DR. MARIO ARTURO RUIZ ESTRADA
79
REVISTA ACADÉMICA ECO (23) : 73-92, JULIO-DICIEMBRE DE 2020
3. Introduction to the National Coffee Production
Function (NCP-Function)
The following section describes the National Coffee Production Function (NCP-
Function). Initially, it consists of four sub-production functions: (1) Coffee
Producers; (2) Coffee Brokers; (3) Coffee Sellers; (4) Coffee Consumers. Each sub-
production function has its respective quadrant. Each quadrant shows a single
dependent variable (
βij
) represented with a vertical line at the quadrant’s centre;
and “
n
” number of independent variables (
αij
) represented with horizontal lines at
the bottom of the quadrant. Finally, all αji were join to the dependent variable
βij
using the linkage of axes application "". All axes in each quadrant run real-time
under the application of dynamic growth rates (see Expression 1.5). Therefore,
there are four quadrants or four sub-production functions, and each quadrant has
its dependent variable “
βij
” by “
n
” number of independent variables “
αij
”. In this
case, there are four outputs from producers (
β0
), brokers (
β1
), sellers (
β2
) and
consumers (
β3
), originating at each sub-production function. Finally, among the
four quadrants there is a single axis that it´s all the final coffee national output
“
β*
”. It joins the output of each of the four sub-production functions by means of
the linkage application “
╬” which links the quadrants by straight lines (see Figure
1). The idea is to build a single surface by linking together in the same physical
space the four outputs of each sub-production function.
The objective of the NCP-Function is to build a large and single surface that
is moving in real time in the same physical space. In fact, the application of the
Omnia Mobilis assumption (Ruiz Estrada, 2011) is a basic condition to generate the
real-time effect of the NP-Function. Hence, the final national output “
β*
” always
displays a dynamic and multi-dimensional behaviour (Ruiz Estrada & Park, 2018)
in real time into its multi-dimensional space. The analysis of the final results of the
NCP-Function depends on the position of the surface and it can determine the
situation of an economy highly dependent on the production, commercialization,
and consumption of coffee. If the acreage is at a positive level, then the stability of
the coffee market will be observed. If the surface remains at zero level, a stagnation
of the coffee market is observed. If the acreage jumps between negative and
positive levels, it can be established that the coffee market is highly vulnerable.
Finally, if the acreage is below the negative level, then the coffee market is in
constant crisis (see Figure 1).