Monetary policy and income inequality in the US - An empirical investigation
Author
Jensen, Christoffer Juul
Term
4. term
Education
Publication year
2025
Abstract
Dette speciale undersøger, hvordan pengepolitiske stød påvirker indkomstuligheden i USA ved hjælp af kvartalsdata fra Q1 1999 til Q4 2023. Analysen anvender to empiriske metoder, Structural Vector Autoregression (SVAR) og Bayesian Vector Autoregression (BVAR), for at kortlægge de dynamiske sammenhænge mellem pengepolitik og ulighed og belyse mulige transmissionskanaler. Pengepolitikken måles ved en skyggerente, der samler både konventionelle og ukonventionelle tiltag og dermed gør det muligt at analysere perioder med nulrenter og kvantitative lempelser på en konsistent måde. Indkomstulighed måles ved Gini-koefficienten (overordnet ulighed) og S80/S20-ratioen (forholdet mellem de 20% rigeste og 20% fattigste). I alle impulssvar analyseres et standardiseret pengepolitisk stød svarende til en stigning i skyggerenten på 1 procentpoint, og modellerne estimeres med 8 lag for sammenlignelighed. Resultaterne peger samlet set på begrænsede og ofte statistisk insignifikante effekter af kontraktive stød på indkomstulighed. Der findes dog enkelte signifikante effekter, hvor Gini-koefficienten stiger, mens S80/S20-ratioen falder, hvilket tolkes som udtryk for, at forskellige transmissionskanaler dominerer afhængigt af ulighedsmålet. På den baggrund konkluderes, at de faldende pengepolitiske renter i perioden ikke i sig selv kan forklare stigningen i indkomstuligheden i USA; mere strukturelle forhold, herunder stigende huspriser, fremstår som mere sandsynlige forklaringer. Studiet bidrager dermed til den policyrelevante debat om pengepolitikkens fordelingsmæssige konsekvenser.
This thesis examines how monetary policy shocks affect income inequality in the United States using quarterly data from Q1 1999 to Q4 2023. The analysis employs two empirical approaches, Structural Vector Autoregression (SVAR) and Bayesian Vector Autoregression (BVAR), to trace the dynamic links between monetary policy and inequality and to illuminate potential transmission channels. Monetary policy is measured with a shadow rate that captures both conventional and unconventional tools, enabling a consistent analysis across zero lower bound and quantitative easing periods. Inequality is measured by the Gini coefficient (overall inequality) and the S80/S20 ratio (income share of the top 20% relative to the bottom 20%). All impulse responses simulate a standardized 100 basis point increase in the shadow rate, and models are estimated with 8 lags for comparability. Overall, the results indicate limited and often statistically insignificant effects of contractionary shocks on income inequality. Some significant effects do appear, with the Gini coefficient rising while the S80/S20 ratio falls, suggesting that different transmission channels dominate depending on the inequality metric. The study concludes that declining policy rates over the period were not, by themselves, the decisive driver of rising U.S. income inequality; more structural forces, including rising house prices, are likely contributors. The findings add to the policy debate on the distributional consequences of monetary policy.
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