What is alarming too, is that Duisenberg was not alarmed, didn’t veto

this nonsense.

After this ‘Duisenberg disaster’, the issue disappeared from people’s

mind, it got transformed into an annual debate on indexation and the

topic of discussion became the level of benefits for the needy. In 2005

Holland still suffers the consequences.

Book IV

Presentations for the general public

In March / April 1996 I put two presentations for the general public in

the Economics Working Papers archive at the Washington University at

St. Louis. In August 1998 there was a third paper. [52] These papers

are directed to a general audience, and to teachers and students. Since

this current book basically addresses economists and uses quantitative

methods, I doubted whether I should include these texts here, also

since there is some overlap that can be distracting. There however are

two good arguments to include them with little adaptation: (i) Once a

fellow economist is starting to grow convinced of the value of my

analysis, then he or she will face the same problem of explaining it to

others. These texts then can be of use. (ii) The historical date of

these texts underlines the co-ordination problem. Even when a good

summary was available, and even when the moral imperative facing

Western nations was clearly formulated, our failing systems of economic

policy making limped along, and caused misery upon misery for many of

its citizens.

15. Unemployment solved !

_A breakthrough in economic theory_

Since the early 1970s Western economies have been plagued by mass

unemployment and the threat of inflation. Over the years since then

various economists have proposed various possible solutions, but never

quite convincing ones. Now there is a novel analysis that means a

breakthrough in economic theory. The present author is quite certain

that the “missing link in the model” has been found. If true, this

analysis offers guidelines for full employment under price stability,

just as Western economies enjoyed in the 1950s. The main point is:

don’t tax lowly productive labour. Why ? To keep it competitive so that

more productive labour will not demand inflationary pay rises. Though

this new analysis is only in the stage of presentation and introduction

at the scientific fora, there is no reason to withhold the present

rough sketch for a general public.

It is well-recognised these years that Western economies have a problem

with jobs with a low level of productivity and thus a low level of

market-earned income. The United States tolerate more poverty - the

working poor - while Europe sets its minimum wage much higher so that

Europa has more unemployment.

This problem with low productivity jobs finds various explanations,

notably those of technology, globalisation, and inflexibility - the

latter ornate for “welfare state sclerosis”. Policies based on these

latter explanations have been enacted for some time now. For quite some

time, in fact; while little is being achieved. It is proper that we

pose the question: why is it that we don’t achieve much ?

Unemployment obviously has a much longer history than the current

problem. Also, the Western track record on unemployment can only be

understood when the record on inflation is taken into account too.

Economic science has much to say on the complex relationship between

inflation and unemployment. Now, we are forced to be brief here. We

will concentrate on what is new and on why it is new.

We set out with the empirical evidence since 1950. This track record

can be divided in meaningful decades:

· The 1950s had low unemployment and low inflation.

· The 1960s had the threat of unemployment, and governments

accommodating inflation in order to actually prevent it.

· The 1970s nevertheless had mass unemployment bursting into the open,

and governments accommodating high and accelerating inflation to battle

it.

· The 1980s-till-now had governments come down hard on inflation, and

accepting high levels of unemployment as the price for stability.

One sees a certain “trade-off” between unemployment and inflation. From

the 1950s till the end of the 1980s the common view among economists

and policy makers was that the unemployment in the trade-off was

“general” unemployment. Nowadays we tend to link unemployment to lowly

productive labour. For us it may be obvious, but compared to the

earlier view it is revolutionary that the once-thought-to-be “general”

unemployment now turns up as a rather specific type. To make the

revolution specific: we will hold that the unemployment in the

trade-off has _always_ been related to the distribution of productivity

across labour.

The crucial insight is that the people who can demand pay rises need

not be the people who run the risk of unemployment thereof. High

productivity workers run less risk of unemployment and can more easily

demand pay rises, while low productivity workers run the larger risk of

unemployment. High productivity workers are more versatile and are able

to shift the risk of unemployment to the lower income groups. When jobs

are scarce, the high productivity workers even crowd out others from

the labour market.

Now obviously, when this is new, then it has not been recognised

before, and then it has likely been missing in policy. And policy that

was based on a wrong analysis, is likely to have been the cause of the

very problem that it wanted to solve.

Let us see how it went wrong. Regard the legal minimum wage and note

that people are not allowed to work below that minimum. Note too that

there_ hence_ will be no earnings that can be taxed in that range. We

can call this range the “tax void” or “tax vacuum”. However, tax

statutes are defined in that range anyhow. Tax statutes in that void

are actually used to define the gross minimum wage. In Europe, the high

gross wage will cause unemployment and its related benefit burden. In

the US, the void is reduced a bit by accepting poverty. In common

economic terms: tax policy and social-economic policy are badly

co-ordinated.

How this has come about is a story of a more technical nature. First

note that OECD countries adjust their taxes for inflation. Tax

exemption in 1996 will often be close to the inflation-adjusted real

value of 1950. On the other hand, research in social psychology shows

that subsistence tends to rise with the general level of income, the

growth of which consists of inflation and real growth. So there is

“differential indexation”. In the 1950s exemption was pretty close to

subsistence, so that there was no void to speak of. Since then,

exemption has lagged behind the standard of living. The

inflation-adjusted subsistence of 1950 may be only a third of 1996

subsistence. When tax exemption lags behind net subsistence, then there

is a multiplier effect on gross subsistence, with a fast increase of

the tax void.

The alternative and new policy would be to scratch taxes in that void

and to allow people to earn their own - decent and untaxed - living.

This alternative policy reminds of an old rule. The Dutch economist

Cohen Stuart proposed in 1889 to put tax exemption at the level of

subsistence. To drive the point home he drafted the following analogy:

“A bridge must carry its own weight before it can carry a load.” In

1996 there is the additional argument that abolishing void taxes will

not cost anything, and that nations will save benefit payments due to

more employment.

More employment.... Does that not fuel inflation ? The pieces of the

puzzle fall into their places when the tax void is related to the

unemployment & inflation problem. The steady rise of the void explains

the track record of unemployment and inflation. The 1950s have been

characterized by relatively low taxes on low income earners, and this

allowed for full employment and low inflation. From the 1960s onwards

the lagging tax exemption started causing problems with unemployment.

The tax policy since at least 1965 enhanced the imbalance of the

internal bargaining positions of labour instead of counter-balancing

it. Hence inflation was persistent, and high levels of unemployment

were required to achieve price stability.

How governments reacted depended upon the view of the day. Since the

proper solution was not known, the problem did not go away. The

differential indexation of tax exemption and the social minimum did not

draw attention to itself. Each year adds only a slight gap which is

hard to see. But over the years the gap has accumulated, and with huge

consequences. And the problem will remain with us in the future unless

policy changes.

Current policy is based upon other explanations. Notably those of

technology, globalisation and flexibility. The ineffectiveness of

current policy can be explained by the fact that these views are not

entirely logical. The arguments of technology, globalisation and

flexibility run up against contradictions. Technology is a source of

wealth, and it boosts the productivity of the lowly productive jobs,

making the problem of poverty and unemployment less serious than it

would otherwise have been. “Globalisation” is a scare word for “trade”.

Trade however is another source of wealth, and it too has been with us

for ages. Rising wealth in distant countries means rising wages over

there, and trade itself thus puts limits to foreign competition. Japan

over the last 40 years is a prime example of this phenomenon, but every

rich nation has had the same experience. Finally the “flexibility” or

“welfare state sclerosis” argument can only explain that the US has

poverty and Europe unemployment, but it does not explain that there is

a problem with low productivity jobs in the first place.

The present situation bears another surprise. We diagnose current

unemployment as inefficient. Be sure that you see what inefficiency

means: it means that there is a solution that is beneficial to some and

that does not hurt others. Having a bright idea always means a

“win-win” situation or a free lunch. In this case it is the move to

full employment under price stability. The present unemployed will find

jobs. The higher productivity group will have a theoretically larger

risk of unemployment, but in practice this risk will be modest as in

the 1950s. Their real gain will come from the services that will be

provided by the jobs of the present unemployed.

Policy makers will be hesitant about an overhaul of the tax system.

Note, then, that the tax system defines our notion of a subsidy. A

wrongly levied tax, in this case the tax void, can be compensated for

by a wage cost subsidy. Abolishing the tax void is more sensible in the

long run, but when this can only be done gradually, then some general

subsidy directed at lowly productive jobs would speed up short term

adjustment. If only those subsidies are reduced when tax exemption

rises towards subsistence.

This was it, in a nutshell. Now I beg your understanding. My analysis

is more complex than can be stated in these few lines. Both tax policy

and social policy are quite complex themselves, and this certainly

holds for their interaction with inflation and unemployment. For

example, you may ask why I haven’t discussed income redistribution

effects. Actually, this is because the alternative policy could be

neutral to the income distribution. The reason for this is that the

analysis focusses only on the link between wage costs and productivity.

But you might want to hear more about this. Also, you might ask whether

above explanation covers all possible cases of unemployment and

inflation. Of course it doesn’t. The analysis does help to clarify that

other types of unemployment need other types of policy, such as

education and so on. But you might want to hear more on that too. These

are just examples of issues, and there are many more issues that need

to be dealt with. Which space forbids. However, given that my model

amends existing economic models, much of the required explaining is

‘common economics’.

There remains one major point. That tax exemption is low, is defended

by OECD governments with the argument that it keeps marginal rates

down. And the attractiveness of low marginal rates is that they spur

economic activity. My finding however is that the latter claim is only

true when the marginal rate has been defined properly. Thus I agree

with the claim, but it must concern the proper marginal tax rate. There

is a difference between the proper rate, which is dynamic, and the rate

used by OECD governments, which is the static and statutory rate.

Dynamic analysis shows that the proper marginal rate will be close to

the average rate. This part of my analysis is important for economic

growth. Having less unemployment will mean lower average taxes, and

thus lower proper marginal rates, and thus more incentives for

sustainable growth. For many of my fellow economists it is this part of

my analysis that will come as the greatest surprise of all. However,

this is not an issue that can be settled in this review, and here I

definitively have to refer to my extensive analysis.

This novel explanation is in the tradition of Keynes and Tinbergen

while it fits in with mainstream economics. When my fellow economist

check and confirm these findings, our economies are likely to enter

into a new high growth path with full employment and low inflation.

Allow me to add the personal note that I am overjoyed by these

findings.

(March 1996)

16. Enable Russia to help itself

World developments in the 1990s show a worrysome parallel to the 1930s

with the Great Depression. Present-day Russia reminds of the pre-war

Weimar republic, where a devastated economy and weak democracy allowed

Hitler to take power. Western nations in the 1990s hinder trade with

Russia and the Eastern nations for fear of unemployment at home, as

they did in the 1930s with Germany. If trade were stimulated instead of

hindered, Russia could regain economic and political stability by

itself. The moral problem is not external and does not concern whether

Russia would need financial aid. The moral problem is internal, and

concerns whether Western political leaders are willing to face their

own errors that cause the present mass unemployment at home.

Russia is shrouded in a veil of doom. A nation once proud about its

achievements, is now, as so many feel, humiliated in the face of

history. A loss of empire, a collapse of economic security, some coup

attempts in both Kremlin and Duma, a rising reign of violence by a

mafia in the main cities and by full-blown fighting at the geographical

fringes, and a political arena that smells more of fear than of

confidence. Like the Weimar republic in pre-war Germany, Russia has

been subjected to the rules of chaos, and yet again the odds are risky

- and risky for the world at large.

Something needs to be done. Something smart, something humane,

something effective and efficient, and something courageous. Therefor,

something which is not likely to happen quickly. However, there is one

single possibility that is very much worth of our attention. It is

something what we actually could do. And what - given the risks of this

moment - we should do

It is _trade_ that will help Russia and the Eastern nations to

recapture economic security and thereby regain political stability.

And, since it is our fear of unemployment that motivates us to block

that trade, Western nations should tackle unemployment at home

directly.

Parallel

Our comparison of present-day Russia with pre-war Germany is no

coincidence. World developments in the 1990s show a worrysome parallel

to the 1930s. The 1930s suffered from the Great Depression. In the

1990s the world is again plagued by mass unemployment. Again there is a

major region that is economically devastated and that desperately needs

access to the world market, and yet again the other wealthier nations

hinder that entry, while concentrating shortsightedly on their own

problems at home, and neglecting the consequences of neglect. The West

might want to reduce the risk of a Russian disaster, but not at the

cost of jobs at home. Trade barriers are there to keep cheap Eastern

products from “flooding” its home market. Europe throws in huge

subsidies for its agricultural exports. Western tariffs or quality

requirements are pitted against Eastern exchange rates, in a war on

trade whatever its consequences on economic and political stability.

