## The Banana Republic Computer (BRC) Explained

In classical economics demand and supply determine price. More demand leads to higher prices and greater output to meet the demand. However, in most circumstances, this adjustment cannot be instantaneous. The BRC recognizes that there is a delay as price signals work their way through the system. When demand is falling, prices may drop to an unsustainable level. For example the price of computer memory has at times fallen below the manufacturing cost. One can call this oversupply. On the upside, when demand is increasing, there can be windfall profits as oil producers recently and briefly enjoyed.

If productivity is increasing and most of the fruits of this increase go to a relatively small number of wealthy individuals, demand relative to supply will fall. This produces a temporary oversupply that will lead to falling sales and/or falling prices and to increasing unemployment. This will in turn lead to a further decrease in demand and more unemployment creating a particularly vicious cycle. That is what the BRC models in a somewhat simplistic way. Click her for a more complete description of the problem.

The BRC computes unemployment, change in Gross Domestic Product (GDP) and change in wages based on a simple model.

You can set the following parameters:

• annual labor productivity increase (productivity increase, default = 3%),
• the fraction of increased output due to increasing productivity that is consumed (demand factor, default = 50%),
• the effect of demand change on employment, 100% means employment would change in direct proportion to the change in demand (job change, default = 25%),
• the effect of demand on wages, 100% means wages are directly proportional to demand (wage elasticity, default = 25%),
• the portion of demand that comes from employment, 100% means all demand is from employment (wage demand, default = 50%),
• Last year computed (last year, default = 2034).

Within the BRC, most values such as GDP and productivity are fractions relative to the first year's values which are set to 1. These are converted to % before being displayed. The settable parameters are converted from % to fractions before being used. Fractions are used in the following description of the calculations the model makes. These calculations are repeated for each year being modeled starting in 2009 and ending in the last year.

• productivity = (previous year's productivity) × (1 + (productivity increase))
• current GDP= (productivity) × (current employment) ÷ (initial employment)
• GDP change = (current GDP) - (previous year's GDP)
• GDP demand change = (demand factor) × (GDP change) + (previous years GDP demand change)
• other demand = 1. - (wage demand)
• current demand = (GDP demand change) + (other demand) + (wage demand) × (previous year's employment) × (previous year's wage) ÷ ((initial employment) × (initial wage))
• demand difference = (current GDP) - (current demand)
• current employment = (previous year's employment) × (1. - (demand difference × (job change))
• current wages = (previous year's wages) × (1. - (demand difference × (wage elasticity))

In the above (other demand) includes such things as government spending, money spent from savings and investment income. It is not a constant as the model suggests. This is one of many oversimplifications. Still the model should give an impression of what would happen if nothing is done to change the current dynamics where most of the gains of productivity go to a small fraction of the population.

Click here for a C++ version of the model with self documenting variable names.

Mountain Math Software