LABOUR MARKET BEHAVIOR IN MACROECONOMICS:
Cycles and Dynamics
Jeremiah Allen
©2004
In the past I assigned the two papers by Blanchard and Diamond, which are listed in the
bibliography of these notes, and the paper by Lipsey. I’ve reduced that to just Tobin, Gordon and my
paper on labour over the business cycle. The other papers, along with the Phillips paper and readings
from Edmund Phelps’s book, are all of historical interest. They show the development of the model
and of “new” labour economics. But these are heavily detailed technically and I doubt that students
actually read them in the past. I think the students were getting the necessary technical detail from
my lectures and using their class notes exclusively.
There are two separate issues in macro-level Labour Market Behavior. One is how the labour
“market” behaves over the business cycle. The questions asked in this part are: which important
variables are pro-cyclical and which are counter-cyclical, and why? That is, what type of behavior
drives the cycles we see? The second issue is how labour market behavior interacts with other
macroeconomic variables in both the short-run and the medium-run. In particular, here we are
interested in how labour market dynamics can affect the level of Yn and, therefore, Un.
I summarized the empirical observations of Phillips and the theory of Phelps, which led to the
DAD/EA-DSAS model, in my ”Output/Inflation” dynamics notes. Here I summarize the theory of
Lipsey, and the empirical observations and theory of Blanchard and Diamond. The latter provide the
link between labour market cycles and the DAD/EA-DSAS model. The two provide the link
between the labour market dynamics and the DAD/EA-DSAS model.
(Note on symbols: I continue to use non-italicized UPPER CASE ROMAN letters for variables:
eg, Ht, Jt .)
I LABOUR MARKET: Cycles
A. Variables:
The so-called “new” labour economics focuses attention on flows rather than stocks. It goes by
two names: “job-matching” and “the flows approach”; I’ll use the latter. (I say “so-called new”
because most of it isn’t really new. The facts that it has “discovered” were well known by labour
economists when I was in graduate school. I read these when surveying the literature for my PhD
dissertation. The first good description of the flows approach, and a good technique for dealing with
it, was published by Curtis Eaton in 1970. Both he and I used it in our PhD dissertations – his
finished in 1968, mine in 1969.)
A “flows approach” requires a new concept: “stasis”. Stasis is when a the size of a stock, which
has flows into it and flows out of it every period, doesn’t change in a period. Consider a pond with a
stream flowing in and a stream flowing out. It is in “stasis” when the size of the two streams are
equal, so the pond is getting neither larger nor smaller. Note that this isn’t quite the same as the pond
being “constant”. The water is flowing in and out; it’s the size that’s constant, not the water. If no
water were flowing in and out it would be a different type of pond. In this example the flows are
continuous. We use discrete periods in this course, so here’s an example using those.
Consider a population of organisms. Some are born each period, some die each period. Stasis in
this population, during a period, is when births during the period equal deaths during the period, so
the size of the population at the end of the period is the same as at the beginning. Note that I avoid
using the word “constant” here. The size of a constant does not change. The size of a stock can
labour market behavior
page 2
change, but if it does not change during a time period, it is in stasis (not “is constant”). Stasis is
similar to dynamic equilibrium, but subtly different. Dynamic equilibrium in a variable, Y, is when Yt
= Yt-1 . When this happens Y may be constant. When a stock that has flows into and out of it is in
stasis, its size is the same in the two periods, but its composition is changing – it isn’t exactly
“constant”.
For now we treat the size of the labour force as a constant (actually it’s in stasis, but I don’t
develop that here). The key variables are Unemployment, UNt and Job Vacancies, Vt . Note that
UNt is the number of unemployed people, not the Unemployment Rate, which is Ut .
Flows into Unemployment in a period for happen two reasons: 1) voluntary quits-to-search, Qt ,
and 2) involuntary “quits”, which we’ll call layoffs, Lt . Here “layoffs” also includes jobs lost when a
firm goes out of business. The difference between voluntary quits and layoffs is that voluntary quits
always create job vacancies. Flows out of Unemployment in a period are hires, Ht. So:
UNt = UNt – UNt-1 = Qt + Lt – Ht , which can be rewritten:
UNt = UNt-1 + Qt + Lt – Ht .
