The Unassuming Economist

From a paper by Martin Boďa, Mariana Považanová, and Michaela Tichá:

“For 38 OECD countries during the period 1991–2022, the paper estimates time-varying trajectories of unemployment-based and employment-based Okun coefficients and studies their synchronicity. Schlicht’s VC method is utilized to estimate Okun coefficients and time-series clustering is applied to identify groups of economies with synchronous business cycle characteristics. The findings defy two prevalent beliefs of Okun’s law since many countries display constant or almost constant trajectories of the (un)employment-output sensitivity, and for many countries Okun’s law need not be stronger in a downturn. Furthermore, countries do not synchronize in their business cycle dynamics as shown in disparate trajectories of Okun coefficients, which argues against a single one-size-fits-all stabilization policy, certainly in less homogeneous economic blocks. Finally, there is strong evidence for labour market flows into and outside the labour force that are associated with informal sector size and translated into lesser sensitivity of official labour market variables across the business cycle.”

From a paper by Diego Andrés Cardoso López, Jesús Antonio López Cabrera & Tatiana Isabel
Caly Amador:

“Rural employment is pivotal to achieving the SDGs but remains structurally vulnerable—marked by high informality, seasonality, and climate exposure—which may weaken the canonical growth–unemployment link posited by Okun’s Law. In Latin America, where rural economies rely on climate-sensitive activities, temperature and precipitation shocks can disrupt productivity and labor absorption, calling for a reassessment of Okun’s relationship in rural contexts. This article analyzes the relationship between rural unemployment, real income growth, and climate variability in Brazil, Colombia, and Mexico from 2012 to 2024 using a Panel Vector Autoregression (P-VARX) model. Results indicate that, contrary to Okun’s prediction, real income growth does not always lower rural unemployment. Climate shocks matter: in Brazil, higher temperatures decrease unemployment in short-run; in Colombia, precipitation shocks—with lags—increase unemployment; and in Mexico, temperature shocks lift unemployment on impact before a partial correction. Human capital reduces unemployment only in Colombia. Based on this evidence, we outline four policy directions: (i) mainstream climate adaptation into rural labor policy; (ii) expand inclusive employment programs that tackle informality and low productivity while aligning skills with labor demand; (iii) invest in rural education and targeted skilling for green and youth employment; and (iv) promote territorial, multisectoral local development and job creation with strong institutional support.”

From a paper by Andrea Foschi, Christopher L. House, Christian Proebsting, and Linda L. Tesar:

“We examine the responsiveness of labor participation, unemployment, and labor migration to exogenous variations in labor demand. Our empirical approach considers four instruments for regional labor demand commonly used in the literature. Empirically, we find that labor migration is a significant margin of adjustment for all our instruments. Following an increase in regional labor demand, the initial increase in employment is accounted for mainly by a reduction in unemployment. Over time however, net labor in-migration becomes the dominant factor contributing to increased regional employment. After five years, roughly 60 percent of the increase in employment is explained by the change in population. Responses of labor migration are strongest for individuals age 20–35. Based on historical data back to the 1950s, we find no evidence of a decline in the elasticity of migration to changes in employment.”

From a paper by Hippolyte Balima, Alexandru Minea, and Cezara Vinturis:

“We investigate the effect of inflation targeting on income inequality across a comprehensive panel of 152 countries spanning over four decades. Using the entropy balancing methodology to address endogeneity issues, we find that inflation targeting significantly increases income inequality. This effect, which is robust across various alternative methods and specifications, is driven by an increase (decrease) in the income share of relatively rich (poor) households. In addition, the impact of inflation targeting is not uniform but varies conditional on redistribution policies, inflation targeting features, the level of economic development, and country-specific characteristics. Our findings contribute to the ongoing discussion on the broad socioeconomic implications of the monetary policy, including measures to mitigate the potential side effects on income distribution.”

From a paper by Karan Bhasin, and Prakash Loungani:

“This paper introduces a hierarchical Large Language Model (LLM) framework for the automated identification of narrative fiscal shocks. We develop a multi-stage architecture to extract austerity episodes from IMF Article IV reports (2004–2020) for 17 OECD countries. Relative to manual coding, our approach improves replicability and auditability by generating a documented sequence of classification steps. Benchmarking against Adler et al. (2024), we find that the LLM-based classification aligns closely with the narrative benchmark, while differing on a small subset of episodes. Local projection estimates indicate that LLM-identified shocks are associated with smaller estimated multipliers than the narrative benchmark, with the difference linked in large part to differences in shock persistence and endogeneity.”