can this nut be cracked?

We have already seen that mathematical modeling leads to a lot of errors.

Mathematical modeling supposes that economic development can be predicted with the same precision as the course of the celestial bodies. That means that the central problem market economies resolve best does not exist, and if it doesn't exist, we don't need it.

If we can plan something, then it is better to plan it. A market economy is only the second best solution. If there is no insecurity, if the future can be predicted with mathematical functions, equations systems or statistics, there is no need for a system whose strength consist in being the best way to deal with insecurity. This is something that no even the most hard-line communists believed at the end of East-Germany, but that is obviously what most academic economists in the western world think.

If precise prognostics about the future were possible, a central planning commission would be more efficient. If it were really the case, as Léon Walras assumes it to be, that the capital and labour flows alone in the use where the (monetary) marginal product is the highest so that at the end it will be the same in all uses, there are no entrepreneurs and no information processing needed. The total equilibrium will be found by anonymous forces as the celestial bodies find their way driven by gravity and centripetal force.

The central idea of a market economy is that decentral information processing through prices is more efficient than central planning. Individuals are better informed than a central planning commission about their alternatives and their possibilities to react to changes in the market and that they can react quicker. The basic idea of a market economy is that it is impossible to foresee the future and the best way to cope with insecurity is a free market society, which can correct errors quicker than any other system.

Mathematic modeling is possible if the relationship between the different parameters of the system are stable, and all the relevant parameters are taken into account in the model. In these case, we can deduce from the past what is going to happen in the future. We don't expect that the course of the celestial bodies are going to change in the next 5 billion years. In 5 billion years the sun will expire then, we are going to see significant changes and we will not care anymore about the little changes in the economy.

However, as long as the future is unpredictable, we need a system that can adapt itself to changes.

For Léon Walras physics and astronomy are the methodological paradigms of the economy. Economists nowadays don't say it explicitly, but implicitly any kind of mathematical modeling supposes that the future is predictable.

For Karl Popper totalitarian states try to form society following a model of society they consider as ideal. Obviously, there is no need for a democratic decision process for someone who already knows the truth. Totalitarian states don't search for a way to find the ideal social order; they already have it. No democracy is needed if it is known what bests fits for all.

Mathematical modeling, applied to economics, is something similar. There is no need for a free market economy, if the best of all worlds, the total equilibrium as Léon Walras defines it, can be found with some equations as well. There is no need for a process allowing to find the truth if the truth is already found.

Free market economy and democracy are similar in the sense that they don't describe an ideal world. They are only a way to find the ideal world, step by step and taking into account all the changes which are going to happen in the future.

It is not really astonishing that in modern textbooks all the dynamic parameters, which lead to qualitative leap are not mentioned. In textbooks on microecnomics, we have three different definitions of equilibrium, the definition of Alfred Marshall, the definition of Léon Walras, the definition of Vilfredo Pareto. It seems that reaching the equilibrium is the goal of economics, and the equilibrium is intensively studied.

Little attention is paid to the role of prices as a signal of scarcity, which allows entrepreneurs to earn money reducing this scarcity and obliges them to react. In textbooks of microeconomics, the quantities adapt themselves to a change of prices, there is no entrepreneur needed.

Léon Walras is an illustrative example that this kind of mathematical modeling can only be done by people with no practical working experience. Anyone else would have realized that he is analysing a market where goods are only changed, but not produced.

The market he is analysing is something like a farmer market for food products, where all food has to be sold at the end of the day because the next day the goods will be spoiled. That means he is analysing a market, where nothing is produced and where changes in the productive structure, the dynamic part of an economy, is excluded. Alternatively, in other words, he is analysing a very short period, where nothing can change. If the seller realises that the can't sell their goods, the only thing they can do is reduce the prices, and if the demand exceeds the offer, prices will rise.

That explains why in his many equations there is only one variable, the price.

