Real Estate Economics & Market Analysis Problem Set

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REAL ESTATE ECONOMICS & MARKET ANALYSIS
Submit in MSWord putting answers below each Sub/Question
1) REAL ESTATE MARKETS
(a) Define and identify the economic purpose of: 1) the Property Market and 2) the
Asset Market. Identify one exogenous force acting upon each market.
(b) Identify the primary determinants on capitalization rates and their expected
directional impacts (positively or negatively correlated) on the cap rate.
(c) How would the asset/property framework explain why a reduction in longterm mortgage rates has the opposite impact on market values than a
reduction in short-term rates.
(d) Many expect long term interest rates to rise this year. Explain the impact on
market values, rents, and construction. Include the role of linkages across
markets in determining the combined impact on the sector as a whole. Please
consider drawing a diagram; while not required, you may find using one helpful.
2) URBAN ECONOMICS AND ECONOMIC BASE THEORY
a. Define Agglomeration; Explain in your own words why it is often
characterized as the source of urban efficiency.
b. Describe the multiplier process and its significance to growth of an urban
economy.
c. Using the San Jose (SAJ) Outlook Precis posted on NYU Brightspace, profile
the economic bases of Seattle and briefly describe the city’s prospects for
future growth using the most relevant economic terms learned.
d. Explain the statement, “An urban economy dependent on any particular set of
export industries is likely to face an episodic economic future.”
e. Explain why globalization leads to further urbanization.
3) LAND USE AND THE IMPACT OF LOCAL GOVERNMENTS
(a) Define externality. Provide one example in relation to real estate markets.
(b) Define (1) fiscal zoning and (2) fiscal capitalization.
(c) Explain why the property tax is often described as the most important ownsource revenue of local governments.
(d) What is the long-run economic incidence of an increase of the property tax?
Explain.
4) ECONOMICS OF HIGHEST AND BEST USE
(a) Define Highest and Best Use.
(b) Explain the statement: “Cities are Value
Propositions.”
Propositions,
not
Cost
SAN JOSE-SUNNYVALE-SANTA CLARA CA
Data Buffet® MSA code: IUSA_MSAJ
ECONOMIC DRIVERS
MANUFAC
HIGH TECH
RELATIVE COSTS
EMPLOYMENT GROWTH RANK
2019-2021
2019-2024
4th quintile
3rd quintile
273
TURING
202
Recovery
Best=1, Worst=410
At Risk
STRENGTHS & WEAKNESSES
STRENGTHS
» Highly skilled workers and a legacy of successful
entrepreneurship allow SAJ to access substantial
venture capital.
» Tech-centered higher education institutions
provide ample pipeline of workers.
WEAKNESSES
» Traffic congestion, regulatory burdens, and high
business and living costs.
» Tech industries prone to large cyclical booms and
busts, above-average volatility.
COVID-19
EXPOSURE
November 2020
X
W
FORECAST RISKS
SHORT TERM
LONG TERM
393
5th quintile
Most=1
Least=403
UPSIDE
» Bigger boost to economy from fiscal and
monetary stimulus.
» Fewer residents leave SAJ because of high costs;
population growth is stronger.
DOWNSIDE
» COVID-19 does more economic damage.
» Large negative wealth effect depresses consumer
spending.
» Commercial real estate demand plummets.
» Venture capital for startups dries up.
MOODY’S RATING
NR
QUALITY
RELATIVE
OF LIFE
U.S.=100%
Best=1, Worst=403
Best=1, Worst=378
18
ANALYSIS
Late
Expansion
In Recession
BUSINESS
187% 147% 180%
Rank: 1
BUSINESS CYCLE STATUS
Mid
Expansion
LIVING
VITALITY
Recent Performance. San Jose-SunnyvaleSanta Clara’s recovery is underwhelming. The
recession is over and job growth bests the California average. However, the increase in employment still lags the national pace and other
large economies. At 5.8%, the jobless rate has
improved significantly but is more than double
where it was at the start of the year. Residential
construction is rebounding after a fall this spring.