(1)
On the supply side, unemployment is in stasis when Ut = 0, or:
UNt = UNt-1  Qt + Lt = Ht .
If Qt + Lt > Ht , Unemployment is increasing:UNt > 0 and UNt > UNt-1 . If Qt + Lt < Ht,
Unemployment is decreasing: UNt < 0 and UNt < Ut-1 .
(2)
The variable that defines firms’ demand for new workers is Job Vacancies (Vt). New Job
Vacancies in a period are created for two reasons: 1) voluntary quits-to-search, Qt , and 2) jobs
created exogenously, Jt , as output, Yt increases. When a Vacancy is filled, it disappears. Filling of
Vacancies in a period is hires: Ht . So:
Vt = Vt – Vt-1 = Qt + Jt – Ht , which can be rewritten:
Vt = Vt = Vt-1 + Qt + Jt – Ht .
(3)
On the demand side, Vacancies are in stasis when Vt = 0, or:
Vt = Vt-1  Qt + Jt = Ht .
(4)
If Qt + Jt > Ht, Vacancies are increasing:Vt > 0 and Vt > Vt-1 . If Qt + Jt < Ht, Vacancies are
decreasing: Vt < 0 and Vt < Vt-1 .
Quantity Demanded in the labour “market” equals Quantity Supplied when Vt = UNt . From
equations (2) and (4), this happens when both UNt and Vt are in stasis and Lt = Jt : new jobs are being
created in the same numbers as workers being laid-off. This is dynamic equilibrium in the labour
market. Note that dynamic equilibrium in the labour market can occur with higher or lower levels of
Vt and UNt . With high levels, the individual sectors are operating at different points on their
individual “phillips” curves: see part IV below. So dynamic equilibrium in the labour market can be
Short-Run.
Movements away from dynamic equilibrium which are caused by reductions in output, and which
increase unemployment, occur when:
1) UNt > Vt  Lt > Jt .
Movements away from dynamic equilibrium which are caused by increases in output, and which
reduce unmployment, occur when:
2) Vt > UNt  Jt > Lt .
labour market behavior
page 3
A full Long-Run equilibrium in the labour market occurs only when all sectors have neither excess
demand nor excess supply, when Quantity Demanded equals Quantity Supplied in every sector.
Because the economy never sits still long enough for labour mobility to make this happen, the labour
market is never in Long-Run equilibrium. (This is sort-of what Keynes had in mind when he
famously said, “In the Long Run, we are all dead.”
B. Cyclical Behavior of Labour Market Variables:
There is a very large body of empirical studies of how labour market variables behave over the
business cycle. These were a staple of the “old” labour economics: there are studies going back to
the 1920s showing these cycles, and Lord Beveridge published his findings in the 1940s. They are
also a staple of the “new” labour economics. The studies listed in the bibliography by Blanchard and
Diamond, by Jackman with others, by Pissarides, and by all the authors in Padoa-Schippa, explicitly
put their empirical findings into the so-called “new” labour economics of “job-matching” or the
“flows approach”. But all of these, both “old” and “new”, agree! Those findings include:
1) Vacancies are pro-cyclical: Vt increase with increases in Yt, and vice versa.
2) Unemployment is counter-cyclical: UNt decreases with increases in Yt and vice versa.
3) Thus, the Vt/Ut relation is strongly pro-cyclical; it increases with increases in Yt and vice versa.
(When this is graphed with UNt and Vt on the axes, it is known as the Beveridge curve after
Lord Beveridge’s findings. Like the Phillips curve, this was considered to be stable. With the
changing make-up in the labour force in the 1970s through the 1990s it shifted around a bit but
has become relatively stable once again.)
4) Quits-to-search are pro-cyclical: Qt increases with increases in Yt and vice versa.
5) Jt – exogenously created jobs – are non-zero (in the aggregate) and strongly pro-cyclical.