Léon Walras is an extreme example to see the overall tendency. The more mathematical modeling is used, the stronger the tendency to exclude all elements that lead to a qualitative leap, which changes the relationship between the different parameters. In the very short run, this is the period Léon Walras is analysing, absolutely nothing changes. If we consider only a moment, the ceteris paribus clause, which presumes that any other things remain equal, is not even needed, because nothing is going to change in a very short space of time.

The adepts of mathematical modeling, there are millions of them out there, argue that this problem can be solved by more mathematical modeling. They suppose that with more mathematical modeling, all relevant parameters can be taken into account.

They don't say that, but that means, that one day it will be possible to make prognostics about the future and, therefore, a free market economy will not be needed anymore.

The author would say that three thousand years of history tells us the opposite. Nothing, absolutely nothing has remained unchanged in the last three thousand years. The distribution of income has changed, the know-how of the people has changed, technology has changed, the behaviour of the people has changed, the impact of religion has changed, the political systems has changed. All this things have an impact on the economy, and all these things will change in the future. We don't know how these things will influence the economic development, and we not even know if in the future we will see some things with a heavy impact on the economy, which right now are completely unknown.

There is little we can learn from history, but we can learn that nothing can be learned from history because everything changes.

On the other hand the free market, looking out of the window we can see that immediately, is not going to resolve all the problems on earth. However, before we discuss the problems of market economies, we should understand their strength. That's why in our little book that the reader can download from the entrance page we give a short overview of the strength of a market economy.

All the economic schools based on classical and neoclassical concepts, more information about the problematic use of the terms classic and neoclassic you will find in the corresponding chapters, like the Austrian school, neoliberalism, ordoliberalism, social market economy have the same problem. They don't understand or underestimate the problem of insecurity. Although this problem is more obvious in the economic schools and tendencies that make heavy use of mathematical modeling, for the reasons described above, it exists as well in the Austrian school, neoliberalism, ordoliberalism, although the situation is different. The Austrian school and neoliberalism underline the function of the market as an exploration process. Until here everything is fine and correct. Exploration process means that the total equilibrium, as imagined by Léon Walras, can't be obtained through some mathematical equations, but only through trial and error because total information and transparency doesn't exist.

The problem is that they presume that investors are obliged to take the risks related to real investment, that they are obliged to go through this trial and error process. The truth is, they are not. Instead of investing in real projects, they can invest in securities, more or less as liquid as money. This is not a theoretical option; this is a reality. The central banks can inject as much money as they want, and right now, we are in the year 2014, they are injecting a lot of money, banks and other financial intermediaries invest only in the stock market, producing bubbles. Austrian economics believes that by injecting less money, the risk of bubbles would be less. That might be true, but that doesn't mean, that real inversions will increase. We will discuss all that in the chapter about Keynes.

We have, therefore, two different kinds of problems. The fans of mathematical modeling simply deny that something like insecurity exists. They don't understand, therefore, the Keynesian theory, because the problem Keynesian theory deals with, for them simply doesn't exist. We realise that quickly if we take a look at the IS-LM model, which aims to be a mathematical presentation of the Keynesian theory, although it remains unclear if insecurity is really taken into account in this model. (In any case people who get in touch with the Keynesian theory only through this model, don't realise that insecurity is the main topic of Keynesian theory. If insecurity can't be calculated, as it is the case of the LM curve, it doesn't exist.) The reader can find a detailed discussion about the IS-LM model in the little book, which can be downloaded from the entrance page of this website.

At the other side, we have tendencies like the Austrian school. We have no mathematical modeling at the Austrian school and actually the Austrian focus one the central problem. We can't really resolve the problem of insecurity but in a market economy, at least, the best-informed people take the decisions, and if the prognostics are wrong, they can adapt themselves best to the new situation.

However, as we can say looking out of the window, the best solution sometimes is not good enough. If investors prefer to invest all their money in the stock market, they don't produce jobs and economic growth, but bubbles. In these case, the state can do better, and the basic argument in favour of a market economy that it leads to the best possible allocation of the resources is not valid anymore. Bubbles on the stock market or the real estate market are the worst misallocation we can imagine. In this case, it is easy for the state to do better.

