A P R I L

2 0 0 0

S P R I N G

Doing
Stephen W. Gilliland
Associate Professor and FINOVA Fellow of
Management and Policy in the Eller College
of Business and Public Administration at
the University of Arizona.

Donald H. Schepers
Assistant Professor of Management at
Baruch College, City University of New York.

O

ver the past year, the economy has
continued to demonstrate remarkable strength. Businesses are
growing and unemployment rates are
lower than at any point in recent history.
And yet the Chicago-based outplacement
firm Challenger, Gray, and Christmas
recently reported that layoffs rose to record
levels in 1999. Why are layoffs accompanying such business prosperity? One obvious
reason is the continued business consolidation through mergers and acquisitions.
Arizona has experienced first hand the
combining of Raytheon and Hughes,
Norwest Bank and Wells Fargo, Honeywell
and AlliedSignal, Phelps Dodge and Cyprus
Amax. These and other mergers and acquisitions often result in staffing redundancies
that are eliminated through layoffs. An
additional factor driving increased layoffs
is that businesses have adopted targeted
layoffs as a competitive business strategy.
Unlike the broad, sweeping layoffs of the
late 1980s and early 1990s, which were
sometimes taken to the extreme point of
“corporate anorexia,” many businesses
now use selective layoffs with managerial
precision. Even the booming high tech and

I S S U E

Right
Internet business world has embraced layoffs as corporate strategy, with recent layoffs
occurring at Amazon, Apple, Toshiba, and
Compaq.
Using layoffs as a management tool fits
economist Joseph Schumpeter’s ideas about
“creative destruction.” Schumpeter argued
that organizations should systematically
abandon established products, services, and
processes and allocate resources toward
those activities that promote and reward
creativity. Clearly, layoffs can be part of the
creative destruction process. And yet, organizations are not just economic entities, but
are also social systems. Employees develop
shared understanding or culture, which can
be part of an organization’s competitive
advantage. Although Southwest Airlines has
clearly developed competitive advantage
through fleet management and customer
service, a large part of their sustained advantage has come from people management
and a highly effective organizational culture.
Layoffs can have destructive effects on an
organization’s culture; management literature
and stories in the popular press are filled
with horror stories of companies that have

ELLE R COLLEGE OF BUSINESS AND PUBLIC ADMINIST RATION

done a poor job of implementing their downsizing. Most managers can probably relate an
example of ineffective downsizing from either
their own company or a colleague’s company.
However, we also see a number of examples
of companies that are doing it right. Indeed,
considerable research has demonstrated that
managing the layoff implementation process
is critical for effective downsizing (for a
summary, see the box entitled “Five Steps
for Effective Downsizing”).

WHAT IS REALLY GOING ON?
This makes us wonder what is really happening. Are companies doing downsizing
right the exception or the rule? Are the horror
stories a thing of the past or are they the
norm? We conducted a survey of HR managers
to address these questions.
The Study
We sent surveys to a sample of Society
of Human Resources Managers (SHRM)
members who held the title of HR director
or HR manager and received 543 responses
from a broad cross-section of industries.1
Approximately 28% indicated some unionization at the employee level. Company sizes

I N S I D E
E-COMMERCE PRIMER...........5
INCOME GAP NARROWS .......8
FORECAST TABLES ..............11
ARIZONA
ECONOMIC INDICATORS ......12

FIGURE 1
Reasons for Layoffs

ranged from 50 to 150,000 and represented
employers of approximately 3.5 million
employees total.
The most common reasons for layoffs were
organizational restructuring, market downturn, and general reduction in force (see
Figure 1). Respondents described the way
they had implemented their most recent layoff along the following dimensions:
• Amount of notice given (days)
• Method of informing (individual meeting,
group meeting, or memo)
• Amount of information provided (range
from none to all pertinent)
• Manager demeanor (range from strictly
business to highly involved)
• Escorting employees off premises (range
from never to always).

THE FINDINGS
On average, respondents provided almost
30 days advance notice of the layoff, with less
than 20% providing no notice. Consistent with
the Plant Closing Law, more notice is given
when the layoff involves more than 50 people
(average 41 days) than when it involves less
than 50 people (average 21 days). These results suggest that the majority of companies
do provide advance notice to employees,
and while legal requirements influence this
PAGE TWO

FIGURE 2
Primary Mode of Informing
Employees They had Been
Laid Off

5 Steps for Effective Downsizing
1. Advance Notice. Organizations
should provide ample advance notice
to employees, thereby giving victims
and survivors the opportunity to
prepare for the layoff.
2. Individual Communication. When
possible, the actual layoff should
be communicated in face-to-face
individual meetings.
3. Give Full Information. People are
better able to accept negative decisions if they understand the reasons
behind the decisions.
4. Treat with Dignity and Respect.
A layoff is a business decision, but
it can be communicated in a personal and sensitive manner. As with
information, it costs nothing to treat
individuals with dignity and respect.
5. Escorting Employees off the
Premises is Usually Not Necessary.
Certainly, if a company is striving
to treat individuals with dignity and
respect, they should not be escorted
them off the premises. Security risks
are inversely related to prior trust
shown toward employees.

FIGURE 3
How Much Information
was Released?

practice, many organizations are providing
notice even when not legally required to do so.
Methods of informing individuals of the
layoff are summarized in Figure 2. Almost
95% of respondents use individual or group
meetings and most of those use individual
meetings. This is consistent with the practices relayed by one HR manager in which
her company used individual meetings unless
the layoff was so large that it would have been
unreasonable for the two-person HR staff to
conduct these meetings, in which case they
used meetings with groups of 30 employees.
The horror stories involving “pink slips” and
impersonal memos appear to be the exception and not the rule. In fact only one respondent indicated that they used pink slips to
inform employees of the layoff.
Information tends to be shared with layoff victims in almost 90% of the cases (see
Figure 3). This information sharing often
includes time for question and answers. One
company told us that the informal “rumor
mill” so effectively disseminates information
regarding the necessity for the layoff that when
the decision is actually communicated to
individuals, most questions deal with benefits
and opportunities for rehire.
Manager demeanor during the communication of the layoff decision appears to be highly
variable in our sample (see Figure 4) with
more individuals getting at least minimally
ARIZONA’S ECONOMY

FIGURE 4
Demeanor During
Implementation of the Layoff

FIGURE 5
Were Employees Immediately
Escorted from the Premises
after Layoff Announcement?

involved rather than maintaining distance. In
our interviews with HR professionals we also
heard that demeanor can be highly variable
within an organization. Those managers that
tend to be more effective and tend to have
better relationships with their employees also
tend to do a better job of communicating
the layoff decision. It seems that one of the
barriers to personal touch in the layoff communication may actually come from legal
concerns and is formalized in layoff implementation plans. We heard from a number of
HR professionals that the layoff implementation guidelines give explicit instructions on
not apologizing and not getting personally
involved to reinforce the fact that the layoff
was a business decision and was nothing
personal. A few companies go so far as to
provide actual scripts to managers to use
when communicating the layoff.
Perhaps our biggest surprise in the results
was with respect to escorting employees.
Over 55% of our respondents indicated that
they never escort employees off the premises
and less than five percent always escort (see
Figure 5). The most illuminating discussion
of this came from a high tech Arizona-based
manufacturing firm with extensive security
in the manufacturing and management facilities. More than most firms, this company has
to be concerned about security and sabotage.
In their first layoff, they escorted people out

of the building and this action, more than
anything else, was heavily criticized by both
victims and survivors. They have never again
escorted in the numerous rounds of successive layoffs and instead give employees two
days to clear up and say goodbye. When asked
about concerns regarding security and sabotage they stated, “we trust these people when
they are our employees and we will continue
to trust them when we have to lay them off.”

ARIZONA’S ECONOMY

CONCLUSIONS
Our survey of over 500 HR directors and
managers suggests that many companies are
doing downsizing right. Advance notice tends
to be provided. Individual or, in some cases,
group meetings are used to communicate
the decision and this is often accompanied by
question and answers and much information
sharing. And although manager demeanor
is quite variable, most companies do not
regularly escort laid-off employees off the
premises. These results suggest that the
horror stories regarding downsizing practices
may actually represent a minority of cases.
It is also interesting to note that there
appears to be a learning process regarding
downsizing practices in some organizations.
The earlier cited case of the company that
initially escorted and then ceased that practice
is one example. The size and experience of the
“layoff team” may be a factor in this learning.

In one company, the layoff team (comprised of
employee relations specialists and managers)
actively reviewed each layoff to identify what
worked and what did not work. At the other
end of the continuum, we also talked to companies that do a poor job of downsizing and
believe they should “get it done, move on,
and put it behind us.” This approach does not
promote learning and the poor layoff practices
appear to continue.
Although the overall picture suggests that
many organizations are doing downsizing
right, there are still a number of companies
that could improve their layoff practices. For
example, one quarter of the companies in our
survey indicated that they escort employees off
the premises sometimes, often, or always. We
tried to determine if there is something about
a layoff or organization that explains this
action on the part of companies, but indicators such as industry type, organization size,
and reason for the layoff were all unrelated
to escorting practices. One possibility is that
poor layoff practices result from unfounded
fear or lack of trust toward the employees.
Ironically, organizations that try to prevent
sabotage by escorting layoff victims off the
premises may actually be creating more
problems and potential for sabotage among
their surviving employees. One survivor of
a particularly harsh and unfair layoff in a
California bank attempted to get even with
his employer by planting a “logic bomb”
in the company’s payroll system. Files were
deleted and the computer system was shutdown. As a result of this sabotage, the bank
lost considerable credibility among its
customers and several managers in the
computer division were fired. Organizations
must remember that the benefits of doing
downsizing right extend to both downsizing
victims and survivors, and thus eventually
to the company. Effective downsizing is one
important component of effective human
resource management. ■
For more information on the survey and sampling
procedure, as well as a complete summary of the results,
see Gilliland, S.W. & Schepers, D.H. (in press), “Why
we do the things we do: A discussion and analysis of
determinants of just treatment in layoff implementation
decisions,” Human Resource Management Review.
1

This study was funded by a grant from the SHRM
Foundation. The interpretations, conclusions, and
recommendations, however, are those of the authors,
and do not necessarily represent those of the foundation.
PAGE THREE

E D U C ATION AN D PROFE SS IONAL PRO G R A M S

eBusiness
Strategies
& Technology
May 4 & 5, 2000
The University of Arizona
Tucson, Arizona

eBusin
Are you eSavvy?

