The notion of macro- and microeconomics dates back to the Norwegian economist Ragnar Anton Kittil Frisch (1895-1973),who–although he did not mention those terms directly—used the expression ”micro-dynamic” to describe the detail of a section of a whole economic system. According to his definition, a microeconomic system ought to be a certain well-defined system where the parameters are known. His definition of macro-dynamic analysis describes the global/complete economic system. These notions have been taken up by the Austrian economist Fritz Machlup, who introduced the terms micro- and macroeconomics, based upon Frisch’s initial definitions.
Essentially, microeconomics methods are used to:
The result of a microeconomic survey could be to determine
Using game theory and artificial intelligence, each stakeholder in a microeconomic system could be viewed as an agent such as:
The outcome of a microeconomic analysis leads in the optimal cases to an economic equilibrium, where the agents interact with benign intentions. Those equilibria can be determined using either operation theoretical or game-theoretical mathematical techniques. The analysis of microeconomic behaviour leads to stifling competition. Microeconomic models require sufficient fine-tuning on given data, and machine learning methods, such learning agents, can be fed on those data sets to see which conditions generate an economic equilibrium for each of the conditions. Microeconomics, therefore, strive to replace those imperfect ”half-baked” data with perfect data sets that come with Big Data. This could remedy uncertainties and lead to more robust statistics.