6) Lt – layoffs – are non-zero and strongly counter-cyclical.
7) Labour market mobility, in particular geographic mobility (labour market migration – moving
from one economic region to another) is pro-cyclical, with one exception:
Return migration – workers who moved from one region to another in the immediate past,
moving back to the first region – is counter-cyclical.
8) Changes in money wages, as Phillips showed, are pro-cyclical.
9) Changes in real wages show no particular cyclicality.
10) The loops in the Phillips curve are counter-clockwise; that is, the difference between a point
and the aggregated Phillips curve is pro-cyclical.
11) The rate of increase in labour productivity is pro-cyclical.
12) The elasticity of labour supply in the short-run is roughly zero. (Most studies have actually
found it to be slightly negative.)
These “stylized” facts create a major problem with all New Classical models. In fact, the true
statement is stronger than that. The facts, in the language of positive science, falsify New Classical
models.
III MODELS and how they fit the FACTS
A: New Classical
In New Classical models unemployment is always voluntary. All increases in UNt are caused by
quits. Layoffs don’t exist: Lt = 0. These are pure “supply side” models. There is no job creation or
destruction coming from changes in aggregate demand. The chain of causality is:
workers don’t take jobs  employment falls  output falls.
labour market behavior
page 4
All reductions in output are caused by workers either not taking jobs because wages offered are too
low, or workers leaving jobs because firms are reducing real wages. Thus, all reductions in output
are caused by Ht falling and Qt rising. Moving along the production function, fewer workers means
less output. End of Story. So the “micro-economic foundations” of New Classical Macroeconomics
is looking at why wages change over the business cycle.
There are two broad types of these New Classical “micro-economic foundations”:
1) “Misperceptions”, or “Fooling”. This has been attributed to Lucas, with his “island” model. But
before Lucas it was called “Friedman/Phelps” and there is a good description of it in Phelps.
Here workers’ expectations lag actual changes in inflation – the parameter “g” in the Adaptive
Expectations equation is less than 1. The lag between expectations and changes in actual
inflation leads to systematic misperceptions by workers:
Real wage is money wage divided by Aggregate Prices. In a dynamic model, the change in real
wage, w, equals the change in money wage, W divided by inflation, . The expected real wage
from any offered money wage is that wage, W, divided by expected Aggregate Prices over the
period of the wage contract, which is current Prices times (1+e).
When inflation is increasing, more workers accept offered jobs because they misperceive the
offered money wage as being a higher real wage than it really is. They are “fooled” by their own
misperceptions of actual inflation – they expect inflation to be lower than it really will be – to
accept jobs. Output goes up as more workers are employed, and the economy moves up the
Phillips curve.
When inflation is falling, fewer workers accept offered jobs because they misperceive the offered
money wage as being a lower real wage than it really is. They are “fooled” by their own
misperceptions of actual inflation – they expect it to be higher than it really will be – to refuse
jobs. Fewer take jobs, more quit, and fewer are employed. Output goes down, and the economy
moves down the Phillips curve.
A special problem with the misperception model is that it generates clock-wise loops in the
Phillips curve, in contradiction to the evidence. I will show this in class.
2) Real Business Cycles, the RBC model: This is a genuinely lunatic idea, but economists seem to
have to talk about it anyway. Here the economy is hit with random productivity shocks. Since
real wages are roughly equal to marginal product, and marginal and average product move
together, when a productivity shock is negative (never-you-mind that no-one knows what a
negative productivity shock is) the real wages offered new hires fall, and firms try to reduce real
wages for existing workers. Fewer workers accept jobs and more quit (Ht decreases and Qt
increases), and output, Yt, falls. The model is symmetric; everything works the same way but
reversed with a positive productivity shock.
The RBC model doesn’t predict any loops in the Phillips curve. But it strictly implies that real
wages and output move together – that real wages are pro-cyclical – because it is decreases
(increases) in real wages that cause decreases (increases) in employment that cause decreases
(increases) in output. So a special problem exists with the RBC model because real wages don’t
have any cyclical relation.
