Corrigendum to “The primary dealer system in lower-income economies” [Emerging Markets Review 45 (2020) 100715]

Endo, Tadashi

doi:10.1016/j.ememar.2021.100805

Cited by 1 publication

(2 citation statements)

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“…Other researches like Tchuindjo et al (2015), Endo (2020), Nyborg et al (2004), Mercer et al (2013), andFerrari et al (2018) took different angle by looking at primary dealers system and its impact on bonds yield. Nyborg et al (2004), Mercer et al (2013) and Tchuindjo (2015) concern on primary dealers trading behavior in US Treasury bonds auction that potentially could result in higher yield.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Nyborg et al (2004), Mercer et al (2013) and Tchuindjo (2015) concern on primary dealers trading behavior in US Treasury bonds auction that potentially could result in higher yield. Endo (2020) study role of primary dealers in low income economies, while Ferrari et al (2018) focus on the effect of primary dealers' funding constraints on sovereign bonds yield in 9 Euro countries. The last name conclude that the constraints can lead to higher yield spread (Ferrari et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

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Determining Factors for 10-Year Local Currency Sovereign Bonds Yield With Dynamic Regression Model

Editya¹

2022

JBPPK

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Sovereign bonds, particularly Local Currency Bonds (LCB) of 10-year tenure, had a strategic role in economy, thus understanding factors affecting its yield’s movement would help government to maintain economic stability. This paper empirically study Indonesia’s 10-year LCB and its relationship with several factors; US Treasury (UST) yield, credit default swap (CDS), foreign ownership, central bank's policy rate (policy rate), exchange rate, volatility index (VIX) and primary dealers' trading behavior. The relationship was modelled using Dynamic Regression Model (DRM), with ARIMA errors to absorb the dynamics. Evaluation on the model's performance was conducted by making prediction on the real LCB yield’s movement during 2021. The best model containing 10y-UST yield and its lag-1, 5y-CDS and its lag-1, exchange rate, policy rate and ARIMA errors of AR(1) and AR(2) could perform well in predicting the real yield. This study confirmed that 10y-UST and its lag-1 are the main drivers for the LCB yield’s movement, along with compelling influence of the exchange rate.

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