Your
answers
are
important!
Your
answers
are
protected
by law.

“If everything’s under control,
you’re going too slow.”
~Mario Andretti

Presented by:

Eller College of Business
and Public Administration

In Partnership with:

The University of Arizona Foundation

Corporate Partners:

COMPAQ
FINOVA Capital Corporation

For more information:

PAGE FOUR

go to: www.bpa.arizona.edu/ebusiness
or call: 520-621-2930
or e-mail: ExecEd@bpa.arizona.edu

A RI ZO NA 'S EC ONO M Y

WHAT’S IN A NAME?
B2B DIALOGUE NEEDS DECIPHERING
by Mary Campbell
Editor, The FINOVA Quarterly

M

ake the rounds of Internet business bulletin boards and chat rooms and
you’ll soon discover that when it comes to business-to-business electronic
commerce, the vocabulary hasn’t kept up with the vision.

Check a little further—visit Web sites that
offer B2B resources, for example—and you’ll
find the confusion pervasive. The phrase
business-to-business [or B2B or B-to-B]
electronic commerce, in fact, has at least
three distinct meanings:
• Open buying and selling among
businesses on line. This is still the most
common model, analogous to shopping at,
say, Office Depot down the road, where some
of the customers are college students buying
wireless phones and some are businesses
looking for software and bulk coffee bargains.
• Intercompany (vendor-to-manufacturer, for example) online systems that
facilitate selection, purchase, and payment
by preselected trading partners. Sometimes
these arrangements function like intranets,
with the Internet as the communication
medium; certain business customers have
password-enabled access to online ordering,
inventory, and invoicing, for example.

PROJECTED GROWTH
IN ELECTRONIC
COMMERCE,
WORLDWIDE,
U.S. DOLLARS

• Brokers or hubs for other buyers
and sellers; infomediaries—said to be
the future of B2B E-commerce.

TOUGH TYPECASTING
Attempts to create tidy categories for online business have yielded varying results, to
say the least. The University of Texas/Cisco
Systems ongoing Internet Economy Indicators
study identifies four segments of the Internet
economy. All overlap, especially the first
two—(1) Internet infrastructure (telecommunications and fiber backbones, dial-up
networking) and (2) Internet applications
—where telecommunication companies and
the likes of Cisco, Dell, IBM, HP, Oracle,
Microsoft and Sun provide the servers,
modems, routers, PCs, and other products
and services that equip the Internet for electronic commerce. The other two segments
are (3) E-commerce—companies selling
products and services either exclusively on

the Internet (Amazon.com) or on line as
part of a larger “bricks and mortar” business
(Southwest Airlines); and (4) electronic
intermediaries or Internet middlemen, such
as eBay, that facilitate interaction between
buyers and sellers. The UT study does not
differentiate between B2B (business-tobusiness) and B2C (business-to-consumer)
E-commerce.
In one online bulletin board discussion,
participants commented on the purported
shift in E-commerce from “the Internet as a
boundless marketplace” to “the Internet as
a way to improve trading systems between
business partners.” One executive, whose
company is engaged in online buying and
selling, admitted he had “never understood
the distinction between business-to-business
and business-to-consumer E-commerce.”
But the editor of an electronic-commerce
E-mail newsletter countered that B2C E-commerce “never really existed” except in the
case of travel and auction sites and “places
like Amazon.com…. B2B EC is simply more
profitable, simpler, and more in demand
than B2C,” he concluded, though predicting
that B2C will grow as a percentage of all
E-commerce. ■
Note: Visit the Internet Economy Indicators site for study
methodology and findings. The “facts” page includes an
estimate of global Internet commerce revenue since 1998—
more than $109.6 billion. The figure is continually updated,
and the numerals on the right—ones, tens, hundreds,
and thousands columns—move at dizzying speeds.
www.internetindicators.com

• All researchers cited expect business-to-business electronic commerce to dwarf businessto-consumer online sales, taking a bigger and bigger share of the total online market.
• International Data Corporation’s projection for online B2B sales in 2002 is much more
conservative than the Forrester Research estimate for two years earlier ($330.6 billion
versus $843 billion).
• B2B sales by infomediaries compared to all B2B sales on line estimated at 1.7% in 1998,
25% or more by 2002, depending on source of projection.

E-Commerce Type

1998

1999

2000

Online B2C Sales

7.8 billion

18 billion

Online B2B Sales

43 billion

B2B Sales through
Infomediaries

750 million (B2)

*

2002

2003

2004

NA

NA

108 billion

NA

100 billion

843 billion (F)

330.6 billion (I)

1.3 trillion (F)

1.5 trillion (G)

NA

NA

211 billion (B2)

NA

NA

NA = Not Available, (I) = International Data, (F) = Forrester Research, (G) = Goldman Sachs & Co., (B2) = Business 2.0 magazine, *Comparable 2001 Data NA

ARIZONA'S ECONOMY

PA G E F IV E

THE INFOMEDIARIES
by Gerald J. Swanson
Associate Professor of Economics, Eller
College of Business and Public Administration

with Mary Campbell

B

usiness-to-business E-commerce
has rapidly evolved from simple
to specialized in three stages:

1 Basic business-to-business
E-commerce is easy to grasp.
The process varies little from open-market
offline trading or from business-to-consumer
E-commerce.
2 Internet-enabled intercompany
buyer-seller arrangements, designed
to the specifications of the participants, are
more complex. Companies that establish such
online relationships with trading partners
differ in their motivation. Some want to make
it convenient to do business with them and
inconvenient to do business with competitors.
Participants generally aim to add value and
strengthen relationships. One international
shipping company set up its B2B network to
do away with the cumbersome mechanics of
phone calls and faxes.
3 The fastest-growing B2B model
involves “infomediaries” and has taken
many by surprise, given the hoopla in recent
years about disintermediation—the obsolescence of the middle man. The Internet
was supposed to do away with the middle
man. With producers and consumers able
to connect directly, there was believed to be
no need for other links in the supply chain.
That turned out to be only partially true.
The Internet has unquestionably displaced
a great many middle men—ask any travel
agent or independent bookstore owner. But
in their place has emerged a new group
unique to the world of E-commerce. These
infomediaries are vertical market makers,
electronic market hubs, vortexes, butterfly
markets, or net market makers—as in
most things Web-related, the terminology is
in transition. Nomenclature notwithstanding,
the fact is that Web buyers need middle men
to bring order to the chaotic assortment
of new suppliers, and suppliers need to be
guided to concentrations of buyers. In addition, infomediaries can act as application
service providers online, assuming responPAGE SIX

The information on pages 5-7
is reprinted from
The FINOVA Quarterly,
published by the Eller College of
Business and Public Administration
and the Alliance for Midsize Business
at the University of Arizona.
For more information about
the Alliance for Midsize Business,
or to subscribe to the
free Quarterly,
contact editor Mary Campbell
at campbell@bpa.arizona.edu
or call 520-621-2281.

sibility for not only hardware and software
but invoicing, customer service, inventory,
and other business functions.
Strictly speaking, infomediaries are Web
sites set up to facilitate B2B or B2C trans-

actions, although the term is generally used
for sites that connect businesses to other
businesses. In much the same way job fairs
bring employers and applicants together,
infomediaries serve as hosts in an electronic
marketplace where buyers and sellers can
gather. They add value by creating market
liquidity—a critical mass of buyers and
sellers—and by reducing transaction costs.
A B-to-B hub is not simply a Web site that
sells to businesses. Staples.com, for example—which sells office products, supplies,
and equipment online caters to business and
is certainly engaged in business-to-business
E-commerce, but it is not a B2B hub or an
infomediary. It is a single site engaging in
transactions with many consumers who are
engaged in business. B2B hubs are networks
of many buyers and many sellers, and their
value grows exponentially as the number of
participants increases.
In its September 1999 issue, Business 2.0
magazine predicted that infomediaries would
account for more than a quarter of all B-to-B
Internet commerce revenues by the year
2002. ■

Please join us in honoring

RICHARD M.
KOVACEVICH
President,
Chief Executive Officer
Wells Fargo & Company
The University of Arizona
2000 Executive of the Year
Friday, April 21, 12:30 pm
The Westin La Paloma Resort
3800 East Sunrise
Tucson, Arizona
For information
call 621-9954

T H E

U N I V E R S I T Y

O F

A R I Z O N A

EXECUTIVE
OF THE YEAR

ARIZONA'S ECONOMY

INFOMEDIARIES
CHANGE THEIR SPOTS
by Gerald J. Swanson
Associate Professor of Economics
Eller College of Business
and Public Administration

stock levels by matching bid/ask offers, and
act as neutral third parties to enforce sales
and settlement terms.(Economist June 1999).
Some Web watchers mention a fourth
category, the barter model, through which
buyers and sellers exchange nonmonetary
assets. In addition, sites like BizBuyer work

with Mary Campbell

T

he industry places infomediaries
into two or three different categories. Varda Lief of Forrester
Research identifies three infomediary
models:

1 Aggregators are like electronic
catalogs. They help buyers in fragmented
markets select products by providing up-tothe-minute price and product information
and a single contact point.
2 Online auctions (such as adauction)
offer reliable channels for sellers to dispose
of perishable or surplus goods or services
at the best possible prices, and for buyers
to get bargain pricing without leaping into
the unknown.
3 Exchanges create liquidity in otherwise fragmented markets, reduce average

by collecting the buyer’s criteria, gathering
and comparing quotes, and arranging the
contact between buyer and seller. The process
is similar to that of other B2B “reverse-auction
sites” (buyer puts in a request, sellers bid
for buyer’s business) like Sorcity.com and
BidtheWorld.com. ■

TWO TYPES OF HUBS
Virtual (Vertical) Hubs

Functional (Horizontal) Hubs

Focus on a specific industry or market.
Examples:

Specialize in a specific function or business
process. Provide the same function or automate
the same business process across different
industries. Expertise usually lies in a business
process. Examples:

• Altra Energy—energy
• Cattle Offering Worldwide—beef & dairy
• PlasticsNet.com—raw materials
(e.g., polycarbonates) and equipment
(e.g., blenders)
• PaperExchange.com—
supplies for publishers
• VerticalNet.com—several B-to-B
companies serving different industries
• Chemdex.com—chemical products
for the biotechnology industry
• Neoforma—hospital product supplies
• SciQuest.com—laboratory products

• IMark.com—used capital equipment
• Employease—employee benefits
administration
• adauction—media buying
• Youtilities.com—corporate energy
management and analysis
• BidCom.com—risk and project
management services

THREE TYPES OF HUBS
Aggregators,
“Electronic Catalogs”

Online Auctions

Exchanges

Method

Demand/supply aggregation;
provides a fixed-price
listing of products

Spatial matching, much like
eBay and other consumer
auction sites

Temporary matching; hub
collects bids from suppliers and
submits them to the buyers

Buyer Benefits

Lower search
and transaction costs

Catalog benefits,
plus better matches,
better prices

Auction benefits, plus peak-load
demand management, hedge
risk in volatile markets

Seller Benefits

Broader customer access,
lower transaction costs

Catalog benefits,
plus better pricing

Auction benefits,
plus liquidate excess supply,
manage volatility

Best Use

MRO products;
preplanned purchases;
fragmented supplier base

Used capital equipment;
perishable capacity;
hard-to-specify products

Near-commodities;
high-fixed-cost assets;
volatile markets

Pricing

Prenegotiated, usually static

Most attractive bid,
prices move in one direction

Marketwide bid-ask;
moves up and down

Challenges

Creating master catalog;
gaining supplier critical mass

Liquidity, misrepresentation,
fraud, fulfillment

Asset specificity;
off-exchange trade

ARIZONA'S ECONOMY

PAGE SEVEN

WHILE TUCSON AND PHOENIX ECONOMIES
MARCH TO THE BEAT OF DIFFERENT DRUMMERS,
THE INCOME GAP NARROWS
By Marshall J. Vest
Forecasting Project Director
March 1, 2000

L

abor shortages and higher oil and commodity prices continue to worry
monetary policy-makers and interest rates are headed up. The economy
continues to grow well above its long-run potential, spurred by the
consumer-spending boom, but higher rates are beginning to have an effect on
interest-sensitive sectors. Arizona’s economy mirrors national trends—strong,
but slowing. Arizona’s two largest metro areas are marching to the beats of
different drummers, as Phoenix loses momentum and Tucson accelerates to
become one of the fastest growing metro areas in the nation. Divergence is due
to different fortunes in their industrial bases. Finally, Arizona’s wage gap is still
wide, but according to a recent study, it is not as wide as originally reported two
years ago. Development of high-tech industries may be both a cure for, and a
cause of, the income gap.
As the New Year begins, the nation’s economy is still on fire. Unemployment is at a
30-year low, job growth is strong, consumer
confidence remains near record levels, and
the index of leading economic indicators is
moving up smartly. The consumer-spending
boom remains in full force. Sales during the
holiday shopping season were spectacular,
and new light vehicles sales recorded a record
16.76 million units in 1999. Although the trend
in new-home sales has been downward since
last spring, sales rose nearly two percent
during 1999, eclipsing 1998’s record level and
marking the fifth consecutive annual increase.
Real GDP, the best overall measure of the
nation’s output, rose at a red-hot 5.8% annual
rate in the fourth quarter, well above the
widely-accepted speed limit of 3-3.5%.
In early February, the Federal Reserve
moved short-term interest rates up another
quarter point in an effort to slow the economy,
but it will likely take two or three (or more)
quarter-point boosts to bring desired results.
While the Fed was busy boosting rates on
short-term treasuries, yields for longer-term
securities fell as the Treasury made major
changes in its debt-management plans. It plans
to pay down debt and reduce the issuance of
long-term bonds. As the long bond took on
scarcity value, investors responded by bidding
up prices, thereby forcing the yields well below
those on shorter-term issues. In the parlance
of economists, the treasury yield curve
“inverted” beyond two-year maturities. This is
PAGE EIGHT

expected to be temporary and does not bode
ill for the economy. Usually, an inverted term
structure reflects investors’ expectations for
a slowing economy (or recession) and falling
yields. Moreover, the recent Treasury market
chaos is not expected to affect corporate or
mortgage markets, where rates remain high
in real terms. In mid-February, for example,
30-year mortgage rates (at par) were being
quoted at 8.5%. In real terms, that is 6.5%,
and that is high when put in historical context.
Typically, when real mortgage rate rise above
five percent, residential building permits fall.
Forecasts for the nation’s economy prepared by the WEFA Group, which we use in
our models, continue to show a slower pace
in 2000 as higher interest rates finally reign
in ebullient consumers.

RECENT TRENDS, ARIZONA
Indicators for Arizona mirror national
trends. Unemployment stood at 4.1% in
December, virtually identical to the national
rate. Arizona remains one of the fastest growing states using job growth as the measure.
Even though job growth slowed during the
year, Arizona’s 3.6% gain (comparable data
through October ’99) ranks third among
all states. Arizona consumer confidence, as
measured by the Behavior Research Center
with sponsorship by Stockton Trust of
Scottsdale, rose to a record during the first
quarter of 2000.

Housing markets continue to enjoy high
levels of activity. At year-end, resales stood
at record levels in both Phoenix and Tucson.
According to preliminary estimates from the
Bureau of the Census, new homebuilding
statewide rose to nearly 63,000 units during
1999, a 3.4% increase. Single-family units
totaled almost 51,000, a 5.4% gain. Gains
were recorded for the whole year even though
permits fell from the peak reached in June.
For example, single-family permits fell from
a 58,000 annual rate in June to 47,500 in
December. Reduced affordability due to
higher mortgage rates and higher prices are
the reason (Exhibit 1).
Retail sales accelerated throughout 1999
and were very strong during the holiday
season. For the entire year, retail sales gained
9.6%, while sales for November and December combined recorded double-digit gains
of 13% from the prior year (Exhibit 2).
As in recent months, auto sales led with the
strongest increases followed closely by furniture and building materials. Restaurant and
bar sales also strengthened at year-end, growing by 11.2% in the fourth quarter.
For the economy to slow, the consumerspending boom and the housing boom must
be subdued. We should expect the Fed to
continue to boost interest rates until slowing
is clearly visible. Higher rates will first be felt
in the building and financial services industries and in new car sales. Those sectors are
the keys to watch in coming months.
Look for employment statewide to increase
by roughly 70,000 this year (3.2%) following
a gain of 86,000 in 1999. Retail sales gains
are expected to slow from 9.0% to 4.0%, and
EXHIBIT 1
Homebuilding
Peaked in Mid-99
Building Permits, AZ
(seasonally adjusted 6-per moving avg)

ARIZONA’S ECONOMY

EXHIBIT 2
Consumers are Still
on Buying Binge
Retail Sales Growth, Arizona (Current Dollars)

residential permits slide to 50,000 from last
year’s 63,000 units.

TUCSON AND PHOENIX
TAKE DIFFERENT PATHS
Arizona’s two largest metro areas continue
to march to the beat of different drummers.
Tucson’s economy is in the midst of a boom
and continues to accelerate while the Phoenix
economy appears to have caught a case of the
dwindles and is losing momentum (Exhibit
3). Job growth has surged in Tucson and in
December, job counts stood 5.3% higher than
one year earlier. With comparable data for
metros through October, Tucson ranks as the
3rd fastest growing metro area. Phoenix has
slipped from one of the fastest growing to a
35th ranking, with job growth of only 2.7%
(December to December).
A difference in growth of export-based jobs
is the most important factor explaining the
divergence of growth in the two areas. Both
grew their industrial job base by nearly 20%
during the decade of the 1990’s, but the timing
of that growth varied significantly (Exhibit 4).
Metro Phoenix added a number of billiondollar semiconductor fabrication plants
during the 1995-97 period. Then during the
Asian crisis, as exports of semiconductor and
electronic components fell, manufacturing
job growth waned during 1998-99. Finally,
consolidation in Arizona’s copper mining
industry reduced employment in that industry
by half in the Phoenix metro area in mid-1999.
Ripple effects from the stalled industrial base
brought slower growth economy-wide.
Over the decade, Tucson saw a surge in its
AR IZ ON A ’S E CON OMY

EXHIBIT 3
Metro Growth Rates Diverge

EXHIBIT 4
Paths Differ for Two Metros

Wage & Salary Job Growth
(Phoenix-Mesa & Tucson MAs)

Industrial Jobs, Phoenix and Tucson
(Mining plus Manufacturing)

industrial base in 1994-95 as Hughes Missile
Systems relocated newly acquired General
Dynamics operations to its Tucson plant. Then,
industrial growth flattened during 1996-97,
only to surge again recently, largely as a result
of Raytheon’s restructuring missile operations
from new acquisitions (Hughes and Texas
Instruments). Although expansions at

Bombardier, which manufactures Learjet and
Challenger corporate business jets, and new
arrival Universal Avionics were the headlinegrabbers during 1999, nearly every manufacturer in Tucson added to payrolls. Last year,
manufacturing employment in Tucson grew
by almost 3,000, or 10%.
The two metro areas have very different
manufacturing concentrations—semiconductors and electronic components in
metro Phoenix and aerospace and optics in
Tucson. Differences in growth—and timing
of growth—have resulted in very different
business cycles.
What should one expect as we go forward?
In Tucson, the pipeline for announced new
relocations and expansions is emptying, so
the current wave is expected to diminish.
However, ripple effects will propel the economy forward at a strong pace well into next
year. In Phoenix, exports are growing once
again and prospects for the world’s semiconductor industry look much brighter. In
fact, forecasts for that industry show a shortage of productive capacity in the near future.
Intel’s recent announcement that it will build
a new $2 billion fab plant in Chandler to open
in 18 months, and news that Microchip will
begin construction of a $1 billion plant originally scheduled to be built in 1996, presages
that the next surge will arrive in 2001-02.

