A very interesting paper has been published by Anup Malani and Ari Jacob, both out of the National Bureau Of Economic Research in Cambridge, MA, USA, "a private, nonprofit organization that facilitates cutting-edge research on and analysis of major economic issues." ( The views expressed in the paper are those of the authors and do not necessarily reflect the views of the NBER.)

The paper is titled "A NEW MEASURE OF SURVIVING CHILDREN THAT SHEDS LIGHT ON LONG-TERM TRENDS IN FERTILITY" [ or as .pdf here ].

What long-term trends in fertility? This [ blue trace is 1950 through 2023]:

The authors start with this:

"The world has experienced a dramatic decline in total fertility rate (TFR) since the Industrial Revolution. Yet the consequences of this decline flow not merely from a reduction in births, but from a reduction in the number of surviving children. We propose a new measure of the number of surviving children per female, which we call the effective fertility rate (EFR). EFR can be approximated as the product of TFR and the probability of survival."

"We specialized EFR to measure the number of daughters that survive to reproduce (reproductive EFR) [EFR] and the number children that survive to become workers (labor EFR) [EFR]."

"We use three data sets to shed light on EFR over time across locations. First, we use data from 165 countries between 1950-2019 to show that one-third of the global decline in TFR during this period did not change labor EFR [EFR], suggesting that a substantial portion of fertility decline merely compensated for higher survival rates."

And the result is that:

"In this paper we offer a new measure of the number of surviving children per reproductive age female. It is motivated by economic models, which posit that households care about the number of children who survive -- not merely the number who are born. It can also be used to test those models. Our measure of surviving children can be specialized -- via EFR and EFR -- to measure growth in the population that produces or that reproduces, respectively."

This figure from the paper gives the best graphical representation of their point:

Why should we care?

Worldwide and National Fertility Rates are predictive of future population totals and very important for future economic conditions. Falling populations have led, in some countries, to shortages of workers to keep up industrial production.

The United Nations has been making a great deal of fuss about Total Fertility Rate and I have written about the issue in "Population Bombing". The popular press hack on about both excessive population growth and population degrowth.

But here is my thought after reading this new paper:

Maybe we have been looking at the wrong statistic. Malani and Jacob suggest that a better way of looking at fertility, from a demographic viewpoint, is to look at their two "new and improved" statistics: Effective Reproductive Rate - Labor and Effective Reproductive Rate - Reproductive.

In the advanced nations, these are running far below the necessary 2.1 replacement rate but have stabilized (no longer dropping) since about 1990. This gives a different picture than the older Total Fertility Rate.

So what?

Analyses of modern societal problems are often based on statistics about or related to the perceived problem. The statistic(s) favored by policy makers are, more often than not, not measures of the problem itself but of something merely related to the problem.

At this website, the statistic most favored by policy makers for the generalized topic here, Climate Change, is one of the many "global average surface temperature" indexes. That statistic is touted in every COPxx meeting as being/going too high.

However, there are well-reasoned opinions that view that index, that statistic, as flawed or even concocted. Some opinions view that statistic as a non-scientific "apples and oranges" mishmash.

Others are perfectly willing to accept statistic in current use but opine that it is not the measure of "Climate Change".

The discussion points for today:

1. World fertility rates - a problem, a solution, an improvement, and/or looming disaster (in which direction)? None of these?

2. Are ANY of the so-called Global Average Surface Temperature indexes appropriate to stand as a measure of Global Climate change?

3. Do you know of any other fields of research that are based on what you think is the wrong metric/measure/statistic?

The idea that TFR is not an appropriate or the most appropriate statistic for population growth studies is intriguing. And has led to the question: are we using the right and/or best statistic as an/the indicator for other societal problems? Are some that we commonly use appropriate in any way whatever or are some simply wrong from the start?

I do have personal opinions about GAST and its indexes, previously expressed on the pages here at WUWT.

Overall, maybe we should be rebooting a lot of topics by asking: "Are we using the right measure of the problem?" Give examples if you have them.