The West is dugging in and seems to repress the recognition that

history is repeating itself. Again the world finds itself in a

deadlock, and yet again chaos feeds on it.

But we should remember the trade war of the 1930s and the rise to power

of Adolf Hitler ! In the 1930s the same mechanism of trade,

unemployment and political instability applied. In this period it was

Germany that was the weak nation. The Versailles Treaty of 1919 that

ended World War I put Germany under a huge reparations bill. The world

forgot that the war had been started by an autocratic Kaiser and that

Germany now had a new, fidging democracy. To pay that bill, this weak

democracy was obliged to cut imports and to spur exports. The

reparations bill worked like a foreign tariff that took away funds that

could have been invested otherwise. By the end of the 1920s Germany

defaulted on its international debt - and thereby indirectly caused the

Wall Street Crash of 1929. Thereafter, all nations scrambled for the

life-boats. Nations feared for their home markets and employment, and

defended themselves by exchange rates and tariffs. In their fear they

made things only worse. The German economy collapsed, and on the

teutonic waves of resentment its weak democracy toppled and Hitler took

power.

Let us now compare: Is the Russian democracy anything other than new

and fidging ? Have its generals not tried to seize power ? Have its

tanks not roared against its very own Parliament building ? Has its

economy not dropped by a third? Or conversely, have all its nuclear

weapons and uranium stores been savely secured ? Have the Western

nations done their utmost in opening their markets ?

Risk not chance

Of course, there is a glimmer of hope. The Russian capacity for

suffering is impressive. Few nations could sustain this suffering and

national disgrace without lapsing into resentment, cruelty and violence

on a much larger scale than we actually see in Russia. The West has

provided some funds and done something more. The world is not at war

and may not be at war for some time. The probability that things go

right is large, and there is only a small chance that things go wrong.

But please consider: If the only glimmer of hope is that _the world is

not at war,_ then the situation is quite depressing. Hope is not the

point, and neither likelihood nor expectation. The point is risk. Risk

comes from the arithmetic of loss multiplied by chance. Thus: risk =

loss * chance. If things go wrong in Russia then the consequences will

be huge, and a small chance _times _a huge loss gives _a risk too

large_.

Internal not external

The West should open its eyes and see the economic logic. Eastern

nations need to take part in the international economy and thus need

modern Western equipment. To buy the latter goods they need the proper

currency. Either someone _gives_ them that foreign currency, the

dollars, yen or marks, or they have to _earn_ it themselves by

exporting. To simply give them credit, on the scale required, is

absurd. Therefor it is access to Western markets that is essential for

those nations and for political stability. Indeed, if they had access,

and if the flow of trade were to start, then the World Bank and IMF

could extend credits and thereby fuel the process towards stability.

At the same time, economic science tells us that it is not trade that

has caused present Western unemployment. Marking trade down as the

culprit, and using trade barriers to solve a situation that trade has

not caused, only makes things worse.

The moral problem is internal and not external. The cause of

present-day unemployment in Western economies is internal management

and not external trade. There is a failure within the internal

co-ordination of macro-economic policy, a failure by our very own

governments. Western nations could tackle their unemployment problem at

home - if only our political leaders were willing to take a hard look

at their own internal policies.

The historic parallel also concerns the current lack of attention for

the internal question. Policy makers that concentrate on an external

trade war neglect the internal opportunities. There is the following

sobering story about the economist John Maynard Keynes. From the early

1930s Keynes advanced his solutions to the Great Depression, and this

culminated in his 1936 book that changed macro-economics. Policymakers

could have reacted already in the early 1930s, ... but only did so

after World War II had already begun.

Conclusion

We might ask: Do we care about the peoples of Russia and the Eastern

nations ? And should we act with economic sense ? However, those

questions are imprecise. The real question is whether our leaders care

so much that they will reschedule their busy agenda’s and really look

into a problem that they cause themselves.

There is every reason to believe that political leaders are quite deaf

on this. So pray that there will not be a new world war. So shout to

your political leaders: Stop that trade war !

Do something about external trade tariffs and internal unemployment.

Enable Russia to help itself.

(March 1996)

17. Will the West repeat Versailles ?

Asia and the Eastern European nations are in a state of economic

turmoil. An important element for improvement is that Western nations

open their markets to more trade. This is in fact what the West could

have done after the fall of the Berlin Wall. But petty shortsightedness

of the governing elites in the West blocks this kind of solution. The

situation reminds one of the Versailles peace conference after World

War I that fostered a lot of resentment and helped cause World War II.

The basis conclusion is that sound economic advice is not listened to.

The best advice on how to steer out of the current world macro-economic

mess is that every parliament installs a committee to enquire into the

process of economic advice. They could study the books by Paul Krugman,

and possibly also my analysis on unemployment and my suggestion for an

Economic Supreme Court.

Western nations show an inadequate reaction towards the Eastern nations

since the fall of the Berlin Wall, and this inadequate reaction is

repeated with respect to the current economic throes of Asia. The West

displays disinterest in the hardship and actual physical pain inflicted

on millions of our fellow human beings, and a neglect of the long run

effects of this egotistic behaviour. Part of this inadequate reaction

however is also caused by wrong applications of economic theory, so

that true compassion that is out there doesn’t get the chance to show

itself. One lesson is that Western nations are advised to restructure

their policy making process so that governments are better served with

proper economic advice.

The negligent way that the Western nations treat the other nations

reminds one of the Versailles peace conference after World War I.

Historians agree about the sad Western attitude at the Versailles

conference. The Western Allies humilated Germany and subjected that

country to decennia of economic hardship, purposely crippling its

economy. These events caused a huge resentment in Germany, and this

fostered the rise of Adolf Hitler. Also, Germany’s defaults on its

financial obligations were a major cause for the 1929 Crash and the

subsequent Great Depression. This episode is another example that two

wrongs don’t necessarily make a right, and it also shows how wrongs can

backlash at the wrong-do-er.

The lesson of Versailles is that opponents can often best be allowed to

grow into a relationship of companionship and economic competition and

co-operation for the betterment of all. Rather than subdue them or take

advantage of temporary weaknesses, they could be helped so that they

could help us. This lesson should now be applied to the current

situations of Asia and Russia.

It is useful to recall that Western nations were not without proper

advice at the time of Versailles. They were warned, and by nobody less

than J.M. Keynes. As Paul Krugman recently stated about Keynes: “After

that war he became famous as the author of _The Economic Consequences

of the Peace_, an eloquent condemnation of the vindictive terms imposed

on the defeated Germans; his concern was vindicated by the rise of

Adolf Hitler, and the memory of his warnings helped convince a

victorious America to aid, not punish, its prostrate enemies after

World War II.”

Indeed, after World War II the Allies helped Germany and Japan to

reorganise their countries and to prosper again. While the average

citizen may be deluded by sentiments of nationalism, religion or

ideology, it normally is a governing elite that abuses those sentiments

for purposes of its own grandeur - and once a decent government is in

place, there often appears little reason to blame that average citizen

for the errors of its country. In the same way post-communist Russia

deserves our sympathy, and the same holds for Asia with its different

history.

But why has the West forgotten this valuable lesson ? Why do Western

governments neglect Nobel Prize winner Jan Tinbergen’s work on the

Optimal Economic Order, and why do we again have a show of petty

egotism and shortsightedness ?

The reason is that the West is not immune to the same ‘governing elite’

processes that can be at the detriment of common welfare. The governing

elites and bureacracies in the West have agenda’s of their own, and

though they are restrained by democratic rules, these rules are not as

strong as they could be. Our systems of checks and balances are a

product of history, and not necessarily of the quality required.

Politicians and bureaucrats often still can lie and get away with it.

The United States e.g. had David Stockman on the budget deficit, and it

took too long before that matter was settled. In general, sound

economic advice still is obstructed by political processes, and

policies and the electorate itself then grow misguided in their

choices.

To better understand the failure of Western democracies on the issue of

economic advice, one can best start by reading Paul Krugman’s books

“The Age of Diminished Expectations” (1990), “Peddling prosperity”

(1994), “Pop Internationalism” (1996), and “The accidental theorist”

(1997). For example, when Krugman discusses US majority leader Armey’s

book “The Freedom Revolution”, he states: “Armey is no fool. He cannot

be unaware that he is fudging his numbers. Possibly he regards a small

fib as justifiable in the service of a higher truth. Or possibly he has

managed to achieve a state of doublethink, in which the distinction

between what is politically convenient to believe and the objective

facts no longer exists [sic]. The end result is the same: His book is

an effort to obscure the stark realities (…)” (1997:60). Similarly, one

can read in the American Economic Review that the US Council of

Economic Advisers is rather proud of its achievements in the last

decades, but we should be aware that this council is a bureaucratic

body, and it hasn’t the independent position that could have protected

the US economy from the events and errors as are related by Krugman in

his “Peddling prosperty” saga or shown by the record of mass

unemployment.

Let us now regard what the West could have done with regards to Russia

after the fall of the Berlin Wall and the first free elections there -

and what could be done now also with respect to Asia. I take my own

1996 paper “Enable Russia to help itself”, and quote from its summary:

“Western nations in the 1990s hinder trade with Russia and the Eastern

nations for fear of unemployment at home, as they did in the 1930s with

Germany. If trade were stimulated instead of hindered, Russia could

regain economic and political stability by itself. The moral problem is

not external and does not concern whether Russia would need financial

aid. The moral problem is internal, and concerns whether Western

political leaders are willing to face their own errors that cause the

present mass unemployment at home.”

Clearly, with this being the state of affairs, one can imagine the

strength of the forces that prevent a proper discussion of these

issues. Western companies embrace tariff barriers to cheap imports -

and raise their own prices. Bureaucrats embrace barriers since these

give a sense of control, and these also justify the very existence of

this bureaucracy. Labour unions will fight unemployment at home with

whatever misguided argument it takes. Governments embrace economic

tales about ‘globalisation’ and ‘competition from cheap labour

countries’ since these distract attention from home grown errors, and

these goverments neglect economists who tell them that ‘globalisation’

and ‘competition from cheap labour countries’ are rather like fairy

tales indeed. Krugman again uses the term ‘globaloney’ - and have you

heard your President or Prime Minister adopting that critical attitude

too ?

The best economic advice for the current situation is as follows - and

I urge upon my fellow economists to adopt and spread that advice too_:

Every parliament could install a committee that will enquire into the

process of economic advice._ This committee could study Krugman’s books

and my suggestions for a solution of mass unemployment and for an

Economic Surpreme Court amendment to the national constitution(s).

Nothing less will do. Note, by the way, that when countries start

installing these committees, the markets will be quick to anticipate

the directions of their conclusions, and economic recovery would

already set in.

We all know Lincoln’s words: “You can fool all of the people some of

the time, and you can fool some of the people all of the time, but you

cannot fool all of the people all of the time.” Let us act upon it, or

show Lincoln wrong. (August 1998)

Notes in 1999: (1) A 1999 UNDP report describes the Eastern European

situation as disastrous, and calls for a quick joining up to the EU (De

Volkskrant October 16 1999). It is courageous that an international

body speaks up like this - and it indicates the seriousness of the

situation. (2) The journalist Peter Michielsen in NRC-Handelsblad

October 30 1999 rightly calls attention to the original borders between

the empires of Rome and Byzantium. The Eastern European countries that

are doing relatively well belong to the Roman area, the others to

Byzantium. He mentions that this cultural distinction has also been

noted by Andreas Oplatka of the Neue Zürcher Zeitung 1994, who again

refers to George Kennan in 1945. I was a bit surprised by this, hadn’t

thought about it in this way. (3) These points however nicely fit what

I have been argueing for ten years now. Enabling people to help

themselves starts with taking account of the local conditions; and

overall the barriers to trade should go.

