Global Future | Part III

Predicting the future is an exercise fraught with error. A model with a set of assumptions is typically applied to a future scenario. These scenarios include the interaction of a hard to define combination of deterministic and random forces. Despite this, a variety of planners make many types of decisions based on future expectations, and these expectations are derived from hypothesis that can be classified as pessimistic or optimistic. There are a variety of Pessimistic scenario types, and popular ones that are plausible tend to involve crisis derived from resource scarcity or environmental degradation. One could debate the realism of assumptions used in energy regime transitions or population/land use pressures, or instead focus on more optimistic scenarios.
The following is an excerpt from my Ph.D. dissertation, McChesney, 2008, pages 23-27, where I discussed the use of my urban growth model in scenario forecasting:
… 1.5 Pessimistic and Optimistic Modeling Frameworks
The conceptualization of a metropolitan change model has considered the effects of scale and selected a three scale spatial structure. An investment flow process has been selected as the temporal change mechanism. Critiques from the experiences of three selected urban growth modelers will be kept in mind during the conceptualization, construction, scenario running and interpretation of the metropolitan change model.
Another influence of model structure is a general conception of the set of forces leading to future change. These set of forces must be different; if they were identical, there would be one extrapolated trend line from empirical observation and there would be no point in engaging in a modeling process. The forces might be complementary, since one increases the speed of change for another. Alternatively, the forces might be competitive, in that the result of one increase is a decrease of another.
Two examples are provided, both of which are depicted on Figure 1.11. The first example is the general scenario results for the Forrester World Dynamics model (Forrester, 1971). The full set of Forrester factors is a complex set of forces depicted as an interconnected set of flow chart relationships. The model was configured in a number of different ways, and a number of scenarios were produced. The output was expressed as a set of time trends on graphs that suggested some complementary and inverse relationships. The five major trends modeled include a (1) stock of natural resources, (2) population change, (3) change in the quality of life, (4) capital investment, and (5) levels of pollution.
A set of computer runs for a number of scenarios was displayed as temporal equations that showed changing stock levels from the years 1900 to 2100. In general, as capital investment and population increased, they did so by drawing down a natural resource stock. Some output increased the quality of life, while other output is expressed as pollution byproducts.
Eventually, the combination of the draw down of the natural resource stock and increasing pollution levels decreases quality of life, but this observation is not sufficient to halt economic and population momentum. Only a peak in the rate of natural resource stock consumption, beyond which there are supply shortages, brings about a decline in both economic activity and population. Depending on what rates of change are assumed, the model produces either a gradual decline or a sudden population crash. The motivation for these scenarios came from Forrester who sought to model the assumptions arrived at by a group of scholars, Club of Rome, who formed in 1968 and who published the book ‘The Limits to Growth’ (Meadows, D.H., Meadows, D.L., Randers, J, and Behrens III 1972). The ideas borrowed from biology analogies and a modified Malthusian theoretical framework.
An alternative scenario is provided in the adjacent graph of Figure 1.11. Three relationships are depicted. The first is an S-curve population transition of the type predicted by the demographic transition theory (Notestein 1945). The second is an aggregated global economic logistics function, or, S-curve, that assumes that the general sequence of economic growth follows an innovation adoption to saturation sequence, and that a microeconomic market with an S-curve growth sequence has an aggregate historical analogy. The third relationship is an environmental Kuznets curve (Grossman and Krueger 1995) which depicts a decline in the quality of the environment as economic and population growth produce pollution. Once aggregate economic activity reaches a certain per capita income, resources are applied to reduce pollution output, and the environment slowly improves.
The demographic transition mechanisms are the increases in technology stocks and technology diffusion, and the formation of urban places within metropolitan commuting fields, which have the effect of first lowering death rates, then after a time lag, reducing birth rates. The end result is a global economy one hundred times larger than it was at the beginning of 1900, a population about five times larger (and a mean per capital income twenty times larger), and an environment which has a modified landscape but no longer a negative impact.
There are three points to be made from this comparison. In the pessimistic future and optimistic future scenarios, the models are highly abstracted and may not consider significant forces that effect economic activity, population change, and environmental quality. Second, the equations that are used to describe these variables preordain the scenario outcomes, except to the extent different magnitudes of outcome result from using different parameter inputs. Third, the metropolitan change model of this research does not seek to replicate either scenario, but, as will be seen in Chapter 5, the combination of the spatial interaction equations, along with the investment flow mechanism, will tend to produce S-curve outcomes.
The model can certainly have parameter values that will induce “Forrester type” of effects. An example of this would be a severe increase in relative distance due to energy price increases, which would be analogous to a shortage of primary inputs that might be thought to result from a compromised natural resource stock. While most of the modeling work done here is purposed on studying changes in the relative population, economic activity and land use of a set of metropolitan areas, and most of these scenarios will be general growth scenarios where the rate of investment flows varies, the model can be forced to produce calamitous outcomes, if desired.



I prefer to work with optimistic scenarios, as so far they have been better predictors of the future than ones based on resource scarcity. Therefore, the prediction from 2010 to 2050 is a stabilized global population, an expanded urban footprint, and a global economy that increases from about 72 trillion dollars in 2010 to 180 trillion in 2050. There are a number of significant milestones in these predictions, one of which is the comparative economic relationship between the United States of America and the People’s Republic of China.
China and the United States
The two largest economies in the world are the United States and China. China’s economic growth rate has been far faster than the United States over the last thirty years, and they have been catching up at a fast rate. China is in the middle of a large scale transportation infrastructure expansion not seen on Earth since the US Highway System was built from 1955-1975. China is building a national highway system, a network of commercial airports, and high speed rail, complementing an existing large water port system. At the current rates of economic growth, China’s GDP PPP (gross domestic product at purchasing power parity), may match the United States around the year 2017. At this point China might be declared in the media to be the world’s largest economy, a ranking change event that last occurred around 1890 when the United States eclipsed the United Kingdom.
Rankings are dependent on definitions, and China will have four times the population of the United States, which means per capita income will only be one forth. In addition, at some point China will not be able to maintain the investment necessary to induce growth rates of 8 to 10 percent per year, and their growth will start to slow down toward the United States 2 to 3 percent annual rate. Therefore, a permanent gap in per capita income may exist. The results of this gap is that while China may end up with the world’s largest fleet of private automobiles, most households will not have two cars but one.


Most Chinese will live in apartments and townhouses instead of single family houses on large lots. The Chinese will live more compactly, and in some respects more efficiently. China will emerge as a developed nation, but with lower per capita consumption patterns. Some people in the United States might mimic these patterns, which means one could see a subset of the US population living more frugally, while at the same time the global economy triples in size and pessimistic assumptions related to over-consumption turn out to be without significant merit.