Research
Research
Access to sufficient and nutritious food is a fundamental human right, yet global access remains highly unequal. This paper uses global macro data to examine the relationship between calorie availability and life expectancy and finds evidence consistent with laboratory findings: both underconsumption and overconsumption reduce longevity. Additional calorie intake increases life expectancy at low levels but the effect diminishes with higher consumption and becomes negative beyond 2,944 kilocalories per person per day. At low intake levels, an additional 1,000 kcal per person per day is associated with an 8-year increase in average life expectancy, whereas at high intake levels the same increase corresponds to a 9-year decline. Using the estimated optimal calorie level, countries are classified as operating in calorie surplus or deficit and a redistribution is simulated in which surplus calories from overnourished countries are reallocated to undernourished ones. Under redistribution, the share of the global population that could attain the optimal calorie intake increases from 18% during 1960–2010 to 38% in 2015. By 2020, it is sufficient to bring 100% of the population to the optimal level indicating that the world produces enough calories to eliminate hunger.
Recession Detection in Japan Using Labor Market Data (with Ronjin Zhang)
Recession indicators are often viewed as U.S.-specific, raising the question of whether labor market–based rules such as the Sahm Rule and the Michez Rule can reliably detect recessions in other countries. To answer this, we evaluate whether such rules can be adapted to Japan by calibrating thresholds and smoothing parameters to Japanese labor market data. We construct a large set of 95,832 recession indicators combining unemployment and vacancy data. The selected classifiers are statistically perfect as they identify all 11 historical recessions in the 1970–2021 training period without generating any false positives. Among these, 193 classifiers lie on the anticipation--precision frontier. Restricting attention to the high-precision segment yields six classifiers with a standard deviation of detection errors below 3 months. The selected classifier ensemble signals recessions, on average, 0.06 months after their true onset. Overall, these findings suggest that slack-based labor market rules provide a general framework for improving real time recession detection across countries.
Recession Detection Using Real Time GDP Data (with Ronjin Zhang)
This paper examines whether real-time GDP announcements can reliably identify business-cycle turning points. Using U.S. real-time GDP vintages from 1947 to 2021, we construct 4,356 recession indicators based on alternative smoothing methods and scaling variations. We then combine these indicators with alternative thresholds to generate 137,457 perfect recession classifiers. The selected classifiers identify all 12 historical recessions without generating false positives or false negatives. Restricting attention to the high-precision segment yields two classifiers with a standard deviation of detection errors below three months, while the selected ensemble signals recessions, on average, 3.04 months after their official onset. The framework accurately identifies recession episodes across vintages, suggesting that discrepancies in prior work may reflect limitations of traditional dating methods in addition to data revisions. Overall, the results indicate that real-time GDP announcements provide a practical proxy for NBER-style recession dating.