The problem with all New Classical models – the problem, that is, with having output be entirely
determined by the behavior of labour – is that they either predict, or rely on, a large number of labour
market behaviors over the cycle that are precisely the opposite of what are observed Thus:
1) New Classical models strictly imply that Vacancies and Unemployment will move together – this
is how they get all the action in output. Since Lt = Jt = 0, then Vt = Qt, UNt = Qt and Vt = UNt.
labour market behavior
page 5
Since unemployment is exclusively workers not taking jobs plus workers quitting jobs in reaction
to (sometimes illusory) too-low real wages, Vt and UNt must be equal and both must be countercyclical; that is, both must go up when output goes down.
But the fact is that, while UNt is strongly counter-cyclical, Vt is as strongly pro-cyclical, and UNt
and Vt move in opposite directions over the cycle. The Beveridge Curve is negatively-sloped.
The reason is that Lt and Jt are not zero, and are rarely equal. Lt is strongly counter-cyclical and Jt
is strongly pro-cyclical. Furthermore, Qt is also strongly pro-cyclical, meaning that increases in
UNt are dominated by high values of Lt . The first Blanchard and Diamond paper cited below
discusses and shows (again) the true relations between, and cyclicality of, Vt and UNt .
2) New Classical models also strictly imply – no, that’s too weak, they rely on – that Qt is countercyclical. It is workers not taking jobs or quitting when faced with too low money wages, that
causes reductions in output. But Qt is strongly pro-cyclical. Again, this has been well-known
since at least the mid-1950’s; three good papers which showed this empirically were published,
two in the American Economic Review, in the 1970’s, long before Real Business Cycles were
hypothesized. The second Blanchard and Diamond paper cited below discusses and shows the
true cyclicality of Qt .
3) New Classical models strongly imply that labour market migration will be counter-cyclical.
Unemployed workers will search, and some proportion of that search will involve migrating to
another region to search. But migration is, in fact, strongly pro-cyclical. And, again, this has
been well known since the mid-1950’s. Good papers re-establishing this empirically were
published by Vanderkamp – cited below – in 1968 and 1972, again well before New Classical
models. More than a dozen new papers showing this have been published in the 1990s.
Further, return migration has been well established as being counter-cyclical, and this was known
as early as Vanderkamp’s 1968 paper. While this is not inconsistent with New Classical theory, it
is predicted by New-Keynesian, as shown in Allen, 2003.
4) There are no layoffs in New Classical models. All unemployment is workers not taking jobs
because they don’t like the wages being offered. But there are layoffs, and these don’t involve
firms asking workers to accept lower wages and the workers refusing. And layoffs are strongly
counter-cyclical.
5) The misperceptions model predicts that the rate of increase in productivity will be countercyclical. As workers don’t take jobs, firm move up, to the left, along marginal and average
product curves. But the rate of increase in productivity is pro-cyclical.
6) In the early 1980’s, the Canadian unemployment rate rose from around 7% to around 11.5% in a
single year. The US, and a number of European countries, had similar experiences. In the early
1990’s, the unemployment rate rose from about 6% to about 8% in the US, and from 7.5% to 12%
in Canada. To account for these observed changes by way of New Classical models, one would
have to have: either: i) extremely high and extremely inaccurate misperceptions of inflation by
everyone, combined with a very high short-run labour supply elasticity; or ii) an unbelievably
large “negative” shock to productivity – ie, have productivity suddenly decrease by 4.5% in a
single year – combined with a short-run labour supply elasticity of about unity.
Misperceptions of this order of magnitude are utterly implausible. What happened at just that
time to cause those misperceptions? Negative productivity shocks are hard to swallow – although
a plausible case could be made for the two OPEC incidents – but no events of anything like that
order occurred in the early 80s. Nor did any occur in Canada in the early 1990s. To swallow the
labour market behavior
page 6
RBC model, one would have to have had a productivity shock in Canada that was more than
double that in the US. Nothing that could remotely account for this happened.
