Master Class Public Finance

  In this essay you will address the most recent recession and the recovery that has followed. Notice as you read the various pieces that there is disagreement over how to analyze the long-term impact of the recession—which also influences how you assess the recovery.  Through the various readings (and there are a fair number that are New York Times articles on assessing the recession and the recovery, these are mostly between 1-4 pages in length) pay attention to the unevenness of the recovery— parts of the country affected differently, different demographic groups also affected differently, for example.  In your essay how to do you analyze the recession and the recovery that has followed. In your essay there are two terms you should try to understand and incorporate into your writing: structural unemployment and gini ratio (or gini coefficient). GUIDELINES (to summarize) 1) Address the following: How do you analyze the recession and the recovery that has followed. 2) The terms structural unemployment and gini ratio (or gini coefficient) should be discussed 3) As part of your essay, why do you think it is so hard to reach a consensus on how to understand the recovery that we are currently going through. 4) Your essay should be a minimum of five typed pages 

5. Please reference the articles attach to be include in the paper.

Economic
Policy
Institute Brief ing Paper

1660 L Street, NW • Suite 1200 • Washington, D.C. 20036 • 202/775-8810 • http://epinet.org

MEASURING EMPLOYMENT
SINCE THE RECOVERY
A comparison of the household

and payroll surveys

by Elise Gould

Tracking the state of the overall U.S. economy requires accurate employment measurements. How-

ever, the two primary measures of employment statistics—the payroll survey and the household

survey—have shown differing trends and levels in employment since the recession began in March

2001. Some differences between the payroll survey and the household survey are detailed below:

• The payroll survey provides a more accurate picture of employment trends in the U.S.

economy. In addition to being significantly larger (with a sample size 600 times greater than

that of the household survey), it is also benchmarked annually to unemployment insurance

tax records and less likely to be subject to large revisions or misreporting.

• According to the payroll survey, employment has fallen by 726,000 jobs since the end of the

recession in November 2001 and employment has fallen by 2.4 million since the start of the

recession in March 2001. In contrast, the household survey indicates that employment has

risen by 2.0 million since the recovery began and by 600,000 since the start of the recession.

• Adjustments for differences between the two surveys (e.g., to account for self-employment or

multiple job holding) do not affect the difference in the trends of the two surveys since 2001.

2

Nonpartisan government experts agree that the payroll survey employment numbers are more

reliable than those from the household survey, despite Secretary of Labor Elaine Chao’s erroneous

claim that experts do not know which survey is better (Utgoff 2003; Congressional Budget Office

2003).1 However, some analysts continue to mistakenly use the household survey to measure

employment.2 Others incorrectly report trends in the household survey, while ignoring the disconti-

nuity in the series that results from the January 2003 population adjustment.3 The payroll survey’s

more precise measure of employment trends provide a clear advantage to the more volatile and

less accurate household survey numbers.

What surveys provide employment statistics for the United States?
Employment statistics for the United States come from both the Current Population Survey (CPS)—

also known as the household survey—and the Current Employment Statistics survey (CES), also

known as the payroll survey. The household survey is a sample survey of about 60,000 households

conducted by the U.S. Census Bureau for the Bureau of Labor Statistics (BLS). Its sample, based

primarily on the U.S. Census, is designed to reflect the entire civilian noninstitutional population.

The payroll data are collected from employers’ payroll records of about 400,000 individual

worksites. This information is gathered by the BLS from a sample based on the unemployment

insurance tax records. Both the household survey and payroll survey data are collected for the

week of each month containing the 12th of that month.

Why is the payroll survey more accurate than the household
survey?

• The payroll survey samples 400,000 business establishments. This represents an average of 40

million jobs each month; in September 2003, 40.5 million jobs were sampled (Getz 2003). In

contrast, the household survey samples only 60,000 households, representing fewer than 70,000

workers. In September 2003, employment estimates were based on a sample of 67,804 workers.

Thus, the payroll survey sample covers 600 times as many workers as the household survey.

• The payroll survey employment estimates are benchmarked to the unemployment insurance

tax records. This yearly process anchors the payroll employment numbers to the comprehen-

sive count of all nonfarm payroll employment. The household survey, on the other hand, is

benchmarked only once a decade to the decennial census, resulting in a less precise employ-

ment measurement than the payroll survey.

