Global GDP

Along with population, global economic productivity (GDP) factors into most sectors of the FeliX model on absolute and per capita bases. Global GPD is shown below for the period 1950 through 2100 along with SSP projections.

Global GDP in bilions of US dollars (2005): historical data from the GGDC is shown in grey, and the projections associated with SSPs 1-5 are shown in dotted lines. The shaded red region indicates the absolute shift in GDP due to high and low population estimates.

Summary Statistics for gross world product (GWP) fit to historical data on absolute and per capita bases.   (Click to enlarge)

Summary Statistics for gross world product (GWP) fit to historical data on absolute and per capita bases.   (Click to enlarge)

The red solid line in the plot represents the FeliX BAU prediction, which is calibrated to historical data from the Maddison Project, a database developed and maintained by the Groningen Growth and Development Centre at the University of Groningen in the Netherlands. SSP projections, shown in dotted lines, are used for validation of the model results.

The BAU scenario uses the central value for population growth (10.6 billion in 2100), while the red shaded region shows the sensitivity of GDP to the 80% confidence interval (CI) for fertility rates (discussed in a previous post). On an absolute basis, GDP is correlated with population (more precisely, the number of able-bodied adults comprising the global workforce), and the outer bounds of the population 80% CI translate to ±9% effect on GDP.

GDP is shown below on a per capita basis in order to isolate the predicted additional contribution of global development to economic growth:

Per capita GDP in US$(2005) for the period 1900-2100.

Per capita GDP in US$(2005) for the period 1900-2100.

Historical data again comes from the GGDC, and the SSP projections are again displayed in dotted lines. This plot shows a much smaller dependence on population estimates, indicating that global development on a per capita basis is largely independent of fertility rates in the FeliX model.

Population I

The population sector of the model drives the evolution of every other parameter of the model, and is in turn affected by other sectors via their aggregate effects on birth rates and life expectancies.

The world population is divided by age into three categories: 0 to 14 years, 15 through 64 years, and 65 plus years. The global workforce is assumed to be 75% of the middle-aged group. Population development is affected by factors including GDP, education, food security, and environmental factors including pollution levels, water quality, and biodiversity. The FeliX global population projection, shown below in red, is calibrated to historical data from the FAO (shown including FAO extrapolations to future population in grey).  

Global population in the BAU scenario of the FeliX model from 1950-2100. The model is calibrated to historical data from FAOSTAT, shown in grey. For comparison, the range of predictions as parameterized by the Shared Socioeconomic Pathways (SSP 1-5) are also shown through 2100.

Summary Statistics (Click to enlarge)

In the BAU scenario, the world population is expected to peak just above 10.6 billion people near the end of this century. For comparison, all five SSP projections are also shown through 2100. The specific factors informing the FeliX population projections will be detailed in a subsequent post.

Population growth in this model is validated by comparison to figures from the World Population Prospects: The 2012 Revision, and the associated Science paper "World population stabilization unlikely this century", both publications of the UN Department of Economic and Social Affairs (UNDESA). This research identifies a median expectation of 10.9 billion, adding:

There is an 80% probability that world population, now 7.2 billion people,                                      will increase to between 9.6 billion and 12.3 billion in 2100.

Because global population numbers are central to every other sector in the FeliX model, we use the high and low projections from UNDESA probabilistic projections (representing the 80% confidence interval) to examine the sensitivity of other figures of merit to the full range of likely fertility rates.