Reticent recovery. The rapid spread of COVID-19 will delay the return to business as usual
in SAJ in the first part of 2021. The option to work
from home will keep most of SAJ’s office workers employed, but no economy is immune. As
in most of the state, SAJ is under new stay-athome orders and most nonessential businesses
are closed. Widespread business closures all but
ensure further layoffs this winter even with another round of federal fiscal stimulus that will extend emergency federal unemployment benefits
and help keep a floor under personal income and
consumer spending. However, SAJ residents are
wealthier and have more savings compared with
national averages and so are better equipped to
ride out the economic punch from an uneven
economic recovery. Relatively stable incomes
should support consumer industries, but risks linger. Until the pandemic is brought under control,
many firms and consumers will remain cautious.
Still got it. Technology firms will remain the
driving force behind the SAJ economy, and the
Bay Area in general will stay the world’s preeminent tech hub. High costs are undoubtedly a deterrent to some, but plenty of firms are willing to
pay a premium for the advantages of doing business in SAJ. The metro area is home to household names in tech, including Apple, Google and
Facebook. Product diversity as well as clustering
effects will ensure the industry’s resilience. Low
costs are a clear appeal of emerging tech hubs,
but the advantages do not go much further than
that. Silicon Valley consistently garners an outsize share of venture capital. The quality of SAJ’s
workforce, abundant venture capital, and innovative culture are unparalleled farther inland.
Checks. Even as Silicon Valley remains the
preeminent tech hub, the population will contract again in 2021 as cost pressures return
and mobility increases as the recovery heats
up late in 2021 and 2022. Population growth
slowed for much of the last business cycle due
to out-migration, particularly among low- and
mid-wage earners who could no longer afford
the sky-high cost of living. After years of slow
growth, SAJ’s population fell in 2019. Out-migration likely paused in 2020 with more residents remaining in place but will resume in the
next few years. Using history as a guide, the
Bay Area also lost residents in the early 2000s.
Then, during the Great Recession, net migration stabilized as residents stayed put, before
picking up with the economy. Once the 2020
recession is fully in the rearview, out-migration
will resume. However, middling population
growth will slow the overheating we saw at the
end of the last business cycle and prove a useful
check on excesses that could cause problems
when they are ultimately unwound.
San Jose-Sunnyvale-Santa Clara’s nearterm outlook is as dicey as that for the rest of
the state and nation. Most job losses tied to
the surge in the virus will be temporary and
SAJ will regain its footing once the pandemic
is under control. However, a full recovery in
employment will take at least two years. A
highly skilled workforce, tech agglomeration,
and a legacy of entrepreneurship will ensure
that the metro area appeals to firms even
amid high costs. SAJ looks forward to a bright
future over the forecast horizon.
1-866-275-3266
Laura Ratz
help@economy.com
November 2020
2014
2015
2016
2017
2018
2019
INDICATORS
2020
2021
2022
2023 2024 2025
184.6
7.9
1,007.4
4.2
5.3
9.8
96.7
1,949.6
1.3
11.8
1,861
8,176
313.0
201.1
8.9
1,046.2
3.8
4.2
10.5
102.8
1,974.5
1.3
10.8
1,897
3,891
346.0
214.6
6.7
1,080.4
3.3
3.9
8.3
109.8
1,987.6
0.7
-0.5
2,099
4,068
374.8
232.6
8.4
1,106.1
2.4
3.3
8.6
117.4
1,992.7
0.3
-7.8
2,592
5,947
397.8
246.6
6.0
1,126.4
1.8
2.7
7.6
124.3
1,993.8
0.1
-10.4
2,466
6,278
441.4
257.3
4.3
1,146.9
1.8
2.6
4.2
130.9
1,990.7
-0.2
-14.1
2,603
3,627
439.7
Gross metro product (C12$ bil)
% change
Total employment (ths)
% change
Unemployment rate (%)
Personal income growth (%)
Median household income ($ ths)
Population (ths)
% change
Net migration (ths)
Single-family permits (#)
Multifamily permits (#)
FHFA house price (1995Q1=100)
247.6
-3.8
1,076.6
-6.1
7.1
4.3
128.9
2,000.8
0.5
-1.7
1,781
5,230
436.3
255.9
3.4
1,082.2
0.5
7.1
2.1
129.6
2,014.9
0.7
1.5
2,064
3,902
452.4
271.1
6.0
1,116.8
3.2
5.4
4.1
134.4
2,027.6
0.6
0.0
2,833
3,955
480.8
282.8
291.4 299.0
4.3
3.1
2.6
1,150.1 1,166.4 1,174.3
3.0
1.4
0.7
3.5
3.2
3.5
6.6
6.2
5.5
141.0
147.5
153.8
2,040.8 2,054.0 2,066.9
0.7
0.6
0.6
0.4
0.4
0.1
3,200
3,348
3,193
4,385
4,726 4,632
521.7
576.1
638.1
MOODY’S ANALYTICS / Précis® U.S. Metro / November 2020
PRÉCIS® U.S. METRO • San Jose-Sunnyvale-Santa Clara CA
ECONOMIC HEALTH CHECK
3-MO MA
May 20
-33.1
9.1
66.1
35.5
119.1
840
1,640
Dec 14
36.3
Employment, change, ths
Unemployment rate, %
Labor force participation rate, %
Average weekly hours, #
Industrial production, 2012=100
Residential permits, single-family, #
Residential permits, multifamily, #
Dec/Dec
Employment, change, ths
Better than prior 3-mo MA
Jun 20
-42.6
11.5
66.0
35.4
118.0
946
1,551
Dec 15
38.5
Jul 20
-21.2
10.5
66.0
35.6
119.9
1,518
9,315
Dec 16
30.3
BUSINESS CYCLE INDEX
Aug 20
-1.3
9.0
66.0
36.1
123.0
2,076
10,577
Dec 17
24.0
Unchanged from prior 3-mo MA
Sep 20
11.2
7.9
65.6
36.1
123.6
2,627
11,483
Dec 18
22.2
Oct 20
9.9
6.8
66.4
36.3
123.7
2,778
3,781
Dec 19
15.3
JAN 2010=100
160
150
140
130
120
110
100
90
10 11 12 13 14 15 16 17 18 19 20
SAJ
Worse than prior 3-mo MA
Source: Moody’s Analytics
Sources: BLS, Census Bureau, Moody’s Analytics
CURRENT EMPLOYMENT TRENDS
15
16
Government
17
18
DIFFUSION INDEX
% CHANGE YR AGO, 3-MO MA
Oct 19
Apr 20 Oct 20
% CHANGE YR AGO
6
4
2
0
-2
-4
-6
-8
-10
-12
19
20
Goods producing
Private services
Sources: BLS, Moody’s Analytics
Total
Mining
Construction
Manufacturing
Trade
Trans/Utilities
Information
Financial Activities
Prof & Business Svcs.
Edu & Health Svcs.
Leisure & Hospitality
Other Services
Government
1.8
0.3
6.3
-0.6
-2.3
4.0
10.0
4.0
2.5
0.4
0.7
1.2
1.3
-3.4
-16.2
-11.2
-1.6
-5.3
0.7
3.7
1.8
-0.3
-1.5
-20.4
-12.9
-0.0
-7.1
-33.1
-3.3
-4.9
-7.8
4.0
-11.0
-5.5
-0.8
-2.6
-31.9
-18.6
-4.2
Sources: BLS, Moody’s Analytics
3-DIGIT NAICS LEVEL, 6-MO MA
70
65
60
55
50
45
14
15
16
SAJ
18
19
U.S.
20
HOUSE PRICE
JAN 2010=100
FORECAST
VS. 6 MO PRIOR
140
135
130
125
120
115
110
105
100
95
W X
?
l
?
?
l
W ?
5-Yr
?
l
?
2-Yr
1998Q1=100, NSA
400
350
300
250
200
150
100
50
98
10 11 12 13 14 15 16 17 18 19 20F 21F 22F 23F 24F
CA
17
CA
Sources: BLS, Moody’s Analytics
RELATIVE EMPLOYMENT PERFORMANCE
SAJ
U.S.
CA
01
SAJ
U.S.
04
07
10
CA
13
16
19
U.S.
Sources: FHFA, Moody’s Analytics
Sources: BLS, Moody’s Analytics
RENTAL AFFORDABILITY
HOUSE PRICE TRENDS
HOUSING AFFORDABILITY
GREATER THAN 100=MORE AFFORDABLE
%
GREATER THAN 100=MORE AFFORDABLE
190
50
40
30
20
10
0
-10
-20
-30
-40
180
170
160
150
140
130
120
110
98
95 97 99 01 03 05 07 09 11 13 15 17 19
SAJ
CA
01
04
07
Overvalued
U.S.
Sources: Census Bureau, BLS, Moody’s Analytics
220
200
180
160
140
120
100
80
60
40
Sources: FHFA, Moody’s Analytics
MOODY’S ANALYTICS / Précis® U.S. Metro / November 2020
10
13
16
Undervalued
19
95 97 99 01 03 05 07 09 11 13 15 17 19
SAJ
CA
Sources: NAR, Moody’s Analytics
U.S.
PRÉCIS® U.S. METRO • San Jose-Sunnyvale-Santa Clara CA
EMPLOYMENT AND INDUSTRY
TOP EmPLOYERS
Cisco Systems Inc.
Lockheed Martin Corp.
Intel Corp.
Alphabet Inc.
Applied Materials Inc.
Flextronics International
Lumileds Lighting Co.
San Jose State University
eBay Inc.
PayPal
Adobe Systems Inc.
Kaiser Permanente
Target Corporation
Good Samaritan Health System
Western Digital
Super Micro Computer
Safeway
Cadence Design Systems Inc.
Regional West Medical Center
KLA-Tencor Corp.
9,500
5,000-9,999
5,000-9,999
5,000-9,999
5,000-9,999
5,000-9,999
5,000-9,999
3,600
3,400
3,300
2,900
2,585
2,400
2,240
2,200
2,000
1,800
1,750
1,625
1,000-4,999
Sources: CA Economic Development, San Benito County 2020, CA
Economic Development, Santa Clara County 2020, City of San Jose,
2019, San Francisco Business Journal Book of Lists, 2017, Silicon Valley
Business Journal Book of Lists, 2017
PUbLIC
Federal
State
Local
9,959
6,926
80,317
ENTREPRENEURSHIP
INDUSTRIAL DIVERSITY
EMPLOYMENT IN NEW COMPANIES, % OF TOTAL
Most Diverse (U.S.)
1.00
0.80
0.0
0.60
Least Diverse
EmPLOYmENT VOLATILITY
Due to U.S. fluctuations
Relative to U.S.
100
80
60
96%
163
100
20
0
SAJ
Due to U.S.
U.S.
COMPARATIVE EMPLOYMENT AND INCOME
% OF TOTAL EMPLOYMENT
Sector
Mining
Construction
Manufacturing
Durable
Nondurable
Transportation/Utilities
Wholesale Trade
Retail Trade
Information
Financial Activities
Prof. and Bus. Services
Educ. and Health Services
Leisure and Hosp. Services
Other Services
Government
SAJ
0.0
4.6
15.1
92.6
7.4
1.4
2.8
7.3
8.8
3.3
21.2
15.3
9.3
2.5
8.5
CA
0.1
5.1
7.6
64.2
35.8
4.0
4.0
9.5
3.2
4.8
15.6
16.1
11.7
3.3
15.0
U.S.
0.5
5.0
8.5
62.8
37.2
4.1
3.9
10.4
1.9
5.8
14.1
16.0
11.0
3.9
15.0
AVERAGE ANNUAL EARNINGS
SAJ
$17,381
$106,042
$242,514
nd
nd
nd
nd
$58,795
nd
$82,928
nd
$82,965
$41,089
$53,231
$114,400
CA
U.S.
$91,905 $143,474
$80,984 $69,453
$111,674 $85,553
$129,452 $88,829
$81,105
$80,103
$64,560 $65,295
$91,388 $90,846
$43,950 $36,772
$202,402 $131,243
$67,581 $58,857
$85,838 $73,795
$59,164 $57,980
$38,019 $30,355
$41,848 $38,978
$101,405 $80,989
Sources: Percent of total employment — BLS, Moody’s Analytics, 2019, Average annual earnings — BEA, Moody’s Analytics, 2018
BUSINESS COSTS
HIGH-TECH
EmPLOYmENT
Energy
SAJ
340.0
29.6
U.S.
7,498.9
5.0
HOUSING-RELATED
EmPLOYmENT
State and local taxes
Ths
Office rent
2013
150
200
250
2018
Source: Moody’s Analytics

MOODY’S ANALYTICS / Précis® U.S. Metro / November 2020
HIGH
Unit labor
% of total
MID
Ths
100
1.2
1.4
1.6
U.S.
Product
Food and kindred products
Chemicals
Primary metal manufacturing
Fabricated metal products
Machinery, except electrical
Computer and electronic products
Transportation equipment
Miscellaneous manufacturing
Other products
Total
$ mil
ND
ND
ND
ND
ND
ND
ND
ND
ND
20,909.4
Destination
Africa
Asia
European Union
Canada & Mexico
South America
Rest of world
Total
$ mil
ND
ND
ND
ND
ND
ND
20,909.4
% of GDP
Rank among all metro areas
7.8
91
Sources: BEA, International Trade Administration, Moody’s
Analytics, 2019
PRODUCTIVITY
REAL OUTPUT PER WORKER, $
172,571
SAJ
113,832
CA
93,674
U.S.
Sources: BEA, Moody’s Analytics, 2018
NAICS Industry
% of total
SAJ
106.1
9.3
U.S.
14,552.2
9.6
Source: Moody’s Analytics, 2019
LOW
Total
50
1.0
CA
LEADING INDUSTRIES BY WAGE TIER
U.S.=100
0
0.8
EXPORTS
0.00
Not due to U.S.
0.6
Sources: Census Bureau, Moody’s Analytics, avg 2012-2016
0.19
0.20
2019
0.4
SAJ
0.40
40
0.2
5415
3341
3344
5191
GVL
5617
6111
5616
7225
6241
4451
7211
Location Employees
Quotient
(ths)
Computer systems design & related srvcs.
5.4
Computer & peripheral equipment manuf.
42.5
Semiconductor & other elect. comp. manuf. 15.5
Other information services
18.4
Local Government
0.7
Services to buildings and dwellings
1.2
Elementary and secondary schools
1.4
Investigation and security services
1.3
Restaurants and other eating places
0.9
Individual and family services
1.8
Grocery stores
0.8
Traveler accommodation
0.7
Source: Moody’s Analytics, 2019
76.9
48.4
41.5
33.1
76.4
17.1
9.9
8.6
65.6
28.6
14.9
8.9
PRÉCIS® U.S. METRO • San Jose-Sunnyvale-Santa Clara CA
SKILLS MISMATCH
MIGRATION FLOWS
% OF TOTAL
INTO SAN JOSE CA
Less than HS
Undereducated
High School
Balanced
SAJ
Some College
Overeducated
U.S.
ECONOMIC DISENFRANCHISEMENT
Associate’s
Bachelor’s
Graduate
0
5
10
15
20
25
30
Index
Gini coefficient
Palma ratio
Poverty rate
Rank*
115
11
393
*Most unequal=1; Most equal=403
Population
Occupations
Sources: Census Bureau, ACS, Moody’s Analytics, 2018
HOUSEHOLDS BY INCOME, %
PER CAPITA INCOME
40,000-59,999
60,000-74,999
75,000-99,999
100,000-124,999
125,000-149,999
150,000-199,999
200,000+
2019
SAJ
SAJ $111,227
CACA
$66,619
0
U.S.
U.S. $56,490
Sources: BEA, Moody’s Analytics
5
SAJ
10
15
20
U.S.
