Chapter 6 – Functional
Income Distribution
Labor Income and Property
Income
Functional Income Hypothesis:
· the marginal propensity to consume depends on the type of income (labor or property)
· there is a lower MPC for property income than for labor income
· Post Keynesians use this hypothesis
The empirical evidence seems to support the
functional income hypothesis – especially studies use national and not just
disposable personal income. Review p.
79 (Fig 4.4) where the % of income consumed correlates closely to proportion of
labor income.
Definitions: labor
share = labor income/national income
and
labor income = salaries plus
bonuses plus fringe benefits
property share = property
income/national income
and
property income =
proprietors income + dividends + net interest income + rental income + corp
retained earnings
Remember our formulations for c:
c=c1(labor inc) + c2(property
income)
or
c=c1(national income) + c2(labor
share)
Labor Data
1.
Department
of Commerce releases data on personal income 3rd – 4th
week of following month.
2.
1st
Friday of each month – monthly employment report – comes from 2 sources:
a.
Household
survey – visits to 50,000 households (very small number).
i.
Employed
persons are those who, in the survey work, were paid employees or worked in
their own business.
ii.
Unemployed
persons are those who were available for work and, made efforts to find
employment sometime during the prior four weeks.
1.
size
of civilian and total labor force
2.
number
of persons employed and unemployed
3.
duration
of unemployment
4.
number
of job seekers
5.
various
unemployment rates
b.
Establishment
Data – based payroll reports in about 390,000 establishments (a very large
sample) that employ more than 1/3 of all workers in US.
i.
number
of people on payroll for production, manufacturing and mining
ii.
construction
workers
iii.
non-supervisory
employees in private service producing industries
iv.
increases/decreases
in jobs in mfg and service industries
v.
average
weekly hours per employee
vi.
average
hourly earnings (very important to rate at change)
vii.
average
weekly earnings
3 very important indicators from the labor data:
·
additions
to non-farm payrolls -- coincident indicator
·
manufacturing
hours worked -- many analysts believe
this is a leading indicator
·
average
hourly earnings (y/y % change) -- good measure of inflation in labor rates –
can use ppi for material but labor inflation even larger part of inflation
2 problems with the data:
1.
There
are large adjustments to non-farm payroll additions. So use a 3 month moving average.
2.
The
data is seasonally adjusted. There are
some very big issues with seasonally adjusted data. Especially with the entry of students into and out of the
workforce in the summer months.
Show websites:
http://www.bls.gov/ces/ and www.bls.gov/news.release/pdf/prod2.pdf
Show CD with ECO2 on it
NFPAY -- excellent
coincident
MFG HRS WKD -- because
companies will try to manipulate hours worked before resorting to hiring &
firing.
Productivity – real output per hour – usually done
just for non-agricultural.