Economics is currently recognized by the broad scientific community, and economists themselves, as a soft science. Unlike objective quantitative methodology associated with hard sciences, economics provides at best some qualitative assessments, sometimes called "stylized facts", of its fundamental assumptions and findings. What one expects from a standard scientific theory is a description of known facts about some measured variables with a finite number of defining parameters and relationships. As a rule, the lower is the number - the better. Also the theory must give quantitative predictions both in time and in different ranges of defining parameters. In the case of economics - across countries.
For example, accurate prediction of lunar phases at very long time horizons was available thousands years ago. There was no theory describing gravitational interaction of masses, however, to describe and predict orbits. Now, using the theory of gravitation, one can explain long-term (as related to the planetary system) changes in the moon-earth-sun interaction and changes in lunar phases at a geological time horizon. Also, one can accurately predict orbit of any satellite in any planetary system knowing only distances and masses. There is a question at a Universe time scale with planetary orbits - what was before the Universe was born and what will be after it will dye or will undego some dramatic changes? This question is on the list of modern science.
There are several key points to characterize a theory as belonging to hard sciences. First, such a theory must use measurable parameters in order to establish quantitative relations between them. Second, the theory should describe a larger part or available measurements and give quantitative predictions. This allows testing and validation of the theory. In principle, one should be able to repeat known laboratory experiments or conduct new passive measurements in order to check both data and theoretical relationships. There is always a weak (or sometimes strong) discrepancy in various data sets and physical theories in the "naked"form are actually sets of scatter plots or statistical relationships. Thererfore, it is not usually required to have an exact description of the entire data set. Moreover, a good theory may be potentially used to distinguish between reliable and unreliable data sets. Third, the theory should define the boundaries of applicability. In other words, the theory should be falsifiable, i.e. the defining quantitative relationships of the theory do not describe real links between the involved parameters beyond some predefined range.
For example, the predictive power of Newtonian mechanics deteriorates with increasing speed of objects and the mechanics developed by Einstein replaces classic mechanics at relativistic velocities. When a theory can give an answer to any question, related or unrelated to the scope of the theory, it is always a wrong theory from scientific point of view.
This blog (being a mirror of a monograph) is aimed at presenting a quantitative theory of economics as expressed by strict quantitative relationships between several measured micro- and macroeconomic variables in such developed countries with market economy as the USA, Japan, the UK, France, Germany, Canada, Italy, Netherlands, Australia, Austria, and others. The set of measured variables includes population, real GDP per capita, inflation, unemployment, labor force participation rate, productivity, and personal income distribution. These macro-economic variables are shown to be functions of demographic parameters.
In our economic research, we follow the requirements for a hard science – quantitative description, quantitative predictions for validation, defining the time interval of validity or the range of defining parameters where the relationships work. On the other hand, we do not pay much attention to the details or "fine structure"of the driving mechanism underlying the observed relationships by limiting ourselves with a strong form of scientific reasoning, i.e. quantitative analysis. This means that we just mention some vague potential links and channels of influence but not provide any extended justification of the relationships expressed in words.
Formally, the sense of any scientific theory consists in obtaining objective (statistical) links between measured variables as described by mathematical equations. In the absence of axiomatic assumptions behind the theory, as adopted in mathematics, there is no way to reduce the observed links to a finite set of meaningful "words". The sence of any variable in a quantitative theory is in the possibility to measure its value only. One can define the term "mass", for example, only though measurements and only these measurements define the term mass as we know and use it both in routine life and science. There is no set of terms, which can explain and describe mass better than the entire set of corresponding measurements.
There are several principal concepts of the quantitative description of links between measured economic variables introduced similar to those adopted in mechanics. They describe the methods and procedures of empirical and theoretical analysis used in obtaining quantitative relationships, provide standard statistical assessment as adopted in physics and economics, and validate the concept by cross-country analysis. The limits of the applicability of the relationships are also defined to meet the principle of falsifiability. This blog (and the monograph) is focused on the resolving of three fundamental economic problems – sources for real economic growth, inflation and unemployment, and personal income distribution.