Book V

Methodology: Definition & Reality

18. How to check ?

At the Dutch Central Planning Bureau, I helped making the Athena model

(CPB (1990)) with its 7000 variables. I had this model at my computer

and could let it do tricks like an obedient dog. But a proposal to an

exercise effectively like the above was rejected by the directorate,

and nowadays I am no longer in the position to make such proposals. The

desktop computer that I have now, in 2004, might have more power than

the 1990 mainframe, but I don’t have the data, the programs, and the

possibility of discussion with colleagues. I have Word for Windows,

_Mathematica_, some crucial books, an occasional visit to the Dutch

Royal Library, and the internet (at low speed). Moreover, I have to

make a living, in a different kind of job, and my time constraints thus

are severe. This explains why I am forced to a logical argument - and

this explains again why I emphasise logic anyhow.

Thus, crucially: it is up to the fellow economists to check my

findings. They / you should actually do this anyhow, since a critical

perspective always is best. For example: What are the data on the

minimum wages in the other OECD countries ? OK, the OECD internet site

shows that 1997 statutory minimum wage is 39% of median wages incl.

overtime in the USA, 60% in France, 30% in Japan, etcetera, quite

sizable

[53] - but what about the tax void, the development, the indexation,

the discouraged workers below the minimum, etcetera ?

[54] What about the shifts of the Phillipscurves in this light ? What

about the effects of the dynamic marginal rate ? How are these topics

in _all_ nations ? And what would happen, if all nations gain

confidence about growth policies again, and they fire up each other and

move all to a new higher growth path ? Clearly, the research agenda is

huge.

The situation since 1989-1991 has been a bit like this: Me stating that

unemployment has been solved (analytically) and inviting the fellow

colleagues to check it - and nothing further happening. This book

should make a difference in that I collect the various articles that I

have been able to write since then. When others see the whole route

then they will also better see the crucial junction where to take the

other turn.

This may also concern the novel contribution to methodology below. [55]

19. Dealing economically with concepts

Maximising information power

Methodology may be seen as _‘economics applied to science’_. The

_methodology of economics_ is the fixed point in that construct - even

economic methodology in the traditional form as presented by Tintner

(1968).

The ‘basic economic problem in science’ is - in my perception or

definition - that some set of concepts can better deal with the data

than another set. New ideas are like manna from the sky, but the manna

must be collected, stored, compared to the older findings, etcetera,

and an optimum must be found, using scarce resources over alternative

ends. This ‘basic economic problem in science’ thus is quite different

from the ‘mundane (non-basic) economics’ that, say, 5% more truth can

be traded against 10% more effort and cost.

The mind has the economic problem of dealing effectively and

efficiently with (i) old concepts, (ii) new information and (iii) the

construction of new concepts. The name of the game is to have concepts

or definitions fit reality as usefully as possible. The definitions

must be chosen as strong as possible, so that uncertainty can be

shifted to observation (and the problems with observation).

The human mind seems to be occupied with reduction of cognitive

dissonance - or, at least, that is a fruitful way to look at that mind.

Here I follow Aronson (1992a&b), who provides a definition of cognitive

dissonance, and data and tests that lend empirical support for it. It

appears that a commonly used method of reduction of cognitive

dissonance consists of the rejection of new information to the

advantage of older views. Frequently the messenger is blamed for the

bad message, and even, after the messenger has been punished, the bad

news is neglected since it came from an unreliable source - namely a

person who had to be punished (while it is forgotten that, if the news

is considered irrelevant, then there was no base for punishment). Man

is a rather prejudiced creature, and thus not so effective and

efficient at information handling - but man has to handle new

information.

Barrow (1998:4) [56] provides us with a useful quote:

“This unifying inclination of ours is a by-product of an important

aspect of our intelligence. Indeed, it is one of the defining

characteristics of our level of self-reflective intelligence. It allows

us to organize knowledge into categories: to know vast numbers of thing

by knowing rules and laws which apply in an infinite number of

circumstances. We do not need to remember what the sum of every

possible pair of numbers is: we need know only the principle of

addition. The ability to seek and find common factors behind

superficially dissimilar things is a prerequisite for memory and for

learning from experience (rather than merely by experience). (…)

All human experience is associated with some form of editing of the

full account of reality (‘we cannot bear too much reality’). Our senses

prune the amount of information on offer. Our eyes are sensitive to a

very narrow range of frequencies of light, our ears to a particular

domain of sound levels and frequencies. If we gathered every last

quantum of information about the world that impinged upon our senses

they would be overwhelmed. Scarce genetic resources would be lopsidedly

concentrated in information-gatherers at the expense of organs which

could exploit a smaller quantity of information in order to escape from

predators or to prey on sources of food. Complete environmental

information would be like having a one-to-one scale map. For a map to

be useful it must encapsulate and summarize the most important aspects

of the terrain: it must compress information into abbreviated forms.

Brains must be able to perform these abbreviations. This also requires

an environment that is simple enough and displays enough order, to make

this encapsulation possible over some dimensions of time and space.

Our minds do not merely gather information; they edit it and seek

particular types of correlation. They have become efficient at

extracting patterns in collections of information. When a pattern is

recognized it enables the whole picture to be replaced by a briefer

summary form which can be retrieved when required. These inclinations

are helpful to us and expand our mental powers. We can retrieve the

partial picture at other times and in different circumstances, imagine

variations to it, extrapolate it, or just forget it. Often, great

scientific achievements will be examples of one extraordinary

individual’s ability to reduce a complex mass of information to a

single pattern. Nor does this inclination to abbreviate stop at the

door of the laboratory. Beyond the scientific realm we might understand

our penchant for religious and mystical explanations of experience as

another application of this faculty for editing reality down fo a few

single principles which make it seem under control. All this gives rise

to dichotomies. Our greatest scientific achievements spring from the

most insightful and elegant reductions of the superficial complexities

of Nature to reveal their underlying simplicities, while our greatest

blunders often arise from the oversimplification of aspects of reality

that subsequently prove to be far more complex than we realized.”

This human property should be used in economics to explain actual

events. Colignatus (1996d) for example applies Aronson’s findings in

social psychology to economics, trying to indicate the actual ‘forces’.

Another application is the very analysis in this book, for example

where we stated earlier:

“If the government on the one hand would desire to use the results of

scientific advice for its budget process, and on the other hand would

not opt for an Economic Supreme Court, then its _definitions _would be

logically inconsistent, and it would thereby tend to create a cause for

dishonesty and improper manoeuvreing and thereby corrupt its

processes.” (above)

While the above relies on structural models, the property can also be

modeled in the reduced form. Chapter 40 uses information indicator _I_

{0, 1}.

Another application is to the methodology of science. Methodology

should harness this human property, and clarify when it is useful and

when it is misleading.

Science aspires at a more unbiased approach. This unbiased approach

also means the deliberate creation of cognitive dissonance, by creating

new concepts and by looking hard at the evidence till it doesn’t go

away anymore.

The evolution of knowledge can be described in terms of an ever

increasing power in the concepts used.

The introduction of a new definition is not simple. The questions

always are: does the definition cover the facts as we know them, does

the definition not introduce hidden aspects that cause confusion and

prevent advancement ? If a new definition wins out, it is, apparently,

only so because it is believed to have passed the test. Though, we

should be critical of this assumption. Only if the environment is

‘critical’, then we might presume a ‘survival of the fittest’ for

concepts. (And all this is reminiscent of Dawkins’s ‘memes’.)

Definitions can be devious in quite vulgar ways. In the English

economics literature, ‘perfect competition’ is defined as the situation

when no agent can affect the price, i.e. all agents are price takers.

The Dutch word for this case is ‘full competition’. The English

definition forces English economists to use the word ‘imperfection’ for

all other cases. Even quite reasonable cases, in the normal state of

human life, when agents have market power but balance at some social

optimum, would be ‘imperfect’. Also a natural monopoly would be an

imperfection - even if one could not conceive the situation differently

since the monopoly is a natural one. It would be better if the English

economists would adopt the Dutch definition, so that the words

‘perfect’ and ‘imperfect’ could be used in their proper sense depending

upon circumstance. This is just a vulgar example of how definitions can

lead one astray.

The competition of alternative concepts can be quite sophisticated

however. Let us illustrate this with three examples. The most

illuminating example may well be Pythagoras’s theorem and its relation

to the circle. This problem concerns mathematics, so that the

discussion is less taxed by semantics and empirical matters - though

there is of course the theory about empirical space. The second example

of ‘falsification’ is surely in the realm of empirics. The third

example concerns the distinction between determinism and volition.

Pythagoras and the circle

Regard a triangle with perpendicular sides _a _and _b _and hypotenuse

_c. _There are two points of view:

1. Pythagoras proved [57] that the square of the hypotenuse

equals the sum of squares of the perpendicular sides, i.e. that _a2 +

b2 = c2_

2. For the circle, it is taken as the defining quality of the

circle, and thus accepted without proof, that the points are at equal

distances from the origin. In other words, a circle with radius _c _is

defined as the collection of points (_a, b_) at a distance of _c _from

the center. Thus _a2 + b2 = c2 _by definition.

The two points of view are presented in Figure 16. The definition of

the circle can be taken for granted, since it is just a definition. On

the other hand, it will be very useful to discuss the proof of the

Pythagoras theorem, since then we see the_ need_ for a proof.

Let us take the square with sides _z = a + b _and surface _z * z = z2

= _(_a + b_)_2. _ Within this square we can see four triangles with

straight sides _a _and _b _and hypotenuse _c, _as has been done in

Figure 16 in the square on the left.

In the square, another tilted square has been drawn, with sides _c _and

thus a surface of _c2_. There are four surrounding triangles, each

triangle has a surface of ½ _a*b. _The surface of the large square is

equal to the surface of the tilted square and the four triangles.

Figure 16: Pythagoras and the circle

__

Thus:

· From the big square itself: _z2 = _(_a + b_)_2_

· From the tilted square and the triangles: _z2 = c2 + 4 ab/2._

Elimination of _z _then gives _a2 + b2 = c2. _

This proof has been taken from DeLong (1971), and he remarks that

Pythagoras proved it differently.

How do we explain that one and the same equation can have two

interpretations that are so widely different, one with the need for

complicated proof and the other with direct acceptance by definition ?

There may be other explanations, but I think the following will do

fine. Note that the definition of the circle relies on the notion of

‘distance’. There are two points of view again, so that point 2 above

actually splits in two parts:

2A) Basically the (Euclidian) distance between two points can be

measured by a straight line section. That is rather simple, and makes

for a readily acceptable definition of a circle.

2B) However, in a system of co-ordinates, that distance can be

reinterpreted in a representation in terms of the co-ordinates. There

are two possibilities again. Either the distance can be defined as

simply the formula _dist_[{_x, y_}, {_a, b_}]

((_x -_ _a_)_2 + _(_y - b_)_2 _) with {_x, y_} the origin - above {x,

y} = {0, 0} - or it can be defined geometrically as the hypotenuse of

the differences of the co-ordinates. If either definition is accepted,

then one can use Pythagoras’s theorem to derive the other.

The essential difference between (2A) and (2B) is that (2A) is

elementary and poor in concepts and results, while (2B) is complexer

and rich in concepts and results. Viewpoint (2A) only allows us to use

measuring rods between arbitrary points and little else. We are allowed

to sweep the rod around the center, and thereby draw the circle, but

then it somehow stops. Viewpoint (2B) allows us to do much more. A line

between two points is interpreted in terms of a system of co-ordinates,

and that opens the scope for new results.

We find that the opposition of (1) against (2) is rather messy, and (2)

actually hides two suppositions. The ease of (2) depends directly upon

the ease of (2A), while (1) actually compares with (2B) that is

complexer. The phrase “In other words” in (2) above thus was

misleading, and actually represents the introduction of another

assumption.

With this clarified, we also note that (2) is stronger than (1), and

that it was possible to seduce the human mind to accept (2) rather

easily. There has been a progression in concepts, resulting in stronger

definitions.

Note that behind all this there is a notion of empirical space. In (1)

there is a hidden assumption of a flat space. In (2B) the assumption is

made explicit, and then open to amendments (curved surfaces, or

abstract spaces). The movement of (1) to (2) thus is, partly, (a) the

advancement in concepts by means of the definition of distance (and the

circle as a collection of equal distance points), (b) the introduction

of the separate step of observation - with the difficulties: when does

the definition apply to reality, or if there is some reality, how do I

select the proper definition ?

The point that is relevant for this book then is: that the definition

is so good, that it in practice substitutes for many everyday empirical

problems. A criterion for a good definition is: that it can be such a

substitute.

