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Using Little's Law, one can calculate throughput with the equation: = where: I is the number of units contained within the system, inventory; T is the time it takes for all the inventory to go through the process, flow time; R is the rate at which the process is delivering throughput, flow rate or throughput.
In addition to the absolute pass-through that uses incremental values (i.e., $2 cost shock causing $1 increase in price yields a 50% pass-through rate), some researchers use pass-through elasticity, where the ratio is calculated based on percentage change of price and cost (for example, with elasticity of 0.5, a 2% increase in cost yields a 1% increase in price).
Throughput (T) is the rate at which the system produces "goal units". When the goal units are money [ 8 ] (in for-profit businesses), throughput is net sales (S) less totally variable cost (TVC), generally the cost of the raw materials (T = S – TVC).
The same example using first pass yield (FPY) would take into account rework: (# units leaving process A as good parts with no rework) / (# units put into the process) 100 units enter process A, 5 were reworked, and 90 leave as good parts. The FPY for process A is (90-5)/100 = 85/100 = 0.8500
In mathematical queueing theory, Little's law (also result, theorem, lemma, or formula [1] [2]) is a theorem by John Little which states that the long-term average number L of customers in a stationary system is equal to the long-term average effective arrival rate λ multiplied by the average time W that a customer spends in the system.
Formally, exchange-rate pass-through is the elasticity of local-currency import prices with respect to the local-currency price of foreign currency. It is often measured as the percentage change , in the local currency , of import prices resulting from a one percent change in the exchange rate between the exporting and importing countries. [ 1 ]
Given an arrival rate λ, a dropout rate σ, and a departure rate μ, length of the queue L is defined as: L = λ − σ μ {\displaystyle L={\frac {\lambda -\sigma }{\mu }}} . Assuming an exponential distribution for the rates, the waiting time W can be defined as the proportion of arrivals that are served.
In monetary economics, the equation of exchange is the relation: = where, for a given period, is the total money supply in circulation on average in an economy. is the velocity of money, that is the average frequency with which a unit of money is spent.