AS HIGH-SKILLED JOBS
ARE CREATED,
INCOMES INCREASE
AT THE HIGHER END,
MAKING THE GAP WIDER!
THE GAP PERSISTS
IF INCOMES OF THE
LOWER-SKILLED POPULATION
FAIL TO KEEP UP.

INCOME GAP AND THE
HIGH-TECH ECONOMY
A study of the nation’s income gap by state
was recently updated, and there is good news
and bad news for Arizona. The bad news is
PAGE NI NE

EXHIBIT 5
Pacific and Border States have Highest Gaps

EXHIBIT 6
Where are the High-Technology Jobs

Ratio of Top Fifth to Bottom Fifth Average Incomes

(High-Tech as a Percent of Total Employment, 1998)

that Arizona still has one of the widest gaps
between the rich and poor of any state
(ranked second to New York, see Exhibit 5).
The good news is that the gap has narrowed
since the first study was released two years
ago. More importantly, real incomes have
increased significantly in recent years.
The older study compared changes in real
incomes from the mid-80s to the mid-90s.
That data revealed significant declines in real
incomes for the bottom fifth of Arizona families (down 37%) and declines in all but the
highest fifth where the gain was a miniscule
2.6%—one of the smallest gains of any state
in the nation. The new data, which compares
the late-80s with the late-90s, still finds declining incomes for the bottom four quintiles,
but the declines are much smaller. The bottom
fifth, for example, shows a decline of only
15%. Moreover, the top fifth now shows an
increase of 21.0%, well above national averages and fourth among western states. These
data compare changes over the entire decade
(the old study compared ’85-’87 to ’94-’96
—data were pooled for three years to
increase sample sizes).
Rather than using a ten-year span, the data
from the two studies may be compared to see
changes during the past two years. Between
’94-’96 (the mid-’90s) and ’96-’98 (the late’90s), average incomes for Arizonans in the
bottom fifth increased by $3,528 or 48.5%.
That compares to an increase of 40.3% for
the nation’s poorest, and is the second best
among western states (Washington recorded
a 49.5% gain). Average income for Arizonans
in the top fifth increased $37,798, or 36.6%,
more than double nationwide averages, and
PAGE TEN

second only to Oregon among western states.
From these comparisons it may be concluded
that all Arizona residents are sharing in
recent prosperity.
What is the relationship between the income
gap and high technology? Is the large income
gap a failure of the state’s economic development policies? During the past decade, these
policies have been aimed at developing the
state’s high-technology sectors that export
their products and provide high-paying jobs.
Arizona has been very successful at developing high-tech jobs, yet a wide income gap
remains. That is not unique to Arizona, however. In fact, states that have developed their
high-tech economy also have the largest gaps,
as shown in Exhibit 6. It only makes sense
that as high-skilled jobs are created, incomes
increase at the higher end, making the gap
wider! The gap persists if incomes of the
lower-skilled population fail to keep up.
Closing the income gap (and ensuring that
all Arizona residents share in the rewards of
the New Economy) requires a two-pronged
approach. First, we must continue to create
opportunities for better-paying jobs by developing high-skill/knowledge-based jobs.
Second, we must ensure that existing residents have the ability to hold those jobs. This
means raising the level of preparedness of
high school students for the world of work,
motivating them to learn, keeping them in
school, and demanding a better outcome
from public schools. It means providing
opportunities for life-long learning, job training, and workforce development programs.
It also means ensuring that we have strong
research universities that provide cutting

edge research and highly educated people.
In the information age, human capital is
the most important factor. We can continue
to import workers from other states to work
in newly created knowledge-based jobs—
and the income gap will persist. Or, we can
give existing residents the knowledge and
skills they need to participate in the New
Economy, and thereby raise the standard
of living for all Arizonans. ■
1

Pulling Apart: A State-by-State Analysis of Income
Trends, Center on Budget and Policy Priorities and
the Economic Policy Institute, January, 2000,
http://www.cbpp.org/1-18-00sfp.htm.

S P O N S O R S

Arizona Joint Legislative Budget Committee
Arizona Portland Cement
Arizona Public Service Company
Bank One Arizona
CB Richard Ellis
Compass Bank
City of Tucson
Coldwell Banker Success Realty
Elliott D. Pollack and Company
Jim Click Automotive Team
Kaufman and Broad
Merrill Lynch
Northern Trust Bank of Arizona
Pima County
Salt River Project
Territorial Newspapers
Tucson Electric Power Company
Tucson Healthcare Council
Tucson Newspapers
U S WEST Communications
U S WEST Dex
ARIZONA’S ECONOMY

F O R E C A S T

Forecasts for Arizona
Personal Income ($ mill)
percent change
Per Capita Personal Income
percent change
Aggregate Retail Sales ($ mill)*
percent change
Population (000s, mid-year)
percent change
Net Migration (000s)
Wage & Salary Employment (000s)
percent change
Goods-Producing
percent change
Construction
percent change
Manufacturing
percent change
Service-Providing
percent change
Trade (Wholesale & Retail)
percent change
Services
percent change

T A B L E S

1999
115,992.1
7.1
23,950.5
3.9
49,514.1
9.3
4,843.0
3.0
98.5
2,164.2
4.1
377.1
1.5
151.1
7.0
214.8
-1.2
1,787.1
4.7
520.4
3.9
662.5
6.1

2000
124,064.3
7.0
24,931.2
4.1
51,651.8
4.3
4,976.3
2.8
85.4
2,233.4
3.2
378.3
0.3
150.0
-0.7
218.2
1.6
1,855.1
3.8
535.4
2.9
696.2
5.1

2001
131,511.8
6.0
25,806.6
3.5
53,580.1
3.7
5,096.1
2.4
74.3
2,285.8
2.3
379.0
0.2
145.1
-3.3
223.7
2.5
1,906.8
2.8
549.4
2.6
722.4
3.8

2002
138,591.1
5.4
26,602.3
3.1
56,245.8
5.0
5,209.7
2.2
71.9
2,336.6
2.2
380.1
0.3
141.4
-2.6
228.4
2.1
1,956.4
2.6
566.5
3.1
744.4
3.0

2003
145,849.0
5.2
27,399.7
3.0
58,944.1
4.8
5,323.0
2.2
73.0
2,391.4
2.3
386.7
1.7
141.6
0.1
234.8
2.8
2,004.8
2.5
581.1
2.6
765.3
2.8

2004
153,784.6
5.4
28,279.3
3.2
61,602.6
4.5
5,438.1
2.2
74.4
2,449.1
2.4
396.4
2.5
144.4
2.0
241.7
2.9
2,052.7
2.4
594.3
2.3
787.1
2.8

2005
162,995.4
6.0
29,338.8
3.7
65,011.5
5.5
5,555.6
2.2
80.0
2,527.2
3.2
407.9
2.9
148.3
2.7
249.2
3.1
2,119.3
3.2
618.5
4.1
815.2
3.6

Forecasts for Phoenix-Mesa Metro
Personal Income ($ mill)
percent change
Per Capita Personal Income
percent change
Aggregate Retail Sales ($ mill)*
percent change
Population (000s, mid-year)
percent change
Net Migration (000s)
Wage & Salary Employment (000s)
percent change
Goods-Producing
percent change
Construction
percent change
Manufacturing
percent change
Service-Providing
percent change
Trade (Wholesale & Retail)
percent change
Services
percent change

1999
80,676.8
7.2
26,474.0
3.8
34,085.9
8.4
3,047.4
3.2
65.8
1,519.3
4.2
278.3
-0.3
109.0
5.4
164.2
-3.1
1,241.0
5.3
369.1
4.8
484.3
6.1

2000
87,134.3
8.0
27,758.5
4.9
36,038.9
5.7
3,139.0
3.0
61.1
1,572.9
3.5
281.1
1.0
108.5
-0.5
168.6
2.6
1,291.9
4.1
383.8
4.0
503.5
4.0

2001
92,915.4
6.6
28,841.7
3.9
37,187.0
3.2
3,221.6
2.6
51.1
1,611.6
2.5
282.0
0.3
103.8
-4.4
174.3
3.4
1,329.6
2.9
395.5
3.0
519.2
3.1

2002
98,192.6
5.7
29,763.5
3.2
39,249.3
5.5
3,299.1
2.4
45.9
1,642.2
1.9
281.0
-0.4
99.4
-4.2
177.6
1.9
1,361.2
2.4
406.2
2.7
530.3
2.1

2003
103,947.8
5.9
30,802.8
3.5
41,673.1
6.2
3,374.6
2.3
44.2
1,673.0
1.9
283.1
0.7
97.2
-2.2
181.9
2.4
1,389.9
2.1
415.9
2.4
538.6
1.6

2004
109,716.3
5.5
31,799.1
3.2
43,662.4
4.8
3,450.3
2.2
44.3
1,704.2
1.9
288.0
1.7
97.7
0.5
186.2
2.4
1,416.2
1.9
422.7
1.7
547.8
1.7