When a definition is a close substitute for reality, then it may

percolate into common culture with more authority. For example: every

citizen can establish the existence of a tax void and Pareto

suboptiomal unemployment purely from the logic of the level of gross

minimum wages and the official tax statutes - and we don’t need big

computers or official bureaus to do some econometrics and then tell us.

Admittedly, there is danger in _seductive_ _and seemingly right_ but

_wrong_ definitions. If ‘child’ is defined as ‘irresponsible young

human’, then we may be tempted to treat children as such and forget to

expect the responsibility that they can handle. But the existence of

this danger should not make us close our eyes to the advantages of good

definitions.

A side issue concerns our concept of ‘space’. Let us first consider an

example of cultural relativism. It appears that different human

cultures can have different approaches to one’s orientation in space,

and that these approaches are wired into the languages used. [58]

Taking a point of reference can be done in three ways: (1) Relative:

taking one-self (“the tree is to the left of the house” - seen by me);

(2) Absolute: taking the sun (“the tree is to the west of the house”);

(3) Intrinsic: taking one of the objects (“the tree is to the back of

the house”). If someone is asked to copy a situation in front of him

towards a place in the back of him, then there will be a different

‘copy’ depending upon one’s language/culture. If you have a cup of

coffee and a pencil in front of you, pick them up, turn yourself

around, and recreate the scene, then a Westerner will use relative

positions, while an Australian Aboriginal will use absolute positions

(and turn the relative positions around). The question now is: while

this only concerns the point of reference, can we imagine something

similar that affects our concept of space itself ?

I take the position that the human mind apparently is able to

conceptualise Euclidean space - and that this actually _defines_ our

concept of space. If we take a non-Euclidean geometry - such as a globe

- then this still can be imagined to exist within Euclidean space.

Pythagoras’s theorem is invalid for triangles drawn on a globe, but to

hold that space is a globe would be erroneous - since our definition of

space would be Euclidean.

One of the questions often posed is whether the universe - interstellar

space - is Euclidean or not. This is a badly posed question. If we

define space as Euclidean, then it is another question whether a ray of

light follows a straight line or is deflected by gravity.

Barrow (1998:p42-44) provides a troubling quote: [59]

“The most important consequence of the success of Euclidean geometry

was that it was believed to describe how the world was. It was neither

an approximation nor a human construct. It was part of the absolute

truth about things. (…) This confidence was suddenly undermined.

Mathematicians discovered that Euclid’s geometry of flat surfaces was

not the one and only logically consistent geometry. (…) None had the

status of absolute truth. Each was appropriate for describing

measurements on a different type of surface, which may or may not exist

in reality. With this, the philosophical status of Euclidean geometry

was undermined. It could no longer be exhibited as an example of our

grasp of absolute truth. (…) These discoveries revealed the difference

between mathematics and science.”

This quote is troubling for the following reasons:

1. If we define ‘space’ as Euclidean, then it is an absolute

truth. This definition seems to maximise our information power. Other

surfaces can be imagined within that space.

2. One might think of ‘empirical space’ as something that must be

measured. The idea is: ‘If it cannot be measured, then it is not

relevant.’ OK, this seems fine in principle. But if a physicist would

use ‘light’ as a measuring rod, then this is asking for problems.

Namely, Euclidean geometry already provides us with our system of

measurement. Defining ‘empirical space’ differently would conflict

with our original definitional grasp of space. Better is: to stick to

the definition, and regard measurements that deviate - e.g. from

gravitational deflection - as the physical properties of the objects

and measurement tools involved.

3. That there is a difference between mathematics and science

does not disqualify the notion of absolute truth. A true deductive

sequence ‘Assumption Conclusion’ has absolute truth. And it should be

realised that scientific theories are mathematical (with the scientist

working on an assumption).

4. It is possible to translate the Dutch ‘lijn’ as ‘point’, and

‘punt’ as ‘line’ (thus conversely) and still find a consistent model

for Euclid’s axioms. But this is a mathematical exercise, and it does

not necessarily have to do with ‘space’.

So it seems that Barrow and I agree for 99%, but still, the 1%

difference features big in some dimension. Note that the discussion

here concerns more a side issue, but it remains useful to indicate the

deeper aspects of Pythagoras’s theorem.

Falsification

The ‘principle of falsification’ is that hypotheses are only scientific

if they are formulated such that they are vulnerable to empirical

testing, and might be falsified. It has been formulated by Popper, see

Keuzenkamp (1994).

The principle has two disadvantages: (1) purely logical, (2)

stochastically.

(ad 1) Take logic first.

Counterargument 1. Regard the statement _All ravens are black_. This

statement will be false when one finds a non-black, say white, raven.

So the statement would be an acceptable scientific hypothesis, since

falsification is possible in principle. But, as the falsificationist

would hold, it would remain a hypothesis, and we should be aware of the

fact that is only a hypothesis, until it had been checked for all

ravens (Tintner (1968:12)). This falsificationist view however is

problematic, since most of us will sense that there is truth in _All

ravens are black_, for example by our definition of a raven.

Counterargument 2. In the extreme, all scientific knowledge would

consist of instances of falsification. It has been falsified that the

Earth is flat, that atoms cannot be broken, that ... But the principle

itself, i.e. that ‘all scientific knowledge would consist of instances

of falsification’, is a definition and is not open to falsification.

While falsification may be a successful research strategy in many

cases, it does not seem to be a fully satisfactory way of organising

science, at least from these two points of logic.

(ad 2) Take stochastics next. Let us regard the typical modelling

situation:

The model:

Estimation:

Observation _X_[+1] forecasts:

Final observation:

_y = X ß +_

_y = X b + e_

_yest_[+1]_ = X_[+1]_ b + _Exp[_e_[+1]]

_y_[+1]

The question now is whether this new observation can falsify the

hypothesis of the empirical estimate. This question is not as simple as

the naive falsificationist first had in mind. The principle of

falsification is formulated as for deterministic reality, while many

empirical models are stochastic. In stochastics, there may be

deviations, and sometimes large ones. There are problems of measurement

in _y _and _X, _the choice of the functional relationship, missing

variables, and the choice of the stochastic specification itself.

One useful empirical answer is optimal control, with the example of a

rocket launched to the moon, where there is continuous adjustment to

observed error (‘falsification‘). This control only works well when

there is a proper definition of the loss function. The issue of the

loss function is a crucial one, but this is not falsificationism.

Logic and stochastics cause me to take the following position.

There is a difference between _all1 _ (universal) and _all2

_(generally, usually, normally). The statement _All ravens are black_

can be seen as:

1. a definition. It then holds universally. Empirical truth then is

conditioned to the logical tautology of the definition that we have

chosen. If we find a white bird that looks like a raven, it cannot be a

raven. (But we think that this definition covers reality, for example

since we have some ideas about genetics and evolution.)

2. an empirical statement - grounded in a stochastic model. It is

shorthand for _All ravenlike birds tend to be rather black_ or whatever

the professional might deem correct. The meaning of such statements is

more subject to context than in the case of well-groomed definitions.

The human mind thus faces the choice: To adopt a definition and run the

risk that this does not fit reality so well, or to adopt a statement on

averages and work out more details of the empirical loss function.

Decisions on such statements thus are sensitive to the loss function,

but the second category requires more detail.

This of course does not solve everything. The distinction of these two

dimensions or perspectives is not like solving all problems in their

domains. Also a definition like _All ravens are black by definition_

does not answer the question whether a particular object is a raven or

is black. Is a size of 10 kilometers acceptable ? Did we look in

daytime or at night ? Must it be alive, and then, what is life ? So the

distinction between definitions and empirical statements is useful, but

it does not solve all problems. The point is not quite that one can

always adjust definitions, but rather that a definition is not reality

by itself. (Though it can get close.)

At one point in history, scientists were willing to accept the periodic

system of elements to catalogue the wide variety of materials around

us. There was apparently little loss involved in accepting these

definitions, or Lavoisier’s periodic table was more gainful than other

catalogs. The definitions did not change the materials, but facilitated

more efficient research. At one point in history, see Mirowski (1989),

economists were willing to analyse human behaviour in terms of utility

maximisation. The approach is an empty box, since any behaviour can be

described as such. For example satisficing behaviour can be represented

as minimising the distance from satisfaction. Also in ‘evolutionary

economics’ the utility maximisation model can be applied though these

researchers are critical of this approach. (While, curiously, Charles

Darwin was inspired, amongst others, by Adam Smith.) The new approach

for laboratory experiments makes us even more critical about the

rationality hypothesis. Utility maximisation however helps organising

one’s thoughts, helps professional discussion, facilitates modelling

and empirical estimation, and is generally considered an advance above

less explicit approaches.

As with the Pythagoras example, but now empirically, there is a switch

from just empirical knowledge to a set of definitions, when the loss

function allows it.

Kuhn (1962) describes major changes as ‘paradigm switches’ (though

someone noted that he used that word in perhaps 40 ways). I rather draw

attention to the change from empirical knowledge to definition. This

change need not be a paradigm switch. Paradigm switches may be the most

intriguing or flashy examples of the introduction of new definitions,

but the change from empirical knowledge to definition does also occur

in ‘normal science’.

Determinism and free will

Holland around 1600 had the theological argument between Gomarus who

defended predestination and Arminius who defended a measure of

volition. This discussion had started before them, didn’t end with

them, and continues till this day, also in these pages.

The 20th century gave a novel twist to the argument, namely quantum

mechanics. Instead of the folly of the gods, there now is a randomizer

with a scientific garb. If objects, and the molecules in our brains,

have random aspects, then this would be neither determinism nor

volition. Quantum mechanics normally is applied at the micro level of

particles, and there is the suggestion that larger aggregations of

masses still would behave in the Newton-Einstein fashion. Schrödinger

however gave an example - his cat - how quantum mechanics could also

extend into this macro world. So the challenge to the debate on

predestination is real. [60]

The quantum model is stochastic of itself. This differs from the

randomness caused by simple measurement errors - the randomness

commonly used in economics. However, economics has some purely

stochastic models of itself too. There is for example the Erlang

queueing model. Consider a postoffice with clients arriving and being

served. Interarrival and service times can be modeled with exponential

distributions, and this allows us to determine the average length of

the queue, the average waiting time, the average utilisation rate of

the service window, and such. If the situation gets more complicated,

then research economists use computer simulation models to find the

best way of operation. This example shows that economics already is

familiar with a model that is stochastic in itself. Note that there are

some ways to re-introduce a degree of determinism - as your barbershop

may require you to make an appointment. The basic observation that we

make here is that the stochastic approach is basically a modeling

method, and there is no implication that arrival and service are

intrinsically random.

The discussion above introduces the various components, and the

question now becomes what to make of it all. The following gives my

solution.

First of all, science _by definition_ avoids the ‘deus ex machina’

assumption. An understanding of reality is looked for without reference

to a god. So our discussion is not burdened with the associations of

eternal damnation (and predestination to this).

Secondly, science _by definition_ aspires at a deterministic

understanding. Scientists may adopt a stochastic approach with only a

limited degree of accuracy, but the target remains a 100% accuracy -

which is determinism. Hence, by definition, scientists have a

deterministic predisposition.

[61]

[62]

Thirdly, the idea of a ‘free will’ is a moral category, differing from

physics. Admittedly, the scientific approach would presuppose that our

moral considerations depend on our brain, and the movements of

electrons and molecules that could be caught in a determistic model -

but the proper conclusion is that we don’t have that model yet. The

existence of time, and in particular the uncertain future, is a

precondition for morality. An ‘existence proof for God’ would be that

in the limit of time, prediction accuracy rises to 100% and all moral

beings are going to make the proper moral choices.

[63] But we don’t know for sure that those choices will be really moral

- and anyway it is hard to see how this could affect us. For example,

we may predict, as social scientists, that when economic conditions

worsen, that politicians then may be more inclined to morally dubious

choices. But we need the passing of time to determine whether this

prediction materialises - and, as human beings, we would still want to

form a moral opinion and discuss the moral aspects. The conceptual gap

between ‘ought’ and ‘is’ remains. Eventually there might be a practical

(non-conceptual) bridge, but for those same practical reasons it isn’t

there yet.

Though science does not refer to gods, we can use a god anyway for

clarification. Janus, the Roman god and name-giver to the month of

January, had two faces, one to the past and one to the future. Figure

17 uses the Janus head as an analogy to locate the various concepts.

