Nie je k dispozícii v slovenčine.
Simone Arrigoni
- 4 May 2026
- WORKING PAPER SERIES - No. 3221Details
- Abstract
- This paper provides novel evidence on how income inequality shapes the heterogeneity of US monetary policy spillovers to GDP across foreign economies. Using state-dependent local projections and exploiting variation in disposable income inequality across 87 countries over 1966-2020, we show that household heterogeneity influences how foreign GDP responds to a US monetary tightening. GDP contracts up to one and a half times more when inequality is above average. However, while higher inequality amplifies negative spillovers in advanced economies, it mitigates them in emerging markets. To rationalise this finding, we use a three-country open economy Two-Agent New Keynesian (TANK) model, which suggests this divergence is driven by differences in participation in international financial markets. Households in emerging markets face greater barriers to international investment, limiting their ability to re-balance portfolios towards higher-return foreign bonds after the shock.
- JEL Code
- D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
F42 : International Economics→Macroeconomic Aspects of International Trade and Finance→International Policy Coordination and Transmission
- 11 August 2020
- WORKING PAPER SERIES - No. 2451Details
- Abstract
- In this paper we assess the merits of financial condition indices constructed using simple averages versus a more sophisticated alternative that uses factor models with time varying parameters. Our analysis is based on data for 18 advanced and emerging economies at a monthly frequency covering about 70% of the world’s GDP. We use four criteria to assess the performance of these indicators, namely quantile regressions, Structural Vector Autoregressions, the ability of the indices to predict banking crises and their response to US monetary policy shocks. We find that averaging across the indicators of interest, using judgemental but intuitive weights, produces financial condition indices that are not inferior to, and actually perform better than, those constructed with more sophisticated statistical methods.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C55 : Mathematical and Quantitative Methods→Econometric Modeling→Modeling with Large Data Sets?