Intuitively, global warming and climate change just makes sense.

Simply put, over the millenniums of Earth’s biologic history, life has developed into a balance that maintains the carbon cycle and the environment in which it lives.  This is obviously true in smaller ecosystems around the planet and is no less true of the Earth as a whole.

Short of grand natural disasters, the history of mankind is that of the only creature that does not reach a level of sustainable interaction with the environment.  In economics, this is referred to as a Malthusian catastrophe.

Anthropogenic Global Warming and Climate Change are the inevitable Malthusian catastrophe.

Why Climate Change Is Not Inevitable | The Nation

http://m.thenation.com/article/193705-why-climate-change-not-inevitable

What “profits” means.

The general dialog often refers to company profits. This is especially true when the discussion turns to minimum wage and corporate taxes. A common belief is that companies require profit in order to remain in business. There appears to be a bit of misunderstanding of what “profit” is, precisely. This lack of precision leads to mistaken conclusions.

There are to fields of study from which to draw a definition of “profit”. These are economics and business accounting. The two yield the same final understanding though alone they both are a bit lacking. The reason is simply that the precise definition often depends on what the point is. Economics, when concerned with profit maximization, isn’t concerned so much with taxes. Business accounting can be all over the map with revenues, earnings before taxes, earnings before interest and taxes, earnings after taxes, and on and on.

The best precise definition that gets to the point of profit is that it is the final amount of monies remaining after all costs, interest, salaries, and taxes have been paid.

The math goes like this;

Costs = wages*labor_hours + rents*equipment.

equipment includes facilities and capital equipment. Wages includes all wages, hourly or salary.

Revenues = price * quantity.

Earnings = Revenues – Costs

Earnings are before taxes and interests which is referred to as EBIT in business accounting. Typically, interest is deductible from earnings before the tax rate is applied.

EBIT = Revenues – Costs

EBT = Revenues – Costs – Interest

Earnings After Taxes = Profit

Profit = (1-t) * EBT

What is significant here is that if EBT is zero, there are no profits and no taxes. It is obviously necessary for a business to be able to cover costs. At the very least, revenues need to equal cost plus interest. But, when all is said and done, as long as revenues cover interest and costs, there is no necessity that a company earn profits or even end up paying taxes.

And, in fact, this is how businesses do tend to operate. Of 25 million companies operating in the US in 2012, they paid a total of about $191 billion in taxes. This amounts to about $7000 per company in taxes. With an effective tax rate of about 26%, the total per company profits amounted to about $21,000. $21,000 per company is pocket change. It doesn’t even cover the income of one minimum wage worker. It is, for all practical purpose, insignificant.

This is not unexpected as it is exactly what is predicted by basic classical economics. In a free market, any profit attracts competition. Competition drives down prices which quickly drive profits to zero.

Market Power

I have been looking for a measure of market power.  There are many good micro economic texts that include generalities of market power.  For instance, “Microeconomic Theory, Basic Principles and Extensions”, Nicholson & Snyder, 10th Edition includes chapters dealing with monopolies and imperfect information.  While excellent material, it isn’t quite what I am looking for.

The measure that I have in mind is based upon demand and supply elasticity.  Consider gasoline or home heating fuel.  Demand tends to be inelastic.  This inelasticity that results from the high utility of fuels presents a level of market power on the supply side.  As well, economies of scale creates additional supply side power.

Elasticity is given as

    e = [Percentage Change in Quantity]/[Percentage Change in Price]  : Prose definition

       = (Δ%q)/(Δ%p)  : Algabreic definition

       = (dq/q)/dp/p)        : Calculus definition

      =  (dq/dp)*(p/q)    : Derivative definition

(It should be noted that the axis for elasticity are flipped from the standard supply and demand diagram axis.  The definition for elasticity places quanity on the independent axis.  The only significance is that of being acustomed to thinking about supply and demand in terms of price being on the horizontal axis.  And, because elasticity is defined in terms of the slope of the line, diagramatically it is slightly different from the customary diagram.)

 

With this in mind, high elasticity is a steeper slope.  For high elasticity, a small change in price is associated with a large swing in quanity.  HIgh elasticity is greater than one, e>1. 

For low elasticity, a large price change in necessary to affect quanity.  Low elasticity, or inelastic, is less than one, e<1.

Supply elasticity is typically positively sloped while demand is typically negatively sloped. 

Gasoline demand tends to have low demand elasticity, |e|< 1 or e > -1.  That is, relatively large market price changes do not appreciabely affect quanity demanded. 