Figure 17: Janus head analogy

Note: This only displays the three opposing concepts in one picture,

without implying that all concepts to the left are equal

or that all concepts to the right are equal.

The Janus head analogy works only up to some degree. We don’t know all

that happened in the past, we can use probability statements for the

past too, and thus we cannot replace ‘past’ with ‘certainty’.

Similarly, as said, science has a deterministic predisposition, so the

future basically is predetermined from a scientific point of view. Yet

the head analogy is useful, since it focusses our attention to these

various subtleties.

Thus, clearly, the Arminius and Gomarus debate can be seen as

non-sensical if they got the two categories of science and morality

confused. Even though we can have a deterministic predisposition, we

still can have moral volition (and be judged by jurors on making wrong

choices). Their debate would be proper in so far as Gomarus would take

predestination in a moral sense - but then the debate is not relevant

for us.

Thus, clearly, quantum mechanics drops out as a fundamental category.

It only remains as a research strategy in the face of apparent

difficulties, but it still is on the road to 100% accuracy.

Admittedly, quantum mechanics itself seems to pose that nature would

have random properties at the micro particle level. Some even argue

that this would be the basic example of _true probability_ - while all

other ‘examples of probability’ (like throwing dice) are basically

deterministic (and we only use probability techniques to make up for

our lack of knowledge or laziness in measurement). In particular,

Richard Gill, professor in mathematical statistics at Utrecht

university, gives this argument at a roundtable discussion:

“We should be collectively ashamed not to know anything about quantum

mechanics. I would like to see all introductory texts in probability

theory going a little into the physical (quantum) theory behind the

geiger counter before using some data of alpha particle counts as an

illustration of the Poisson process; I would like a discussion of the

Bell inequalities together with a modicum of quantum mechanical

background to show how elegant probabilistic reasoning shows that the

quantum world is truly random (unless you would like to go for an even

more weird non-local deterministic theory).” (1997b)

Indeed, also economists are familiar with the concept of Brownian

movement, or the random walk, and use this model for example in

analysis of the stock markets. Or in the labour market, with labour

supply _LS_ and employment _LE_, unemployment is _u_ = 1 - _LE/LS:_ but

_u _then basically is a probability, since the model does not provide

an additional explanation why one person works and the other doesn’t.

But Gill’s argument does not convince me. The point is: you may _pose_

that nature would be such, but you don’t know _for sure_. You are still

using only a model. The scientific challenge remains to develop a model

that increases accuracy.

Yes, there is the Heisenberg uncertainty model that if you measure

position then you no longer know speed, and if you measure speed then

you no longer know position: and this model nicely captures a basic

notion of uncertainty. But, try for a better model then - and take some

thousands years more to do so.

[64]

[65]

[66]

As a corollary, we can take a position on path-dependency (hysteresis)

and chaos.

Some authors use the word ‘chaos’ in the sense of path-dependency. For

example, a small variation in first conditions (starting point,

parameter) can cause a widely different result - a butterfly flapping a

wing can cause a tropical storm. Since we already have the term

‘path-dependency’ for this, we better reserve ‘chaos’ for the meaning

of ‘seemingly random’. A chaotic system, in this proper sense, then

gives a fully deterministic description, but the outward appearance

that some variables would be random. Here it is strange that people who

are in favor of ‘chaotic modeling’ also use this to be against

determinism.

Path-dependent and chaotic models can be useful. The orbit of Earth

around the sun looks solid, but over the billion years it seems pretty

random. There is Schrödinger’s cat model that shows the macro world

depending upon a micro state. There are the strange models in history

and biology, where for example a meteor wipes out dinosaurs. OK, all

these models exist, and they can be real good descriptions of true

states of nature. But all this does not disprove the definitory

deterministic predisposition of science. If you would run the movie

again from the start (which is currently said to be a Big Bang, but I

don’t know about that), then you would get, by the models that science

tries to develop, the same result. If you would argue that anything

else might pop up, and your mother could be a dinosaur with a pig’s

head, and if you would develop models that would show this, then you

are quite in danger of being out of science. (You would drop out on

this definition, but could be in on the other criteria.)

Concluding this section, we find that definitions indeed guide our

understanding of nature. The definition of science itself guides our

perceptions - for example when it guides us into taking quantum

mechanics as a model only instead of as ‘reality itself’.

A reason to be strict about this definition of science is that people,

who would argue that nature is basically random, would also tend to

reject deterministic results of science. A deterministic result of

science is for example (1) that divergent indexation of tax exemption

and the standard of living causes a tax void, and (2) that the

existence of a tax void can be used to ‘abolish taxes’ without costs.

It would be a pity if this result were to be rejected because of a

fundamentalist ‘random view of the world’.

From stylized fact to definition

Our subject is the political economy of western welfare states, and in

particular employment and inflation aspects. This subject is quite

complex, and we must be modest about our results. Of course we can use

statistics of the national accounts, and thus indirectly we use the

statistical labour of thousands of statisticians, and indirectly the

results of thousands of firms and of millions of citizens that filled

in their tax forms. Economic literature provides a wealth of models and

interpretations of these data. In my case, I also rely on my own

experience in constructing a national economic model. All this,

however, does not mean that we can forget about modesty, on the

contrary. Nevertheless, it is my conjecture that we can achieve a more

enduring result than just awareness of complexity.

What is interesting in economic discourse is the concept of ‘stylized

fact’. When an economist observes some regularity, he is rather

inclined to use that term. We shall use the term more conservatively,

and we are hesitant about observing regularities. But we also can

fruitfully employ the term when there is a regularity indeed. In some

cases, when the regularity is so strong that our loss function comes in

the epsilon zone, then we even can switch to definitions.

So we adopt the methodology:

(a) state what we consider to be the stylized facts

(b) define our concepts so that the stylized facts are covered by

definitions

(c) develop theorems and proofs

(d) link back to conclusions about reality.

A _ proposition - _as a statement on reality - can be regarded as a

mathematical theorem about/within a model of stylized facts. When there

is a tautology, we attain truth by definition.

We here deliberately refer to Bochenski (1956, 1970:20): “The word

‘proposition’ has been variously used, (...) nowadays commonly as the

objective content of a meaningful sentence”.

Some students of the History of Economic Thought will see a clear

resemblance of above methodology and what Schumpeter called the

“Ricardian vice”. Quoted by Tintner (1968:7):

“His interest was in the clear-cut result of direct, practical

significance. In order to get this he cut this general system to

pieces, bundled up as large parts as possible, and put them in cold

storage - so that as many things as possible could be frozen and

“given”. He then piled one simplifying assumption upon another, until,

having really settled everything by these assumptions, he was left with

only a few aggregative variables between which, giving these

assumptions, he set up simple, one-way relations so that, in the end,

the desired results emerged almost as tautologies.”

This is almost exactly what we shall do, except that we generate

tautologies.

Step (d) comes closest to the Popperian falsificationist criterion. Our

deductions need not be insulated against testing, even though this

present book abstains from econometric testing since we are too much

involved in creating our concepts and constructing consistent and

useful _propositions_. [67] Abolishing the Tax Void is a good and cheap

test anyway for the relevance of this analysis.

It is useful to keep Solow’s comment in mind:

“There is something deeply satisfying - not to say suspicious - about

any proposition that seems to deduce important assertions about the

real world from abstract principles.” (1976:148)

So, advisedly, the reader better checks what we are doing here, and

governments should run their own regressions and models before they

make policy decisions. But of course I only dare to present my results

here since I am confident that they, in the hands of competent and true

scientists, allow a real advancement.

Relating to Hicks 1983

In his essay “A discipline not a science” (1983:365-375), John Hicks

argues that economics is too far from the accuracy reached in the

material sciences, and explains that he cannot ‘altogether’ deny that

he himself has converged on a ‘critical’ attitude. This attitude

concentrates on the clarification of terms, i.e. their definitions,

also by using quite unrealistic models. For example: “Though the

concepts of economics (most of the basic concepts) are taken from

business practice, it is only when they have been clarified, and

criticised, by theory, that they can be made into reliable means of

communication.” (p372-3).

Hicks then concludes that economics is a Discipline. His quote of

Keynes (in II.7) above is taken from these pages. My position on this

is twofold - the position of hard science with soft data. On one hand I

embrace the critical attitude. Indeed, we should develop sound

definitions, and remain critical about how these are applied in

communication. That is the meaning of the Definition & Reality

methodology. And it brings us far, since we can advise to abolish the

Tax Void without running regressions and a computer model. On the other

hand, Tinbergen’s efforts have not been in vain, and models with

estimated coefficients are useful tools for policy analysis. For

example, some economists may reject the _existence _of a Phillipscurve,

and all economists should be critical about the data and the parameter

values, but such a _relationship _remains useful in a macromodel that

is used for evaluation of policy alternatives. It would be curious to

accept the concept of a ‘model’ and to accept other relationships like

a consumption function, and reject the use of a Phillipscurve: even

though the uncertainties are quite comparable.

In other words, our method remains econometrics, even though we end

here with an increased awareness of the role of definitions. We are

just in the phase that running regressions is useless if the model is

no good. Regressions come in only when we have a good candidate, and

regressions even might benefit from some definitory relationships. We

even would like to do those regressions ourselves if we had the data

and the time. So, for now, let us first develop what we conjecture to

be the proper model.

20. Structural and reduced form

There is the useful distinction between the structural and reduced

form:

· the structural form represents actual relations as good as possible,

· the reduced form gives the simplest representation, with the

interaction minimised.

With _y _a vector of endogenous variables, _x _a vector of exogenous

variables, and _f_ and _g_ functions, then a structural form is _y =

f(y, x) _and a reduced form is _y = g(x)._

Since econometrics can only approximate reality, the true structural

form can only be approximated. What we consider to be a structural form

is an intersubjective consensus. We anyhow have to adopt an

approximation, which means that many factors have been removed.

However, for two models we can often clearly see that one is simpler

than the other, and then we can usefully apply this distinction between

the structural and reduced form.

The distinction between structural and reduced form also affects the

structure of this book. The next chapters concern the structural form,

actually starting with the textbook IS-LM model. We relax the

assumption of homogeneous labour, and introduce heterogeneous labour.

First we look at labour supply only. Then we look at supply and demand,

and at the equilibrating dynamics, which causes the topic of the

Phillipscurve. We show how the Phillipscurve and the

Constant-Wage-Inflation Rate of Unemployment (CWIRU, a.k.a. NAIRU or

natural rate) shift as a consequence of minimum wages or poverty. We

then relate minimum wages and poverty to developments in taxation. The

co-ordination failure on taxes and minimum wages not only causes the

internal imbalance on the labour market, but also an external

imbalance, with international trade.

The discussion of the structural form results into the need for more

scientific clarity. Though much seems to depend upon empirical

parameters, some aspects however are more fundamental. This leads to

the discussion of the reduced form. We first develop a theorem on the

influence of taxation on employment and unemployment regimes in welfare

states. Since taxation depends upon social choice, we then discuss

Arrow’s theorem on social choice (structural form again). We also note

that there may be a confusion about inefficiency and the existence of a

‘free lunch’. Having established the possibility of rational social

choice, we then develop a theorem on stagnation in the policy making

process (reduced form again).

21. Direct application to the Economic Supreme Court

In chapter 8 we stated: “If the government on the one hand would desire

to use the results of scientific advice for its budget process, and on

the other hand would not opt for an Economic Supreme Court, then its

_definitions _would be logically inconsistent, and it would thereby

tend to create a cause for dishonesty and improper manoeuvreing and

thereby corrupt its processes.”

We can directly apply our Definition & Reality methodology. The point

is that desiring for a scientific base and not making a Court is

logically inconsistent. Parliament and President may _‘define’_ their

‘Council of Economic Advisers’ as ‘scientific’ but when there are

little safeguards, then _reality_ takes over, and the Council will _de

facto_ not have sufficient power to resist political meddling.

The appendices contain an example draft for a Constitutional Amendment

for an Economic Supreme Court and a description, taken from the White

House internet site, of the CEA. The difference should be clear.

Law-givers know: If a law does not fit logic and reality, then people

will see themselves forced to ‘break’ the law. “You are damned if you

do, and damned if you don’t.” People in such situations will tend to

grow dishonest, since it is often easier to massage events rather then

clearly state that the law is impossible and go on strike or whatever.

They don’t see it as ‘dishonest’, but as ‘flexible’. And once people

are on that road, they will rationalise their behaviour by thinking

that this is the way that the world works, and become more willing to

perform other acts of dishonesty.

