Table 5.

Simple Phillips curve coefficients with real GDP growth (qoq, sa).

	Gaussian			Fat-tailed			Gaussian(${\lambda }_{VAR}$)			Gaussian(${\lambda }_{RGDP}$)			Gaussian(${\lambda }_{HICPx}$)
Coeff.	System	SgEq		System	SgEq		System	SgEq		System	SgEq		System	SgEq
$\alpha$	0.041	0.042								0.040	0.041
$\rho$	0.945	0.945								0.951	0.951
$\beta$	0.031	0.030								0.029	0.028
(a) Simple Phillips curve estimated until 2019:Q4
	Gaussian			Fat-tailed			Gaussian(${\lambda }_{VAR}$)			Gaussian(${\lambda }_{RGDP}$)			Gaussian(${\lambda }_{HICPx}$)
Coeff.	System	SgEq		System	SgEq		System	SgEq		System	SgEq		System	SgEq
$\alpha$	0.088	0.090								0.070	0.069
$\rho$	0.943	0.942								0.947	0.948
$\beta$	0.006	0.006								0.020	0.020
(b) Simple Phillips curve estimated until 2021:Q2

Note: Posterior mean of Phillips curve coefficients based on various modelling assumptions. The first top row denotes the class of the error distribution—i.e. Gaussian is normal errors, Fat-tailed is $t$-errors, and Gaussian($\cdot$) is normal errors with exogenous time-varying variance—and the second row describes whether the equation was estimated as a system (System) or as single equation (SgEq).