Gasoline supply tends to have high elasticity as marginal cost is small for changes in quantity, |e|> 1 or e > 1.   Small changes in market allow for large changes in the quanity produced and supplied.

So, for gasoline, the demand curve is near horizontal, with 0> e_d > -1,  while the supply curve is near vertical,  with  e_s > 1.

The elasticity of one curve affects the shift of the other. 

For gasoline, it takes a larger change in market price to induce small changes in supply output. 

The Affect Of China Manufacturing On The U.S. Economy

A fundamental effect on the US economy has been the rise in China manufacturing exports.  A considerable number of specific explanations regarding the US economy are misplaced, attributing things like unemployment, energy costs, and every manner of economic measure to incorrect causes.  Rather,  unemployment, employment participation, energy costs including pump prices, US federal outlays, US federal budget deficit,  public debt,  consumer credit expansion, income levels, even the global housing bubble, have some foot in the rise of manufacturing exports from China.  Some are easily demonstrated, others are secondary, the response to the shifting structure of the US economy which is significantly affected by the global markets.  Regardless, a significant number of economic changes are clearly traced back to the 1998-2000 time frames. Some of the economic effects are detailed here, specifically

The Growth of Chinese Exports:  An Examination of the Detailed Trade Data (Nov 2011)

Abstract: Over the past decade, Chinese exports have boomed, increasing far faster than GDP growth. What can account for this explosion? Our paper uses finely detailed Chinese export data (8-digit HS codes) combined with U.S. trade data to explore this question. Although exchange rate policy clearly boosted the trade surplus, and the structure of the economy, e.g. abundant cheap labor, encouraged investment, these alone cannot account for the changing composition and acceleration of exports. We find that the growth in exports is most likely a product of effective Chinese industrial policy and fortuitous timing. The detailed trade data reveal that key “new” technology goods, such as cell phones, LCD screens, and laptops played a critical role.

Finally, we use the data to examine the relationship between Chinese exports and global manufacturing, in particular U.S. manufacturing employment. We find that increased Chinese competition in both domestic and U.S. export markets likely lowered U.S. manufacturing employment between 2000 and 2007. Chinese policy is not, however, wholly responsible. Some job losses, such as in textile production, were no doubt the result of China’s natural comparative advantages, while other U.S. job losses are attributable to relatively low investment and slow GDP growth in the United States following the 2001 recession.

The Growth of Chinese Exports: An Examination of the Detailed Trade Data

http://www.federalreserve.gov/pubs/ifdp/2011/1033/default.htm

Some issues for consideration include “comparative advantage”, “absolute advantage”, global market competitiveness, and U.S. business investment in manufacturing in order to fully appreciate the breadth of China’s manufacturing boom.

All in all, six key economic factors can be shown to begin with China becoming a major manufacturer.

1. Fuel Costs Due To Increasing China Demand.

2. US Employment – Employment to Population Ratio.

3. US Median Household Income Falls beginning 2000.

4. US Federal Budget Deficit

5. HOUSING BUBBLE

6. Mortgage Backed Securities

The significant point is that of the timing of China exports began around 2000.

China Manufacturing GDP

It was this ramping up of China manufacturing that set the stage for numerous effects on the US economy.

————————————————–

Fuel Costs Due To Increasing China Demand.

With regard to the increase in the cost of fuels on the global market place, what exactly occurred as a result of China manufacturing adding to the demand for fuel in the global market place is a significant question.

Seen here, at the very least, it is clear that the real dollar price of gasoline began it’s steady rise around 2000. Seen here, the real price was flat from 1988 through 2000, when it began to rise. (The sudden collapse of demand due to the recession of ’09 can be seen along with the recovery of the economy which is marked by rising demand and increasing prices.)

Retail Gasoline Price Level

We may ask ourselves what the complete set of factors underlie the price changes.  Still, it is apparent that this began in 1999 to 2000.

——————————–

US Employment – Employment to Population Ratio.

A highly significant change began in 2000 as the US labor market began changing.  In 2000, the employment to population ratio began its downward trend.

Seen here, the long upward trend that began in the ‘60s reversed.

Employment To Population Ratio

——————————————–

US Median Household Income Falls beginning 2000.

US median household income began falling in 2000, as China became a major world exporter.  Median income saw a reprieve as the housing boom stimulated the economy.  This was short lived.

Median Income

————————————-

US Federal Budget Deficit

Seen here, the US federal budget deficit demonstrates a distinct change in 2000.

