The Unassuming Economist

From a paper by Ebrahim Merza, Mohammad Alawin, and Muna Husain:

“Inflation volatility remains one of the most important challenges for policymakers, households, and businesses alike. When prices fluctuate unpredictably, people lose confidence in their ability to plan ahead. Households struggle to budget and save, firms hesitate to invest and hire, and policymakers face higher pressure to act without clear guidance. Recent global crises—whether energy shocks, food price surges, or supply chain disruptions—have shown how quickly instability spreads across borders. This raises a central question: why are some countries more vulnerable to inflation volatility than others? Following Aisen and Veiga (2006), this study addresses that question by examining the determinants of inflation volatility across three income-based groups: lower-middle-income, upper-middle-income, and high-income economies, using panel data covering the period 1996-2024. Using both fixed and random-effects models, we find that inflation persistence and high inflation levels are the strongest drivers of volatility, while higher income levels and stronger governance support price stability. External shocks—such as trade openness, oil price fluctuations, and exchange-rate misalignments—show varied effects across income groups, emphasizing the importance of context-specific responses. The findings suggest that when countries invest in credible institutions and reliable policies, they can transform external shocks from being destabilizing forces into manageable challenges.”

From a paper by Franziska Ohnsorge, Richard Rogerson, and Zoe Leiyu Xiea:

“Analyses of GDP per capita differences across countries focus almost exclusively on differences in productivity. This paper shows that there are also large differences in medium-run dynamics in the employment-to-population ratio. The paper finds a general tendency for productivity growth to be negatively correlated with changes in the employment to population ratio for a large sample of EMDEs—a phenomenon described using the term jobless development in this paper. The paper also shows that there are large differences in the steady state levels of the employment to population ratios that countries are converging to. There are also countries that experience substantial increases in their employment-to-population ratio during the development process. Using a two-stage procedure, the paper studies this issue in a large sample of EMDEs. In the first stage, the paper estimates differences in steady-state employment ratios across countries. In the second stage, it documents which institutional and policy factors are correlated with steady-state employment ratios. The paper finds particularly large differences across countries in steady-state employment ratios for women. Fewer legal protections of women’s rights are associated with lower steady-state employment ratios for women, without an offsetting positive effect for men.

From a paper by Pradyumna Dash, Ankit Kumar, and Chetan Subramanian:

“This study investigates the effects of U.S. monetary policy on income inequality in open economies from 1970 to 2016. We find that a 100-basis-point increase in the federal funds rate leads to a cumulative reduction of about 0.15% in income inequality over three years. Interestingly, we show that the effect of US monetary policy on inequality varies over time. The impact also varies by exchange rate regime: in flexible regimes, the reduction can reach nearly 0.3%, while in pegged regimes, it diminishes to around 0.13%. This impact in pegged regimes is influenced by wage rigidity and labor market regulations in the economy. To explain these results, we develop a two-agent small open economy model that incorporates rigid wages, highlighting the link between monetary policy and inequality dynamics.”

From a paper by Makram El-Shagi, and Steven J. Yamarik:

“This paper examines the impact of Federal Reserve policy on income inequality across US states. We use the local projections method of Jordà to estimate impulse response functions for each state. We find that a restrictive monetary policy increases income inequality in almost all states, but of differing magnitudes. We also use panel analysis to examine the possible transmission mechanisms that account for these differences. Our empirical results confirm the theoretical predictions – inequality is increased by higher inflation, home ownership, and earnings in the finance, insurance and real estate (FIRE) sector; but decreased by higher housing prices, unionization rates, educational attainment and minimum wage.”

From a paper by Thomas Chalaux, Dave Turner and Steven Cassimon:

“Recent research by authors from the IMF, ECB and the Bank of England has identified Random Forests as the most effective method for predicting crisis episodes and superior to the more traditional approach of probit/logit modelling. We challenge that finding when predicting recessions for 20 OECD countries. A customised algorithm that selects probit models, matches the performance of Random Forests in out-of-sample quarterly predictions using real-time data over a two-year horizon, including the period of the Global Financial Crisis. This enhanced performance is attributed to a “wisdom of crowds” feature whereby predictions are averaged from many well-fitting probit equations, comparable to Random Forests averaging many trees. Both country-specific and pooled Random Forests are estimated, and, although the latter has a superior out-of-sample performance, a disadvantage of the pooled approach is that recession risks are highly correlated across countries and rarely very elevated, so that it is unlikely that a recession is ever ‘more likely than not’. The estimation framework is also separately applied to 8 consecutive quarterly horizons and demonstrates that different explanatory variables matter at different horizons; activity variables are more important for immediate quarters, but financial cycle variables (especially credit and house prices) dominate at horizons beyond that.”