Conversely, once sufficient safeguards are in place, then the Council

is _de facto_ an Economic Supreme Court (even if it does not have that

name). With a properly defined scientific base for the budgetary

process, economists could also more confidently predict the economy’s

course, since there would be less random noise and chaos about the

application of known knowledge.

22. Methodological summary

We consider all Western economies, or, more properly with Japan

included, the OECD area. Hence, the student of this book will expect

masses of OECD data, and masses of structural models of the OECD

countries, or at least a model for the whole OECD area. There is none

of that. We in fact use only some example data for the small country of

The Netherlands. Why is that ? And how can we possibly utter our

ambitious claims ? The answer to these questions is fourfold:

· there are mathematical theorems and proofs for the reduced form of a

typical welfare state

· we use some key properties that will be documented here

· this chapter on methodology explains the validity of the method

· for the data and structural models we refer to ‘existing economics’.

The approach of this book is to use logic in order to circumvent the

uncertainty of parameter estimates. Though the book doesn’t give full

statistics, it is conjectured that the theorems capture the stylized

facts. A_ proposition - _as a statement on reality - can be regarded as

a mathematical theorem about/within a model of stylized facts. When

there is a tautology, we attain truth by definition.

Our first proposition establishes conditions under which both

unemployment and full employment are possible. This relates to the

_partial _arguments of economists about the labour market. Our second

proposition gives the integral argument, or _general _theory, how (un-)

employment situations are managed. The employment regime can be chosen

by conscious choice, or there is lack of knowledge. Lack of knowledge

forks into two cases. With full employment, the situation is dubbed

‘chance’. With unemployment, it is called a co-ordination failure.

It is useful to state that our point of departure was not mathematical

economics itself. This book has been written against the backdrop of

the voluminous studies Central Planning Bureau (1992a&b) and Colignatus

(1992). It is from this experience that these two propositions have

been selected as being of foremost importance. We want to focus on main

mechanisms that block full employment and prosperous growth in modern

welfare states. It is thought that the two propositions, in a sense

simple but in another sense complex, help to clarify a fruitful

direction for both analysis and policy improvement.

To be sure: this approach does not imply a rejection of time series

econometrics ! I am an econometrician myself. Below I will e.g. develop

a definition of ‘risk’ that deals with uncertainties - and in my view

the 95% confidence interval should be replaced by an interval based on

a well specified loss function. So I am supportive of uncertainty

approaches. However, econometric models also contain definitions and

institutional equations, and it is my conjecture that these have not

gotten the attention required. In particular the regime switch of

1950-1970 to 1970-2005 will be difficult to determine by time series

methods. Studying marginal changes within a regime will not uncover

results about the switch. It would be wrong if time series analysts

would only accept time series as data, and not such regime states. The

Definition & Reality methodology then can help us out. [68]

Governments that become interested in the present analysis will no

doubt require that it is tested against the data of their own country.

This is advisable indeed. However, the claims of this book are

primarily mathematical certainties, and additional empirical data will

mainly provide didactic assurance. Since country parameters are

different, practical policy must rely on the structural models of

course, and data will be needed for detail decisions. But at an

abstract level, the developments would be similar.

Book VI

Structural models

Chapter 23 gives a textbook macro-economic model so that we better

appreciate the point of reference of ‘existing economics’. Chapter 24

clarifies heterogeneity and nonlinear taxation. There is nothing new

here yet either. The subsequent chapters then take up the same subject

matter, and gradually add elements and interpretations that support the

novel analysis.

23. A textbook macro-economic model

Our textbook model is a very simple and unpretentious first year

undergraduate model. It is not interesting for itself, but for our

later discussion.

The IS-LM model

We follow Dornbusch & Fischer (1994), chapters 1 - 4. The basic

macro-economic identity for annual real values is:

_C + G + I + NX YR YD + (RTAX - TRF) C + S + (RTAX - TRF)_

_C_ = consumption

_G_ = government consumption

_I_ = investment

(incl. unintended stocks)

_NX_ = exports minus imports

_YR_ = real gross domestic product

_YD_ = _YR - RTAX + TRF _= _C + S

_= disposable income

_TRF_ = government transfer payments [69]

_RTAX_ = real tax revenue

_DEF _=_ G + TRF - RTAX = S - I - NX

= _government deficit

_S _= saving [70]

We take _G, TRF_ and _NX_ as exogenous and known. We are now only

interested in expectational equilibrium. Aggregate demand is _YR* = C*

+ G + I* + NX. _ With the rate of interest _i _and the marginal tax

rate _r, _behavioural relations are:

_C* = TRF + c (YD* - TRF) + C0_

_I* = I0 - b i*_

_RTAX* = r YR*_

_ _

In equilibrium_ C = C* _gives _YR* = YR - _since _C = C*_ iff _YD =

YD* _iff _I* = S* = I = S. _This can be represented by the IS curve:

_YR = TRF + c (YD* - TRF) + C0 + G + I0 - b i + NX _

_ _

_i = _(_C0 + G + I0_ _+ NX + TRF - _(1 - (1 - _r_) _c_) _YR _) / _b_

(IS)

For the money and bond market:

_L + DB WN / P MX / P + SB_

_L_ = demand for real balances

_DB_ = demand for real bond holdings

_SB_ = real value of the supply of bonds

_WN_ = nominal financial wealth

_P_ = price level

_MX_ = money stock (_M1, M2 or M3_) [71]

Liquidity demand is:

_L = k _(1 _+ h / _(_i - imin_))_ YR_

_ _

Equilibrium on the money market _L = MX / P_ gives the LM curve:

___ _(LM)

Intersection of the IS and LM curves gives equilibrium for _YR_ and

_i_, and from these the other variables can be solved, in particular

the price level _P = MX / L_[_YR, i_]_._

Note that we also use: [72]

_Y_ = _P YR_

While the IS-LM model already tells us something about inflation - via

the quantity of money - there is also the labour market where wages

drive up costs and prices. The IS-LM sectors of the economy and the

labour market are linked via Value Added _Y._

The production function

For our purposes we can use a Cobb-Douglas function with employment

_LE_ and capital _KE_:

_YR = Y0 LE a KE 1 - a_

_Y_ _ P YR = W LE + i PK KE,_

We assume that firms maximise profits - and since we assume constant

returns to scale, there is no surplus. If firms accept wage _W_, then

the marginal productivity of labour equals the real wage _W / P, _and_

_then this determines _LE _which must be at most labour supply _LS.

_Unemployment then follows as _u = 1 - LE / LS. _If companies also

accept the rental price of capital, then the marginal productivity of

capital must equal _i PK / P, _and this determines the employed real

capital stock _KE_, which must be at most total stock _KS._

The additional equations from these marginal conditions are (and we

assume expectational equilibrium on these too):

_LE = Y / W_

_KE = _(1_ - _ )_ Y / _(_i PK_)

With _YR, P _and _i _given from above, there is one degree of freedom

from either _PK_ or _W_. It is customary to close the model with a

relationship that sets the average wage _W_. [73]

_YR_ = real income

_LE_ = employment

_KE_ = employed real capital stock

_KS_ = total real capital stock

_LS = _labour supply

_u_ = rate of unemployment

_W _=_ _average wage

_WT _= _W LE _= total wage sum

_ _

In a full model, the price of capital must relate to investments _I

_and to wealth _WN. _Also, apart from a theory on unemployment, we also

need a theory on idle capital _KS - KE. _We could also include

intermediate goods, as these appeared to have been important in the Oil

Crises. These alternatives however lead too far for our purposes.

Important for our purposes however is inflation. We already indicated

that the price level _P _is relevant for inflation. The crucial thing

to note is that inflation is the relative _change_ of the price level,

so that it is a dynamic concept.

Dynamics versus statics

Let _p _be an arbitrary price.

_Statics_ assumes a timeless dimension. With supply _S_[_p_] and demand

_D_[_p_]_,_ equilibrium (in expectations) is given by _S_[_p_]_ =

D_[_p_] and it solves for the equilibrating price _p·_.

_Dynamics_ concerns developments in time. The price movement _p’ =

dp/dt _is related to excess demand _D_[_p_]_ - S_[_p_]_, _so that_ p’ =

dp/dt = f_[_D_[_p_]_ - S_[_p_]]_. _The solution of this differential

equation gives the movement towards equilibrium. Dynamics causes

different concepts of equilibrium: depending upon the specification of

variables and function, the equilibrium can be market clearing (_p_°)

or the fulfillment of expectations (_p_*). Economic agents generally

have different speeds of reaction when expectations are not fulfilled.

When there are surprises, there can be a ‘trade-off’ between prices and

quantities.

Phillipscurve

For the labour market, dynamics implies a relationship between

unemployment and the change in wages. This relationship is called the

(wage-) Phillipscurve. Sometimes there is an additional assumption of a

strong relationship between wages and product prices, [74] and then the

(price-) Phillipscurve gives the relationship between unemployment and

prices.

The existence of a Phillipscurve thus follows essentially from the

concept of dynamics itself. For the labour market, the price_ _is the

wage _w_ and excess demand is represented by unemployment _u _(thus

negative excess demand; with vacancies neglected partly because of

unreliable measurement), so that _w’_ = _f_[_u_]. Much debate in

macro-economics about whether the Phillipscurve ‘exists’ or not, could

have been cut short by noting that it is a standard market adjustment

equation. The true debate is about the proper form and stability of its

parameters.

In the simplest model we choose inflation, [75] and have, with _u = 1 -

LE /LS:_

dLog[_P_] = _f_[_u_]

and this would add another restriction that closes the model. For

example:

dLog[_P_] = dLog[_P_]* - 0.1 Log[ _u / u*_ ]

would give an expectations augmented form, and when _u = u*_ then

expectations will be fulfilled, and _LE = LS _(1_ - u*_).

It is useful to note that above model does not yet contain an explicit

reaction function of the monetary authorities with regarding to

inflation. Money can be fixed or chosen to grow at a predetermined

rate. In practice there will be a flexible reaction, and then part of

the ‘Phillipscurve regression between dLog[_P_] and _u_’ will reflect

that reaction function.

Macro-economic interactions

The textbook relations are simple in themselves, but the interactions

already can be rather complicated. Figure 18 presents some common

macro-economic interactions.

Figure 18: Some macro-economic interactions

The influence of income in that figure is stated in terms of growth

dLog[_YR_], [76] and the influence of prices is stated in terms of

inflation dLog[_P_]. Positive transmissions are in black and explained

in Table 5, negative transmissions are dashed in red and explained in

Table 6.

Table 5: Positive impulses

_Positive _

_Cause_

_Prime effect_

_Then_

_Then again_

_YR P_

growth

increases demand

adds to inflation

_u DEF_

more unemployment

less income, less tax revenue

more expenditure on benefits

higher deficit

_P i_

more inflation

the Central Bank (CB) raises interest rates to fight it

possibly, though, inflation means more profits and a reduced demand on

loans

and thus a lower rate of interest: but then the CB will maintain the

level of interest

_i DEF_

higher interest rates

the government has a higher interest bill

higher deficit

_DEF i_

a higher deficit

more demand for loans, more supply of bonds

thus a higher rate of interest

_DEF YR_

a higher deficit

sustained expenditure

and thus sustained growth (at least by that channel)

Table 6: Negative impulses

_Negative_

_Cause_

_Prime effect_

_Then_

_u P _

more unemployment

lower wage demands

and thus less inflation

_P DEF_

more inflation

more tax revenue

and thus a lower deficit

_i YR_

a higher rate of interest

makes investments more costly

and thus lower growth

_YR u_

more growth

more demand for labour

lower unemployment

24. Heterogeneity and nonlinear taxation

Heterogeneity versus homogeneity

Homogeneity assumes that _S_[_p_]_,_ _D_[_p_]_ _and _p _are real

variables, while heterogeneity assumes vectors or densities. This book

takes the density approach. In fact, employment _e_[_w_] =

Min[_s_[_w_]_,_ _d_[_w_]] also provides the earnings or income

distribution, i.e. the function that gives the number of people earning

a level of income _w_, for labour supply _s_[_w_] and labour demand

_d_[_w_].

Nonlinear versus proportional taxation

The proportional tax is _r Y_. A linear but non-proportional tax is

_Bentham_[_w, x_]_ = r (w - x)_, though proportionality comes back

again by assuming _x_ = 0. A nonlinear tax adds curvature (see chapter

29), and then interacts with heterogeneous labour.