• Large revisions and misreporting are also less likely for the payroll than for the household

employment numbers. In recent years, the household survey has undergone far more exten-

sive revisions than the payroll survey, particularly with respect to population estimates. In

January 2003, an additional 576,000 jobs were added.

3

• The household survey’s smaller sample size contributes to the increased variability in its

employment estimates. Figure 1 displays the employment estimates for the household survey
and the payroll survey. The household survey is extremely volatile, indicating its inadequacy

for analyses of month-to-month employment

trends.

• Statistical agencies use the payroll survey for measuring employment trends and for other analyses

of economic conditions. For instance, the Bureau of Economic Analysis (BEA) uses employment,

hours, and wages from the payroll survey to estimate gross domestic product (GDP) for service

industries, and the BLS relies on payroll employment and hours (supplemented with self-employ-

ment from the household survey) to estimate productivity. The strengths of the household survey

are in measurements that the payroll survey is not set up to do, such as the unemployment rate,

self-employment, the employment-to-population ratio, occupations, and breakdowns by demo-

graphic. While the household survey is useful for measuring this type of economic information,

the payroll survey is a much better tool for measuring employment levels and trends.

FIGURE 1

Payroll and household survey employment trends

* Adjusted for population discontinuities.

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Household survey employment*

Payroll survey employment

Jan. July Jan. July Jan. July Jan. July Jan. July Jan. July
1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003

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Government experts agree that the payroll survey is more accurate
Both the Congressional Budget Office and the Bureau of Labor Statistics have commented on their

preference for the payroll survey numbers over the household survey numbers:

“The establishment [i.e., payroll] survey better reflects the state of labor markets, the Congressional
Budge Office believes, not only because other indicators also imply rather weak labor market

conditions but because large revisions or misreporting appears less likely for the establishment than

for the household data. Data on tax withholding conform better to the establishment survey’s results

than to the household survey’s; in addition, both the share of employed people who are working part

time for economic reasons and the still-low labor force participation rate indicate weaker labor

markets than those existing at the trough. Three other measures suggest the same conclusion:

during the first half of the year, the unemployment rate rose, both initial and continuing claims for

unemployment insurance remained elevated, and the help-wanted index fell.” (emphasis added)

—Congressional Budget Office 2003, p. 11

“It is our judgment that the payroll survey provides more reliable information on the current trend in
wage and salary employment. The payroll survey has a larger sample than the household survey—
400,000 business establishments covering about one-third of total nonfarm payroll employment.

Moreover, the payroll survey estimates are regularly anchored to the comprehensive count of

nonfarm payroll employment derived from the unemployment tax records.” (emphasis added)

—Bureau of Labor Statistics 2003, pp. 4-

5

A response to critics of the payroll survey
Some have speculated that the household survey provides a better indication of the trend in em-

ployment at and around turning points in the business cycle. These critics question whether the

payroll survey accurately and fully picks up new businesses, known as “firm births.” This problem

may be especially exacerbated when measuring employment in a recovery.

In its estimates of employment, the BLS addresses the problem of firm births and deaths using

past history and various estimation techniques to provide an adjustment factor to the current series.

In addition, updates to the payroll survey are conducted annually to adjust for any discrepancies.4

In September 2003, Allan Meltzer speculated in The Wall Street Journal that the BLS may have
been undercounting post-recession firm births. Meltzer was expecting the revised numbers to show

an increase in employment because generally revisions are upwards in a recovery; that is, revised

employment numbers add to the ranks of the employed. However, the BLS announced in October

that its analysis of detailed tax records through March 2003 would result in a downward revision of

total nonfarm payroll employment by approximately 145,000 for the March 2003 reference month

(BLS 2003b).

A second critique of the payroll survey is that it leaves out self-employment. However,

because the household survey employment reports do not distinguish between the self-employed

who are gainfully employed and those who are searching for work—and because the numbers of

5

self-employed nonearners would be expected to increase during tough economic times—the omission

of self-employment numbers from the payroll survey may more accurately reflect overall employment

trends.

