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.