Finally, all micro-data studies of short-run labour supply elasticity find it to be essentially zero.
B: New-Keynesian
All of the known results are consistent with New-Keynesian models. I use “Keynesian” to mean
the conventional IS/LM model of aggregate demand, with an aggregate supply curve in the
conventional shape, subject to downwardly sticky Prices and Wages. I use “New-Keynesian” to
mean a Keynesian model that has been made dynamic, so that it deals with output and inflation. The
DAD curve is derived from static IS/LM, and fiscal or monetary policy shifts the DAD curve as in
the Keynesian model. The EA-DSAS curve is derived from the Phillips curve and Okun’s law, so it
is positively sloped, and it shifts up and down as inflationary expectations become higher or lower.
Underlying the New-Keynesian model is that Jt and Lt are determined by demand for output. Jt
increases as Aggregate Demand (AE) increases and vice-versa; Lt increases as Aggregate Demand
falls and vice-versa.
Micro-economics predicts that unemployed workers will engage in search when the expected
return from search is greater than the cost of search. When UNt is high and Vt is low, the expected
return from search is low and workers search less. Less search means fewer quits: a worker quits-tosearch only when s/he expects to find a better job (this is standard human capital theory). See Allen,
2003, for a full model of this.
That Vt and UNt move in opposite directions reflects that changes in output are primarily the
result of changes in Aggregate Demand, that “New-Keynesian” models are correct. When Aggregate
Demand falls, Jt and Vt fall because firms are choosing to reduce output, while UNt rises as firms
reduce Ht and increase Lt. When Aggregate Demand rises, Jt and Vt rise because firms are choosing
to increase output, while UN falls as firms increase Ht and reduce Lt. The cyclical behavior of UN
and Vt are dominated by Lt and Jt , which are demand-driven. Lt is strongly and negatively related to
changes in Aggregate Demand, and Jt is strongly and positively related to changes in Aggregate
Demand.
In New-Keynesian models output is mainly determined by demand. Inflation is jointly determined
by the level of Aggregate Demand and inflationary expectations (as in the model you’re doing in the
EXCEL assignment). This model is consistent with all of the stylized facts about labour market
dynamics described above, and actually predicts almost all of those facts. It is also consistent with
the observed variations in output, inflation and the exchange rate over the past two decades.
None of the New Classical models can make that claim. All of them are inconsistent with most of
the stylized facts about labour market dynamics, and some are inconsistent with all of the stylized
facts about labour market dynamics. In addition, all of them have difficulty with the observed
variations in output, inflation and the exchange rate over the past two decades. They have so much
difficulty with this that Robert Lucas, who won a Nobel prize for his work on New Classical macroeconomics, now says that New Classical models “didn’t work”. And presumably, “don’t work”.
labour market behavior
page 7
IV LOOPS, “TIME VARYING NAIRU” or “HYSTERESIS”, SHIFTS OF U* and Y* and
LABOUR MARKET BEHAVIOR
A. Loops, Lipsey and Labour Market Behavior
All supply-side models also have difficulty with the loops, and with “hysteresis” or “TimeVarying NAIRU”. (This latter phenomenon is described in Gordon.) The New-Keynesian model,
because it’s based on a correct model of labour market behavior, has no difficulty with these.
There are four strands to the reasoning here, which weave together to produce a coherent picture.
The first strand is empirical. Labour economists have observed what they labeled “hysteresis”.
Hysteresis is the fact that the NAIRU, Un, the level of unemployment associated with Yn, isn’t a
constant. It isn’t just that it moves around, it moves around systematically. If unemployment stayed
low for some period of time, the NAIRU fell, and if unemployment stayed high for some period of
time, the NAIRU rose. This is described in Gordon, but it was known well before he wrote that
paper. It was observed in most OECD countries during the eighties, when unemployment rates were
high for a contracted period.
The second strand is Phillips’s finding of the counter-clockwise loops around his eponymous
curve. The third strand is Lipsey’s explanation for those loops. The fourth and final strand is also
empirical – it is the actual labour market behavior over the business cycle. You can read Gordon. I
summarize Lipsey below. For these notes, for simplicity I treat inflationary expectations as zero, so I
can ignore them..