Population adjustments to the household survey
The BLS periodically revises the household survey to account for new Census Bureau population

estimates. In the last four years, there have been two population adjustments: one in January 2000

and one in January 2003. The shift in January 2000 was based on the new population estimates

from the decennial Census and added about 1.5 million persons employed. The shift in January

2003, based on new estimates of faster than expected population growth since the 2000 Census,

added another 576,000. At each shift, a discontinuity occurs in the series, reflective of only new

population estimates and not an actual jump in employment.

To make valid comparisons with the numbers since January 2003, previous employment

numbers must be adjusted upward to account for new population estimates. The BLS warns that

use of the household survey employment numbers without making these adjustments makes any

estimates of trends since January 2003 not comparable with those for earlier months (Bowler et al.

2003). The household employment estimates in Table 1 reflect these population adjustments.
One of the most egregious mistakes made by some analysts reporting employment trends is to

omit these population adjustments in their estimates. One such omission was in a Heritage Foun-

dation report, based on the household survey numbers, which claimed that more than one million

new jobs had been created between October 2002 and October 2003 (Beach and Hederman 2003).

This report improperly includes the 576,000 jobs added in January 2003 due to the upward revi-

sion to population that month. Additionally, the payroll survey, a better indicator of employment

trends, indicates a loss of 291,000 jobs during the same time period (see Table 1).

Unfortunately, because BLS publications do not highlight the break in series caused by the

increase in population in January 2003, this is a relatively common mistake in the media. Robert

TABLE 1:
Employment trends using the payroll and household surveys

Date Payroll employment Household employment*

March 2001 132,527,000 138,002,503
November 2001 130,900,000 136,586,11

9

October 2002 130,408,000 137,532,428
October 2003 130,117,000 138,014,000
November 2003 130,174,000 138,603,000

Oct. 2002 to Oct. 2003 -291,000 481,572

Nov. 2001 to Nov. 2003 -726,000 2,016,881
March 2001 to Nov. 2003 -2,353,000 600,49

7

* Population adjusted.

6

Samuelson, columnist for The Washington Post, and Floyd Norris, reporter for The New York Times,
left out the BLS updates to the household survey data in their reporting of employment trends

(Norris 2003; Samuelson 2003a). To his credit, Samuelson promptly posted a correction to his

employment numbers (Samuelson 2003b). Use of the payroll survey, which is less susceptible to

large revisions and more accurately measures employment, would have avoided these and other

similar miscalculations in employment numbers.

What are the trends in employment?
The National Bureau of Economic Research determined that the trough in business activity oc-

curred in November 2001 for the recession beginning in March 2001. Therefore, we examine

trends since the beginning of the recession and since the beginning of the expansion—March 2001

and November 2001, respectively.

Since the beginning of the recession, employment has fallen by 2.4 million jobs. Since the

end of the recession two years ago, there have been about 726,000 jobs lost, marking this as a

period of “jobless recovery.”

How is employment defined in the household and payroll surveys?
The household survey counts people as employed during the reference period if they worked as a

paid employee, worked on a farm, were self-employed, worked without pay in a family business,

or worked in a private household. The household survey also counts people as employed if they

are on unpaid leave during the reference period. The payroll survey, however, only counts people

as employed if they were nonfarm workers who worked for pay for any part of the reference

period (including persons on paid leave), excluding the other categories of workers measured by

the household survey. To reconcile these differences, the household survey must be reduced by

agricultural workers, the self-employed, unpaid family workers, private household workers, and

those on unpaid leave.

On the other hand, the payroll survey counts each job separately when employees work at

more than one job. The household survey counts each employee only once regardless of the

number of jobs they hold. The household survey employment numbers must be increased to

include multiple job holders to make it comparable with the payroll survey.

How does the household survey reconciliation
alter employment numbers?
To better understand why the surveys display different trends, it is important to make the two

surveys as comparable as possible. In this section, the household employment numbers are

adjusted to account for the differences in the surveys. Specifically, this reconciliation subtracts

agriculture, self-employment, private households, unpaid family workers, and those on unpaid

leave, and adds multiple job holders to the reported household employment numbers. The house-

hold employment numbers are seasonally adjusted to make the two surveys comparable.

7
120
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Household survey
employment reconciliation

As shown in Figure 1, the household and payroll survey employment levels ebb and flow,

sometimes drawing close together and sometimes shifting further apart. In January 1998, the

difference between the two surveys was 7.3 million. In July 2000, the surveys were as close as

4.7 million, while in October 2003, the difference was back up to 7.9 million.