US Federal Budget Surplus (-Deficit)

It is notable that there is a preceding trend that began in around 1970 that deserves some explanation.  (I don’t have one.)  Never the less, while the deficit trend of 1970 was reversed during the administrations of President George Bush and President Bill Clinton, it was in 2000 that the deficit began its spiral down to a peak in response to the recession of ’09.

The US public debt and federal outlay trends are simply tied by accounting and need no detailing here.

The fact that the initial driver of the US deficit was driven by China’s manufacturing boom is apparent in the data.  It is a reaction to the declining US manufacturing base, declining employment to population ration, and efforts to maintain GDP.

——————————–

HOUSING BUBBLE

Seen in the graphic below, the most recent housing bubble began no later than 2002, following shortly on the heels of China’s increase in manufacturing export boom.

Housing Bubble

The causal link between the change in the global market and the housing bubble is indirect.  The loss of declining US manufacturing necessitated alternative mechanisms to facilitate economic growth.  One was in the housing market, driven by a housing bubble.

Additional effects, such as the rise in mortgage backed securities and credit default swaps, also followed.  Not directly driven, like the housing boom itself, they filled the vacuum left by China becoming competitive in the global economy.

————————————-

Mortgage Backed Securities

As well, the onset of mortgage backed securities was delayed, showing it’s larger growth beginning in the 2003-2004 time frame. It was driven by multiple mechanisms, not the least was the housing bubble which presented the opportunity for MBS supply. While the causal factors are links down the chain, the stage was initially set by the boom in China manufacturing and the reaction of the markets to the loss of a US manufacturing base with no alternative replacement.

Mortgage Backed Securities

Mortgage Backed Securities Volume

—————————————

Conclusion:

There are a few more economic effects that deserve attention, such as unemployment, consumer credit expansion, income levels, which have some foot in the rise of manufacturing exports from China.

There is the curious fact that, while employment and wages fell from 2000 through 2009, GDP did not reflect these trends.  The small recession of 2001 was offset by housing and financial markets.

Never the less, it is clear that the single driving force that eventually led to the recession of 2009 began in 2000.

References

Board of Governors of the Federal Reserve System International Finance Discussion Papers Number 1033 November 2011 The Growth of Chinese Exports: An Examination of the Detailed Trade Data Brett Berger Robert F. Martin

[url=http://www.federalreserve.gov/pubs/ifdp/2011/1033/default.htm]FRB: The Growth of Chinese Exports: An Examination of the Detailed Trade Data[/url]

[url]www.federalreserve.gov/pubs/ifdp/2011/1033/ifdp1033.pdf[/url]

[url=http://www.eia.gov/todayinenergy/detail.cfm?id=5550]Gasoline prices rise due to increased crude oil costs – Today in Energy – U.S. Energy Information Administration (EIA)[/url]

[url=http://research.stlouisfed.org/fred2/graph/?id=EMRATIO]Graph: Civilian Employment-Population Ratio (EMRATIO) – FRED – St. Louis Fed[/url]

http://en.wikipedia.org/wiki/File:Median_US_household_income.png

MacroEconomic Models

I found a good free macro econ text. It is Intoductory Macroeconomics, by Povey, and is available at users.ox.ac.uk/~sedm1375/book.pdf‎.

For me, what makes it excellent is that it presents the macro economic models in their succinct mathematical formulation. The classical and Keysian are there, the first being long run and the second being short run.

As long run economics goes, there is no imbalance or market inefficiencies. The First Theorem of Welfare Economics holds, perfect cometition. The labor, money, and financial markets all clear.

The basics of this Classical Economic model allows for the equation of exchange, MV=PQ which is also GDP=C+I+G+NX.

A consequence of the equation of exchange is that at long term equilibrium and efficiency afforded by the Classical model, prices are a function of the supply of money, specifically the countable supply in circulation. MV=PQ is an identity. All money spent on Q, accounted for by P, is all money in M. It is also all income spent on Q. As such, prices are always a function of the money supply, given that Q is set. This is what accounts for inflation, an increase in the money supply without a corresponding increase in production.

Another consequence of the money supply on prices is that only after-tax, disposable income, has any effect on prices. In the long run, equilibrium to equilibrium, the tax level has no effect on the standard of living. Standard of living, Q/l, quanity of goods per person or labor hour, is a function the labor employeed and the efficiency of that production.

This should be readily apparent. All that increases and decreases in taxes do directly is change the money supply in the equation of exchange. There are Keynsian implications of changes in taxes, but these are short run impulses and not a consequence of the classical economic equilibrium model.