2005
115,917.6
5.7
32,852.3
3.3
46,186.3
5.8
3,528.4
2.3
46.8
1,745.9
2.4
295.2
2.5
100.2
2.6
191.0
2.5
1,450.7
2.4
434.2
2.7
559.8
2.2

Forecasts for Tucson Metro Area
Personal Income ($ mill)
percent change
Per Capita Personal Income
percent change
Aggregate Retail Sales ($ mill)*
percent change
Population (000s, mid-year)
percent change
Net Migration (000s)
Wage & Salary Employment (000s)
percent change
Goods-Producing
percent change
Construction
percent change
Manufacturing
percent change
Service-Providing
percent change
Trade (Wholesale & Retail)
percent change
Services
percent change

1999
19,081.9
7.8
22,561.4
5.0
7,778.5
7.1
845.8
2.7
17.1
344.3
5.0
54.5
7.5
21.6
5.8
31.0
10.8
289.8
4.5
72.6
3.1
111.2
5.8

2000
20,482.3
7.3
23,614.3
4.7
8,264.2
6.2
867.4
2.6
16.7
356.2
3.4
55.8
2.4
22.4
4.0
31.7
2.2
300.3
3.6
75.5
4.0
116.2
4.5

2001
21,870.7
6.8
24,674.8
4.5
8,710.1
5.4
886.4
2.2
14.0
365.7
2.7
56.4
1.0
22.6
0.9
31.9
0.7
309.4
3.0
78.1
3.4
120.7
3.9

2002
23,105.1
5.6
25,580.4
3.7
9,153.8
5.1
903.2
1.9
11.8
372.2
1.8
56.6
0.5
22.5
-0.7
32.3
1.2
315.6
2.0
80.1
2.6
123.7
2.5

2003
24,349.5
5.4
26,508.3
3.6
9,570.0
4.5
918.6
1.7
10.2
377.7
1.5
56.8
0.4
22.3
-1.0
32.7
1.2
320.9
1.7
81.5
1.7
126.1
2.0

2004
25,555.0
5.0
27,387.6
3.3
9,949.8
4.0
933.1
1.6
9.3
382.1
1.1
57.2
0.6
22.2
-0.5
33.1
1.1
324.9
1.2
82.3
1.0
128.0
1.5

2005
26,837.7
5.0
28,306.5
3.4
10,395.0
4.5
948.1
1.6
9.8
388.6
1.7
57.8
1.1
22.4
0.9
33.4
1.1
330.8
1.8
84.3
2.4
130.6
2.0

* Aggregate Retail Sales includes retail, food, restaurant & bars and gasoline sales.
Source: Economic and Business Research Program, Eller College of Business and Public Administration, The University of Arizona.
A R IZO N A’ S ECO N OMY

PAGE ELEVEN

A R I Z O N A

E C O N O M I C

YUMA METROPOLITAN REGION
Civilian Labor Force, ADES
Employment
Unemployment
Unemployment Rate (%)
Employees on Nonagricultural Payrolls, ADES
Total
Mining
Construction
Manufacturing
Trans., Comm. & Publ. Util.
Trade
Finance, Ins. & Real Estate
Services
Government
Sales ($000s) ADOR
Gross Retail
Retail
Restaurants & Bars
Gasoline, EBR
Gallons (000s) ADOT
Contracting
Value of Construction Contract Awards ($000s) F.W. Dodge
Total
Residential Building
Non-Residential Building
Non-Building
Number of Dwelling Units Awarded, F.W. Dodge
Total
One Family Houses
MOHAVE-LA PAZ REGION
Civilian Labor Force, ADES
Employment
Unemployment
Unemployment Rate (%)
Employees on Nonagricultural Payrolls, ADES
Total
Mining
Construction
Manufacturing
Trans., Comm. & Publ. Util.
Trade
Finance, Ins. & Real Estate
Services
Government
Sales ($000s) ADOR
Gross Retail
Retail
Restaurants & Bars
Gasoline, EBR
Gallons (000s) ADOT
Contracting
Value of Construction Contract Awards ($000s) F.W. Dodge
Total
Residential Building
Non-Residential Building
Non-Building
Number of Dwelling Units Awarded, F.W. Dodge
Total
One Family Houses

I N D I C A T O R S

JAN
2000

% change versus year ago for:
most
most
recent
recent
month
12-months

SEP
99

OCT
99

NOV
99

DEC
99

75,950
50,600
25,350
33.4

70,175
51,700
18,475
26.3

68,175
52,925
15,250
22.4

64,500
52,350
12,150
18.8

...
...
...
...

2.2
3.8
-4.1
-6.2

8.1
8.7
6.6
-1.9

41,225
n/a
2,850
2,325
1,725
11,025
1,175
7,725
14,400

42,350
n/a
2,900
2,325
1,750
11,450
1,250
7,850
14,825

42,925
n/a
2,900
2,350
1,850
11,650
1,275
8,000
14,900

43,400
n/a
2,925
2,400
1,850
12,250
1,300
8,275
14,400

...
...
...
...
...
...
...
...
...

1.9
n/a
14.7
6.7
-2.6
0.4
2.0
-0.3
2.1

8.1
n/a
13.4
9.5
0.8
2.1
1.9
-1.8
21.0

72,153
56,097
7,382
8,674
7,423
14,634

82,657
64,634
8,636
9,387
7,702
15,255

90,326
71,371
8,733
10,222
8,186
16,104

132,662
110,653
9,858
12,151
9,223
16,104

...
...
...
...
...
...

23.9
25.2
3.3
32.5
-4.2
4.2

9.0
7.8
8.2
20.1
10.3
1.6

13,472
5,328
5,961
2,183

22,102
8,673
11,149
2,280

9,127
5,011
2,290
1,826

9,363
5,358
1,566
2,439

9,677
4,659
4,660
358

-14.7
-33.1
86.4
-80.9

-13.3
-13.5
-16.9
-7.5

66
66

144
64

64
60

63
63

61
61

-19.7
-19.7

2.4
-6.5

74,350
71,200
3,150
4.2

73,825
70,925
2,900
3.9

74,175
71,350
2,825
3.8

74,100
71,100
3,000
4.0

...
...
...
...

5.9
6.1
0.0
-5.5

7.7
7.8
5.2
-2.4

42,825
n/a
3,650
3,575
2,050
13,075
1,475
10,575
8,250

43,125
n/a
3,550
3,625
2,025
13,225
1,525
10,825
8,200

43,375
n/a
3,600
3,625
2,025
13,400
1,525
10,700
8,350

43,700
n/a
3,650
3,775
2,025
13,400
1,525
10,700
8,475

...
...
...
...
...
...
...
...
...

4.2
n/a
9.8
4.1
-2.4
0.0
3.4
6.2
8.7

3.0
n/a
8.1
3.2
-1.5
3.3
0.6
3.6
1.5

90,934
67,475
11,572
11,887
10,172
22,161

95,972
72,166
12,235
11,571
9,494
21,949

98,645
73,835
12,030
12,780
10,234
24,833

121,254
94,623
12,408
14,223
10,795
31,951

...
...
...
...
...
...

18.0
13.4
16.4
64.3
18.8
25.9

10.8
9.3
10.3
21.2
10.6
20.6

57,097
15,369
3,216
38,512

56,090
13,984
7,685
34,421

19,888
14,615
5,273
0

28,841
19,516
8,871
454

24,379
18,651
909
4,819

8.2
44.2
-84.5
29.3

-3.5
13.8
-54.8
26.9

160
160

143
141

147
147

194
182

391
123

187.5
-6.8

19.8
6.3

See notes at bottom of Arizona - Quarterly table.

PAGE TWELVE

A RI ZO NA’S EC O NO M Y

A R I Z O N A

COCHISE-SANTA CRUZ REGION
Civilian Labor Force, ADES
Employment
Unemployment
Unemployment Rate (%)
Employees on Nonagricultural Payrolls, ADES
Total
Mining
Construction
Manufacturing
Trans., Comm. & Publ. Util.
Trade
Finance, Ins. & Real Estate
Services
Government
Sales ($000s) ADOR
Gross Retail
Retail
Restaurants & Bars
Gasoline, EBR
Gallons (000s) ADOT
Contracting
Value of Construction Contract Awards ($000s) F.W. Dodge
Total
Residential Building
Non-Residential Building
Non-Building
Number of Dwelling Units Awarded, F.W. Dodge
Total
One Family Houses
GILA-GRAHAM-GREENLEE REGION
Civilian Labor Force, ADES
Employment
Unemployment
Unemployment Rate (%)
Employees on Nonagricultural Payrolls, ADES
Total
Mining
Construction
Manufacturing
Trans., Comm. & Publ. Util.
Trade
Finance, Ins. & Real Estate
Services
Government
Sales ($000s) ADOR
Gross Retail
Retail
Restaurants & Bars
Gasoline, EBR
Gallons (000s) ADOT
Contracting
Value of Construction Contract Awards ($000s) F.W. Dodge
Total
Residential Building
Non-Residential Building
Non-Building
Number of Dwelling Units Awarded, F.W. Dodge
Total
One Family Houses

E C O N O M I C

I N D I C A T O R S

JAN
2000

% change versus year ago for:
most
most
recent
recent
month
12-months

SEP
99

OCT
99

NOV
99

DEC
99

57,700
51,775
5,925
10.3

56,450
51,575
4,875
8.6

56,375
52,575
3,800
6.7

56,250
52,525
3,725
6.6

...
...
...
...

8.5
10.4
-12.4
-19.2

4.3
6.0
-12.0
-15.7

43,775
n/a
2,600
2,425
2,350
11,425
1,025
9,875
14,075

44,050
n/a
2,625
2,450
2,350
11,725
1,025
10,025
13,850

44,950
n/a
2,675
2,375
2,450
12,375
1,025
10,150
13,900

45,425
n/a
2,675
2,350
2,475
12,750
1,025
10,225
13,925

...
...
...
...
...
...
...
...
...

9.8
n/a
28.9
5.6
3.1
11.1
2.5
9.7
8.2

4.0
n/a
15.7
8.3
1.8
1.2
-0.6
6.0
3.4

77,350
58,838
8,301
10,211
8,738
17,634

80,528
60,191
8,987
11,350
9,312
16,290

82,814
64,555
8,789
9,470
7,584
21,934

87,794
68,739
10,051
9,004
6,834
20,770

...
...
...
...
...
...

-6.6
-9.3
9.3
0.1
-27.6
42.7

9.1
4.3
7.7
50.9
37.5
34.0

12,429
7,025
1,045
4,359

34,889
7,372
22,023
5,494

28,028
5,064
3,859
19,105

9,765
5,892
1,643
2,230

10,086
6,191
3,190
705

-69.1
-52.4
3.8
-95.7

-0.3
-12.1
-4.6
26.9

81
81

76
76

61
57

68
66

58
56

-69.1
-39.1

-9.8
-2.5

35,300
32,775
2,525
7.2

34,700
32,425
2,275
6.6

34,750
32,575
2,175
6.3

34,550
32,300
2,250
6.5

...
...
...
...

4.8
6.2
-11.8
-15.8

3.2
3.9
-5.1
-7.9

26,475
n/a
2,000
n/a
775
5,925
n/a
4,550
8,050

26,450
n/a
2,025
n/a
750
6,050
n/a
4,500
7,950

26,575
n/a
2,050
n/a
750
6,175
n/a
4,500
7,925

26,550
n/a
2,025
n/a
775
6,075
n/a
4,600
7,925

...
...
...
...
...
...
...
...
...

5.0
n/a
2.5
n/a
-6.1
7.0
n/a
3.4
12.0

2.0
n/a
8.7
n/a
-4.7
3.0
n/a
4.6
1.5

42,791
32,283
5,352
5,156
4,412
3,203

43,000
32,507
4,979
5,514
4,524
11,243

43,701
33,384
5,024
5,293
4,239
12,810

50,043
40,378
4,861
4,804
3,646
12,510

...
...
...
...
...
...

7.2
7.0
4.0
12.2
-18.8
56.9

4.9
3.1
3.0
22.0
10.0
-18.0

11,490
5,268
1,815
4,407

12,698
6,164
2,326
4,208

8,454
4,468
0
3,986

6,479
6,330
149
0

7,970
4,768
141
3,061

88.8
33.3
...
375.3

19.9
11.8
-19.8
114.9

42
38

43
43

38
34

97
45

39
39

21.9
21.9

18.2
4.5

See notes at bottom of Arizona - Quarterly table.

AR IZON A ’S ECON O MY

PAGE THIRTEEN

A R I Z O N A

APACHE-NAVAJO REGION
Civilian Labor Force, ADES
Employment
Unemployment
Unemployment Rate (%)
Employees on Nonagricultural Payrolls, ADES
Total
Mining
Construction
Manufacturing
Trans., Comm. & Publ. Util.
Trade
Finance, Ins. & Real Estate
Services
Government
Sales ($000s) ADOR
Gross Retail
Retail
Restaurants & Bars
Gasoline, EBR
Gallons (000s) ADOT
Contracting
Value of Construction Contract Awards ($000s) F.W. Dodge
Total
Residential Building
Non-Residential Building
Non-Building
Number of Dwelling Units Awarded, F.W. Dodge
Total
One Family Houses
COCONINO-YAVAPAI REGION
Civilian Labor Force, ADES
Employment
Unemployment
Unemployment Rate (%)
Employees on Nonagricultural Payrolls, ADES
Total
Mining
Construction
Manufacturing
Trans., Comm. & Publ. Util.
Trade
Finance, Ins. & Real Estate
Services
Government
Sales ($000s) ADOR
Gross Retail
Retail
Restaurants & Bars
Gasoline, EBR
Gallons (000s) ADOT
Contracting
Value of Construction Contract Awards ($000s) F.W. Dodge
Total
Residential Building
Non-Residential Building
Non-Building
Number of Dwelling Units Awarded, F.W. Dodge
Total
One Family Houses

E C O N O M I C

I N D I C A T O R S

JAN
2000

% change versus year ago for:
most
most
recent
recent
month
12-months

SEP
99

OCT
99

NOV
99

DEC
99

51,350
45,500
5,850
11.4

50,050
44,650
5,400
10.8

49,500
44,175
5,325
10.8

49,475
43,625
5,850
11.8

...
...
...
...

-1.8
0.5
-15.8
-14.3

0.7
2.1
-7.8
-8.5

43,975
n/a
2,000
1,500
2,500
7,900
1,175
7,400
20,550

43,750
n/a
2,000
1,500
2,550
7,825
1,050
7,250
20,650

43,325
n/a
1,925
1,475
2,550
7,750
1,075
7,025
20,600

43,075
n/a
1,875
1,475
2,525
7,725
1,075
6,925
20,550

...
...
...
...
...
...
...
...
...

0.2
n/a
0.0
-3.3
2.0
3.0
-2.3
5.3
-2.1

0.3
n/a
-1.0
1.1
2.2
4.0
-2.7
3.0
-1.9

70,536
54,477
6,237
9,822
8,405
13,896

100,013
85,226
5,599
9,188
7,539
12,340

63,701
48,825
4,996
9,880
7,912
14,194

91,196
76,032
4,758
10,406
7,899
13,902

...
...
...
...
...
...

47.4
45.6
10.1
96.4
42.0
76.3

19.5
17.7
3.7
47.0
33.1
23.9

57,713
13,639
22,119
21,955

16,264
5,720
5,774
4,770

24,212
13,966
8,421
1,825

62,378
6,964
52,160
3,254

13,058
12,040
188
830

133.8
259.2
-90.6
257.8

73.8
70.4
102.2
37.7

132
132

61
61

136
84

55
55

100
100

222.6
222.6

60.9
70.3

134,150
128,500
5,650
4.2

132,625
127,725
4,900
3.7

131,900
126,775
5,125
3.9

132,875
127,050
5,825
4.4

...
...
...
...

6.8
7.1
1.3
-5.1

5.3
6.0
-7.2
-11.9

107,600
1,075
7,425
6,325
3,425
27,550
3,350
30,075
28,375

108,250
1,025
7,175
6,300
3,450
27,450
3,275
30,150
29,425

107,750
1,000
7,125
6,275
3,425
27,225
3,300
29,875
29,525

106,775
1,000
7,050
6,275
3,350
27,000
3,350
29,650
29,100

...
...
...
...
...
...
...
...
...

7.8
0.0
9.3
-2.7
6.3
4.1
4.7
7.8
14.8

6.3
7.1
6.7
-0.1
3.3
4.6
5.7
7.8
8.3

203,462
145,363
37,374
20,725
17,735
60,532

200,037
143,185
35,673
21,179
17,377
57,664

218,412
146,273
51,128
21,011
16,827
53,238

228,361
177,824
29,877
20,660
15,681
67,561

...
...
...
...
...
...

30.4
28.8
15.5
85.4
34.1
44.1

14.9
11.9
11.9
51.5
37.0
19.3

45,131
33,787
3,356
7,988

62,213
21,949
11,245
29,019

31,937
17,970
8,320
5,647

37,085
24,782
3,055
9,248

68,608
30,826
13,337
24,445

81.8
32.9
111.5
196.4

-5.5
-12.4
-5.6
17.0

310
240

218
205

178
174

214
206

329
203

72.3
19.4

-4.6
4.1

See notes at bottom of Arizona - Quarterly table.

PAGE FOURTEEN

ARIZONA’S ECONOMY

A R I Z O N A

E C O N O M I C

PHOENIX-MESA METROPOLITAN REGION (MARICOPA AND PINAL)
Civilian Labor Force (000s) ADES
Employment
Unemployment
Unemployment Rate, Seas. Adj.(%)
Employees on Nonagricultural Payrolls (000s) ADES
Total
Mining
Construction
Manufacturing
Durable
Nondurable
Trans., Comm. & Publ. Util.
Trade
Wholesale
Retail
Finance, Ins. & Real Estate
Services
Government
Sales ($000s) ADOR
Aggregate Retail Sales
Retail
Food, EBR
Restaurants & Bars
Gasoline, EBR
Contracting
Value of Construction Contract Awards ($000s) F.W. Dodge
Total Awards
Residential Building
Non-Residential Building
Non-Building
New Housing Units Authorized, Census C-40
Total Units
Single Family Units
2-4 Unit Structures
5-plus Unit Structures
Housing Sales and Prices, ARMLS
Total Sales ($000s)
Total Units
Average Price ($)
Phoenix Skyharbor International Airport, PSIA
Total Passengers
Total Aircraft Movements

I N D I C A T O R S

JAN
2000

SEP
99

OCT
99

NOV
99

DEC
99

1,605.9
1,556.1
49.8
2.7

1,601.9
1,555.6
46.3
2.8

1,609.3
1,565.6
43.7
2.8

1,614.6
1,570.1
44.5
2.9

...
...
...
...

2.9
2.7
7.7
0.0

5.6
5.4
13.7
11.4

1,513.8
2.9
115.4
170.2
130.7
39.5
80.0
364.9
92.5
272.4
124.3
466.5
189.6

1,529.1
2.9
115.8
170.3
130.7
39.6
80.8
368.8
92.0
276.8
125.6
471.0
193.9

1,543.0
3.0
117.0
169.8
130.4
39.4
81.4
375.4
92.3
283.1
126.3
475.9
194.2

1,556.5
3.0
116.2
170.2
130.8
39.4
81.8
383.6
92.6
291.0
127.3
479.8
194.6

...
...
...
...
...
...
...
...
...
...
...
...
...

