The dominant relations in the Infrastructure model are those that determine the expected levels of infrastructure stocks and access, spending on infrastructure, and the impacts of infrastructure on health and productivity. The expected levels of infrastructure stocks and access are influenced by socio-economic factors related to population, economic activity, governance, and educational attainment. In almost every case there are also path dependencies that supplement the basic relationships, reflecting the considerable inertia in infrastructure development.

Spending on infrastructure is divided into private and public spending, with the latter further divided into ‘core’ and ‘other’ infrastructure. ‘Core’ infrastructure refers to those types of infrastructure that are explicitly represented in the model; ‘other’ infrastructure refers to those types of infrastructure that are not explicitly represented in the model (see Infrastructure Types). Public spending on core infrastructure, GDS(Infra), is driven by the required spending to meet the expected levels of infrastructure (INFRABUDDEMMNT and INFRABUDDEMNEW), total government consumption (GOVCON), and the demands on government consumption from other categories. Public spending on other infrastructure, GDS(InfraOther), is driven by average GDP per capita (GDPPCP), total government consumption (GOVCON), and the demands on government consumption from other categories. Deficits and surpluses of government funds will affect the actual levels of funds allocated for both core and other infrastructure. The public spending on core infrastructure leverages a certain amount of private spending on core infrastructure, with the amount leveraged depending upon historical relationships found in the literature, which nominally reflect the variation in public and private returns between particular types of infrastructure. Finally, in recognition of the incremental approaches that public budgeting decisions usually follow, our model avoids unusually sharp increases in public spending on infrastructure by smoothing it out over time.

Infrastructure development directly affects multifactor productivity, with this effect being treated separately for non-ICT and ICT related infrastructure. The use of solid fuels in the home and access to improved water and sanitation directly affect human health through their effects on the mortality and morbidity rates of specific diseases—diarrheal diseases, acute respiratory infections, and respiratory diseases.

For detailed discussion of the model's causal dynamics, see the discussions of flow charts (block diagrams) and equations.