Is the exchange rate a shock absorber or a source of shocks? Evidence from the U.S.

De, Kuhelika; Sun, Wei

doi:10.1016/j.econmod.2019.10.015

Cited by 18 publications

(14 citation statements)

References 32 publications

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“…We estimate the model using the two‐step principal component approach (Bernanke et al, 2005; Stock & Watson, 2011; Bahadir & Lastrapes, 2015; De & Sun, 2020; among others use this same approach) in which the factors are estimated by principal components prior to estimation of the FAVAR. The first step is to extract the common latent factors ( F t ).…”

Section: Empirical Model and Datamentioning

confidence: 99%

Macroeconomic shocks and racial labor market differences

Compton

Giedeman

et al. 2021

Southern Economic Journal

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We investigate the effects of three structural macroeconomic shocks (monetary, demand, and supply) on the labor market outcomes of black and white Americans using a factor‐augmented vector autoregression (FAVAR) framework with 136 U.S. macroeconomic indicators from 1973 to 2017. Our results indicate that adverse macroeconomic shocks have differential effects on labor market outcomes for blacks and whites, hurting blacks disproportionately more than whites. Black Americans' labor market outcomes appear to be significantly more sensitive to macroeconomic shocks than are the outcomes for white Americans. Our findings indicate that business‐cycle costs are disproportionately borne by black Americans and that racial inequality in the labor market rises in recessions. The strongest effects occur in recessions caused by supply side disturbances. Our results suggest policymakers should take these heterogeneous effects into account when designing policy.

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Section: Empirical Model and Datamentioning

confidence: 99%

Macroeconomic shocks and racial labor market differences

Compton

Giedeman

et al. 2021

Southern Economic Journal

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“…We introduced exchange rate into the equation because we assume exchange rate pass-through effect. Specifically, exchange rate channel is arguable one of the potent channels that global shocks contemporaneously affect stock markets (see also Nilavongse et al, 2020;Zeev, 2019;Malika andUmar, 2019 andDe andSun, 2019). Studies have also established that the tapering announcement had an immediate impact on US Treasury bill rate and US 10-year sovereign bond yield (Mishra et al, 2014;Goes et al, 2017 andMatheson, 2015).…”

Section: Model Variable Measurement and Justificationmentioning

confidence: 99%

Spillover effects of the US monetary policy normalization on African stock markets

Kalu

Okoyeuzu

Ukemenam

et al. 2020

JED

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PurposeWe study the contemporaneous effects of US monetary policy normalization on African stock market using panel data from six African countries.Design/methodology/approachDaily data from May 1, 2013 to December 31, 2018 were used in order to accommodate the announcement effects since the US monetary policy normalization announcement was made in May 2013, while the rate hike was in December 2015. The study used the FE, RE and PMG models.FindingsThe results revealed that US 10-year bond yield and Treasury bill rate shocks negatively affect stock prices in Africa. S$P500 shock positively affects African stock prices.The result revealed that the integration of African financial market to the global financial market is a major source of vulnerability. The finding that US Treasury bill rate is a major depressant of the African stock prices reveals the short-termism of foreign polio inflows into African economies.Originality/valueWe provide inexorably insight into the interplay of financial systems globally. It can be useful for the purposes of generalization in developing economies in the shape of African countries. More so, this study could be replicated in another economic bloc or region with the aim of further exposing the far-reaching spillover effects of the US monetary policy normalization.

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“…We estimate the model using the two-step principal component approach (Bernanke et al, 2005;Stock and Watson, 2011;Bahadir and Lastrapes, 2015;De and Sun, 2019 among others use this same approach) in which the factors are estimated by principal components prior to estimation of the FAVAR. The first step is to extract the common latent factors (Ft).…”

Section: Data and Model Specificationmentioning

confidence: 99%

“…Uhlig (2005),Peersman (2005),Farrant and Peersman (2006),Scholl and Uhlig (2008),Peersman and Straub (2009),Mountford and Uhlig (2009),Abdallah and Lastrapes (2013), andDe and Sun (2019) among others use sign restrictions for identification of structural shocks. The advantage of the sign restrictions…”

mentioning

confidence: 99%