The theory assumes that the critical drivers of social activity - in all contexts and at all levels of development -- can be traced to the interaction among three master variables– population, resources, and technology. Measurement of the master variables is usually a first step in quantitative analysis and grounds the theory in an empirical context. Population refers to the size, distribution, and composition of people, and to changes thereof. Each of these variables can be differentiated along a number of sub-factors or variables – depending on the issues at hand or the interest of the analyst. The same can be said about resources and technology. Technology refers to all applications of knowledge and skills in mechanical (equipment, machinery, etc.) as well as organizational (institutional) terms. This concept of technology encompasses both soft and hard dimensions, and often the former is as important as the latter. Resources are conventionally defined as that, which has value to include all elements critical to human existence (such as water, air, etc.), provides a perspective on the concept of resources intimately connected to requisites for basic survival. The specific metric or metrics used in any investigation is usually driven by the research design and its purpose.
In lateral pressure theory, the master variables constitute the basis for identifying the state profile and to calculate a state’s profile type. At each point in time, a state is characterized by one set of “master variables” that define the empirical parameters of the polity and provide the basis for policy agenda as well (Choucri and North: 1987, 205-208)1. Normalization of the selected indicator ensures that the master variables are (1) of same order of magnitude, and (2) independent of their units of measure. This step ensures that lateral pressure profiles of different states are comparable and meaningful. The normalization technique used is the fractional share of a state s in the global aggregate value (“world” total) of the indicator in year t.
Thus we define the master variables as follows: