This document analyzes the impact of household debt and deleveraging on the US gaming industry. It finds that: 1) A significant amount of consumer spending between 2002-2007 was driven by debt and housing appreciation, fueling gaming revenue growth. 2) As households pay down debt from unprecedented levels, it is dampening discretionary consumer spending and therefore gaming industry revenues. 3) Regional gaming markets dependent on regions with high debt levels like Arizona, California and Florida have seen worse declines, while Texas's gaming markets have fared better with its lower household debt. 4) The analysis concludes that high household debt and deleveraging will continue to limit gaming industry spending growth through at

1. Apertor Research www.apertorhospitality.com
October 12, 2010 Gregg Carlson
Advisor
702.506.0475 x540
gcarlson@apertorhospitality.com
Consumer Deleveraging and the U.S. Gaming Industry
Household Debt Slows Industry Deleveraging
©2010 Apertor Hospitality, LLC.
All Rights Reserved.

2. Executive Summary 2
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Executive Summary
In late 2009 to early 2010, U.S. GDP data improved suggesting that a U.S. economic recovery had
begun. 2Q10 GDP datapoints have since “rolled over” triggering fears that the U.S. could face a
double dip recession. Current consensus is that the U.S. economy will recover at a slow pace over
an extended period of time.
Casino operators in the U.S. continue to face a challenging operating environment due to slow
growth in consumer spending. The open question for the gaming industry is when demand will
improve enough to drive a sustainable recovery.
Subsequent to the recession in 2002, U.S. consumer spending grew at a robust pace driving
growth in the U.S. gaming industry until late 2007 to 2008. Today, it is well understood that a
significant amount of consumer spending between 2002 and 2007 was driven by debt driven
consumption tied to housing appreciation. Estimates we have viewed suggest that as much as
$2.2 trillion was extracted from housing appreciation through debt increases between 2003 and
2007. Much of this amount flowed into consumer spending, which in turn drove revenue growth
in the gaming industry.
The mortgage debt driven consumer spending tailwind that ended in 2007 is now a headwind as
households deleverage from unprecented historical levels. As we write, U.S. households continue
to save more and deleverage through both debt write-off and repayment. While this behavior
may be healthy for individual households, we believe that it will continue to dampen spending in
the gaming industry.
At this juncture, the subjects of deleveraging and increased household saving have been
addressed by economic forecasters and to a lesser degree by industry analysts. We initially
focused on these issues a year ago by surveying available data and preparing an analysis of
the topics to develop our thesis that consumer spending in the gaming industry was being
dampened by deleveraging and would likely continue to be impacted for an extended period of
time.
Post the 2007 household leverage peak, deleveraging has been a mixed bag as the non-
mortgage consumer credit to income ratio has now moved down to the year 2000 benchmark
(pre household debt run up level) suggesting that deleveraging may have largely already
occurred in this category of household debt. However, the largest category of household debt is
mortgage debt. In this category, debt to income levels have moderated from a peak of 101% in
2007 to 91% today, but appear to have way to go before the deleveraging process is complete.
For household mortgage debt to be deleveraged back to year 2000 levels, debt ratios would
need to decrease to 65% of future personal disposable income. This implies that only 25% of
the deleveraging process may have been completed to date. On the other hand, if debt levels
ultimately bottom at higher rates of personal income at 80% or 70% for example, the consumer is
further along in the process.
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3. Executive Summary 3
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
It is not known what the eventual long-term debt to income run rate will be and how much of
the deleveraging process will be acomplished by the individual components of income growth,
debt repayment and default. Economists we have surveyed have indicated that they expect
the mortgage deleveraging process to continue over the next few years, but they do not know
precisely where debt to income levels may bottom out (e.g. at 80%, 70% or 60% debt to income
levels).
If future personal income growth remains flat over a period of time, we know that a significant
amount of debt (our estimate is $2.5 to $2.6 trillion) would have to be deleveraged to arrive at
a 65% debt to income level (i.e. year 2000 level) with smaller amounts of deleveraging required
to reach eventual higher run-rate debt to income levels.[1] Our belief is that a deleveraging of
this magnitude could keep discretioniary consumer spending in check for an extended period
of time. As a result, we believe household mortgage debt deleveraging will remain a negative
structural issue for the gaming industry. Because the U.S. household remains in an unprecented
economic position following the 2008 to 2009 downturn, we cannot forecast with certaininty
how this issue will play out over time as the overall future debt to income level will be driven by a
combination of income growth, debt paydown and default.
This analysis includes a drill down into specific U.S. region and state level personal income growth
rates and debt to income levels and compares these metrics to specific regional gaming market
revenue performance to form a view on future performance in for these markets. We also
present aggregrate household debt levels, aging trends and distressed debt data to provide an
overall historic and current perspective on these issues.
Our overall industry forecast is that current high household debt levels, deleveraging and
weak income growth will continue to keep discretioniary gaming industry spending growth
subdued during 2011, 2012 and maybe longer. Our regional and state level analyses suggest that
significant differences exist between specific regions and states in terms of income growth and
debt to income relationships. We believe these relationships could influence a divergence in the
pace of recovery in individual gaming markets and operators located in these markets.
In general, regions and states that experienced the highest rates of housing appreciation during
the housing boom years now have the highest ratios of debt to income. These states which
include Arizona, California, Florida and Nevada, among others, are home to some of the gaming
markets that have experienced the worst declines since the industry downturn began in 2008. On
the other hand, states like Texas that experienced modest housing appreciation during the boom
currently have the lowest relative household debt to income levels in the U.S. Gaming markets
that depend on Texas customers (e.g. Louisiana) have fared ralatively better since 2008 than
1 Our estimates suggest that an eventual debt to income run rate of 80% based on an approximate 1.5% to 2.0% personal income growth
rate over a three year period with unchanged tax rates, implies that between $720 and $860 billion of mortgage debt would need to be
deleveraged over this period. If the deleveraging is accomplished entirely by repayment (which is not likely in our opinion), the annual
consumer spending growth rate may be reduced by approximately 70 basis points, which is significant in our opinion. As we expect some
portion of this debt reduction to be accomplished via default, the actual consumer spending basis point reduction would be smaller.
©2010 Apertor Hospitality, LLC. All Rights Reserved.

4. Executive Summary 4
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
markets like the Las Vegas Strip that draw customers from feeder markets like California, where
household debt to income levels remain high.
We present a summary of the aggregate ramp-up of housing related household debt since
2000 and the related post 2002 recession consumer spending boom that culminated in 2008.
In this research, we endeavor to provide a granular and regional view of the deleveraging issue.
Our research suggests that operators, developers and investors should assess both household
personal income growth rates and debt levels of their target customers in order to properly judge
the depth and revenue potential of particular markets.
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5. Introduction 5
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Introduction
Real U.S. GDP was recently revised downward to 1.6% for 2Q10. GDP has now sequentially
declined for the second quarter in a row after the third and fourth quarter 2009 increases as
follows:
Figure 1 – Real U.S. GDP
6% 6%
4% 4%
2% 2%
3Q08
4Q08
1Q09
0% 0%
1Q06
2Q06
3Q06
4Q06
1Q07
2Q07
3Q07
4Q07
2Q08
3Q09
4Q09
1Q10
2Q10
1Q08
2Q09
-2% -2%
-4% -4%
-6% -6%
-8% -8%
Source: Bureau of Economic Analysis
Recovery euphoria driven by improved Fall 2009 to Spring 2010 economic data points has been
followed by fear of a double dip recession as economic metrics have since rolled over. Currently,
there is a large amount of economic uncertainty and debate tied to reliance of government
stimulus, budget deficits and negative economic signals from the credit markets, among other
factors. Current consensus is that although the worst may be behind us, the economy is limping
along in a slow growth fashion with structural issues that pose risks to a more typical cyclical
recovery.
In recent years GDP growth has been driven by consumer spending (PCE) growth. Between 4Q09
and 1Q10, PCE growth decoupled from GDP growth. PCE growth during 2Q10 remains well below
the growth rate achieved during 2003 to 2007. PCE recreation services, the category that includes
gaming revenues, has been correlated to PCE.[2] During 2Q10 recreation services spending
remained negative despite positive growth in overall PCE.
Between 2003 and 2007, a significant amount of consumer spending was driven by credit (debt)
growth tied to housing (mortgages). This credit bubble has now burst triggering the worst U.S.
downturn since the depression. During 2008, aggregate U.S. household balance sheets took an
unprecedented $13 trillion hit (driven by declines in financial asset and household real estate
values) that sent a massive shockwave through the economy that continues to reverberate today.
Overall consumer spending and industries that depend on it have been significantly negatively
impacted.
2 PCE recreation services include commercial and racino gaming spending as well as recreation spending in other categories (e.g. bowling).
©2010 Apertor Hospitality, LLC. All Rights Reserved.

6. Introduction 6
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Revenues in the U.S. gaming industry (commercial and tribal casino operators) have followed the
downward trend in overall consumer spending. As we write, the industry is not out of the woods
yet owing to an overall levered balance sheet and out of balance supply and demand conditions
in most markets. Most public casino operators and regions where commercial gaming exists have
reported declines in revenue on a same store basis since the industry peak of 2006.
In this analysis, we examine overall consumer income levels and spending patterns, household
leverage and the recent household deleveraging trend in an effort to understand how
consumer spending will affect gaming industry revenues and therefore, cash flows and leverage
looking forward. We specifically examine select broad macro metrics, consumer debt related
metrics, relationships between income, spending, tax and saving rates as well as employment-
unemployment trends. We also present recent results from regional gaming markets throughout
the U.S. We have presented data in a chart format and provide historic perspective of the metrics
examined.
In February 2010, we published our initial analysis of this issue titled The U.S. Gaming Industry
and the Great Deleveraging. Based on our research at the time, we hypothesized that recovery
in the industry would be protracted, slow and at risk due to the large amount of household
debt that will need to be repaid over the next several years that would consequently dampen
discretionary consumer spending, GDP growth and therefore spending in the industry. Today
our thesis is largely unchanged as we believe the deleveraging process and tepid income growth
will continue to dampen consumer spending and overall economic growth in the U.S. gaming
industry for the foreseeable future.
For ease of use, the report is comprised of series of charts organized into five sections plus
appendices as follows:
SECTION
1. Summary of Select National & Regional Economic Metrics
2. Personal Income and Consumer Spending Data
3. Household Debt Metrics
4. Regional Gaming Market Data
5. Consumer Spending and Industry Revenue Regression Analysis,
Industry Debt Metrics and Pace of Deleveraging
APPENDIX
1. Residential Real Estate Values
2. Regional Personal Income Growth Rates
3. Regional Household Debt to Income Levels
4. Household Debt to Income Levels in Select States
5. Total U.S. Household Debt and Other Credit Metrics
©2010 Apertor Hospitality, LLC. All Rights Reserved.

7. SECTION 1:
Summary of Select National & Regional Economic Metrics
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8. SECTION 1: Summary of Select National & Regional Economic Metrics 8
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Figure 2 shows that consumer spending growth decoupled from GDP growth during 4Q09 and
1Q10 (after years of strong correlation). Inventory restocking drove GDP growth in Q409. The
question today is whether sustainable demand will follow so that restocking is not a one-time
phenomenon. 2Q10 GDP growth was recently revised downward while consumer spending
growth rates remain below pre-recession growth rates. Consumer spending for recreation
continues to remain negative and has remained largely negative since 2007.
Figure 2–GDP and consumer spending growth
8% 0.25% Gross domestic
6% 0.20%
product growth
(left axis)
4% 0.15%
2% 0.10% Personal
consumption
0% 0.05% expenditures
growth (left axis)
1Q01
2Q01
3Q01
4Q01
1Q02
2Q02
3Q02
4Q02
1Q03
2Q03
3Q03
4Q03
1Q05
2Q05
3Q05
4Q05
1Q06
2Q06
3Q06
4Q06
1Q09
2Q09
3Q09
4Q09
1Q00
2Q00
3Q00
4Q00
1Q04
2Q04
3Q04
4Q04
1Q07
2Q07
3Q07
4Q07
1Q08
2Q08
3Q08
4Q08
1Q10
2Q10
-2% 0.00%
-4% -0.05%
Recreation
services growth
-6% -0.10% (right axis)
-8% -0.15%
Source: Bureau of Economic Analysis, Apertor Research
Figure 3 shows that Las Vegas Strip gaming revenue has been correlated to consumer
confidence for an extended period of time prior to the 2008 recession. Absolute revenues
declined during the 2008 – 2010 recession despite the increase in supply. As a destination
market, LV Strip fundamentals are sensitive to international, national and regional economic
conditions. Recent consumer confidence data points remain weak as the July 2010 reading of
50.4 sequentially declined from June 2010. Index values closer to 100 are considered to be normal
non-recessionary numbers. Like the LV Strip, same store revenues have also declined in most
regions during the recession.
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9. SECTION 1: Summary of Select National & Regional Economic Metrics 9
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Figure 3 – Consumer confidence and monthly LV Strip gaming revenue
$’s in millions Consumer confidence index
LV Strip gaming revenue Consumer confidence
$700 140
$600 120
$500 100
$400 80
$300 60
$200 40
$100 20
$0 0
Mar 01
Jun 01
Sep 01
Dec 01
Mar 02
Jun 02
Sep 02
Dec 02
Mae 03
Jun 03
Sep 03
Dec 03
Mar 04
Jun-04
Sep 04
Dec 04
Mar 05
Jun 05
Sep 05
Dec 05
Mar 06
Jun 06
Sep 06
Dec 06
Mar 07
Jun 07
Sep 07
Dec 07
Mar 08
Jun 08
Sep 08
Dec 08
Mar 09
Jun 09
Sep 09
Dec 09
Mar 10
Jun 10
Source: Nevada Gaming Commission, Conference Board, Apertor Research
Figure 4 shows the relationship between consumer confidence and the U.S. unemployment rate.
Consumer confidence began to decline during the latter half of 2007 and a rise in unemployment
followed. Consumer confidence currently remains low, and unemployment has become a
significant national issue. A consensus view has developed that unemployment may now
be a structural issue as it is currently expected to remain high for the foreseeable future. The
unemployment rate does not include underemployed workers.
Figure 4 – U.S. consumer confidence and unemployment
U.S. Unemployment Rate Consumer confidence
12% 140
10% 120
100
8%
80
6%
60
4%
40
2% 20
0% 0
Feb 01
Apr 01
Jun 01
Aug 01
Oct 01
Dec 01
Feb 02
Apr 02
Jun 02
Aug 02
Oct 02
Dec 02
Feb 03
Apr 03
Jun 03
Aug 03
Oct 03
Dec 03
Feb 04
Apr 04
Jun-04
Aug 04
Oct 04
Dec 04
Feb 05
Apr 05
Jun 05
Aug 05
Oct 05
Dec 05
frb 06
Apr 06
Jun 06
Aug 06
Oct 06
Dec 06
Feb 07
Apr 07
Jun 07
Aug 07
Oct 07
Dec 07
Feb 08
Apr 08
Jun 08
Aug 08
Oct 08
Dec 08
Feb 09
Apr 09
Jun 09
Aug 09
Oct 09
Dec 09
Feb. 10
Apr 10
Jun 10
Source: Conference Board, Bureau of Labor Statistics, Apertor Research
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10. SECTION 1: Summary of Select National & Regional Economic Metrics 10
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Regional Unemployment Trends
The U.S. unemployment rate is considered to be a lagging economic indicator. Business and
consumer confidence will need to increase so that economic growth can resume in a manner
that drives employment growth. Businesses are currently not investing in hiring due to weak
consumer demand conditions. Consumers are currently not spending due to weak employment
and income growth. We do not believe the gaming industry can significantly recover without
a recovery in employment. Regional unemployment trends have generally followed national
trends as unemployment significantly increased during 2009 and 2010.
Figure 5 shows that unemployment in the northeast increased during 2008 and 2009 and
has remained high during 2010. The northeast includes several states with significant gaming
markets including New Jersey, New York and Pennsylvania.
Figure 5 – Northeast region unemployment rate (%)
14 14
CONNECTICUT DELAWARE MAINE
12 12
MASSACHUSETTS NEW HAMPSHIRE NEW JERSEY
10 NEW YORK PENNSYLVANIA RHODE ISLAND 10
8 VERMONT WEST VIRGINIA 8
6 6
4 4
2 2
0 0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 June 2010 July 2010
Source: Bureau of Labor Statistics, Apertor Research
Figure 6 shows unemployment trends in the Midwest significantly increased during 2009 and
remains high during 2010. The Midwest includes several states with significant gaming markets
including Illinois, Indiana and Missouri. Gaming facilities exist in all states included in this region.
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11. SECTION 1: Summary of Select National & Regional Economic Metrics 11
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Figure 6 – Midwest region unemployment rate (%)
14 ILLINOIS INDIANA IOWA KANSAS 14
12 12
MICHIGAN MINNESOTA MISSOURI NEBRASKA
10 10
OHIO OKLAHOMA WISCONSIN
8 8
6 6
4 4
2 2
0 0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 June 2010 July 2010
Source: Bureau of Labor Statistics, Apertor Research
Figure 7 shows that unemployment remains high for most southern states in 2010. Several states
include significant gaming markets including Florida, Louisiana and Mississippi.
Figure 7 – Southern region unemployment rate (%)
14 14
ALABAMA ARKANSAS FLORIDA
12 GEORGIA KENTUCKY LOUISIANA 12
10 MISSISSIPPI NORTH CAROLINA TENNESSEE 10
8 TEXAS VIRGINIA 8
6 6
4 4
2 2
0 0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 June 2010 July 2010
Source: Bureau of Labor Statistics, Apertor Research
The Western U.S. includes some of the states that have been the hardest hit by the recession
including Arizona, California and Nevada (see Figure 8 below). The region also includes states
with major gaming markets (Arizona, California, and Nevada) that are enduring major headwinds
due to their reliance on the region for visitation. The latest data points for June and July 2010
remain challenged.
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12. SECTION 1: Summary of Select National & Regional Economic Metrics 12
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Figure 8–Western region unemployment rate (%)
16 ALASKA ARIZONA CALIFORNIA COLORADO 16
14 HAWAII IDAHO MONTANA NEVADA 14
12 NEW MEXICO NORTH DAKOTA OREGON SOUTH DAKOTA 12
10 UTAH WASHINGTON WYOMING 10
8 8
6 6
4 4
2 2
0 0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 June 2010 July 2010
Source: Bureau of Labor Statistics, Apertor Research
Our view is that improvement in the unemployment rate will lag increases in consumer
spending which will in turn be driven by other economic factors (e.g. household deleveraging
or not, tax rates, improvement in the housing market, exports, etc.). Research we have reviewed
suggests that levels of household leverage in specific regions of the U.S. preceded increases
in unemployment, not visa versa, thus casting doubt that initial mortgage defaults reflected
difficulties in the labor market.[3] Instead it was increased difficulty in repayment of household
debt that precipitated the downturn. Household leverage currently remains high relative to the
pre-recession 2008 period.
Figure 9 shows that after years of growth retail sales significantly declined during the latter
half of 2008. Since their low during 2008, retail sales have continued to grow slowly in a positive
manner. Retail sales for July were better than expected and positive on a year-over-year basis.
Despite the recent positive data point, fears exist that sales may be challenged during the
upcoming key holiday shopping season. Continued improvement in sales could move economic
expectations higher and provide evidence that recent inventory restocking was not a one-time
event.
3 For further detail see Household Leverage and the Recession of 2007 to 2009, Arif Main & Amir Sufi, University of Chicago, October 2009.
©2010 Apertor Hospitality, LLC. All Rights Reserved.

13. SECTION 1: Summary of Select National & Regional Economic Metrics 13
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Figure 9 – Retail sales (seasonally adjusted) ($’s in billions)
Retail and food services sales y/y retail and food services sales
$400 15%
$380
$360 10%
$340 5%
$320
$300 0%
$280
$260 -5%
$240 -10%
$220
$200 -15%
Jan 01
Apr 01
Jly 01
Oct 01
Jan 05
Apr 05
Jly 05
Oct 05
Jan 06
Apr 06
Jly 06
Oct 06
Jan 09
Apr 09
Jly 09
Oct 09
Oct 00
Oct 02
Oct 03
Oct 04
Oct 07
Oct 08
Jan 00
Jan 02
Jan 03
Jan 04
Jan 07
Jan 08
Jan 00
Apr 00
Apr 02
Apr 03
Apr 04
Jly 00
Jly 02
Jly 03
Jly 04
Apr 07
Apr 08
Apr 00
Jly 07
Jly 08
Jly 00
Source: U.S. Department of Commerce, Apertor Research
Household Balance Sheet Data
In Figure 10, we present household balance sheet data supplied by the Federal Reserve.[4]
Between 2000 and 2006, household real estate and financial assets increased on an absolute
values basis while debt increased as well. During 2007 household real estate values decreased
followed by a more significant decrease in real estate and financial asset values in 2008 that
triggered a massive $13 trillion decrease in household net worth.[5] To put this number into
perspective, the amount roughly matches one year of output from the entire U.S. economy. The
decrease in net worth is depicted in red in Figure 10 for 2008.
On a more granular basis, leverage measured on an asset to debt basis decreased between 2000
and 2006 due to housing and financial asset value increases. As a result of the significant collapse
in housing values between 2007 and 2008, leverage ratios are higher as of 1Q 2010 (4.91x assets
to liabilities) than 2007 (5.48x assets to liabilities), the year that immediately preceded the onset
of the recession during 2008. On a total debt to disposable income basis, debt ratios increased
between 2000 and 2007 (95% to 132%) and have since decreased to 120% at 1Q10 largely due to
debt default and repayment as income has been generally flat between 2008 and 2010.
The majority of total household debt is comprised of mortgage debt. Our calculations imply that
if mortgage debt is ultimately deleveraged from the 2007 peak to the year 2000 debt to income
level (101% to 65%), 25% of the process has occurred based on a current 91% debt to income
reading. This calculation suggests that there is more deleveraging to follow over the next few
4 The schedule includes amounts derived from households, domestic hedge funds and nonprofit organizations. Financial assets include
assets of both households and hedge funds. Liabilities include home mortgages, consumer credit and other liabilities. Home mortgages and
consumer credit comprise approximately 96% of the liabilities line item. Per Federal Reserve Flow of funds document Z-1, schedule B.100 at
1Q10, home mortgage debt and consumer credit has decreased approximately $303 billion between 2007 and Q110.
5 The amount also includes domestic hedge funds and non-profit organization assets and liabilities per Federal Reserve Flow of Funds
document Z-1, schedule B.100.
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14. SECTION 1: Summary of Select National & Regional Economic Metrics 14
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
years. What is not precisely known at this juncture is whether mortgage debt to income levels will
eventually bottom out and how much deleveraging will occur through default.
The Wall Street Journal recently reported that between 2Q08 and 2Q10 the majority of household
debt reduction has been accomplished by default.[6] Currently household debt delinquencies and
bankruptcies remain high suggesting that the default rate will remain high for the time being. As
debt to income ratios remain in unprecedented territory, it remains to be seen how much debt
will be paid down by belt tightening or by default, and if overall debt and mortgage debt levels
are ultimately brought down from debt to income levels of 95% to 65% (current year levels to
year 2000 levels). While debt relief via default may directly positively impact consumer spending,
we do not believe strong overall growth in consumption will likely resume with this backdrop due
to resulting tight credit conditions and lack of consumer confidence, among other factors.
During 2009 and 2010, household real estate values decreased further while financial assets
values (driven by 2009 equity market gains) offset real estate declines as total asset values slightly
increased. The net effect is a modest increase in net worth (4.3% and 2.0% respectively). Personal
income and consumer spending growth have been weak since 2008 and remain weak today.
Our regression analysis of changes in household net worth to consumer spending suggests that
net worth changes have a significant impact on consumer spending in subsequent years. See
Section 5 for additional detail. Our thesis remains that the 2008 hit to net worth, lack of income
and credit growth as well as deleveraging will keep consumer spending growth in check looking
forward. Our view is that barring some unidentified catalyst, industries like the gaming industry
that are dependent on discretionary consumer spending will continue to face a weak demand
environment.
As we write, the Federal Reserve reported that U.S. aggregate household net worth fell 2.7%
between 1Q10 and 2Q10 with the decrease primarily driven by financial asset losses tied to the
2Q10 U.S. stock market decline.[7]
6 For additional information see,” Number of the Week: Defaults Account for Most of the Pared Down Debt,” Wall Street Journal, September
18, 2010. The WSJ article implies that as much as 90% of deleveraged debt total over the last two years has been accomplished by default.
Economists we have spoken to indicate they maintain debt default estimates that significantly vary from this published estimate. We were
unable to reconstruct this number based on our review of recent Federal Reserve Z-1 data and other data. At this juncture opinions vary as
to the total amount of debt that has gone into default over the last two years.
7 For additional information see the 1Q10 & 2Q10 Federal Reserve publication Z-1, schedule B.100 issued June and September 2010.
©2010 Apertor Hospitality, LLC. All Rights Reserved.

15. SECTION 1: Summary of Select National & Regional Economic Metrics 15
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Figure 10 – U.S. Household Balance Sheet ($’s in trillions)
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010Q1
Household real estate 12,136.6 13,572.9 14,919.4 16,395.1 18,982.0 22,084.6 22,943.6 20,978.0 17,037.8 16,572.6 16,507.2
Other 4,567.7 4,747.8 4,998.9 5,270.9 5,649.3 6,303.3 6,791.8 7,058.9 6,852.2 6,487.9 6,485.7
Total tangible assets 16,704.3 18,320.7 19,918.3 21,666.0 24,631.3 28,387.9 29,735.4 28,036.9 23,890.0 23,060.5 22,992.9
% change in household real estate 14.0% 11.8% 9.9% 9.9% 15.8% 16.3% 3.9% -8.6% -18.8% -2.7% -0.4%
Deposits 4,376.1 4,875.8 5,153.2 5,348.5 5,732.4 6,139.9 6,753.1 7,406.5 7,972.8 7,755.7 7,651.6
Credit market instruments 2,464.6 2,374.3 2,527.5 2,723.1 2,997.9 3,327.4 3,479.4 4,089.4 4,024.9 3,983.1 4,180.2
Equities 8,204.6 6,783.5 5,121.4 6,749.9 7,483.9 8,093.0 9,643.7 9,626.4 5,913.5 7,463.9 7,793.3
Mutual funds 2,704.2 2,614.6 2,218.4 2,911.0 3,427.7 3,669.1 4,188.1 4,596.1 3,326.0 4,152.0 4,318.7
Pensions 9,171.3 8,764.3 8,189.4 9,718.9 10,635.5 11,460.1 12,750.6 13,390.7 10,415.8 11,948.6 12,345.4
Equity in non-corp business 4,870.1 5,031.6 5,261.2 5,852.4 6,758.3 8,358.0 8,843.4 8,797.6 7,326.6 6,507.7 6,525.3
Other 1,610.2 1,732.3 1,778.7 1,990.7 2,192.5 2,267.2 2,465.6 2,780.2 2,688.7 2,699.1 2,728.4
Total financial assets 33,401.1 32,176.4 30,249.8 35,294.5 39,228.2 43,314.7 48,123.9 50,686.9 41,668.3 44,510.1 45,542.9
% change in financial assets -3.9% -3.7% -6.0% 16.7% 11.1% 10.4% 11.1% 5.3% -17.8% 6.8% 2.3%
TOTAL ASSETS 50,105.4 50,497.1 50,168.1 56,960.5 63,859.5 71,702.6 77,859.3 78,723.8 65,558.3 67,570.6 68,535.8
Home mortgages 4,798.4 5,305.4 6,009.9 6,894.4 7,835.3 8,874.3 9,865.0 10,538.5 10,496.9 10,334.4 10,240.3
Consumer debt 2,188.9 2,353.9 2,474.4 2,610.6 2,734.3 2,869.1 3,064.5 3,263.6 3,346.1 3,267.6 3,259.2
Total Household Debt 6,987.3 7,659.3 8,484.3 9,505.0 10,569.6 11,743.4 12,929.5 13,802.1 13,843.0 13,602.0 13,499.5
Other debt and liabilities 390.6 349.5 321.7 360.2 459.7 440.6 514.9 563.9 422.1 466.4 470.9
Total Debt and liabilities 7,377.9 8,008.8 8,806.0 9,865.2 11,029.3 12,184.0 13,444.4 14,366.0 14,265.1 14,068.4 13,970.4
NET WORTH 42,727.5 42,488.3 41,362.1 47,095.3 52,830.2 59,518.6 64,414.9 64,357.8 51,293.2 53,502.2 54,565.4
% change in net worth -0.4% -0.6% -2.7% 13.9% 12.2% 12.7% 8.2% -0.1% -20.3% 4.3% 2.0%
$ change in net worth (239) (1,126) 5,733 5,735 6,688 4,896 (57) (13,065) 2,209 1,063
Assets/liabilities ratio 6.79 6.31 5.70 5.77 5.79 5.88 5.79 5.48 4.60 4.80 4.91
mortgage debt to disposable income 65.5% 69.4% 75.0% 82.3% 88.1% 95.7% 99.5% 101.1% 95.8% 93.7% 91.3%
consumer debt to disposable income 29.9% 30.8% 30.9% 31.2% 30.8% 30.9% 30.9% 31.3% 30.5% 29.6% 29.1%
household debt to disposable income 95.4% 100.1% 105.9% 113.5% 118.9% 126.6% 130.4% 132.4% 126.4% 123.3% 120.4%
Source: Federal Reserve Publication Z-1, Apertor Research
©2010 Apertor Hospitality, LLC. All Rights Reserved.

16. SECTION 2:
Personal Income and Consumer Spending Data
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17. SECTION 2: Personal Income and Consumer Spending Data 17
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
In Figure 11, we present nominal personal income and consumer spending growth. Nominal U.S.
personal income growth ranged between 1% and 3% from 2003 to 2007 with a peak growth rate
of 2.7% achieved at 1Q06. During 3Q08 to 1Q09, growth declined for the first time during this
decade. Growth resumed during 4Q09 and has continued through 2Q10, albeit at a sluggish sub
1% rate. In summary, recent data points suggest the recovery is progressing at a slow pace.
On a state and regional level, personal income growth rates have followed the national pattern as
the effect of the recession and recent recovery has been widespread. The current sluggish growth
in personal income could slow the household deleveraging process as personal income is the
“top line” item that provides cash flow which allows households to deleverage via debt pay down.
While the growth pattern in personal income was fairly consistent throughout the U.S., state and
regional level variations do exist that could influence the pace of deleveraging in specific regions.
For regional and state level personal income detail, see Appendix 2.
Nominal U.S. consumer spending grew at a 1% to 2% rate between 2003 and 2007 before
collapsing during 3Q08 to 1Q09. Positive consumer spending growth has resumed, but at a low
sub 1% growth rate during late 2009 through 2Q10 (the latest available data point). We believe
that growth will continue but at an ongoing low rate absent an increase in wage growth that is
currently running at .5%.
Figure 11 – Nominal personal income and consumer spending (PCE) growth
Nominal Personal Income Growth Nominal PCE Growth
4% 4%
3% 3%
2% 2%
1% 1%
0% 0%
-1% -1%
1Q01
2Q01
3Q01
4Q01
1Q05
2Q05
3Q05
4Q05
1Q06
2Q06
3Q06
4Q06
1Q09
2Q09
3Q09
4Q09
1Q00
2Q00
3Q00
4Q00
1Q02
2Q02
3Q02
4Q02
1Q03
3Q03
3Q03
4Q03
1Q04
2Q04
3Q04
4Q04
1Q07
2Q07
3Q07
4Q07
1Q08
2Q08
3Q08
4Q08
1Q10
2Q10
-2% -2%
-3% -3%
Source: Bureau of Economic Analysis, Apertor Research
Figure 12 shows that between 2001 and 4Q05, the cumulative overall growth in consumer
spending was greater than the growth in nominal personal income due to borrowing and the
2003 tax cut. Between 2006 and 2008, consumer spending grew at a slower rate than personal
income as household borrowing contracted. During 2009, the consumer spending growth rate
outpaced the income growth rate due to lower tax rates.[8]
8 Nominal personal income growth is reported on a pretax basis, while consumer spending on an after tax basis. The lower tax rate in 2009
applied to personal income allowed consumer spending to grow at a higher period-to-period growth rate than personal income. If, for
example, the tax rate had remained unchanged with no other variables, the growth rate of the two economic series would have been
similar. See the NIPA accounts at the Bureau of Economic Analysis for additional information.
©2010 Apertor Hospitality, LLC. All Rights Reserved.

18. SECTION 2: Personal Income and Consumer Spending Data 18
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Figure 12 – Nominal personal income and PCE growth, taxes and savings
20% 3.0%
2.5% Personal Savings
2.0% % of Nominal PI
15% 1.5% (left axis)
1.0%
0.5% Tax % of Nominal
10% PI (left axis)
0.0%
-0.5%
-1.0% Nominal PCE
5% Growth (right
-1.5%
-2.0% axis)
0% -2.5% Nominal Personal
Income Growth
1Q01
2Q01
3Q01
4Q01
1Q02
2Q02
3Q02
4Q02
1Q03
3Q03
3Q03
4Q03
1Q05
2Q05
3Q05
4Q05
1Q06
2Q06
3Q06
4Q06
1Q09
2Q09
3Q09
4Q09
1Q00
2Q00
3Q00
4Q00
1Q04
2Q04
3Q04
4Q04
1Q07
2Q07
3Q07
4Q07
1Q08
2Q08
3Q08
4Q08
1Q10
2Q10
(right axis)
Source: Bureau of Economic Analysis, Apertor Research
Figure 13 compares y/y growth in real employee earnings to the y/y growth in real consumer
spending. The differential between the lines is comprised of employment growth and funds
generated for spending by consumer borrowing. During expansions this differential increased as
employment and credit growth occurred. During consumer spending slowdowns, y/y growth fell
back to zero as employment and borrowing contracted. The retrenchment in borrowing typically
preceded the next up cycle in consumer spending.
During 2009, consumer spending was significantly below the underlying rate of wage growth
due to a negative borrowing rate. An increase in earnings and/or decrease in savings would
have a positive effect on consumer spending growth. Recent earnings data points indicate that
earnings have essentially flat lined while savings remain at an elevated rate.
Figure 13 – Y/Y change in real consumer spending (PCE) and real hourly earnings
10% Y/Y Real PCE Y/Y Real Average Hourly Earnings 10%
8% 8%
6% 6%
4% 4%
2% 2%
0% 0%
-2% -2%
-4% -4%
-6% -6%
1Q71
4Q71
3Q72
2Q73
3Q75
2Q76
2Q79
3Q81
2Q82
1Q83
4Q83
2Q85
1Q86
4Q86
1Q89
4Q89
2Q91
1Q92
4Q92
3Q93
1Q95
4Q95
3Q96
3Q99
1Q01
4Q01
3Q02
2Q03
3Q05
2Q06
2Q09
1Q74
4Q74
1Q77
4Q77
3Q78
1Q80
4Q80
3Q84
3Q87
2Q88
3Q90
2Q94
2Q97
1Q98
4Q98
2Q00
1Q04
4Q04
1Q07
4Q07
3Q08
1Q00
Source: Apertor Research[9]
The Federal Reserve has reported that various types of credit have contracted since 2007 as
banks have pulled back on lending.[10] The household debt service ratio (debt repayments as
% of income) also continues to fall. As debt levels shrink, consumers are spending less of their
9 Chart data for Figures 13, 15, 16 and 17 was sourced from the Bureau of Labor Statistics, Bureau of Economic Analysis and prepared by
Apertor Research. The format and rational for the chart was developed and sourced from a book titled Ahead of the Curve by Joseph H. Ellis,
October 2005.
10 See, James Thompson and Kent Cherny, Commercial Bank Lending, Federal Reserve, March 2010.
©2010 Apertor Hospitality, LLC. All Rights Reserved.

19. SECTION 2: Personal Income and Consumer Spending Data 19
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
income on repayments of mortgage and consumer loans. Falling interest rates are also reducing
payments. Despite the decline, the debt service ratio needs to fall to at least another 1 percent
more to reach levels seen during 2000. See Figure 14 below.
Figure 14 – Household debt service payments as a % of disposable personal income
14.5% 14.5%
14.0% 14.0%
13.5% 13.5%
13.0% 13.0%
12.5% 12.5%
12.0% 12.0%
11.5% 11.5%
11.0% 11.0%
10.5% 10.5%
10.0% 10.0%
Jan-80
Apr-81
Jul-82
Oct-83
Jan-85
Apr-86
Jul-87
Oct-88
Jan-90
Apr-91
Jul-92
Oct-93
Jan-95
Apr-96
Jul-97
Oct-98
Jan-00
Apr-01
Jul-02
Oct-03
Jan-05
Apr-06
Jul-07
Oct-08
Jan-10
Source: Federal Reserve
Figure 15 depicts the relationship between real consumer spending and the combined effect of
changes in employment (a lagging indicator) and hourly earnings (a leading indicator). The chart
shows that changes in employment and earnings impact spending as the lines move closely
together. The chart suggests that these two economic factors account for the majority of the
change in consumer spending. Net borrowing or savings by consumers accounts for the majority
of difference between the y/y real PCE (consumer spending) and y/y combined effect of real
earnings and employment growth. Between 2002 and 2006 the gap between the lines occurred
during the period when household mortgage debt significantly increased. During 2008 and 2009
the sharp reduction in borrowing (offset to some degree) by a tax cut forced consumer spending
lower than the combined effect of wage growth.
Figure 15 – Y/Y change in consumer spending and combined real earnings & employment growth
Y/Y Real PCE Y/Y Combined Real Earnings and Employment Growth
10% 10%
8% 8%
6% 6%
4% 4%
2% 2%
0% 0%
-2% -2%
-4% -4%
-6% -6%
1Q71
4Q71
3Q81
2Q91
1Q01
4Q01
3Q72
2Q73
3Q75
2Q76
2Q79
2Q82
1Q83
4Q83
2Q85
1Q86
4Q86
1Q89
4Q89
1Q92
4Q92
3Q93
1Q95
4Q95
3Q96
3Q99
3Q02
2Q03
3Q05
2Q06
2Q09
1Q74
4Q74
1Q77
4Q77
3Q78
1Q80
4Q80
3Q84
3Q87
2Q88
3Q90
2Q94
2Q97
1Q98
4Q98
2Q00
1Q04
4Q04
1Q07
4Q07
3Q08
1Q00
Source: Apertor Research
©2010 Apertor Hospitality, LLC. All Rights Reserved.

20. SECTION 2: Personal Income and Consumer Spending Data 20
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Figure 16 shows that unemployment (shown inverted at the right scale) is a lagging indicator. In
past cycles unemployment has generally continued to decrease well after economic cycles have
peaked while it has tended to increase well after consumer spending began to recover. History
and the recent slightly positive consumer spending data suggest that if consumer spending
continues to rise in a modest manner unemployment could rise further but then will eventually
fall at a modest rate.
Figure 16 – Y/Y change in consumer spending and unemployment rate (rate presented on inverse basis – see right axis)
Y/Y Real PCE Lagged Three Months Unemployment Rate
10% 0%
8% 2%
6%
4%
4%
6%
2%
8%
0%
-2% 10%
-4% 12%
1Q71
4Q71
3Q72
2Q73
3Q75
2Q76
2Q79
3Q81
2Q82
1Q83
4Q83
2Q85
1Q86
4Q86
1Q89
4Q89
2Q91
1Q92
4Q92
3Q93
1Q95
4Q95
3Q96
3Q99
1Q01
4Q01
3Q02
2Q03
3Q05
2Q06
2Q09
1Q74
4Q74
1Q77
4Q77
3Q78
1Q80
4Q80
3Q84
3Q87
2Q88
3Q90
2Q94
2Q97
1Q98
4Q98
2Q00
1Q04
4Q04
1Q07
4Q07
3Q08
1Q00
Source: Apertor Research
Figure 17 also shows that employment is a lagging indicator as employment trends have
followed consumer spending. Past recoveries depicted in the chart look like jobless recoveries
during the early stage of the recovery period. The chart suggests that if consumer spending
continues to increase employment will eventually follow. The current open question is the pace of
consumer spending looking forward as the most recent data point has “rolled over” from recent
higher levels (2Q10 vs. 1Q10).
Figure 17 – Y/Y change in real consumer spending and growth in employment
y/y real PCE lagged three months growth in civilian employment
10% 10%
8% 8%
6% 6%
4% 4%
2% 2%
0% 0%
-2% -2%
-4% -4%
1Q71
4Q71
3Q72
2Q73
3Q75
2Q76
2Q79
3Q81
2Q82
1Q83
4Q83
2Q85
1Q86
4Q86
1Q89
4Q89
2Q91
1Q92
4Q92
3Q93
1Q95
4Q95
3Q96
3Q99
1Q01
4Q01
3Q02
2Q03
3Q05
2Q06
2Q09
1Q74
4Q74
1Q77
4Q77
3Q78
1Q80
4Q80
3Q84
3Q87
2Q88
3Q90
2Q94
2Q97
1Q98
4Q98
2Q00
1Q04
4Q04
1Q07
4Q07
3Q08
1Q00
Source: Apertor Research
©2010 Apertor Hospitality, LLC. All Rights Reserved.

21. SECTION 3:
Household Debt Metrics
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22. SECTION 3: Household Debt Metrics 22
Consumer Deleveraging and the U.S. Gaming Industry
October 12, 2010
Figure 18 depicts household debt to GDP. Household debt to GDP increased between 1975 and
2006 to 2007 before falling in 2008 and 2009. Despite the decrease, debt levels remain elevated
relative to history. McKinsey pointed out that historically, some economies have successfully
operated at high debt to GDP levels while others, despite lower debt levels, have faced
difficulties. As a result, debt to GDP levels cannot be evaluated single handily as many factors
drive economies. Nonetheless, debt levels in the U.S. economy currently remain at high levels
relative to history.
Figure 18 – Household debt to GDP
100% 100%
90% 90%
80% 80%
70% 70%
60% 60%
50% 50%
40% 40%
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
1Q2010
Source: Bureau of Economic Analysis, Apertor Research
Figure 19 depicts the relationship between mortgage, other household debt and disposable
personal income (i.e. personal income after tax) from 2000 to 1Q10. Household debt (mortgage
and other) relative to income rose steadily until 2007 and has since declined owing to
deleveraging and modest income growth. Further reduction of debt to income, requires a
combination of continued income growth and debt repayment or default.
Household Mortgage Debt
The mortgage debt to income relationship was 65% and 101% at 2000 and 2007 (the peak
year) and has since dropped to approximately 90%. Economist we have spoken to, believe that
mortgage deleveraging will persist which will cause the debt to income relationship to continue
to fall on a percentage basis over the next several years. What is not presently known is precisely
where the relationship may bottom out on a go forward extended run-rate basis. The current
90% mortgage debt to income relationship suggests that approximately 25% of the mortgage
deleveraging process has taken place since the peak, based on a debt to income relationship
of 101% at 2007 and 65% at 2000. Based on a 1.5% to 2.0% income growth rate forecast over
the next three years and eventual long-term forward looking debt to income run rate of 80%,
implies that between $720 and $850 million of debt would need to be deleveraged from current
mortgage debt levels during this period. Our estimate suggests that at this deleveraging pace
and if the deleveraging process was comprised entirely of repayments, consumer spending
growth could be reduced by approximately 70 to 80 basis points per annum. Higher income
growth rates and a longer than three year ramp-down assumption and/or deleveraging via
default would reduce this drag on consumer spending.
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