scholarly journals A volatility smile-based uncertainty index

2021 ◽  
Author(s):  
José Valentim Machado Vicente ◽  
Jaqueline Terra Moura Marins
Author(s):  
Pengshi Li ◽  
Aichuan Xian ◽  
Yan Lin
Keyword(s):  

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Erhan Mugaloglu ◽  
Ali Yavuz Polat ◽  
Hasan Tekin ◽  
Edanur Kılıç

PurposeThis study aims to measure economic uncertainty in Turkey by a novel economic uncertainty index (EUI) employing principal component analysis (PCA). We assess the impact of Covid-19 pandemic in Turkey with our constructed uncertainty index.Design/methodology/approachIn order to obtain the EUI, this study employs a dimension reduction method of PCA using 14 macroeconomic indicators that spans from January 2011 to July 2020. The first principal component is picked as a proxy for the economic uncertainty in Turkey which explains 52% of total variation in entire sample. In the second part of our analysis, with our constructed EUI we conduct a structural vector autoregressions (SVAR) analysis simulating the Covid-19-induced uncertainty shock to the real economy.FindingsOur EUI sensitively detects important economic/political events in Turkey as well as Covid-19-induced uncertainty rising to extremely high levels during the outbreak. Our SVAR results imply a significant decline in economic activity and in the sub-indices as well. Namely, industrial production drops immediately by 8.2% and cumulative loss over 8 months will be 15% on average. The losses in the capital and intermediate goods are estimated to be 18 and 25% respectively. Forecast error variance decomposition results imply that uncertainty shocks preserve its explanatory power in the long run, and intermediate goods production is more vulnerable to uncertainty shocks than overall industrial production and capital goods production.Practical implicationsThe results indicate that monetary and fiscal policy should aim to decrease uncertainty during Covid-19. Moreover, since investment expenditures are affected severely during the outbreak, policymakers should impose investment subsidies.Originality/valueThis is the first study constructing a novel EUI which sensitively captures the critical economic/political events in Turkey. Moreover, we assess the impact of Covid-19-driven uncertainty on Turkish Economy with a SVAR model.


Author(s):  
Romano Trabalzini ◽  
William A McGhee
Keyword(s):  

Author(s):  
Yan-Ling Tan ◽  
Muzafar Shah Habibullah ◽  
Shivee Ranjanee Kaliappan ◽  
Alias Radam

The purpose of this study is to estimates the size of the shadow economy for 80 countries from nine regions spanning the period 1975-2012 based on Tanzi-type currency demand approach (CDA). This study contributes to the literature in three distinct ways. First, we augment CDA regression with a macroeconomic uncertainty index (MUI). Second, the construction of the uncertainty index is based on the dynamic factor model (DFM). Third, the pooled mean group (PMG) estimator allows in capturing the heterogeneity across countries in the short-run dynamics but imposing restrictions in the long-run parameters. The results confirm the existence of the longrun equilibrium relationship among the variables examined. All coefficients show expected signs along with statistical significance. More importantly, the macroeconomic uncertainty index variable show positive relationship, suggesting that public tend to hold more currency in an uncertain macroeconomic environment. In addition, we observe that developing regions (ranging from 19.9% to 37.3%) exhibit relatively large size of the shadow economy. On the contrary, developed regions have a considerable smaller estimate (ranging from 13.7% to 19.0%) of the size of shadow economy. On average, the world estimate of the shadow economy as a percentage of GDP is about 23.1%. Keywords: Shadow Economy; Currency Demand; Macroeconomic Uncertainty; Pooled Mean Group.


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