25
30
0
WORKERS WHO LIVE IN SAJ
-2,000
-4,000
-6,000
-8,000
-10,000
-12,000
77.2%
Top Five Outside Sources of Jobs
San Jose CA
San Francisco CA
Oakland CA
Santa Cruz CA
Salinas CA
Riverside CA
Share
6.6
4.5
0.6
0.6
0.1
-14,000
-16,000
Top Five Outside Sources of Workers
San Jose CA
San Francisco CA
Oakland CA
Santa Cruz CA
Stockton CA
Salinas CA
Share
8.3
8.2
1.8
1.0
0.7
GENERATIONAL BREAKDOWN
EDUCATIONAL ATTAINMENT
POPULATION BY GENERATION, %
% OF ADULTS 25 AND OLDER
100
80
Millennial
25
60
28
Gen X
40
22
Baby Boom
20
14
11
0
Silent &
Greatest
SAJ
0
5
10
15
SAJ
20
25
< High school Some college Graduate school 30 U.S. Sources: Census Bureau, Moody’s Analytics, 2019 16 Domestic Foreign Total 17 18 19 2016 2017 2018 2019 -20,449 19,990 -459 -25,698 17,908 -7,790 -23,656 13,219 -10,437 -27,495 13,371 -14,124 Sources: IRS (top), 2018, Census Bureau, Moody’s Analytics Sources: Census Bureau, Moody’s Analytics, avg 2011-2015 Gen Z -25,386 NETMigration, MIGRATION, Net SAJ # COMMUTER FLOWS 86.8% 16,952 11,634 6,303 4,765 2,921 2,562 2,517 2,464 2,399 2,161 94,255 Net migration Sources: Census Bureau, ACS, Moody’s Analytics, 2019 RESIDENTS WHO WORK IN SAJ 10,475 10,019 3,737 2,197 1,999 1,941 1,603 1,597 1,488 1,474 68,869 Oakland CA San Francisco CA Sacramento CA Stockton CA Los Angeles CA Merced CA Seattle WA Santa Cruz CA Modesto CA San Diego CA Total out-migration 20,000-39,999 09 10 11 12 13 14 15 16 17 18 19 San Francisco CA Oakland CA Los Angeles CA New York NY Sacramento CA San Diego CA Santa Cruz CA Seattle WA Stockton CA Anaheim CA Total in-migration FROM SAN JOSE CA 0-19,999 $ THS 120 110 100 90 80 70 60 50 40 30 2018 0.47 4.1 7.2% Number of Migrants 13 13 22 20 28 29 21 27 16 11 CA U.S. High school College Sources: Census Bureau, ACS, Moody’s Analytics, 2019 MOODY’S ANALYTICS / Précis® U.S. Metro / November 2020 POPULATION BY AGE, % ?75 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 0 2 SAJ 4 6 U.S. 8 Sources: Census Bureau, Moody’s Analytics, 2019 10 PRÉCIS® U.S. METRO • San Jose-Sunnyvale-Santa Clara CA GEOGRAPHIC PROFILE POPULATION DENSITY MEDIAN HOUSEHOLD INCOME POPULATION & HOUSING CHARACTERISTICS Units Total area Total water area Total land area Land area - developable Land area - undevelopable sq mi sq mi sq mi sq mi sq mi 2,694.5 15.6 2,678.8 845.8 1,833.1 125 296 113 186 79 pop. to developable land ths % of population % of population % of population 2,323.4 1,990.7 58.8 21.6 18.1 11 40 396 2 4 37.4 257 Population density Total population U.S. citizen at birth Naturalized U.S. citizen Not a U.S. citizen AVERAGE COMMUTE TIME Value Rank* Median age Total housing units Owner occupied Renter occupied Vacant ths % of total % of total % of total 706.3 51.8 42.0 6.2 45 335 16 354 1-unit; detached 1-unit; attached % of total % of total 51.2 10.3 377 28 Multifamily % of total Median year built 35.5 1975 29 * Areas & pop. density, out of 410 metro areas/divisions, including metros in Puerto Rico; all others, out of 403 metros. Sources: Census Bureau, Moody’s Analytics, 2019 except land area 2010 Sources: ACS, Moody’s Analytics MOODY’S ANALYTICS / Précis® U.S. Metro / November 2020 About Moody’s Analytics Moody’s Analytics provides financial intelligence and analytical tools supporting our clients’ growth, efficiency and risk management objectives. The combination of our unparalleled expertise in risk, expansive information resources, and innovative application of technology helps today’s business leaders confidently navigate an evolving marketplace. We are recognized for our industry-leading solutions, comprising research, data, software and professional services, assembled to deliver a seamless customer experience. Thousands of organizations worldwide have made us their trusted partner because of our uncompromising commitment to quality, client service, and integrity. 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