The Phillips curve dynamics showed counter-clockwise loops:
W
3
2
4
1
5
0,6
U
U*
The figure above shows a typical seven period cycle (0 – 6) from trough to trough. Lipsey proposed
an explanation for these loops based on the geometry of the curve and how that affects the
aggregation.
First, he noted that the shape was a generalization of a basic Supply and Demand model for
labour. The horizontal axis can be read as: (S–D)/S, where S and D are quantity of labour Supplied
and quantity Demanded in a market. The point where S = D is Un, the point where the curve crosses
the horizontal axis. This is shown in the figure below.
Lipsey then transforms the straight line into the curve for two reasons. First, U cannot be less than
zero, so the curve must asymptotic to some vertical line as it moves left – that is, as (S–D) becomes
labour market behavior
page 8
increasingly negative. This is the dotted line on the figure below. Second, observing that money
wages are sticky downwards, the curve must become asymptotic to some horizontal line as it moves
right – that is, as (S–D) becomes large and positive. (Here I use W = 0 as the asymptote; it’s probably
a bit lower.) This produces a smooth curve, which is the Phillips curve.
Wt
(St – Dt)/St
0
The Phillips curve is an aggregate – a curve for the economy as a whole. But Lipsey noted that
the basic Supply and Demand model applies at all levels of the economy: sectors, geographic regions,
and even individual firms. At each of these levels it would have the shape found by Phillips.
However, when aggregating these lower level curves, something interesting happens.
Consider an aggregate economy consisting of three lower level labour sectors, labeled A, B, and
C. These could be regions, industrial sectors, or occupations, or any combination of these. For
simplicity, I’m going to condense the upswing of a business cycle – that part of the cycle from trough
to peak – to just three time periods. The trough is period 0, the peak is period 2, and period 1 is the
middle of the upswing. The three periods for each of the three sectors is shown below. For each
sector the horizontal axis is (S – D)/S, where S is quantity of labour Supplied (number of workers
searching), and D is quantity Demanded (number of job vacancies). The dotted line is the point
where this equals zero – that is, where S = D. (Or, in a labour market model, where UNt =Vt .) The
vertical axis is rate of change of money wages: W = (Wt – Wt-1)/Wt-1 .
What Lipsey noticed was that, if all three sectors weren’t at exactly the same point on their
curves at the same time, when the three points were aggregated, one would get a point that was to the
right of the true curve! Furthermore, as the distance to the right of the true curve becomes greater,
the difference between the points being aggregated becomes greater! What causes this is the
curvature. As one moves a given horizontal distance to the left twice, the second time one moves up
vertically by more than one did the first time.
This is shown on the figures below. The difference on the horizontal axis between 0 and 1 for
sector A is twice the distance between 0 and 1 for sector B, and in sector C the distance between 0
and 1 is zero. Aggregating these will give a horizontal distance between 0 and 1 that is the distance
in sector B. (Use the distance in sector B as the numeraire, d. To aggregate, first add A + B + C =
(2d + 1d + 0) = 3d, then divide by 3; you get 1d.) Now repeat that process for the vertical distance.
You can see that the vertical distance from the horizontal axis to point 1 in sector A is nearly four
times the distance from the horizontal axis to point 1 in sector B, and it is zero in sector C.
Aggregating these will give a vertical distance of around 1 2/3 the distance in sector B – shown for
labour market behavior
page 9
reference on the sector B graph as point “1-agg”. (Use the vertical distance in sector B as the
numeraire, . To aggregate, first add A + B + C = (4 + 1 + 0) = 5, then divide by 3; you get 1
2/3.)
A
B
C
1
2
1-agg
2
2
1
1
0
0
0
Lipsey’s explanation of the loops begins by noting that the economy is made up of a large number
of smaller sectors. He then argued, and all evidence showed, that during an expansion – the move
from point 0 to point 2 on the sector curves shown above – individual sectors don’t all expand at the
same rate. In the example with three sectors above, sector A expands relatively quickly, sector B
expands at the average rate, and sector C expands relatively slowly. During expansion, then, the
sectors are at different places on their individual “phillips” curves. Aggregating them when they are
at different points gives points to the right of the “true” curve.
