10/1/11

Summer issue of Theoretical and Practical Research in Economic Fields

As an Editor, I am happy to announce that the summer issue of the Theoretical and Practical Research in Economic Fields has been published. There is my paper as well, pp. 86-93:

THE EVOLUTION OF FIRM SIZE DISTRIBUTION
Ivan O. KITOV
Institute for the Geospheres‟ Dynamics
Russian Academy of Sciences, Moscow, Russia

Abstract
Significant differences in the evolution of firm size distribution for various industries in the United States have been revealed and documented. For theoretical considerations, this finding puts major constraints on the modelling of firm growth. For practical purposes, the observed differences create a solid basis for selective investment strategies.

Keywords: firm size distribution, Pareto distribution, the USA, evolution, investment

JEL Classification: L11, L17, G1

Summer issue of Journal of Applied Economic Sciences

The summer issue of the Journal of Applied Economic Sciences has been published. It includes our paper "A win-win monetary policy in Canada", pp.160-180

Abstract
The Lucas critique has exposed the problem of the trade-off between changes in monetary policy and structural breaks in economic time series. The search for and characterization of such breaks has been a major econometric task ever since. We have developed an integral technique similar to CUSUM using an empirical model quantitatively linking the rate of inflation and unemployment to the change in the level of labour force in Canada. Inherently, our model belongs to the class of Phillips curve models, and the link between the involved variables is a linear one with all coefficients of individual and generalized models obtained by empirical calibration. To achieve the best LSQ fit between measured and predicted time series cumulative curves are used as a simplified version of the 1-D boundary elements (integral) method. The distance between the cumulative curves (in L2 metrics) is very sensitive to structural breaks since it accumulates true differences and suppresses uncorrelated noise and systematic errors. Our previous model of inflation and unemployment in Canada is enhanced by the introduction of structural breaks and is validated by new data in the past and future. The most exiting finding is that the introduction of inflation targeting as a new monetary policy in 1991 resulted in a structural break manifested in a lowered rate of price inflation accompanied by a substantial fall in the rate of unemployment. Therefore, the new monetary policy in Canada is a win-win one.


Keywords: structural break, inflation, unemployment, labor force, modeling

9/28/11

Good time to sell oil futures

In May 2011, we predicted oil (WTI) price to fall to the level of $70 per barrel by the end of 2011. This is a monthly revision for September 2011. We consider the average oil price of $84 per barrel what is equivalent to the producer price index of 244 in September. (Actual estimate will be published by the Bureau of Labor Statistics in the middle of October.)


Figure 1 compares our prediction with actual oil price in 2011. In August 2011, the predicted price is a bit higher than the measured one. In any case, we expect the price to fall by approximately $5 per month to the level of ~$70 in December 2011. We also expect the price to slowly fall through 2016 and put the uncertainty bounds for the long-term trend in oil price. The level of oil price in 2016 is between $30 and $60 per barrel. These bounds are also shown in Figure 1.

A week ago, when oil price was at ~$79 per barrel, we recommended buying oil futures. The intuition behind this idea was that $79 is approximately $5 below the expected price for September. This is a disequilibrium which should be recovered in the short run. Today, oil price is at the level of ~84. This is the equilibrium level for September. A small hike in oil price is possible during the next few days. However, at a two-week horizon, oil price should fall again. Therefore, I recommend selling now and buying in approximately two weeks or when the price will be around $75. It will grow to the level of ~$82 to $85 in October or November.
Figure 1. Oil price prediction in 2011. The price is expected to fall by $5 per month between June and December 2011. The price level is ~$70 in December 2011. We also show the range of expected price evolution by 2016.

Paul Krugman on the progress of economics

I avoide re-posting any other author in this blog. However, this post (see below in red) from Paul Krugman  deserves to be reposted one-to-one becasue I agree with many of his statements on macroeconomics. At the same time, Paul needs to make a step ahead and to look at the principal problem of macroeconomics as a science  - the absence of quantitative justification and the direct rejection of empirical proof as the tool of the macroeconomics progress. When one cannot measure the progress of a science in quantitative terms - this progress cannot be seen.  Hence, economics has to open itself for a criticism from the broader scientific society before it becomes a second rate sect, which is very close to be the truth

Does Economics Still Progress?



