Modelling time series properties of Australian lending interest rates

The purpose of this paper is to examine the time series properties of Australian residential mortgage interest rates, and in doing so, establish whether or not selected home loan rates （product-level monthly home loan interest rates for CBA） exhibit the expected cyclical and seasonal variations and whether seasonality, if present, is stochastic or deterministic. In particular, due to a well established presence of cyclicality in financial markets＇ interest rates and strong correlation between financial markets＇ interest rates and home loan interest rates, the paper presumes that cyclicality is also to be found in home loan interest rates. Furthermore, the paper tests the hypothesis that home loan interest rates, for selected products, exhibit the three identified （＂Spring＂, ＂Autumn＂ and ＂The end of the Financial Year＂） season-related interest rate reductions. The paper uses a structural time series modelling approach and product-level home loan interest rates data from one of the biggest banks in Australia, Commonwealth Bank of Australia （CBA）. As expected, the results overall confirm the existence of cyclicality in home loan interest rates. With respect to the seasonality of home loan interest rate, although most of the analysed variables show the presence of statistically significant seasonal factors, the majority of the statistically significant seasonal factors observed cannot be attributed to any of the three considered seasonal effects.

INDUSTRIAL PRODUCTION IN GERMANY AND AUSTRIA:A CASE STUDY IN STRUCTURAL TIME SERIES MODELLING

Industrial production series are volatile and often cyclical. Time series models can be used toestablish certain stylized facts, such as trends and cycles, which may be present in these series. Incertain situations, it is also possible that common factors, which may have an interesting interpretation,can be detected in production series. Series from two neighboring countries with close economicrelationships, such as Germany and Austria, are especially likely to exhibit such joint stylized facts.

The impact of EV71 vaccination program on hand,foot and mouth disease in Zhejiang Province,China:A negative control study

Objective:To estimate the potential causal impact of Enterovirus A71(EV71)vaccination program on the reduction of EV71-infected hand,foot,and mouth disease(HFMD)in Zhejiang Province.Methods:We utilized the longitudinal surveillance dataset of HFMD and EV71 vaccination in Zhejiang Province during 2010-2019.We estimated vaccine efficacy using a Bayesian structured time series(BSTS)model,and employed a negative control outcome(NCO)model to detect unmeasured confounding and reveal potential causal association.Results:We estimated that 20,132 EV71 cases(95%CI:16,733,23,532)were prevented by vaccination program during 2017-2019,corresponding to a reduction of 29%(95%CI:24%,34%).The effectiveness of vaccination increased annually,with reductions of 11%(95%CI:6%,16%)in 2017 and 66%(95%CI:61%,71%)in 2019.Children under 5 years old obtained greater benefits compared to those over 5 years.Cities with higher vaccination coverage experienced a sharper EV71 reduction compared to those with lower coverage.The NCO model detected no confounding factors in the association between vaccination and EV71 cases reduction.

Structural analysis and forecast of gold price returns

Gold has multiple attributes and its price is affected by various factors in the market.This paper studies the dynamic relationship between the gold price returns and its affecting factors.Then we use the STL-ETS,neural network and Bayesian structural time series model to predict the gold price returns,and compare their performance with the benchmark models.The results show that the shocks of crude oil returns and VIX have the positive effect on gold price returns,the shocks of the US dollar index have the negative effect on gold price returns.And the fluctuation of gold price returns mainly depends on crude oil price returns shocks.STL-ETS model can accurately fit the fluctuation trend of the gold price returns and improve prediction accuracy.

Using state space models as a statistical impact measurement of survey redesigns: a case study of the labour force survey of the Australian Bureau of Statistics

The goals of any major business transformation programme in an official statistical agency often include improving data collection efficiency,data processing methodologies and data quality.However,the achievement of such improvements may have transitional statistical impacts that could be misinterpreted as real-world changes if they are not measured and handled appropriately.This paper describes a development work that sought to explore the design and analysis of a times-series experiment that measured the statistical impacts that sometimes occur during survey redesigns.The Labour Force Survey(LFS)of the Australian Bureau of Statistics(ABS)was used as a case study.In the present study:(1)A large-scale field experiment was designed and conducted that allowed the outgoing and the incoming surveys to run in parallel for some periods to measure the impacts of any changes to the survey process;and(2)The precision of the impact measurement was continuously improved while the new survey design was being implemented.The state space modelling(SSM)technique was adopted as the main approach,as it provides an efficient impact measurement.This approach enabled sampling error structure to be incorporated in the time-series intervention analysis.The approach was also able to be extended to take advantage of the availability of other related data sources(e.g.,the data obtained from the parallel data collection process)to improve the efficiency and accuracy of the impact measurement.As stated above,the LFS was used as a case study;however,the models and methods developed in this study could be extended to other surveys.