The Unassuming Economist

From a paper by Lisa Capretti, and Lorenzo Tonni:

“The empirical literature on the relationship between income inequality and economic growth has
produced highly heterogeneous and often conflicting results. This paper investigates the sources of this heterogeneity using a meta-analytic approach that systematically combines and analyzes evidence from relevant studies published between 1994 and 2025. We find an economically small but statistically significant negative average effect of income inequality on subsequent economic growth, together with strong evidence of substantial heterogeneity and selective publication based on statistical significance, but no evidence of systematic directional bias. To explain the observed heterogeneity, we estimate a meta-regression. The results indicate that both real-world characteristics and research design choices shape reported effect sizes. In particular, inequality measured net of taxes and transfers is associated with more negative growth effects, and the adverse impact of inequality is weaker – or even reversed – in high-income economies relative to developing countries. Methodological choices also matter: cross-sectional studies tend to report more negative estimates, while fixed-effects, instrumental-variable, and GMM estimators are associated with more positive estimates in panel settings.”

From a paper by Shih-Yen Pan , Lawrence P. King & Elias Nosrati:

“The International Monetary Fund (IMF) has been one of the world’s most powerful international
organisations in setting the parameters for economic reforms in the developing world. In this study,
using annual cross-national data from 1980–2019, we investigate the impact of the IMF’s lending programmes on poverty incidence in participant countries. Departing from the prevailing practice of relying on instrumental variables, we employ a novel difference-in-differences approach that ensures clean comparisons between ‘treatment’ and ‘control’ units based on their programme participation histories. Besides providing a quantitative estimate of the average programme effect, we evaluate whether the IMF’s alleged anti-poverty focus in recent decades has made any difference. We find that IMF programme participation leads to large increases (4.2-5 percent of the total population) in the proportion of a country’s population living under the $6.85=day international poverty line (2017 PPP) and the country-specific Societal Poverty Line. We also find that the poverty reduction measures incorporated by the IMF into its programmes have not been effective in mitigating the poverty-increasing programme effects. Overall, our findings suggest that IMF programmes have been detrimental to the welfare of vulnerable populations in participant countries.”

From a paper by Kardelen Cicek, Julieth Pico Mejía, Marcos Poplawski-Ribeiro, Alberto Tumino:

“This paper analyzes the redistributive effects of inflation across 18 European economies from
2021:Q3 to 2022:Q2, using unique micro-datasets for this country sample. We estimate inflation’s impact on household welfare through the consumption basket, income, and wealth channels. Our main contribution is incorporating real assets into the wealth channel and accounting for behavioral responses to inflation in both the income and wealth channels. These factors significantly alter inflation’s distributional effects compared to previous literature. The inflation shock is estimated to have caused an average welfare loss equivalent to 18.5 percent of annual household income across our sample, with households in the poorest income quintiles suffering the largest losses. Cross-country differences also widen when real assets are incorporated, with a few economies even showing welfare gains for some or all quintiles because house prices rose faster than inflation.”

From a paper by Claus Brand, Gavin Goy, and Wolfgang Lemke:

“Using a novel macro-finance model we infer jointly the equilibrium real interest rate r*, trend inflation, interest rate expectations, and bond risk premia for the United States. In the model r* plays a dual macro-finance role: as the benchmark real interest rate that closes the output gap and as the time-varying long-run real interest rate that determines the level of the yield curve. Our estimated r* declines over the last decade, with estimation uncertainty being relatively contained. We show that both macro and financial information is important to infer r*. Accounting for the secular decline in interest rates renders term premia more stable than those based on stationary yield curve models.”

From a paper by Guivis Zeufack Nkemgha, Le Roi Nso Fils, and Ulrich Kevin Kamwa:

“This paper examines the impact of trade liberalisation on income inequality across 24 Sub-Saharan African (SSA) countries from 2000 to 2020. Using IV-Tobit and 2SLS models, we consistently find that greater trade openness significantly exacerbates inequality in the region. Critically, we document an inverted U-shaped relationship between trade and inequality—similar to the Laffer Curve—but this mitigating effect is only observed in high-income, less corrupt, and democratic SSA countries. In addition, trade openness demonstrates a dual, contradictory effect on inequality: the disruptive impact on employment significantly outweighs the mitigating effect of the education channel. This disparity underscores that without robust labour market and social protection policies, the negative employment consequences of trade liberalisation will dominate the potential equalising gains from human capital development.”