In a few hours Sylvia Nasar and I will have an on-stage dialogue at the 92nd Street Y, centered around her new book The Grand Pursuit, which offers a set of fascinating portraits of the makers of economics. (Irving Fisher invented the Rolodex?) But as I was reading her book I have to admit that I found myself wondering whether there’s much to celebrate.



I’ve never liked the notion of talking about economic “science” — it’s much too raw and imperfect a discipline to be paired casually with things like chemistry or biology, and in general when someone talks about economics as a science I immediately suspect that I’m hearing someone who doesn’t know that models are only models. Still, when I was younger I firmly believed that economics was a field that progressed over time, that every generation knew more than the generation before.



The question now is whether that’s still true. In 1971 it was clear that economists knew a lot that they hadn’t known in 1931. Is that clear when we compare 2011 with 1971? I think you can actually make the case that in important ways the profession knew more in 1971 than it does now.



I’ve written a lot about the Dark Age of macroeconomics, of the way economists are recapitulating 80-year-old fallacies in the belief that they’re profound insights, because they’re ignorant of the hard-won insights of the past.



What I’d add to that is that at this point it seems to me that many economists aren’t even trying to get at the truth. When I look at a lot of what prominent economists have been writing in response to the ongoing economic crisis, I see no sign of intellectual discomfort, no sense that a disaster their models made no allowance for is troubling them; I see only blithe invention of stories to rationalize the disaster in a way that supports their side of the partisan divide. And no, it’s not symmetric: liberal economists by and large do seem to be genuinely wrestling with what has happened, but conservative economists don’t.



And all this makes me wonder what kind of an enterprise I’ve devoted my life to.

9/22/11

Time to buy oil futures

Several day ago I showed that oil price had fallen below expectation in August. Today oil price has been falling since the very morning  and now  is approaching $80 per barrel. We predicted $70 in December 2011.  Thus, oil price has to grow again and it's good time to buy futures.

9/18/11

Scientists, experts and lay public

Blogger Sean on Discover Magazine compares various types of experts.  Specifically, he answers the question why people trust opinion of experts in physics and do not trust economists.

This is a simple question if to separate firm scientific knowledge and scientific hypothesis.  People do trust well established physical knowledge like mechanics, and thus, they trust physicists in every day activity. For example, aircrafts, ships, satellites, buildings in seismic zones, TV, mobile telephony, etc. is the materialized scientific knowledge. It is beyond discussion of experts and lay public that numerous physical laws deserve absolute trust. (Imagine an expert discussion on the impossibility of mobile telephony as based on the absence of electro-magnetic waves. A hundred and fifty years ago such a discussion would be absolutely reasonable.)   All these physics (or scientific in a broader notation) laws are almost fully justified by laboratory experiments and other types of measurements. Because these laws are now an indispensible part of every day life people forget that this was and is the essence of scientific knowledge. 

However, there are scientific topics which have no reliable scientific solutions (yet or forever) and are characterized by a higher uncertainty in both theories and experiments. In my view, these new horizons in the hard sciences, which are formulated as hypothesis, should not be presented for the broader audience (lay public) as robust scientific knowledge. They do not have robust solutions or materializations yet. When positioned as well established scientific knowledge these hypothesis ignite severe discussion between experts and lay public. They use the uncertainty gaps in experimental justification and put forward own interpretations with various applications in real life.

I would treat “global warming” (as induced by human activity) as one of such hypothesis which should be better experimentally justified. There are so many gaps in  the estimates of major sinks and sources of greenhouse gases that the relative inputs in the final balance is not clear yet. Notice, I do not say that this hypothesis is not scientifically void. I just say that a Nobel Prize for it was a premature and political decision which has changed the terms of the scientific discussion.    

Now we come to economics and economic experts. It is well known that economics (I do not include finances, business, etc.) is a science without experimental or observational justification. When one judges by the prediction of large scale outcomes like recessions economics does not show any result at all. (Many economists are proud of that, however.) It is in drastic contrast to the predictions of the hard sciences - we foresee that our airplane will land with a very high probability in line with actions of many physical laws, staring with Bernoulli one, which creates the lifting force. Otherwise we would never use the plane.  Here the term “economic experts” comes. These are people who discuss measured macroeconomic values without any quantitative justification.  That’s why I do not like the term “expert” as applied to physicists. When I hear it I usually see a round table with several economic experts discussing a problem without any solution in scientific terms. As a rule, they can explain any process or phenomena with the same words and arguments they used to explain the opposite process and phenomena two years ago. For me its enough to decide that they are worth nothing together with their words. Economic experts use a very limited agrument base to explain everything.

