Appendix C: Survival Analysis Regression Results | RDP 2026-02: Shifts in Australian Price-setting Behaviour around Large Shocks

RDP 2026-02: Shifts in Australian Price-setting Behaviour around Large Shocks Appendix C: Survival Analysis Regression Results

Matthew Fink and Jonathan Hambur

May 2026

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The tables below include coefficients from the survival analysis that correspond to the beta term in Equation (1). Transformation of a given coefficient $(β)$ to a cross-sample quarter frequency Calvo parameter equivalent $(θ)$ is achieved via:

(C1)

θ = \exp (- \exp (β) * (\frac{365.25}{4}))

Table C1: Survival Analysis Results
Annual
	Advertised prices	Regular prices
2018	−3.871*** [−3.866, −3.876]	−4.800*** [−4.791, −4.809]
2019	−3.859*** [−3.855, −3.864]	−4.866*** [−4.857, −4.875]
2020	−3.884*** [−3.879, −3.888]	−5.005*** [−4.996, −5.014]
2021	−3.940*** [−3.935, −3.945]	−5.171*** [−5.163, −5.180]
2022	−3.804*** [−3.800, −3.809]	−4.936*** [−4.927, −4.945]
2023	−3.720*** [−3.715, −3.725]	−4.769*** [−4.760, −4.778]
No of observations	49,916,224	13,139,762
Notes: *** denotes statistical significance at the 1 per cent level. Coefficients are computed by adding estimated year dummy coefficient to base year coefficient and testing the difference from zero using a Wald test. All standalone coefficients are statistically significantly different from zero. Square brackets show lower and upper bound 95 per cent confidence intervals, which are based on the linear combination of base year and dummy year coefficients and take account of covariance between these parameters. Sources: ABS; Authors' calculations.

Table C2: Survival Analysis Results
Quarterly
	Advertised prices	Regular prices
2018:Q1	−3.800*** [−3.794 , −3.805]	−4.894*** [−4.883 , −4.904]
2018:Q2	−3.966*** [−3.961 , −3.972]	−4.726*** [−4.716 , −4.737]
2018:Q3	−4.139*** [−4.134 , −4.145]	−4.818*** [−4.808 , −4.828]
2018:Q4	−3.650*** [−3.645 , −3.655]	−4.815*** [−4.806 , −4.825]
2019:Q1	−3.974*** [−3.969 , −3.979]	−4.980*** [−4.970 , −4.990]
2019:Q2	−3.766*** [−3.761 , −3.772]	−4.858*** [−4.848 , −4.868]
2019:Q3	−3.998*** [−3.993 , −4.003]	−4.988*** [−4.978 , −4.998]
2019:Q4	−3.745*** [−3.740 , −3.750]	−4.679*** [−4.670 , −4.689]
2020:Q1	−3.920*** [−3.915 , −3.925]	−4.831*** [−4.822 , −4.841]
2020:Q2	−3.728*** [−3.723 , −3.733]	−4.812*** [−4.802 , −4.822]
2020:Q3	−3.774*** [−3.769 , −3.780]	−5.001*** [−4.991 , −5.011]
2020:Q4	−4.131*** [−4.126 , −4.136]	−5.346*** [−5.337 , −5.356]
2021:Q1	−3.917*** [−3.912 , −3.922]	−5.060*** [−5.050 , −5.070]
2021:Q2	−3.953*** [−3.948 , −3.958]	−5.345*** [−5.336 , −5.354]
2021:Q3	−3.972*** [−3.967 , −3.977]	−5.048*** [−5.039 , −5.058]
2021:Q4	−3.952*** [−3.947 , −3.957]	−5.207*** [−5.197 , −5.216]
2022:Q1	−3.843*** [−3.838 , −3.848]	−5.076*** [−5.067 , −5.085]
2022:Q2	−3.617*** [−3.612 , −3.622]	−4.892*** [−4.883 , −4.901]
2022:Q3	−3.998*** [−3.993 , −4.003]	−5.033*** [−5.024 , −5.042]
2022:Q4	−3.837*** [−3.832 , −3.842]	−4.808*** [−4.799 , −4.817]
2023:Q1	−3.913*** [−3.908 , −3.918]	−4.990*** [−4.981 , −4.999]
2023:Q2	−3.727*** [−3.722 , −3.732]	−4.668*** [−4.659 , −4.677]
2023:Q3	−3.779*** [−3.774 , −3.784]	−4.804*** [−4.795 , −4.814]
2023:Q4	−3.504*** [−3.499 , −3.509]	−4.608*** [−4.599 , −4.618]
No of observations	49,916,224	13,139,762
Notes: *** denotes statistical significance at the 1 per cent level. Coefficients are computed by adding estimated year dummy coefficient to base year coefficient and testing the difference from zero using a Wald test. All standalone coefficients are statistically significantly different from zero. Square brackets show lower and upper bound 95 per cent confidence intervals, which are based on the linear combination of base year and dummy year coefficients and take account of covariance between these parameters. Sources: ABS; Authors' calculations.