Lipsey then argued (and all modern evidence supports) that after a period or two at the peak of the
expansion all markets will have expanded close to equally. They will all be close to the same point
on their individual “phillips” curves. Aggregating will give a point that has moved to the left, close
to the “true” curve. Since the observed points remain to the left during contraction, the assumption
was that contraction affects the individual sectors more smoothly than does expansion.
This is a brilliant piece of reasoning. Chris Archibald, among others, tested Lipsey’s conjecture
by using regional labour markets as the “individual markets” of Lipsey’s theory. His findings
supported Lipsey’s conjecture.
But Lipsey missed one point, one that reinforces his reasoning. That is that quits-to-search, and all
other observable labour market mobility (except return migration), is pro-cyclical. Thus, as
expansion takes place, not only do some markets expand more quickly than do others, but labour
mobility increases substantially. This causes the points in the individual sectors to “converge” to be
close the to the same in each sector. Rather than draw the full graphs, I’ll just write out how this
works.
Look again at the three sectors above. After one period, wages in sector A have risen
substantially; wages in sector B have risen a bit, and wages in sector C haven’t risen at all. Saying
the same thing, S < D in sector A, S = D in sector B, and S > D in sector C. Labour market theory
has workers moving from lower wage, excess supply, sectors to higher wage, excess demand sectors.
Virtually all empirical studies bear out this fairly obvious theoretical conclusion. So, as the economy
expands, workers become more mobile. The mobility is from the slower growing or stagnant sectors,
like sector C above, to the faster growing sectors which will have higher wage growth in order to
attract mobile workers, like sector A above.
labour market behavior
page 10
The mobility will cause the convergence that is shown on points 2 on the three graphs above.
Workers move from C to A. The increased supply of workers in sector A reduces excess demand
there, causing a movement to the right along its “phillps curve”. This also reduces the rate of growth
of money wages in A. The reduced supply of workers in sector C reduces excess supply of labour
there, causing a movement to the left along its “phillps curve”. This also increases the rate of growth
of money wages in C. Both of these continue as long as there are wage and employment differentials
between A and C, and the economy stays at high output/low unemployment. And both of these cause
the points in sectors A and C to converge. As they do, the aggregated point shifts to the left.
B. Time Varying NAIRU or Hysteresis, shifts in Un and Yn and Labour Market Behavior:
My explanation for the “time-varying” NAIRU, or what is often called “hysteresis” in labour
economics literature, uses Lipsey’s idea, but enlarges on it by recognizing the role that labour
mobility plays in causing convergence in individual markets. Lipsey ignored the economic behavior
that would cause individual labour markets to converge. Here I add this behavior, which reinforces
Lipsey’s conjecture.
There are two implications of Lipsey’s geometric/aggregation argument this that are extremely
important. The first is that, since individual sectors will never fully converge (until “we’re all dead”),
the true Phillips curve is always to the left of the observed Phillips curve. The second implication is
even more interesting and important. This implication, combined with observed labour market
behavior, provides a full explanation of so-called hysteresis or “time-varying NAIRU”.
The “true” Phillips curve is always to the left of the observed Phillips curve. But the observed
points move closer to the true Phillips curve as the individual labour markets making up the
aggregate market converge. Since labour mobility, which causes the convergence, is pro-cyclical, the
observed Phillips curve moves closer to the true Phillips curve the longer the economy remains at
low levels of unemployment. That is, the observed Phillips curve shifts left as the economy remains
at low levels of unemployment. As it shifts left, the point where it crosses the horizontal axis, Un,
also shifts left. Voila, the “time-varying NAIRU”!