In turn, the possibility to explain everything attracts the lay public. People like the illusion of understanding. In many economic blogs one can observe how readers repeat the arguments from economic experts without understanding that these experts have explained nothing. Emotionally, it is better to trust experts than scientists, who usuall do not have ready answers to all questions.

As a remark. Some physicists propose a scientific revolution in economics (Bouchaud, J.-P., (2008). Economics needs scientific revolution, Nature, v.455, 30 October 2008). I would start with a simple data analysis in line with classical mechanics (Ivan O. Kitov, 2009. “Does economics need a scientific revolution?, Quantitative Finance Papers 0904.0729, arXiv.org). Actually, economic data do not match even basic requirements of physics. They are usually incompatible over time. One needs lots of efforts to recover major time series like inflation, GDP per capita, rate of unemployment, etc. (http://mechonomic.blogspot.com/).

Therefore, a researcher in the hard sciences is hardly an expert explaining all observations and usually knows what s/he knows and what s/he does not know. The latter is the matter to investigate. When a researcher works as an expert and brings to the unprepared audience (almost any place except specialed seminars, workshops, conferences, etc.) some hypothesis with a large uncertainty it usually has a negative result. At best, nobody understands and forgets.
The worst case, politicians use one of many possibilities under the higher uncertainty for their dirty profit. As an example, I recall a long discussion in the USSR about the necessity to turn nothern rivers to the Caspian sea, which had been losing water and thus area before the 1970s. The reason is clear – money and resources, i.e. power, and this project was supported by many (specially selected) experts who forecasted the sea to disapper according to their linear models. The Soviet government was ready to start. In terms of long term observations, for an inner lake oscillations is a natural regime (as was argued by many scientists, chiefly, physicists) and the Caspian sea has been growing since the 1970s and has already inundated many small villages. The conclusion - do not give any chance to politicians to use your knowledge in their interests. In other words, do not be “experts”.

In reality, it was not the strong scientific opinion but the disintegration of the Soviet Union that stopped the project. Nobody is able to stop the greater political project “global warming”.

9/13/11

On the evolution of age dependent mean income

I published a dozen papers on personal income distribution between 2003 and 2009. One of the principal topics was the evolution of the mean (median) income and its dependence on age. Specifically,  I have shown that the age of largest mean income increases proportionally to the square root from real GDP per capita. (Actually, the mean income was used instead of GDP per capita because the Census Bureau does not include several important sources in the Current Population Surveys. See Figure 1 for differences.) Using this link I have also predicted that this peak mean income will enter the age group between 55 and 64 years after 2015.  Before 1975, the peak mean income was in the age group between 35 and 44 years. Figure 2 presents the mean incomes in various age groups as normalized to the largest mean income in a given year.  
According to Figure 1, the growth in the mean income practically stopped in 2000 and the real GDP per capita has returned to 2004. Accordingly, the growth in the age of the largest mean income also effectively stopped in 2004. Since we do not expect fast economic growth in the 2010s, the age of peak mean income may move in the 55 to 64 year group around 2020.
This observation is a crucial one for our model of personal income distribution. It is the only model which ties the age dependent income distribution with the level of real GDP per capita. Slow economic growth is equivalent to slow evolution of personal income distribution. At the same time, the age dependent personal income distribution does not depend on other factors: calendar time, education, human capital, taxes, interest rate, etc.  
Figure 1. Real GDP per capita (measured in chained 2009 $) and mean income ( in 2010 $) between 1967 and 2010. The mean income is related only to people with income (211,000,000 in 2010) and the GDP per capita is calculated for the whole population.
Figure 2. Mean incomes in various age groups (“20” corresponds to the ages between 15 and 24, and so on) normalized to the largest mean income for a given year. For example, the largest mean income in 2010 belongs to the age group between 45 and 54 years and thus the normalized mean income is 1.0 for this group.

Drang nach Osten — «натиск на Восток»

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