Some literature

The following references put the argument into perspective.

In his presentation of the IS-LM model, John Hicks (1937) could

disregard differences in labour as being of secondary complication. For

our purposes, however, the case of heterogeneous labour causes a

crucial difference. Policy co-ordination then involves three

distributions:

1. the gross income distribution that corresponds to the productivity

distribution,

2. the net income distribution aspired by the policy maker (‘society’),

3. the actual net income distribution, resulting from taxes imposed

(including e.g. the social security ‘insurance’ payroll tax) and from

expenditure.

There is early recognition in the literature of the need for

heterogeneous labour in discussing dynamics. For example, 20 years ago,

Solow (1976:152), occasionally but not consistently using the more

accurate term ‘surface’:

“George Perry, who was one of the earliest quantifiers of the Phillips

surface, has recently produced an alternative explanation of great

interest [reference]. Perry’s basic insight is that the aggregate

unemployment rate may be an ambiguous measure of pressure in the labor

market when the composition of the labor force and of the group of

unemployed is changing. (...) In other words, the Phillips curve would

have shifted upward. (...) Perry quantifies this observation by making

the plausible assumption that an unemployed body generates downward

pressure on the wage level proportional to the amount of “unemployed

labor” he or she represents. In turn, the amount of unemployed labor

can be measured by the number of dollars of wages it represents.”

No economist working in the field and worth his salt will have

neglected Solow’s paper. Issues of the substitutionability of one kind

of labour for another, and of dispersion measures for the differences

in responses, can found even earlier in the literature.

Van Praag & Halberstadt (1980) present a continuous productivity

distribution.

Bruno & Sachs (1985) give a standard reference for stagflation. Their

formal analysis uses homogeneous labour and proportional taxes, though

some of their statements allow for an interpretation of heterogeneity

and nonproportionality.

The need for modelling heterogeneous labour and nonproportional

taxation is clearly recognized in the literature, see e.g. Beenstock et

al. (1987) and Minford & Ashton (1993). Layard, Nickell & Jackman

(1991), another standard, allow for heterogeneous labour, yet tend

towards proportionality in taxation.

In addition, these references use dynamics but do not explicitly

discuss the consequences of changes in tax parameters. Auerbach &

Kotlikoff (1987) give a wealth of information on fiscal dynamics but do

not specifically tackle stagflation.

Other references which put the Phillipscurve in perspective are Okun

(1981), Blanchard & Fischer (1989), Friedman (1991), The Economist

(1994) and Phelps (1994). Extensive theoretical and empirical work has

been done by the Central Planning Bureau (1992a&b), Gelauff (1992) and

Colignatus (1992b).

25. Summary of current views

It is useful to recognise some current views on the labour market and

the influence of taxes. This allows us to better see the impact of our

new analysis.

A simple view

There exists a simple popular view that makes two errors:

· it is _static _and not_ dynamic_

· it assumes _homogeneity _and not _heterogeneity_.

This model is the comparative statics model with homogeneous supply and

demand for labour. Borjas (1996:159), Mankiw (1998:125) and The

Economist of February 26 1994 present that model. As a model it of

course is consistent and it can help us to get our thoughts started,

but as a representation of real markets it is erroneous.

Figure 19 gives the wage _W _on the vertical axis and supply and demand

quantities on the horizontal axis. (Note the causal order.) It must be

mentioned that marginal tax rates have played a role in the deduction

of the supply and demand curves.

In this Marshallian model, the original equilibrium is attained at the

intersection of the _LS _and _LD _curves, at wage _W°_ and employment_

LE°. _An income tax causes workers to demand a higher wage, and supply

shifts up, to _LS1. _Premiums that raise wage costs for employers cause

these employers to offer a lower direct wage, and demand shifts down,

to _LD1. _The new equilibrium of _LS1 _and _LD1 _is _LE < LE° _ where

employers pay direct wage _W1 > W°_ and where workers receive net _W2

< W°._

For this model, with supply and demand schedules derived with marginal

analysis of utility and profits, there is an important role for

statutory marginal tax rates. First best here are lump sum taxes and

zero marginal rates.

Figure 19: Statics

Marshallian model for the influence of the tax wedge

There are clear objections to this model:

· It is comparative statics, with homogeneous and flexible labour.

· It concerns any kind of tax, while some taxes are socially desired

and generate employment. The model doesn’t distinguish between optimal

and suboptimal taxes.

· Empirical research shows that labour supply elasticities are low.

Elasticities are higher for partners, but that is less relevant here.

People are very much in the position that they have to work for a

living, and taxes generally pose no restraint on the availability for

the labour market. This means that _LS ~ LS1 ~ vertical. _(Borjas

(1996) shows this graph too.)

· The model does not really allow for unemployment. We might define _U

=_ _LE° -LE_, but _LE° _is an unobserved variable. Firms and workers

react to observed variables, and in those terms there is full

employment. Even if labour would be inflexible in this model, then

there still would be no involuntary idleness at the net wage earned.

The use of this model thus is limited. Mankiw (1996) correctly presents

the model as a ‘tax incidence’ model, and we should be hesitant of

other conclusions.

The Simple View however regards this model as a real description of

real labour markets, and it thus makes the category mistake of using

arguments concerning the income distribution for issues of growth and

employment.

The reader is advised to read again Chapter 2 of Keynes’s 1936 _General

Theory_. The_ General Theory_ is in my perception an effort to

seriously develop dynamics. Keynes’s precursors did discuss dynamic

developments, but always ended up in static modelling. See also

Patinkin (1976:140 footnote 4).

In the following quote, Keynes discusses a real wage reduction caused

by prices. For our purposes, we might substitute a real wage reduction

caused by taxes.

“To sum up: there are two objections to the second postulate of the

classical theory. The first relates to the actual behaviour of labour.

A fall in real wages due to a rise in prices, with money-wages

unaltered, does not, as a rule, cause the supply of available labour on

offer at the current wage to fall below the amount acually employed

prior to the rise of prices. To suppose that it does is to suppose that

all those who are now unemployed though willing to work at the current

wage will withdraw the offer of their labour in the event of a small

rise in the cost of living. Yet this strange supposition apparently

underlies Professor Pigou’s _Theory of Unemployment_ [voetnoot] and it

is what all members of the orthodox school are tacitly assuming.”

(Keynes (1936:12-13)).

Note, by the way, that the format of Figure 19 can always be used in

terms of the _average _wage _W. _So the format of Figure 19 may be

inviting to our intuition, in that we think that we indeed can draw a

diagram like that, but we then should be aware that our true model is

heterogeneous labour and not homogeneous labour.

A complex view

An alternative view is more empirical, thus inherently more dynamic,

and builds on Keynes’ observation. Empirical research, see e.g.

Ashenfelter & Layard (1986), Theeuwes (1988), Hum & Simpson (1991) and

Gelauff (1992) shows that marginal tax rates have ‘surprisingly’ low

elasticities. The reason for a lesser importance of marginal rates is

that labour supply is not flexible, but rather fixed. That labour

supply is primairily given by demographic factors, is for example a

well known assumption of practical models developed at the Dutch

Central Planning Bureau. In Western economies people will have to

become active on the labour market in order to earn a living, and taxes

hardly form a barrier. People are still very much like Marx’s

proletariat, and they have little else to fall back on but to supply

their labour. There is some choice for partners and for people on

benefits, but this does not have a major impact. For the majority, if

anything, the average wedge is more important than the marginal one,

see Den Broeder (1989). Recently Minford & Ashton (1993) see scope for

a larger effect of marginal rates, but, their study is still far from

explaining stagflation, partly for the reason that it is not fully

dynamic.

By consequence, the major equilibrating forces exert themselves on the

wage and the related employment. Here arises the dynamic situation of

(wage) inflation and unemployment, and thus the issue of the

Phillipscurve. Thus, conceptually, tax rates have their major impact

not on labour supply but on the Phillipscurve.

The next question then is whether their effects are positive or

negative. The common argument is that a higher marginal rate fuels

inflation. Whether this is the case then becomes the next issue.

Efficiency wages intermezzo

Before we can continue the discussion, a note on the ‘efficiency wage

theory’ is required. The idea is here that, though people are forced to

work to earn a living, they still can choose whether they shirk or not.

They take account of a probability of getting caught and getting fired,

but supervision would be expensive, and, if fired, one eventually could

find another job. Unemployment then is required to discipline the

workers. Borjas (1996:459) provides an introductory discussion, and the

graphs are quite similar to the supply and demand schedules of old.

I tend to regard this approach as an example of academic excess. This

may be an error on my side, but let us look at some of the arguments:

10% of the European labour force is unemployed, hence Europeans

apparently shirk a lot ! And employers are so dumb that they cannot

think of cheap ways to determine productivity, like setting standards

and such. Agreed, shirking is undoubtedly a phenomenon, and eventually

the superior economic model will include a subtle relationship between

wage, effort and productivity to determine the last digits, but all

this is less relevant for the Great Stagflation and the need for an

Economic Supreme Court.

A more sophisticated view

Graafland (1990) introduced another approach at the Dutch Central

Planning Bureau, and he refers here to Hersoug (1984). The

Phillipscurve here is derived using a model of wage bargaining between

unions of employers and employees. The approach is adopted by Gelauff

(1992) on the CPB model MIMIC, Gelauff & Graafland (1994). It recently

is refined by Graafland and De Mooij (1998), Bovenberg, Graafland and

De Mooij (1998), Jongen and Graafland (1998), Graafland & Huizinga

(1999), [77] Graafland and Nibbelink (1999), Oers, De Mooij, Graafland

and Boone (1999), and De Mooij (1999). In this approach, a higher

statutory marginal rate actually increases employment, instead of

reducing it as the Simple View and many standard Phillipscurves would

hold. The mechanism is as follows:

· A higher marginal rate (under constant average) penalizes wage

demands, lowers such demands, reduces (wage) inflation and thus

increases employment.

· A higher average rate (under constant marginal) causes compensating

wage demands at the margin, and reduces employment.

These properties actually are well known, as they are consistent with

analyses concerning a Tax-based Incomes Policy (TIP). For example the

Congressional Budget Office (1977:119):

“In recent years there have been proposals to use tax incentives and

other schemes to encourage more moderate price behavior. (...) Rather

than overriding market forces, these newer proposals attempt to take

advantage of market incentives by making moderate price and wage

increases a matter of self-interest for firms and employees. The best

known of these proposals involves tax incentives to reward or penalize

wage decisions that deviate from some established standard.”

This view however still does not take account of the dynamic marginal

rate. There are also the issues of labour heterogeneity and optimal

taxation that we have encountered in discussing the Simple View, but

that have not had sufficient attention. These issues will be discussed

below.

Confusions

Given more than one view, there is scope for confusion. This has in

fact occurred.

· The OECD policies referred to above, directed at lowering statutory

marginal rates, have been advocated using the rhetoric of the Simple

View even though economic advisers often are aware of the Complex View.

· If one would really think that high marginal rates reduce work effort

and supply, then a situation of high unemployment would call for higher

rates - that would reduce unemployment. Policy however has been to

reduce rates.

Secondly, when these views are confronted with the effects of the

policy of rate reduction, there again is ample scope for confusion.

When unemployment has been reduced, then this is being seen as

corroboration of the Simple View. For example the data on the US now

show the combination of a reduction of taxes on higher incomes and some

reduction of unemployment, and it will now be difficult for policy

makers to accept other lines of arguments. Actually, in so far as there

has been some success in practice, it is because the policies have also

lowered average rates. Higher budget deficits have been relied on to

pay for additional benefits and average rate reductions for higher

incomes. The reduction of marginal rates actually had a negative

impact.

In most cases unemployment has remained high. In this case one should

expect that policy makers would reconsider their views. They don’t seem

to do this, and rather look at the few cases where there seems to have

been success along the expected pattern.

A specific example is the Dutch 1990 tax reform (known as “Oort reform”

[78]). This reform was supported by computations using the MIMIC model,

see Gelauff (1992). The reform reduced both marginal rates and

exemption. The reduction of statutory marginal rates reduced Phillips

curve sensitivities, and induced larger wage claims and lower

employment. The reform however also included a reduction of average

taxes, and this caused employment to rise on balance. We may restate

the situation in more mundane terms: the reduction of average taxes was

sold on the political market as a reduction of marginal rates.