Both the US and Canadian economies expanded during the decade of the 1990s, beginning around
1992. This was the longest period of sustained expansion – that is, the longest period of continuous
increases in Y – ever seen. Yet inflation rates were remarkable stable, varying within a band of
0.5%. And during this expansion U dropped from over 7.5% in the US in 1992 to 4.0% in
2000. This shows a substantial leftward shift in Un. Studies have also shown that, in fact, regional
labour markets have converged in the US – unemployment differences between regions dropped
steadily during the 1990s. Gordon describes the first half of this expansion; the graph I handed out
describes the entire period from 1990 to 2004. That graph shows that the leftward shift continued
over the entire decade of the 1990s in the US.
[You can reproduce this argument for yourselves for having Un shift right. Normal random
differences in productivity increase cause individual labour markets to pull apart. If the economy is
contracting and unemployment is rising, labour mobility falls. The mechanism that would bring the
individual markets together is disabled. As higher levels of unemployment continue, the markets pull
farther and farther apart from the random disturbances. The farther apart the individual markets, the
farther to the right is the observed Phillips curve, and the farther to the right is the point where it
crosses the horizontal axis, Un. Here the time-varying NAIRU shifts to the right..]
You can see that this analysis uses “supply-side” effects. And it uses a lot of micro-economic
underpinnings. Yet the analysis is purely a Keynesian analysis: labour reacts to changes in output,
but the initial changes in output that drive the changes in labour are caused by changes in Aggregate
labour market behavior
page 11
Demand. The model here builds on known micro-economic facts and uses them to explain known
macro-economic facts. In short, it is good science.
In conclusion, New Classical models get almost everything wrong. New-Keynesian models get
almost everything right. If we follow standard rules of science, which model do we consider correct?
V
A DYNAMIC MACRO MODEL WITH LABOUR MARKET EFFECTS
I don’t have time to write this up, and we’ve run out of class time to do it. You have enough
theory now to see its shape though. Good luck to you all as you finish this semester. To those of
you that go to graduate school, good luck there.
VI
A SHORT BIBLIOGRAPHY
Here is a list of papers which show the labour market cycles and dynamics described above. After
each reference, I give numbers in parentheses of just which facts the paper shows. The references
below are only those that came quickly to me from my own research. It is incomplete.
Allen, Jeremiah. 2003. “The Time Patterns of Internal Migration: Human Capital meets Job
Matching”, Review of Regional Studies, 33, 3. (7,8,4)
2. Blanchard, Olivier and Peter Diamond. 1989. “The Beveridge Curve”, Brookings Papers on
Economic Activity (1), 1–60. (1,2,3,4)
3. Blanchard, Olivier and Peter Diamond. 1990. "The Cyclical Behavior of the Gross Flows of
U.S. Workers." Brookings Papers on Economic Activity, (2), 85-155. (1,2,3,4)
4. Blanchard, Olivier and Peter Diamond. 1992. "The Flow Approach to Labor Markets."
American Economic Review (May) 82(2) 354-359. (1,2,3,4)
5. Devine, Theresa and Nicholas Kiefer. 1990. Empirical Labor Economics: The Search
Approach, New York: Oxford University Press.
6. Eaton, B. Curtis. 1970. “Studying Mass Layoffs Through Markov Chains.” Industrial
Relations 9(4) 394-403.
7. Jackman, R., R. Layard, and S. Savouri. 1991. "Mismatch: a framework for thought." in PadoaSchioppa, 1991, 44-101. (1.2.3)
8. Mortensen, Dale T. 1986. “Models of Search in the Labor Market”, Handbook of Labor
Economics, Amsterdam: North-Holland.
9. Padoa-Schioppa, Fiorella (ed.).1991. Mismatch and Labour Mobility, Cambridge: Cambridge
University Press. (1,2,3,7)
10. Pissarides, C. and J. Wadsworth. 1989. "Unemployment and the Inter-Regional Mobility of
Labour." Economic Journal, 99, 739-755. (8)
11. Vanderkamp, John. 1968. "Interregional Mobility in Canada: A Study of the Time Pattern of
Migration." Canadian Journal of Economics, I, 595-608. (7,8)
1.