scholarly journals The Two Growth Rates of the Economy

2020 ◽  
Author(s):  
Alexander Adamou ◽  
Yonatan Berman ◽  
Ole Peters
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
The United States ◽  
Ensemble Average ◽  
Gdp Per Capita ◽  
Average Growth Rate ◽  
Average Growth ◽  
Starting Point ◽  
Time Average ◽  
Per Capita

Economic growth is measured as the rate of relative change in gross domestic product (GDP) per capita. Yet, when incomes follow random multiplicative growth, the ensemble-average (GDP per capita) growth rate is higher than the time-average growth rate achieved by each individual in the long run. This mathematical fact is the starting point of ergodicity economics. Using the atypically high ensemble-average growth rate as the principal growth measure creates an incomplete picture. Policymaking would be better informed by reporting both ensemble-average and time-average growth rates. We analyse rigorously these growth rates and describe their evolution in the United States and France over the last fifty years. The difference between the two growth rates gives rise to a natural measure of income inequality, equal to the mean logarithmic deviation. Despite being estimated as the average of individual income growth rates, the time-average growth rate is independent of income mobility. (Stone Center on Socio-Economic Inequality Working Paper)

scholarly journals Assessing the lockdown effect from excess mortalities

2021 ◽  
Author(s):  
Alexej Weber
Keyword(s):  
Growth Rate ◽  
South Korea ◽  
Growth Rates ◽  
Excess Mortality ◽  
Reproduction Number ◽  
Average Growth Rate ◽  
Average Growth ◽  
Reproduction Numbers ◽  
The Difference ◽  
Pharmaceutical Interventions

AbstractBackground and AimsThe reported case numbers of COVID-19 are often used to estimate the reproduction number or the growth rate. We use the excess mortality instead, showing the difference between most restrictive non-pharmaceutical interventions (mrNPIs) and less restrictive NPIs (lrNPIs) with respect to the growth rate and death counts.MethodsWe estimate the COVID-19 growth rate for Sweden, South Korea, Italy and Germany from the excess mortality. We use the average growth rate obtained for Sweden and South Korea, two countries with lrNPIs, to estimate additional death numbers in Germany and Italy (two countries with mrNPIs) in a hypothetic lrNPIs scenario.ResultsThe growth rate estimated from excess mortality decreased faster for Germany and Italy than for Sweden and South Korea, suggesting that the mrNPIs have a non-negligible effect. This is not visible when the growth rate is calculated using the reported case numbers of COVID-19. This results in approximately 4 500 and 12 000 more death numbers for Germany and Italy, respectively.ConclusionThe reproduction numbers or growth rates obtained from reported COVID-19 cases are most likely biased. Expanding testing capacity led to an overestimation of the growth rate across all countries analyzed, masking the true decrease already visible in the excess mortality. Using our method, a more realistic estimate of the growth rate is obtained. Conclusions made for the reproduction number derived from the reported case numbers like the insignificance of most restrictive non-pharmaceutical interventions (lockdowns) might be wrong and have to be reevaluated using the growth rates obtained with our method.

scholarly journals Inherent random fluctuations in COVID-19 outbreaks may explain rapid growth of new mutated virus variants

2021 ◽  
Author(s):  
Kenneth Bodin ◽  
Joacim Rocklov
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Rapid Growth ◽  
Virus Genome ◽  
Average Growth Rate ◽  
Average Growth ◽  
Virus Variant ◽  
Profound Impact ◽  
The Uk ◽  
Random Fluctuations

A new virus variant of SARS-COV-2 has had a profound impact on society while governments have taken action to limit its impacts by enforcing lockdowns and limiting spread from the UK to other countries. Variants with mutations in the virus genome are likely to occur, but do not always associate to significant changes in the biology of the virus, or the disease. For the variant VOC 202012/01 (also referred to as B.1.1.7), however, preliminary reports indicate it may be more transmissible. Here we use a simulation model calibrated to the inherent random fluctuating transmission pattern of COVID-19 to investigate what the probability may be for detecting more transmissible virus variants post facto. We find that post facto identification of successful virus variants of SARS-COV-2 are likely to exhibit growth rates that are substantially larger than the average growth rate. This finding has implications for interpreting growth rate and transmissibility of new virus variants.

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