like R&D. This behavior is rooted in the "real options" theory, where businesses choose to wait and defer decisions when the future is uncertain, as the option to wait becomes more valuable. If everyone in the economy pauses, it leads to a slowdown. These "uncertainty shocks" can cause short, sharp recessions, followed by quick rebounds as pent-up demand is released. However, persistent uncertainty, like that observed during Brexit, can cause long-term damage to GDP due to prolonged deferral of investment and other economic activities. Today's major drivers of long-term uncertainty are identified as politics and AI. Political instability, fueled by social media and a shift towards more extreme positions, is seen as a permanent factor. AI, with its accelerating pace of change, also represents a significant and persistent source of uncertainty. To mitigate the effects of uncertainty, firms should: 1. **Become more flexible:** Opt for renting or leasing equipment and having shorter-term contracts for workers, even if it's more expensive, to gain adaptability. 2. **Pay more attention to politics:** Recognize that politics increasingly impacts business and engage in lobbying or stay informed about political developments. 3. **Implement contingency planning:** Develop plans for various unforeseen events, as these can provide a framework for agile responses during uncertain times. While flexibility might seem like a zero-sum game, for individual businesses, it allows them to adapt and avoid costly mistakes, especially in industries undergoing rapid change. From a policymaker's perspective, reducing uncertainty involves promoting stable policy processes, such as independent central banks and predictable budget policies, to remove themselves as a source of uncertainty. While sometimes short-term disruptions are necessary for long-term gains, persistent uncertainty, especially from political and technological shifts, is likely to be a defining feature of the economy for the foreseeable future, leading to higher costs of capital, increased risk premiums, and lower investment.