The household survey reconciliation brings the employment estimates much closer together

(see Figure 2). For much of the series, payroll employment is higher than the reconciled house-
hold survey. The July 2000 gap shrinks from 4.7 million before the reconciliation to 2.4 million

and the October 2003 gap shrinks from 7.9 million to 158,000. The levels of employment are

much closer and the difference in trends for the recovery is reduced by about one-third. The

household survey reconciliation indicates a gain of one million jobs since November 2001 and

100,000 jobs since March 2001. With the reconciliation, the difference in employment trends

since November 2001 is 1.7 million, whereas without the reconciliation, there is a difference of

2.7 million between the household and payroll employment trends (see Table 1).

The employment trends of the payroll survey and the household survey reconciliation still

produce divergent results, though the differences are smaller than before the reconciliation. The

fact remains that the household and payroll surveys report different trends since 2001. Because

the trends are different, it is important to report the employment numbers from the more accurate

survey. The payroll survey remains the best indicator of employment trends.

FIGURE 2

Reconciliation of payroll and household survey employment

Jan. July Jan. July Jan. July Jan. July Jan. July Jan. July
1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003
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Conclusion
The payroll survey has a clear advantage in measuring employment trends in the U.S. economy. The

payroll survey employment numbers are based on one-third of total nonfarm payroll employment and

are benchmarked to the complete enumeration of nonfarm payroll employment yearly. Overall, the

payroll survey provides a more precise and less volatile measure of employment and employment

trends than the household survey.

December 2003

Endnotes
1. Chao’s comment was that the “experts may argue about the advantages and disadvantages of each survey”
(Chao 2003).

2. See, for example, Melloan (2003).

3. See The Heritage Foundation (2003) and Norris (2003).

4. The BLS has revised its updating process to produce these corrected estimates even faster than in previous

years. For instance, the data up through March 2003 will be updated in February 2003 rather than June 2004.

9

References
Beach, William W. and Rea S. Hederman Jr. 2003. “Tax cuts working: Over one million new jobs.” The Heritage

Foundation, WebMemo No. 363. Washington, D.C.: The Heritage Foundation.
< http://www.heritage.org/Research/Taxes/wm363.cfm >

Board of Governors of the Federal Reserve System, Division of Research and Statistics. 2003. Reconciliation of
Household and Payroll Employment. Washington, D.C.

Bowler, Mary, Randy E. Hg, Stephen Miller, Ed Robison, and Anne Polivka. 2003. Revisions to the Current
Population Survey Effective in January 2003. Washington, D.C.: Bureau of Labor Statistics.

Bureau of Labor Statistics. 2003a. The Employment Situation: August 2003. Washington, D.C.: Bureau of Labor
Statistics. USDL 03-467.

Bureau of Labor Statistics. 2003b. The Employment Situation: September 2003. Washington, D.C.: Bureau of
Labor Statistics. USDL 03-523.

Bureau of Labor Statistics. 2003c. CES Net Birth/Death Model. Washington, D.C.: Bureau of Labor Statistics.

National Bureau of Economic Research, Business Cycle Dating Committee. 2003.
< http://nber.org/cycles/july2003.html >

Chao, Elaine. 2003. Where the workers are. The Wall Street Journal, December 9.

Congressional Budget Office. 2003. The Budget and Economic Outlook: An Update. Washington, D.C.: Congres-
sional Budget Office.

Kathleen Utgoff. 2003. Commissioner, Bureau of Labor Statistics before the Joint Economic Committee. U.S.
Congress, September 5.

Melloan, George. 2003. That ‘jobless recovery’ isn’t so jobless after all. The Wall Street Journal, December 9.

Meltzer, Allan H. 2003. A jobless recovery? The Wall Street Journal, September 26.

Norris, Floyd. 2003. Grasping at the statistics on the self-employed. The New York Times, December 6.

Getz, Patricia. 2003. Personal correspondence with the Division Chief, Current Employment Statistics, December 9.

Samuelson, Robert. 2003a. Economic turnaround? The Washington Post, July 30.

Samuelson, Robert. 2003b. The ‘big media’ myth. The Washington Post, August.