This is a fundamental problem that should be fully understood. We discuss the problem in the little book about Keynes which can be downloaded from the homepage of this website.

If the reader thinks that the problem is irrelevant, the ardent adepts of the Austrian school very often do that, because they had not even understood their hero Friedrich Hayek, he can imagine that he has won 10 million dollars in the lottery and what he would do with this money. The answer will alway be the same. The reader would buy a house, a nice car and so on. The money left he would give to a financial intermediary, an assurance company or a bank, in the hope that they will find some profitable investment. The problem is, as we see at the moment, that they have the same problem. Investing money is not at all a simple task. It may be a simple task for Léon Walras because he resolved the problem theoretically with some mathematical equations supposing that the capital automatically finds the most profitable use and that at the end the profit is the same in every use. However, Léon Walras never tried to put his ideas into practice.

It may appear strange that bubbles always arises in markets as different as the stock market and the real estate market. Keynes focus on the stock market and the liquidity preference theory only applies to the stock market, because buildings are very illiquid. So, at first, glance, this seems to be strange. However, actually, it is not strange. Buildings are obviously very illiquid, it is not possible, to get the money invested back at any moment, as it is the case with an investment in the stock market. Nevertheless, the situation is similar because a building can be mortgaged. For a bank, it is, therefore, a calculable risk, in any case, more calculable than investing in a company.

Specialised machines, in general, can't be sold, and if the company goes bankrupt, their value is near scrap value. In times of crises, when everybody believes that things get worse, nobody will invest in risky projects.

We understand very easily the strength of a market economy, we don't need any single mathematical equation to understand the advantages, but we risk to sub estimate the problems of market economies if we use a lot of mathematical equations.

The same problem arises when we suppose transparency. If we suppose transparency, the basic problem of a market economy is excluded.

The problem of academic economists is that they not even understand the problem and, therefore, they won't resolve it either.

Keynes doesn't really defines the term insecurity. Obviously, insecurity is the result of a lack of data. If we are well informed, there is no insecurity. Insecurity is therefore due to a lack of information or a lack of know-how, that allows the interpretation of the information or both.

Lack of information or know-how means as well that a number of possible alternatives is reduced. If institutional investors prefer investment in the stock market instead of investments in real projects, they do that, because the investment in real projects they know seems to be too risky or because they don't know at all other alternatives.

The Keynes solution, lowering the interest rates, is one possible solution to the problem. The lower the interest rate, the easier it is to find profitable investments and the lower is the risk.

The other solution is much more complicated, and we will try throughout this manual to explain by examples what we mean. The other solution would be to find profitable investments. Therefore, more data are needed.

It is not helpful, when in one part of the planet there is a problem and on the other side of the planet the solution for the problem if they don't know each other or if data are missing about the rentability.

The only sector the author knows where a systematic research is done are drugs. Pharmaceutical companies search systematically, asking shamans, healer and nomads which plants they believe to have a therapeutical effect. These affirmations can be tested later under controlled circumstances and the plants having a therapeutical effect can then be produced on an industrial scale.

However, researches like this are not done systematically. There are for an instant a lot of bioplastics, which have the big advantage of being sustainable and biodegradable. Not all of these bioplastics are suited for any use, but some of them can substitute existing plastics based on oil. If studies like that exist, this is, for instance, the case of bioplastics, they have been financed by the European-community and have no further impact.

Nobody knows if it is not more profitable to invest in bioplastics, substituting, for instance, the existing CD boxes by boxes made of bioplastics than investing more money in the stock market. We are not going to discuss here the usefulness of bioplastics. If they are useful or not is as well a question of how they are produced and where they are produced. We only want to give an example for the fact that sometimes investment on the stock markets are preferred, because investments in real projects are difficult to evaluate.

It is crucial to the understanding of economics to understand the Keynesian theory. A quick overview of the Keynesian theory can be downloaded from the homepage of this website.

In the Keynesian theory, all kind of innovation is explicitly excluded. That doesn't mean that Keynes excludes all kind of innovation, new products, new markets or change in the productive structure. That only means that we can't expect them to happen. If investors don't invest enough, interest rates must be lower to make real investments more interesting. Insecurity remains the same but with lower interests the risks lower.