Politicians had their eyes fixed on the reduction of marginal rates and

the reduction of unemployment, and they got what they wanted to see,

without realising that the mechanism in MIMIC was entirely different,

and that proper exploitation of this mechanism would lead to even lower

unemployment.

26. Heterogeneous labour

We will first discuss heterogeneous labour supply, and forward a

hypothesis on its distribution. Note that supply is difficult to

observe, since generally we only observe actual employment, which is

the minimum of supply and demand. However, data on actual earnings do

allow the encouraging conclusion that the earnings distribution can be

approximated by a lognormal distribution. For an indication we look at

Dutch data on the distribution of income in 1950 and 1988. We complete

this chapter by a more thorough sets of definitions for earnings, cost

and income accounting, and we construct integrals that are relevant for

the minimum wage.

Dromedary supply

Let us first regard labour supply.

At a Dutch economists “Masterclass” session in Fall 1991, Orley

Ashenfelter explained that labour supply was unresolved and actually

some kind of a researcher’s nightmare. In a break I put my suggestion

on the blackboard, and my ‘quiggly’ line (see below) at least drew the

compliment of an amused smile. I almost put this suggestion into

Colignatus (1994a), but backed away from that since it was not

essential for that paper (and I used only the normal right hand side of

the supply graph). However, to my surprise and pleasure I saw that same

quiggly line in De Groot & Keuzenkamp (1995) who discuss results of

Quah (1993).

De Groot & Keuzenkamp have another subject than labour supply. Their

problem is whether international economic growth results into

convergence, as Adam Smith’s “The Wealth of Nations” seems to imply. De

Groot & Keuzenkamp refer to the results of Quah (1993) who has compiled

the distribution of output per labourer per country, which turns out to

be that quiggly line.

To understand the point, let me first explain my reasoning on labour

supply. At low productivity, one has to work 24 hours around the clock

in order to survive. For example, if subsistence is at _B _and

productivity is _y_, then the hours are _B / y. _Hours thus quickly

rise when _y _drops (the working poor)._ _When productivity increases,

one quickly starts working less hours, particularly since the kind of

work at that level often concerns hard labour. At higher levels of

productivity again, the kind of work is less exacting and pay is

better, and one may work longer hours again. However, at the highest

levels of productivity, labour again becomes a relative disutility. In

summary, when plotted in a graph, the figure looks like a dromedary,

starting high at the left, having a dip in the neck, then the bump, and

sliding away towards the tail.

If labour supply is like this, then it likely affects the productivity

distribution across nations. While every individual has his or her own

parameters, aggregation may average things out, and as a result one

nation then may stand for a certain income group. Thus Quah’s finding

is consistent with my intuition and indirectly confirms it.

Figure 20 plots the quiggly line, for imaginary income _y_ in thousands

of dollars and subsequent working hours per week, for both long and

short ranges of income so that the curvature can better be appreciated.

Figure 20: Supply in hours per week, depending upon income

Note: These are not observations, just give an hypothesis on shape

I’m still working on a correct form of the complete utility function.

Barro & Sala-i-Martin (1995) give a recent discussion of the trade-off

of work and leisure in the context of growth, and that might be a

fruitful framework. However, for the present purposes, our development

may stop here.

Dutch income distribution data

The literature on the distribution of income has resulted into a

general impression that this distribution can be approximated by a

lognormal distribution, see e.g. Pen & Tinbergen (1977). For the

purposes of our exposition it is useful to test this impression. [79]

Also, since we will discuss long periods of indexation, notably from

1950 till 2002, it is also useful to look at the distribution in 1950

and a recent one. We then take the distribution data in the appendices

for Holland 1950 and 1988.

Figure 21 and Figure 22 plot the resuls of a (rough) estimation. It

appears that we get the best fit when we transform the data into

logarithms (and recompute the frequency densities - i.e. the

transformation required to deal with different class sizes). The

logarithmic data are approximately normal, as can be seen in the plot

of log[income] versus its frequency density. We can transform the

estimated distribution for a plot in the income-frequency format.

Figure 21: Dutch income distribution 1950

Figure 22: Dutch income distribution 1988

In the 1988 plot, the estimation has been done with the 1988

‘parttimers’ dropped, but they are included again in the

income-frequency plot so that we can better appreciate that their

inclusion would confuse a discussion on fulltimers. But it is nice to

see the dromedary shape returning.

We conclude that income can indeed be approximated as a lognormal

distribution, and throughout time; at least as a stylized fact that we

can use for propositions and illustrations. [80]

Definitions and formulas

There are some useful definitions and formulas for heterogeneous labour

markets. These hold for any distribution, not just the lognormal

distribution. Let _y _and _w_ be micro values that have a certain

density. First of all, there are the following accounting definitions,

for annual and nominal values:

· _ _= the profit rate, expressed as a markup on labour costs

· _y_ = labour costs + profit = _w _(1 +_ _) = product revenue =

productivity

· labour cost quote = LCQ = _w / y _= 1 / _ _(1 +_ _)

· labour costs = _w _= (direct) wage + nonwage (but labour related)

costs

· _w _= net labour income + (direct + indirect) taxes + premia + other

nonwage costs

· tax = _T_[_w_] = (direct + indirect) taxes + premia

· gross labour income = labour costs - other nonwage costs = net labour

income + tax

· Neglecting the “other nonwage costs” gives _w_ = labour costs = gross

labour income. (Thus the _w_ are labour earnings only if the other

nonwage costs are zero.)

Observed labour costs have a density _fw_[_w_]. Since the product is _y

= w _(1 +_ _), equalisation of profit rates with respect to labour

would give the labour cost density _fw_[_w_] as a shift of the

productivity density _fy_[_y_]. Normally, though, the profit rates are

equalised in terms of capital, which for example causes different

Labour Cost Quotes (LCQ) per sector of industry, and then the relation

between _fw_[_w_] and _fy_[_y_] is a more complicated affair.

The proper labour supply density _sp_[.] depends on net labour income

(_w - T_[_w_]). But supply can, with the neglect of “other wage costs”,

be regarded as a function of labour cost _w_, as:

_s_[_w_] = _sp_[_w_ _- T_[_w_]]

Labour demand is a density _d_[_w_]. Total supply follows from the

integral:

&

The employment density is the minimum of supply and demand, and equals

the observed labour cost density:

_e_[_w_] = Min[_s_[_w_], _d_[_w_]] = _fw_[_w_]

For total employment we take account of a minimum wage _M_.

For the discussion below it is also useful to compute aggregate labour

costs and its (nominal) tax revenue:

Important are the average wage _W = WT / LE _ and the average tax rate

_ATXR =_ _TAX / WT _(when we can neglect other nonwage costs).

Densities for unemployment _ud_ and vacancies _vd_ follow from the

difference between supply and demand and actual employment:

_ud_[_w_] = _s_[_w_] - _e_[_w_] & _vd_[_w_] = _d_[_w_] -

_e_[_w_]

The aggregate unemployment and vacancy are _U _and _V, _and their rates

are:

_u = (LS - LE) / LS = u_[_M_] & _v = (LD - LE)

/ LS = v_[_M_]

Figure 23 gives the stylized fact that vacancies tend to occur at

higher income brackets and unemployment at lower ones. The figure is

quite stylized, since it is a difficult issue to construct plausible

_s_[_w_] and _d_[_w_].

Figure 23: Supply and demand of labour

If labour supply _LS _was homogeneous, we would have difficulty

explaining that _u LS _ would be unemployed, since these persons are

similar by assumption. Basically then _u _is a probability.

For heterogeneous labour we could use characteristics and a mechanism

that explains why some are employed and others not. This mechanism

could be related to the shift of the densities over time due to

aggregate demand, inflation, technology, job changes and the like. In

fact, we would use such methods to determine _ud_[_w_] and _vd_[_w_] in

practice - and perhaps we would not start with _w _as the defining

characteristic, but start with other characteristics and work towards

the wage. However, we will not look into this deeply. We will use

heterogeneity mainly to explain the effect of the minimum wage. For a

level of income above the minimum wage we again assume some

probability, quite analoguous to the homogeneous case. Basically, an

agent has offers for various kinds of jobs and incomes, and associated

probabilities (and one for unemployment). The _s_[_w_]_ _and _d_[_w_]

thus have a stochastic base._ _

Minimum wage unemployment differs from the ‘normal’ unemployment above

the minimum. Thus:

_u = um + un_

Only part of _um_ can be gainfully employed when the minimum wage would

be abolished.

Only _un_ will exert a meaningful pressure on wages. A major dynamic

process is that _um_ rises over time, contributing to the phenomenon of

hysteresis. Labour market processes and wage settlements might stay

stable in terms of _un_, i.e. the “normal” unemployment rate, but they

shift in terms of _u_, the overall unemployment rate.

One may wonder why _M _is nonzero, when its abolition would create

employment _ume. _The apparent reason for governments is that labour

markets are not fully competitive and require some regulation. This

issue is taken up again in the next chapter on subsistence.

These integrals don’t say how large the densities are. An indication of

how much _M _‘bites’ is difficult to find. An approach is the

following. Let us define _ms_ such that (for example) 1% of supply has

an earning power of less than _ms_. Similarly, _md_ for demand. Then

Table 7 distinguishes six situations. [81]

Table 7: Combinations of _ms, md_ and _M_

_ _

_ms < md_

_md < ms_

Minimum wage irrelevant (_M < md_)

_M < ms < md_

_M < md < ms_

Minimum wage irrelevant (_M < md_)

_ms < M < md_

_ _

See point (b) below.

_ _

_md < M < ms_

See points (a) and (b) below.

_ms < md < M_

_md < ms < M_

There are some notable effects:

(a) On the supply side, if _ms < M_, then would-be earners of _ms <

w < M_ become eligible for benefits. When they accept these benefits

voluntarily or from social pressure, they, in a sense, form no real

supply. Yet they are supply, otherwise they would not be eligible for a

benefit.

(b) On the demand side, if _md < M,_ then there would be a real

demand for _md < w < M_ if government would reduce _M_. But this demand

is not relevant when _M_ exists.

A crucial point to see is that, as we here are concerned with

productivity, that we can use subsidies to manipulate the densities,

for example by subsidising a particular industry or profession. Doing

this of course causes an accounting problem: does the _w _on the

horizontal axis measure productivity before or after such subsidy ? The

most practical approach is to use _w _inclusive of subsidies - because

market measurements are always inclusive. Subsidising firms would allow

them to hire at higher wages: this would shift _d _to the right._

_Subsidising workers would allow them to work for lower wages: this

would shift _s _to the left. What happens to employment is not a priori

obvious.

It turns out that the minimum wage is important in practice. Our

analysis will strongly rely on minimum wage unemployment. In this we

differ a bit from the original position taken by Keynes. As Tobin

(1972: 122) states:

“But why is the money wage so stubborn if more labor is willingly

available at the same or lower real wage ? Consider first some answers

that Keynes did not give. He did not appeal to trade union monopolies

or minimum wage laws. He was anxious, perhaps over-anxious, to meet his

putative classical opponents on their home field, the competitive

economy.”

In my view, Keynes’s argument (as further explained by Tobin) is to the

point, and aggregate demand, sticky wages and the co-ordination

failures on these are established concepts in macro-economics. However,

the record of the Great Stagflation is very much influenced by the

minimum wage problem, and thus it is that kind of analysis that merits

our attention here.

Amendment to the textbook model on the Phillipscurve

With respect to the textbook macro-economic model in chapter 23, we can

introduce a minimum wage component in unemployment _uM_ that can rise

gradually over the long run due to taxation. With _u_ = _uM_ + _uR_

(_R _from ‘remainder’) a possible Phillipscurve with less dampening

effect of _uR_ is:

dLog[_P_] = dLog[_P_]* - __ Log[ (_uM_ + _uR_)_ / u*_ ]

Alternatively, the two submarkets have their own curves. In both cases,

it must be determined how the two submarkets develop and how they

interact. The most obvious hypothesis is that high productivity labour

sets the trend for the development of wages. When minimum wage

unemployment rises stronger than general unemployment, then the higher

educated have more scope for wage demands, and then there is an upward

effect on wages and prices, even stronger so when price expectations

come into play. This would show an unfavourable (upward or rightward)

shift of the (aggregate) Phillipscurve.

27. Subsistence