SOURCE: Governing (CERNIK SAYS—This is a good publication to become aware of if your interest is the

study of American state and local governments)

HERE FOR THIS ARTICLE ONLINE: http://www.governing.com/columns/public-finance/effect-federal-

budget-cuts-states-localities.html#

The Effect of Federal Budget Cuts on States and Localities

When the federal government starts reducing its deficit, watch out below!

BY: John E. Petersen | January 2011

The electorate made it clear in November: Congress should cut up the federal credit card and
restore fiscal sanity. Road maps on how to do that were seldom mentioned. And it’s no wonder,
since getting to a balanced budget will be exceedingly painful.

Right now, the federal deficit runs around $1.4 trillion dollars. A big share of that — $1 trillion — is
cyclical and caused by the Great Recession and accompanying stimulus spending and tax cuts. The
remainder — $400 billion — is structural or “built-in” to the budget. With the current economy
recovering slowly, the federal government raises in current revenues about 57 cents to 63 cents for
every dollar it spends. Even in good times, it raises only 90 cents for every dollar spent. Given the
existing tax system and the way Medicaid, Medicare and Social Security are designed, that
structural deficit is destined to increase steadily. So we’ll have to cut spending, raise taxes or a
combination of both.

But what programs do we cut and what taxes do we raise? The answers unleash a political fight too
large for this humble column to take on. But we know one thing: State and local governments are
deeply tied to federal finances, and they will feel the pain from federal cost cutting and revenue
increasing.

In fiscal 2010, $654 billion in federal grants went to states and localities — an amount that equaled
26 percent of all state and local spending. A big chunk last year represented funding from the
American Recovery and Reinvestment Act, payments from which have peaked and are rapidly
phasing out, reducing annual payments to state and local governments to about $60 billion. But that
reduction in temporary federal outlays does not figure into reducing the “structural deficit.” The $400
billion gap still must be closed. The billions in federal programs directed toward state and local
governments — and the multitude of tax preferences that benefit them — will provide fertile grounds
for filling the deficit hole.

Let’s look at grants, one of which is Medicaid. More of the Medicaid load might be shifted to states,
which now annually contribute $150 billion of their own funds to match federal grants of $220 billion.
The feds might save $35 billion by making that cost match 50-50 across the board. Meanwhile,
federal grant programs for education send $80 billion per year to the states; and another $200 billion
to income security, transportation and community development programs. If the feds reduce all
grants by 20 percent, a $100 billion revenue hole would be created in state budgets — but only 25
percent of the federal structural budget gap would be closed.

That’s not even the major danger. Via their taxpayers, states and localities receive indirect benefits
through federal tax deductions and credits. These “tax expenditures” (foregone revenues because of
preferential tax treatments) amounted to $73 billion last year, including the deductibility of state and
local property, income and sales taxes ($51 billion), and the exemption of the interest on state and

local bonds and interest from federal income taxation ($22 billion). These preferences are on the
chopping block, and their loss or reduction would prove costly to state and local governments whose
citizens would find their tax burden increasing.

Finally, there are indirect cost-cutting or tax-increasing measures. Under federal tax laws,
homeowners now write off their mortgage interest costs. Over the years, this favoritism has driven
up housing prices. Real estate values, now in very bad shape, serve as the foundation for local
property taxes. But the feds lose $100 billion or so from the interest deduction. That makes it an
attractive target for reducing the federal deficit. But such a step might permanently bend down future
growth in housing prices and accordingly, the property tax base.

And there’s more. Expanded use of user charges and sales taxes to enhance federal revenue would
mean intense intergovernmental competition for revenues. For example, raising the federal motor
fuel tax by 25 cents to reduce the deficit would mean $30 billion in added federal revenues. But that
would curb the ability of states to raise such taxes, even in the event of declining revenues.
Ultimately all tax collectors go to the same well for water.

State and local officials must prepare for the fiscal Armageddon. This admonition may come as a
shock to newly elected governors and state legislators who rode into office astride promises to cut
back government. They are likely to find that that job will be done in Washington. Overnight, they
may have a lot less money to spend and more needs to spend it on.

This article was printed from: http://www.governing.com/columns/public-finance/effect-federal-
budget-cuts-states-localities.html