The other solution, more difficult to obtain, is lower insecurity by improving the transfer of know-how promoting innovation. This is hard to be done because it requires that the academic teacher are something like entrepreneurs and the behaviour, feeling, know-how, etc. of a public employee is the exact opposite of an entrepreneur.

The standardisation of the academic curricula and the mathematical modeling proves that right now they not even have understood the problem.

In theory economists with their cross-sectional knowledge are best suited to detect areas where existing technologies can be used to resolve existing problems. Rarely they are the authors of an innovation, but it is well possible, that we don't have a lack of innovation, but a lack of transformation of innovation into marketable products.

Even institutions like the German Fraunhofer-Gesellschaft, which focuses on applied science, is operating at a loss and must be subsidised (with 1200 million Euros a year, to be exact) by the government. There is not a lack of innovation, but scientists are not entrepreneurs.

It could be, to give an example, a useful exercise for students to study what this kind of institutions are doing, there are a lot of them, and to look for an application of the results of their research.

To give a concrete example of the problem, Fraunhofer-Gesellschaft invented the audio compression algorithm mp3, but they were not able to introduce it into the market. That was done later very successfully by Steve Jobs.

We will see more examples of this kind throughout this website. Economists should be trained to match problems and solutions, what very often requires cooperation on an international level.

Academic economists write thousand of "discussing papers", which were never discussed, about innovation. Same universities have more or less understood the problem and created new masters, Master's programme in Economics of Innovation and Growth, perhaps that works, but in the rest of the world they are still more occupied with things like the pareto optimum and the Walrasian total equilibrium.

In general, economist prefer to model mathematically economic growth. That's more comfortable because no data were needed. The aim of these studies is unclear because they have no real impact on innovation. Concrete studies about the possibility to resolve a concrete problem with a concrete technology would be much more helpful and would allow the students to obtain skills they really need. More discussion papers are not needed, there are already too many of them, and they are only read by people who are writing discussion papers.

The normal procedure to produce a "seminar thesis", necessary to get credit points, is to go to the university library, read some books and make a resume of these books. That's not what happens in real life. In real live different people with different qualification work together and more and more at an international level.

Universities are in a better condition to cooperate at an international level, because they have the same interests and goals, training students, and financial question are more or less irrelevant.

It is not very difficult to find millions of projects, where different universities can work together on a concrete problem. That would even be practical because they can obtain data for which private companies would be obliged to invest money and time.

Students of economics in Peru, for instance, can evaluate the possibilities of wind power systems in Peru and how the must be adapted to suit the climatical, geographic and social structure in Peru. In the best case, it should be possible that Peruvians can maintain them alone with any further assistance. In case that there is a lack of know-how, it can be evaluated how much does it cost to train the people and how this is to be organised.

Students in the United States on the other side can evaluate, which companies in the United States produce this kind of wind power systems and if it is possible to adapt them to the Peruvian conditions, how much does it cost and how this project can be financed. The author presumes that small systems are better than the very big ones used in Germany, because of transportation problems. Perhaps something like that, but cheaper, Small Wind Electric Systems. Another solution would be to train people in Peru and to produce them there.

We have no intention to discuss here the possibilities and problems of using wind energy in Peru. However, we expect that this simple example shows that the Walrasian total equilibrium can not be achieved with some mathematical equations and that it is very plausible, that insecurity is related to a lack of data and know how.

Price elasticity and consumer rent is, of course, an interesting topic. We can talk about it, we will do that in that manual, but ten minutes is enough. There is no need to explain the idea in plain words, graphically and mathematically. If the basic idea, quite simple, as most economic concepts, is understood, we can pass to the next topic.

That's the way we can save time; it is possible to teach the same concepts taught today in 8 semesters in 2 semesters if we put things simple and straightforward. The two years saved could be spent on concrete projects. There is no need to train people for writing "discussion paper" because nobody cares about discussion papers. This is only interesting for academic careers, but for nothing else.

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