2.7
-46.4
5.3
-0.8
-0.4
-2.0
4.3
3.7
2.3
4.1
3.8
3.0
1.6

3.3
-24.4
8.2
0.1
0.2
-0.5
6.6
3.7
4.1
3.5
6.0
2.7
2.0

2,771,949
1,998,398
333,307
309,479
130,765
641,118

2,760,800
1,931,822
346,066
338,676
144,236
657,778

2,962,466
2,142,178
352,059
324,733
143,496
644,504

3,601,968
2,730,298
354,655
356,920
160,095
695,051

...
...
...
...
...
...

10.4
11.1
-5.4
15.2
31.9
2.0

8.7
10.5
-4.3
9.2
16.8
10.8

646,713
436,707
142,296
67,710

549,427
342,959
151,545
54,923

720,095
400,880
137,228
181,987

623,409
439,590
130,187
53,632

705,463
412,321
212,051
81,091

-11.3
-21.8
32.3
-24.4

-12.7
-3.2
-31.1
-15.0

3,930
3,050
58
822

2,900
2,392
31
477

3,243
2,306
37
900

3,572
2,501
42
1,029

...
...
...
...

-6.9
-10.8
61.5
2.5

2.2
5.4
10.1
-9.1

654,891
4,212
155,482

759,417
4,939
153,759

601,433
3,807
157,981

728,080
4,477
162,627

...
...
...

5.3
-3.4
9.0

16.6
9.6
6.3

2,527,351
45,269

2,870,923
48,929

2,933,337
47,217

2,844,390
49,305

...
...

8.7
6.1

5.7
4.3

PHOENIX-MESA METROPOLITAN REGION (MARICOPA AND PINAL) - QUARTERLY DATA

Demographics & Vital Statistics (000s, seas adj) ADHS & EBR
Population
Natural Increase
Births
Deaths
Net Migration
Personal Income by Source ($mil, SAAR) EBR
Total Personal Income
Earnings by Place of Work
Less: Contributions for Social Insurance
Plus: Adjustment for Residence
Plus: Dividends, Interest & Rents
Plus: Transfer Payments
Per Capita Personal Income ($, SAAR) EBR
See notes at bottom of Arizona - Quarterly table.
ARIZONA’S ECONOMY

% change versus year ago for:
most
most
recent
recent
month
12-months

% change versus year ago for:
most
most
recent
recent
quarter
4-quarters

IV
98

I
99

II
99

III
99

IV
99

2,988.3
7.2
12.8
5.6
17.7

3,012.2
7.4
13.1
5.7
16.5

3,035.5
7.5
13.2
5.8
15.8

3,058.5
7.5
13.4
5.8
15.6

3,081.6
7.5
13.4
5.9
15.5

3.1
4.9
5.0
5.1
-12.3

3.2
6.3
6.2
6.0
-11.2

77,273
58,658
4,077
-165
12,199
10,658
25,858

78,490
59,835
4,143
-167
12,194
10,771
26,057

79,853
60,943
4,207
-164
12,327
10,956
26,307

81,343
62,109
4,275
-163
12,520
11,151
26,595

83,021
63,375
4,349
-163
12,799
11,358
26,941

7.4
8.0
6.7
1.0
4.9
6.6
4.2

7.2
8.2
6.7
0.4
3.3
6.1
3.8

PA GE F IF TE EN

A R I Z O N A

E C O N O M I C

TUCSON METROPOLITAN REGION (PIMA) - QUARTERLY DATA
Civilian Labor Force (000s) ADES
Employment
Unemployment
Unemployment Rate, Seas. Adj.(%)
Employees on Nonagricultural Payrolls (000s) ADES
Total
Mining
Construction
Manufacturing
Durable
Nondurable
Trans., Comm. & Publ. Util.
Trade
Wholesale
Retail
Finance, Ins. & Real Estate
Services
Government
Sales ($000s) ADOR
Aggregate Retail Sales
Retail
Food, EBR
Restaurants & Bars
Gasoline, EBR
Contracting
Value of Construction Contract Awards ($000s) F.W. Dodge
Total Awards
Residential Building
Non-Residential Building
Non-Building
New Housing Units Authorized, Census C-40 adjusted by EBR
Total Units
Single Family Units
2-5-plus Unit Structures
Housing Sales and Prices, TAR
Total Sales ($000s)
Total Units
Average Price ($)
Tucson International Airport, TAA
Total Passengers
Total Aircraft Movements

I N D I C A T O R S

JAN
2000

SEP
99

OCT
99

NOV
99

DEC
99

402.5
389.1
13.4
3.0

405.8
392.4
13.4
3.2

410.0
397.1
12.9
3.2

410.1
396.6
13.5
3.4

...
...
...
...

6.5
5.5
50.2
36.0

6.7
6.4
15.9
10.6

341.0
1.9
22.6
30.7
25.0
5.7
14.1
70.3
11.0
59.3
13.5
111.5
76.4

347.6
1.9
22.5
30.9
25.2
5.7
13.9
71.3
11.0
60.3
13.7
113.2
80.2

353.0
1.9
22.5
32.1
26.4
5.7
14.0
73.2
11.0
62.2
13.8
114.2
81.3

354.4
1.9
22.6
32.2
26.5
5.7
14.1
74.5
11.1
63.4
14.1
114.9
80.1

...
...
...
...
...
...
...
...
...
...
...
...
...

5.3
-9.5
8.7
9.9
13.2
-3.4
3.7
1.8
-0.9
2.3
2.9
5.0
7.7

4.1
-7.7
9.7
4.7
5.9
-0.3
1.6
2.0
0.8
2.2
3.3
4.4
5.0

626,691
433,730
83,894
73,429
35,638
118,901

622,438
417,112
87,106
78,805
39,415
118,368

674,310
475,786
88,614
71,031
38,879
117,332

838,075
618,169
89,268
82,849
47,789
137,457

...
...
...
...
...
...

11.7
12.7
-2.9
11.1
36.5
25.3

8.0
9.2
-1.8
5.9
23.5
21.3

127,728
58,297
61,160
8,271

81,615
49,100
19,982
12,533

129,423
41,439
69,889
18,095

120,116
70,577
16,859
32,680

126,500
69,102
33,525
23,873

4.3
-0.1
51.1
-20.3

-3.7
-19.0
9.8
64.8

732
624
108

639
511
128

423
360
63

903
522
381

...
...
...

30.7
-0.7
130.6

3.0
-2.1
30.2

123,510
884
139,718

125,791
881
142,782

114,234
793
144,053

119,866
796
150,585

...
...
...

0.6
-5.7
6.6

20.3
12.2
7.3

254,945
20,533

300,908
23,221

302,342
22,780

295,796
23,629

271,852
24,310

-3.9
-0.3

0.6
4.1

TUCSON METROPOLITAN REGION (PIMA) - QUARTERLY DATA

Demographics & Vital Statistics (000s, seas adj) ADHS & EBR
Population
Natural Increase
Births
Deaths
Net Migration
Personal Income by Source ($mil, SAAR) EBR
Total Personal Income
Earnings by Place of Work
Less: Contributions for Social Insurance
Plus: Adjustment for Residence
Plus: Dividends, Interest & Rents
Plus: Transfer Payments
Per Capita Personal Income ($, SAAR) EBR

% change versus year ago for:
most
most
recent
recent
month
12-months

% change versus year ago for:
most
most
recent
recent
quarter
4-quarters

IV
98

I
99

II
99

III
99

IV
99

832.3
1.1
2.9
1.7
4.8

837.7
1.2
2.9
1.7
4.2

842.9
1.2
2.9
1.7
4.0

848.3
1.2
2.9
1.7
4.2

853.8
1.2
2.9
1.7
4.3

2.6
5.1
2.4
0.5
-10.5

2.7
6.7
2.4
-0.3
-19.4

18,218
11,455
809
211
3,879
3,482
21,888

18,563
11,735
827
220
3,915
3,521
22,160

18,907
11,982
844
224
3,970
3,575
22,430

19,253
12,218
859
228
4,033
3,632
22,697

19,605
12,441
874
234
4,110
3,694
22,962

7.6
8.6
8.1
10.9
5.9
6.1
4.9

7.8
9.3
8.6
12.2
5.3
5.7
5.0

See notes at bottom of Arizona - Quarterly table.
PA GE S IX TE EN

AR I ZO NA ’S EC ONO M Y

A R I Z O N A

E C O N O M I C

ARIZONA MONTHLY DATA
Civilian Labor Force (000s) ADES
Employment
Unemployment
Unemployment Rate, Seas. Adj. (%)
Employees on Nonagricultural Payrolls (000s) ADES
Total
Mining
Construction
Manufacturing
Durable
Nondurable
Trans., Comm. & Publ. Util.
Transportation
Trade
Wholesale
Retail
Finance, Ins. & Real Estate
Services
Government
Federal
State & Local
Schools
Hours Worked Per Week, Manufacturing, ADES
Average Hourly Earnings ($) ADES
Copper Mining
Construction
Manufacturing
Utilities
Retail Trade
Wholesale Trade
Sales ($000s) ADOR
Aggregate Retail Sales
Retail
Food, EBR
Restaurants & Bars
Gasoline, EBR
Gallons (000s) ADOT
Utilities
Communications
Amusements
Rentals - Personal Property
Contracting
Mining - Metal, Oil & Gas
Hotel/Motel
Value of Construction Contract Awards ($000s) F.W. Dodge
Total Awards
Residential Building
Non-Residential Building
Non-Building
New Housing Units Authorized, Census C-40
Total Units
Single Family Units
2-4 Unit Structures
5-plus Unit Structures
Bankruptcy Filings, U.S. Bankruptcy Court
Total
Chapter 7
Chapter 11
Chapter 13

I N D I C A T O R S

JAN
2000

% change versus year ago for:
most
most
recent
recent
month
12-months

SEP
99

OCT
99

NOV
99

DEC
99

2,437.2
2,325.5
111.7
4.0

2,425.5
2,327.0
98.5
4.0

2,434.1
2,343.0
91.1
4.0

2,436.4
2,345.6
90.8
4.1

...
...
...
...

