Cause-specific mortality rates: Common trends and differences

In contrast to the traditional approach that uses total mortality rates, we want gain additional insight into past development of by concentrating on a more detailed breakdown data, namely causes death. We work with data from five developed countries (USA, Japan, France, England and Wales, Australia), two sexes, split rates main groups death (Infectious&Parasitic, Cancer, Circulatory diseases, Respiratory External causes). As it was shown in Arnold Sherris (2016), these time series cause-specific are cointegrated so, there exist long-run equilibrium relationships between them. While previous research focused stationary part system present paper study its non-stationary part. For this explicitly extract common stochastic trends original variables compare them across different datasets. By testing cointegration assumptions about trends, able get better representation understanding how evolving. believe patterns emerging such analysis could indicate link fundamental biological processes as aging.