In our framework, real economic growth is related to only one demographic parameter and does not depend on any other parameter economic or non-economic. Inflation and unemployment are also entirely described by a single relation to the change rate of labor force level, which is completely defined by real economic growth and demographic fluctuations. Personal income distribution is also driven by age structure and real economic growth, the latter defining long-term changes in individual income trajectories.
Therefore, real economic growth in developed countries does not depend on monetary policy. This observation is in line with old hypothesis on the neutrality of money for real economies. This independence isnot correctly (actually just in opposite direction) interpreted by conventional economics, however. In fact, the independence implies that only monetary expression does matter and is the measured variable to study. In other words, there is no specific configuration of goods and services, which can cost more thangiven and measured one. Thus, all possible configurations of goods and services cost the same amount of money for given year. This effectively makes monetary description independent on physical and technological content - the observed set of goods and services is equivalent to any imaginary one, which might be realized in different conditions - political, social, climatic, etc., but not demographic.
The monograph describes real economic growth only in terms on the total final product cost. This effectively excludes from our study such exciting economic terms as marginal productivity, human capital, supply and demand shocks, productivity and technology shocks, education, and many others, which are related to technological and other kinds content of economy only. These terms are good for a conventional economic reasoning but absolutely irrelevant to the quantitative description adopted in the current study.
I have to confess. I do not like economic reasoning and conventional economic theory. There are several reasons for that. First, as an ordinary physicist, I always rely on measurements for any judgment. The absence of an experimental justification undoubtedly makes any theory just an assumption or educated guess. No of conventional economic models, which I am aware of, is empirically justified. Second, the evolution of any macroeconomic parameter is usually modeled with the same "success" using juxtaposed theoretical approaches and contradicting, if not random, sets of parameters. At a theoretical level, this observation is supported by the existence of numerous competitive models. At the level of practical applications, one can recall myriads of mutually excluding explanations of the same macroeconomic facts.
A simple example is the explanation of the influence of oil prices on real economic growth. In 2002, an increase in oil price above $20 per barrel was considered as a traction force for the global economy with an average deceleration of 0.5% to 1%. In 2006, the influence of the price decrease below $50 was also interpreted in the same way. My opinion on the influence is an opposite one. There is no one-to-one causal link between any part of developed economy and the whole economy. Any change in one part of the economy must be competely compensated by opposite change in some other part. In physics, such compensation is called a conservation law.
Third, top economists too often use words like mystery, mysterious, etc. This is more appropriate to religious activity than to science. To confirm this observation I would like to cite the 2004 Nobel Prize laureate E.C. Prescott, who wrote in "The Wall Street Journal" (December 11, 2006): One of the mysteries of the 1990s is how to explain the economic boom when the increase in capital investment – as measured by national accounts – grew at subdued pace. Harvard Professor G. Mankiw titled his essay "The inexorable and mysterious tradeoff between inflation and unemployment". In spite of clear metaphoric usage of these words, one can feel the flavor of the deep inconsistency between the practice of economic observations on one side and the accuracy of theoretical description and the power of economic predictions on the other side. This is a clear dissatisfaction. Imagine now that your personal and social prosperity is in the hands of a person who can only say that there is no economic variable, which has an well-understood behavior and can be controlled somehow. Moreover, they insist that nobody could, can, and will be able to present a consistent theoretical description of economic variables. So to say, economic problems are too complicated to allow ordinary hard sciences to resolve them.
Here I make an attempt.

Our model is presented in the following article:

Kitov, I., Kitov, O., Dolinskaya, S., (2008). Comprehensive Macro – Model For The US Economy, Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(4(6)_Wint), pp. 405-418.

We present a comprehensive macroeconomic model for the U.S. There exist strict long-term relations between real GDP, price inflation, labor force participation, productivity, and unemployment. The evolution of real GDP depends only on exogenous demographic forces. Other macro-variables follow up the real GDP. The links between the variables have been valid during the last several decades. All relations were (successfully) tested for cointegration. Statistical estimates are also presented. The relationships allow a reliable prediction of the macroeconomic state at very large (more than 9 years) time horizons

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