3.8
3.7
6.2
0.0

5.7
5.7
7.2
4.3

2,164.6
9.8
159.5
218.8
168.1
50.7
107.1
69.1
513.5
114.5
399.0
147.0
651.7
357.2
44.1
313.1
170.3
40.6

2,189.3
9.9
159.6
219.1
168.3
50.8
107.8
69.6
519.9
114.4
405.5
148.5
656.7
367.8
43.8
324.0
179.2
40.7

2,209.2
9.9
160.9
219.6
169.1
50.5
108.7
70.1
528.9
115.1
413.8
149.6
661.8
369.8
43.4
326.4
182.4
40.4

2,224.1
9.8
160.0
220.1
169.4
50.7
109.3
70.6
538.8
115.8
423.0
150.6
666.9
368.6
44.4
324.2
180.5
40.3

...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...

3.4
-22.2
5.9
0.6
1.4
-1.9
3.9
3.4
3.5
2.4
3.8
4.7
3.1
4.9
-1.3
5.8
7.4
1.0

3.5
-12.7
8.8
0.7
1.0
-0.3
5.2
5.9
3.5
3.7
3.5
5.2
3.4
2.8
0.2
3.2
3.8
-0.1

20.34
14.48
12.64
18.07
11.72
13.64

20.26
14.47
12.63
17.77
11.64
13.45

20.04
14.45
12.71
17.52
11.57
13.42

19.54
14.63
12.77
17.45
11.37
13.69

...
...
...
...
...
...

14.7
1.7
2.3
-2.9
-1.5
2.7

5.1
-0.5
4.0
0.9
0.5
1.4

4,059,843
2,846,661
521,178
459,126
232,878
199,280
539,935
195,413
42,764
279,170
892,079
75,544
119,384

4,093,401
2,806,843
541,129
493,590
251,839
206,629
416,214
194,321
68,074
275,909
910,887
76,290
156,757

4,344,202
3,056,207
550,500
486,464
251,031
201,034
430,062
216,483
62,485
298,275
904,949
49,270
163,849

5,261,990
3,916,716
554,559
511,582
279,133
211,866
395,288
193,735
58,470
289,198
995,306
45,816
115,377

...
...
...
...
...
...
...
...
...
...
...
...
...

13.0
12.5
5.7
14.0
36.9
-1.0
5.2
9.2
9.8
7.5
9.5
-36.9
12.3

10.2
10.2
6.8
8.7
22.6
11.9
2.6
14.4
9.3
1.8
12.8
-17.0
6.5

971,773
575,420
240,968
155,385

835,298
455,921
231,729
147,648

971,164
503,413
235,280
232,471

897,436
579,009
214,490
103,937

965,741
558,558
268,001
139,182

-6.3
-15.3
32.5
-17.4

-9.5
-4.6
-24.2
-0.3

5,162
4,188
86
888

4,011
3,385
70
556

4,125
3,109
65
951

4,843
3,439
89
1,315

...
...
...
...

-0.5
-6.7
107.0
15.6

4.0
5.9
10.3
-4.5

1,792
1,434
14
344

1,776
1,412
18
346

1,779
1,338
104
337

...
...
...
...

...
...
...
...

-2.2
-11.7
550.0
17.8

-6.7
-6.9
-0.3
-6.4

See notes at bottom of Arizona - Quarterly table.

ARIZONA’S ECONOMY

PAGE SEVENTEEN

A R I Z O N A

E C O N O M I C

ARIZONA QUARTERLY DATA
Demographics & Vital Statistics (000s, seas adj) ADHS & EBR
Population
Natural Increase
Births
Deaths
Net Migration
Personal Income Derivation ($mil, SAAR) EBR
Total Personal Income
Earnings by Place of Work
Less: Contributions for Social Insurance
Plus: Adjustment for Residence
Plus: Dividends, Interest & Rents
Plus: Transfer Payments
Components of Earnings ($mil, SAAR) BEA
Wages and Salaries
Other Labor Income
Proprietor’s Income
Farm
Nonfarm
Per Capita Personal Income ($, SAAR) EBR
Average Wage Per Employee, Annual Rate ($) EBR

I N D I C A T O R S

IV
98

I
99

II
99

III
99

IV
99

4,754.3
10.6
20.1
9.5
24.9

4,789.8
10.0
20.1
10.1
25.5

4,825.3
10.3
20.0
9.6
25.2

4,860.3
10.2
19.9
9.8
24.3

4,894.3
10.2
20.0
9.9
23.5

2.9
-4.4
-0.5
3.8
-5.6

3.0
0.8
2.6
4.6
1.9

112,303
80,772
5,622
298
18,724
18,132

113,008
81,267
5,666
298
18,559
18,550

115,035
82,902
5,763
300
18,834
18,761

116,385
83,981
5,827
302
18,921
19,008

119,540
86,270
5,962
305
19,612
19,316

6.4
6.8
6.0
2.4
4.7
6.5

7.1
8.1
7.1
6.9
4.0
5.9

66,629
6,135
7,987
416
7,571
23,622
31,114

65,593
5,963
8,204
419
7,785
23,594
30,425

68,891
6,259
8,428
391
8,037
23,840
31,679

70,523
6,360
8,591
321
8,270
23,946
...

...
...
...
...
...
24,424
...

8.9
6.1
11.8
8.4
12.0
3.4
6.0

9.3
5.7
10.3
11.5
10.3
4.0
5.6

TRAVEL AND TOURISM - MONTHLY DATA
AUG
99
Visits to Parks & Other Recreational Areas, ADOT, NPS & ASPB
Northern Arizona
Historical
Scenic
Water Based Recreation
Southern Arizona
Historical
Scenic
Water Based Recreation
International Border Crossings, USINS & USCS
U.S. Citizens
Aliens
Vehicles

SEP
99

OCT
99

NOV
99

DEC
99

Sources and abbreviations:

ADES: Arizona Department of Economic Security
ADHS: Arizona Department of Health Services
ADOR: Arizona Department of Revenue
ADOT: Arizona Department of Transportation
ARMLS: Arizona Regional Multiple Listing Service
ASBD: Arizona State Banking Department
ASPB: Arizona State Parks Board
ASU: Arizona State University, College of Business,
Research Centers
PAGE EIGHTEEN

% change versus year ago for:
most
most
recent
recent
month
12-months

2,508,480
182,235
803,110
1,523,135
149,928
24,968
84,779
40,181

1,976,923
171,514
649,705
1,155,704
148,152
26,157
90,573
31,422

1,724,053
161,514
571,487
991,052
206,403
39,449
131,829
35,125

1,259,076
104,133
302,834
852,109
212,423
41,643
146,458
24,322

890,306
69,620
250,992
569,694
200,249
44,083
146,034
10,132

17.4
-10.2
9.8
26.0
16.9
-3.4
28.3
17.9

2.5
-1.8
0.9
4.0
-2.3
-2.4
-4.3
6.8

740,751
1,861,796
808,392

755,654
1,922,220
917,545

726,449
2,004,215
879,493

775,423
2,019,873
855,098

820,408
2,306,446
...

2.4
4.3
4.9

5.3
1.6
6.0

MEASURES OF INFLATION AND PRICES - MONTHLY DATA

Consumer Price Index (1982-1984=100) BLS
U.S. - All Urban
U.S. - Wage Earners

% change versus year ago for:
most
most
recent
recent
quarter
4-quarters

SEP
99

OCT
99

NOV
99

DEC
99

167.9
164.7

168.2
165.0

168.3
165.1

168.3
165.1

BEA: Bureau of Economic Analysis, U.S.
Department of Commerce
BLS: Bureau of Labor Statistics, U.S. Department of Labor
Census C-40, Bureau of the Census, U.S.
Department of Commerce
EBR: Economic & Business Research Program,
The University of Arizona
F.W. Dodge, Division of McGraw Hill Information Systems
Co. (proprietary data provided by special permission)
NPS: National Park Service, U.S. Department of the Interior

JAN
2000
168.7
165.5

% change versus year ago for:
most
most
recent
recent
month
months
2.7
2.8

2.3
2.3

NSCCC: Nogales-Santa Cruz Chamber of Commerce
PSIA: Phoenix Skyharbor International Airport
SAAR: Seasonally adjusted at annual rates
TAA: Tucson Airport Authority
TAR: Tucson Association of Realtors
USINS: U.S. Immigration & Naturalization Service,
U.S. Department of Justice
U.S. Bankruptcy Court, District of Arizona
USCS: U.S. Customs Service, U.S. Department
of the Treasury

ARIZONA’S ECONOMY

A R I Z O N A

E C O N O M I C

I N D I C A T O R S

MEASURES OF INFLATION AND PRICES -QUARTERLY DATA

Consumer Price index (1982-84=100) ASU & BLS
Metropolitan Phoenix*
Western Region (U.S.)
U.S. - All Urban Consumers
U.S. - Urban Wage Earners
Price Indexes (1992=100) BEA
Gross Domestic Product
Personal Consumption Expenditures

% change versus year ago for:
most
most
recent
recent
quarter
4-quarters

IV
98

I
99

II
99

III
99

IV
99

181.5
165.8
164.0
160.7

n/a
167.3
164.6
161.2

n/a
168.3
166.2
162.8

n/a
170.0
167.2
163.9

n/a
170.5
168.3
165.1

2.3
2.8
2.6
2.7

3.0
2.7
2.2
2.2

103.3
103.1

103.8
103.4

104.1
104.0

104.4
104.5

104.7
104.8

1.3
1.7

1.3
1.5

*discontinued. See notes at bottom of Arizona - Quarterly table.

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