A massive multiplayer videogame is a set of thousands of people whose unpredictible and simultaneous actions have (or might have) inmediate consequences on any other player, doll, character or whatever we want to call it.
Mr. Volcker, former Fed chairman, confessed himself astonished of the speed of cause-consequences during this crisis. Most economists and policy makers are astonished. The global economy has changed in the last years, we have to get used to it. Also we have to get used to see that consequences can be amplified compared to causes. The usual extreme example of the theory of chaos is that a tiny butterfly moves its wings in Beijing and its consequence is a storm in New York (reverse cities if you want). In the same way, using the appropiate techniques, negative consequences could be cushioned or even avoided if we can determine since the butterfly started to fly that it would have consequences in New York and we can know which consequences they could be. In this message I will try to describe why, once this economic crisis has been unleashed, many economic predictions from most gurus are not accurate and why some techniques extensively used in Asian videogames help economic predictions and decissions more than traditional linear techniques. In traditional linear way of thinking, based on formula and algorithms, accuracy of raw data determines the accuracy of results as you can find in my first cite below "The process of measurement is central" (1). They work extremely well during quiet periods. While one economy grows, for example, between 2% to 5% year after year. They can predict easily anything, even a deep crisis. Even easier if they predict a financial crisis. Until now, decission making and prediction processes has been conducted in a linear way of thinking. Mostly based on something called "quantitative methods" (2), in economics it is a sequel of monetarism developed in Chicago and in other American universities many years ago and even today. But what if they have to analyse trillions of data? what if empiric data are changing fast, up and down, constantly? what if the formula itself changes because behaviours changes, inside or abroad, with dramatic consequences inside our field of observation? (2) Their models, their algorithms, their formula, their linear way of thinking do not work at all and produce wrong results and predictions. A tiny example, economic authorities rule against recession because they receive a report that states that GDP has declined 0.2%. If that report states that GDP decined 2% they would rule in a different way. And if that report shows that GDP declined 20% their rules would be completely different. But what if those data, 0.2% in the example, are wrong? Or what if they are correct but the consequences from external economies make that it turns from 0.2% to 2% or 20% in one month? On the other hand, some decission-makers ask to have those new concepts available right now for their actual decissions. For example, one of the decissons of the G20 meeting in November or December was to create an "early warning system" for the IMF. It means a system designed according to something that we discussed here, a set of indicators based not on "ceteris paribus" premises (3), but on "omnia mobilis" (4) or, at least, on "beyond ceteris paribus" (5). http://groups.google.com/group/world-thread/browse_thread/thread/a8189c944b38128a/aa50de230f3aed1d?hl=en&lnk=gst&q=omnia+mobilis#aa50de230f3aed1d Finally, once we have results of our report, nowadays we cannot use linear way of thinking. We should use "fuzzy logic" (6) or similar techniques because the true goal of decission makers is not to know whether growth will be exactly 0.1% or -0.1% in order to discern whether technically we will be into a recession or not. Decission makers want to know a set of actions that predictibly will have extremely negative consequences on economies to avoid those decissions, and their second goal to know a set of actions that predictibly will have positive consequences on GDP growth to choose one among them. The exact value of the consequence of their actions is not very relevant (to create 4 millions jobs or 4,050,000 jobs is not very relevant for US decission makers) if in order to know that value exactly they might suffer a high price in terms of risk of error. Unfortunately many gurus are educated just on traditional premises. And even worse, some of them do not have an open mind to accept their range of error. Fortunately, many others, although educated in traditional techniques, openned their minds to new ones and, at least, use them optionally for important analysis. Peace and best wishes. Xi (1) Quantitative methods. Quantitative research is the systematic scientific investigation of quantitative properties and phenomena and their relationships. The objective of quantitative research is to develop and employ mathematical models, theories and/or hypotheses pertaining to natural phenomena. The process of measurement is central to quantitative research because it provides the fundamental connection between empirical observation and mathematical expression of quantitative relationships. Quantitative research is widely used in both the natural sciences and social sciences, from physics and biology to sociology and journalism. It is also used as a way to research different aspects of education. The term quantitative research is most often used in the social sciences in contrast to qualitative research. http://en.wikipedia.org/wiki/Quantitative_methods A typical training of quantitave methods applied to decission making. http://www.ebsglobal.net/programmes/quantitative-methods (2) We have talked in this group about why consumer price index is not accurate during crisis, people change their purchasing habits while methodologies to gather date do not change so fast. Also, GDP is not accurately gathered because societies change their behaviours too. For example underground economy, black economy, hidden economy or whatever you call it, blossom during crisis and we cannot measure it. In economies based on farmery it is easier because we can watch from satellites how fields develop, but industrial economies are more difficult. Financial economies are completely impossible to be measured accurately. (3) Cēterīs paribus is a Latin phrase, literally translated as "with other things the same." It is commonly rendered in English as "all other things being equal." A prediction, or a statement about causal or logical connections between two states of affairs, is qualified by ceteris paribus in order to acknowledge, and to rule out, the possibility of other factors which could override the relationship between the antecedent and the consequent. A ceteris paribus assumption is often fundamental to the predictive purpose of scientific inquiry. In order to formulate scientific laws, it is usually necessary to rule out factors which interfere with examining a specific causal relationship. Experimentally, the ceteris paribus assumption is realized when a scientist controls for all of the independent variables other than the one under study, so that the effect of a single independent variable on the dependent variable can be isolated. By holding all the other relevant factors constant, a scientist is able to focus on the unique effects of a given factor in a complex causal situation. Such assumptions are also relevant to the descriptive purpose of modeling a theory. In such circumstances, analysts such as physicists, economists, and behavioral psychologists apply simplifying assumptions in order to devise or explain an analytical framework that does not necessarily prove cause and effect but is still useful for describing fundamental concepts within a realm of inquiry. http://en.wikipedia.org/wiki/Ceteris_paribus (4) I do not know any accurate definition in English and I could not find any decent definition over the net. But it can be translated to something like: "Based on the Theory of chaos, "omnia mobilis" is the assumption that every single entity (material or non-material) changes and produce actions non-stop. Those actions produce consequences on any other entity." (5) To create useful models under omnia mobilis assumption is not feasible nowadays and computers could not work with so many data. Therefore, most researchers work on "beyond ceteris paribus". "Beyond ceteris paribus" do not handle all existing entities and their actions, but states a set of indicators that are meaningful to warn on external actions that might have meaningful consequences on the field that we work with. As far as I know, these techniques are used just on Asian videogames and by Chinese decission makers as one of their source of information. As it is also studied in Japan and in South and Southeastern Asia, I guess that it can be used in those countries for somedecission making processes, but I cannot be sure because my lack of information. Regarding actual use of it in economies, as far as I know, China is the only country that uses it in some actual local economies nowadays and always in experimental purposes. (6) Fuzzy logic is a form of multi-valued logic derived from fuzzy set theory to deal with reasoning that is approximate rather than precise. http://en.wikipedia.org/wiki/Fuzzy_logic --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "World-thread" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/world-thread?hl=en -~----------~----~----~----~------~----~------~--~---
