2016
DOI: 10.1016/j.ecosys.2015.08.004
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Forecasting the South African inflation rate: On asymmetric loss and forecast rationality

Abstract: Using forecasts of the inflation rate in South Africa, we study the rationality of forecasts and the shape of forecasters' loss function. When we study micro-level data of individual forecasts, we find mixed evidence of an asymmetric loss function, suggesting that inflation forecasters are heterogeneous with respect to the shape of their loss function. We also find strong evidence that inflation forecasts are in line with forecast rationality. When we pool the data, and study sectoral inflation forecasts of fi… Show more

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Cited by 6 publications
(2 citation statements)
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“…Krüger and LeCrone (2019) show that this method has a high power and is robust to fat tails, serial correlation, and outliers. The method has been used to evaluate forecasts of a number of economic variables by professional forecasters (Aretz, Bartram, and Pope 2011;Pierdzioch, Rülke, and Stadtmann 2013; Mamatzakis and Koutsomanoli‐Filippaki 2014; Fritsche et al 2015; Pierdzioch, Reid, and Gupta 2016; Tsuchiya 2016a, 2016b; Christodoulakis 2020), government agencies (Auffhammer 2007; Krol 2013; Tsuchiya 2016a; Giovannelli and Pericoli 2020), international organizations (Christodoulakis and Mamatzakis 2008; Tsuchiya 2016a; Giovannelli and Pericoli 2020), and central banks (Capistrán 2008; Baghestani 2013; Pierdzioch, Rülke, and Stadtmann 2015; Ahn and Tsuchiya 2019; Caunedo et al 2020). These studies overwhelmingly suggest that forecasts that are biased or inefficient under MSE loss are rational under asymmetric loss.…”
Section: Introductionmentioning
confidence: 99%
“…Krüger and LeCrone (2019) show that this method has a high power and is robust to fat tails, serial correlation, and outliers. The method has been used to evaluate forecasts of a number of economic variables by professional forecasters (Aretz, Bartram, and Pope 2011;Pierdzioch, Rülke, and Stadtmann 2013; Mamatzakis and Koutsomanoli‐Filippaki 2014; Fritsche et al 2015; Pierdzioch, Reid, and Gupta 2016; Tsuchiya 2016a, 2016b; Christodoulakis 2020), government agencies (Auffhammer 2007; Krol 2013; Tsuchiya 2016a; Giovannelli and Pericoli 2020), international organizations (Christodoulakis and Mamatzakis 2008; Tsuchiya 2016a; Giovannelli and Pericoli 2020), and central banks (Capistrán 2008; Baghestani 2013; Pierdzioch, Rülke, and Stadtmann 2015; Ahn and Tsuchiya 2019; Caunedo et al 2020). These studies overwhelmingly suggest that forecasts that are biased or inefficient under MSE loss are rational under asymmetric loss.…”
Section: Introductionmentioning
confidence: 99%
“…To this end, I build on research by Elliott et al (2005Elliott et al ( , 2008, who study optimal forecasts under asymmetric loss. The seminal work in this field by Granger (1969), Varian (1974), and Zellner (1986) as well as early applications Diebold 1996, 1997) have recently been applied in several fields such as financial forecasting (Aretz et al 2011;Fritsche et al 2015), fiscal forecasting (Artis and Marcellino 2001;Elliott et al 2005), central banking (e.g., Capistrán 2008;Pierdzioch et al 2016a), as well as GDP and inflation forecasting (Christodoulakis and Mamatzakis 2008;Pierdzioch et al 2016b;Sun et al 2018). The basic assumption in this field of research is an asymmetric loss function.…”
Section: Introductionmentioning
confidence: 99%