Wages vs. Employment to Population Ratio.

The relationship between wages and the supply and demand for labor may be divided into two time periods.  In the most general sense, the trend for employment to population ratio changed in the year 2000. The yearly trend, from 1985 through 2012 is show here.

From 1985 through 2000, the employment to population ratio rose from 60.4% to 64.4%.  This trend was a continuation of the upward trend that began in 1962.   From 2000 through 2012, the employment to population fell, from 64.4% to 58.3%, in 2009 when the global economy receded.  From 2009 to 2012, has remained relatively flat, rising .3%.

The relationship between wages and the supply of labor becomes apparent when the wage index is presented as a function of the employment to population ratio.  This is shown here.

From 1985 through 2000, the global economy continued on the upward growth that began after the end of WWII.  This growth created a demand for labor.  As the availability of labor tightened up, the wages increased.  After 2000, changes to the global economy shifted the labor market leverage from the supply side to the demand side.

Linear regressions may be accomplished in Excel or at ttp://www.xuru.org

Notably, recessionary periods of  1990, 2000, and 2007 show up as an additional decrease on top of the general trend of falling AWI to EmpRatio. They are offset slightly from the official NBER dates though NBER resolution is to the month while data here is to the year.

A dummy variable may be introduced for declines in EmpRatio.  This provides the addition of regressions for the entire time period as well as two periods seperated by the year 2000.

The online tool provides for multiple linear regression with may be compared by residual sum of squares.  The results for sum of squares are show below with the best RSS with two periods seperated at 2000 and a multiple regression on an AWI dummy variable.

Single Variable

Full Data                              52,218,458.52

1985 through 2000            3,686,210.435

2000 through 1985           993,570.5394

Multiple Regresion, Dummy on EmpRatio

Full Data                              46,885,620.06

1985 through 2000            3,634,240.307

2000 through 1985           950,598.2904

Multiple Regresion, Dummy on AWI

Full Data                              52,218,414.03

1985 through 2000            3,034,561.403

2000 through 1985           898,929.0276

This seems to make the case that wages are sensitive to demand for labor.

Data Source:

BLS : http://data.bls.gov/cgi-bin/surveymost?ln

SSA : http://www.ssa.gov/oact/cola/awidevelop.html

CPI : ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.txt

Considerations in Economics.

I received the following feedback.

“Bravo, well worth the read – all 3 three posts – regardless of where one stands in relation to this subject.   Very well reasoned, logical, easy to read and follow, concise and insightful. You would make an outstanding college economics professor, or author of textbooks for dummies… thanks for the education.“

So, I figured, what the heck…  I’ll start a blog.

The attempt, here, is to present empirical evidence or deductive reasoning in economic topics.  For the most part, I look towards articles and comments for idea and opinions in economics.

For instance, in an article “What Is Money and How Do You Destroy It?“, it is reported that “Mitt Romney says Mr. Bernanke’s policies have “over-inflated” the currency.”

I ask, can it be shown to be true?

My response is; “Mitt Romney is clearly wrong. Bernanke took office in Feb 2006. From 2000 thru 2005 the average monthly percent change in the CPI was 0.22%. From Feb 2006 thru Nov 2011, the average monthly rate of change for the CPI has been 0.21%. While the average monthly rate of change (linear regression giving the rate of the rate of inflation) remained flat over the period of 2000 through the end of 2005, since Bernanke took office, the monthly rate of change has trended downward. Perhaps Romney’s error is that he starts from an oversimplified hypothesis and comes to a conclusion without actually checking the facts. But, as I look at the CPI data now, it is clear that the Fed policy has been anything but inflationary.”

But, Mitt isn’t really talking about price inflation. He is speaking of monetary inflation. So I haven’t really proven him wrong. Still, without price inflation, we really don’t care about monetary inflation. So, when Mitt says, “Mr. Bernanke’s policies have “over-inflated” the currency.” He isn’t, in fact, right. He isn’t right because there is no basis for concluding that the currency is “over-inflated”. And, without proof that it is, then it isn’t. There is the rub, Mitt makes a statement that is not true but cannot be proven false. It will be true if and only if, at some later date, we get price inflation. Then we can say that Bernanke had over-inflated the currency. But, at least for now, we cannot say that he has.

The space available in commenting is limited.  And, it lacks the ability to present the graphs which help demonstrate the facts.

So, this blog is a place where I can expand on these considerations in economics.  It contains articles on what I can show, either empirically or with some deductive reason.