BRINNER2
10.ppt
Business Investment
“Investment”: not “financial” in the everyday sense but purchases of plant & equipment, (or additions to inventories)
“I” is demand today, supply tomorrow; unique among GNP spending categories
The capacity created by I is flexible (through variation in shifts, maintenance schedules, etc) so purchase can be delayed in tough times
BRINNER3
10.ppt
Business Investment
-10%
-5%
0%
5%
10%
15%
20%
1983
1985
1987
1989
1991
1993
1995
1997
1999
Investment Growth Real GDP Growth
A key question for economists seeking to understand the business cycle was: “Why are the cycles in investment growth so much greater than those in output growth?”
BRINNER4
10.ppt
Gross & Net Investment
I is “gross investment” I-CCA is “net investment” a capital stock rises from period to period by
the amount of net investment or I(gross)=I(replacement)+I(net) K (Capital this period)=
= K\1 + I (gross) - D = K\1 + I (net)
BRINNER5
10.ppt
The Optimal Level of Capital
Simple World: It takes· one $2500 machine· housed in a $2500 building· plus $3000 of labor · to make $5000 of output.· Machines last 10 years, buildings 25,
decaying linearly.· No substitution is possible.
BRINNER6
10.ppt
The Optimal Level of Capital
K / Y = ($2500+$2500) / $5000 = 1 Thus Optimal=Necessary K = 1 x Y If Y is constant at $5000, then so must be K K decays/depreciates each year by
· 10% x $2500 (equip)=$250· 4% x $2500 (building)=$100· thus I (replacement) must be $350 per year to
keep K stable at $5000, with $2500 of each type of K
BRINNER7
10.ppt
The Optimal Level of Capital
What if the producer wants to boost output (Y) by 3% to $5150?
K must rise to $5150, meaning I (net) must be $150 added to I(replacement) $350 implies I(gross) = $500
So investment in that year is 10% of output In fact, these are the numbers for the US
Machines & Factories Required to Produce Output
0
2000
4000
6000
8000
10000
12000
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
$ B
illi
on
Real GDP Private Cap
Accelerator Data: Change in Output vs Levels of Gross & Net Investment
$(200)
$-
$200
$400
$600
$800
$1,000
$1,200
$1,400
$1,600
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
Change in Real GDP Gross Investment Net Investment
Recent shift to even higher investment relative to GDP is due to new technology opportunities
Note: Net Investmentroughly matches theUS change in GDP
BRINNER10
10.pptAccelerator Model Implications for the Business Cycle
Note how variations in Y get amplified in variations in I
A $150 change in Y required a $150 change in I Or, a 3% change in Y required a 40+% change
in I Realistically, the response to an output change
isn’t so sudden, and the base level of investment includes some net addition because output is trending up
BRINNER11
10.ppt
The Optimal Level of Capital I = I(gross)= I (replacement) + I(net)
• I (replacement)=dep. rate x K = c1 x K=c1 x Y• I (net) = c2 * [ Y - Y \1]
I = c1 * Y + c2 * [ Y - Y\1 ] Note that the level of investment is a function of the
change (the first derivative) in output; By extension, the growth of investment (the first
derivative) is a function of the acceleration (the second derivative) in output:
Hence the Accelerator Model of Investment
BRINNER12
10.ppt
The Optimal Level of Capital
In a more realistic model, production can temporarily rise without adding K by adding a shift or overtime or delaying maintenance, thus c1 is not rigidly fixed, and new capital- or labor saving technology can be introduced so c2 is also not rigidly fixed
The microeconomic basis of c2: the optimal capital-output ratio• relative prices and productivity for capital , output, and
labor determine this• the first basic extension is the Cobb-Douglas production
model
BRINNER13
10.ppt
The Optimal Level of Capital
Y= KbL(1-b)
dY/dK=marginal product of capital = bK(b-1)L(1-b)
» =b (1/K) KbL(b-1)
» =b (1/K) Y» =b Y/K = b * Average Product of Capital
marginal product of capital = b * average product of capital
BRINNER14
10.ppt
The Optimal Level of Capital
dY/dK=marginal product of capital = b * Y/K = b * Avg. Product of Capital The real price paid per unit of capital is Pk / Py In equilibrium, this price is its marginal product
• Thus Pk/Py = b * Y /K Solve for K to find the optimal K:
• K = b * Py/Pk * Y Or the optimal K/Y ratio = b* Py/Pk
• Just like the simple fixed coefficient model, except the ratio is now sensitive to the real price of capital
BRINNER15
10.ppt
The Optimal Level of Capital
The price paid per unit of capital is Pk / Py In equilibrium, this price is its marginal
product Pk/Py = b * Y /K What is b, that is how can it be interpreted
beyond “the exponent of capital”?
• b= (Pk * K) / (Py * Y)• = capital income / total income• hence the capital share of income
BRINNER16
10.ppt
The “Price or Cost” of Capital
The cost of funds (“r”)... ...minus price appreciation of the real
asset (“inflation”)... ...plus the cost of perfect maintenance =
the rate of depreciation (“d”)
So the cost, Pk/Py = r - inflation + d
BRINNER17
10.pptTransitions between Targeted Equilibrium Points
In practice, future K (K*) is targeted to hit the optimal level consistent with an expected future path of Y (Y*) given an expected cost of capital ( (Pk/Py)* )
K* = b Q* (Py/Pk)* Economists add lag structures to reflect
expectations
BRINNER18
10.ppt
Examples from a specific company The company manufactures equipment used to
facilitate construction:» Aerial work platforms (“AWP” in next slides for lifting people ; 2
types--”scissor lifts” and “boom lifts”» Material Handlers to lift bricks, wood, etc
The “output” driving the need for capital is thus construction spending
You will see that the cycle in this firm’s equipment sales are far greater than the cycle in construction
Construction is itself more volatile than GDP
BRINNER19
10.ppt
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
50,000
1985
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
0
7,000
14,000
21,000
28,000
35,000
42,000
49,000
56,000
63,000
70,000
Total Booms Straight Booms Articulated Booms
Scissors Total Units
-80%
-60%
-40%
-20%
0%
20%
40%
60%
80%
100%
1985
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Total Booms Straight Booms Articulated BoomsScissors Total Units
The cyclical volatility of scissors is similar to that of total booms, but slightly greater
Historical Patterns in Aerial Work Platform Demand Growth and Volatility of Industry Sales
• The boom and scissors markets are locked in tandem, with scissors remaining near 70%. (Total aerial work platform units are charted against the right scale, scissors and all others against the left scale)
• Articulated booms enjoy a persistent, stable market preference versus straight booms
AWP Unit Sales AWP Sales Growth
Yea
r O
ver
Yea
r G
row
th R
ate
Num
ber
of U
nits
by
Pro
duct
Lin
e
Total N
umber of U
nits
BRINNER20
10.ppt
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
25%
1985
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
-60%
-45%
-30%
-15%
0%
15%
30%
45%
60%
75%
Nonresidential ConstructionIndustrial Production (excluding computers)Gross Domestic ProductTotal Units
-60%
-40%
-20%
0%
20%
40%
60%
80%
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Aerial Work PlatformsValue of Semiconductor ShipmentsSales of ElectronicsSales of Semiconductors - Worldwide
Perhaps the growth of this sector is best appreciated by comparing it to a widely-hailed, high-growth, and high-tech sector: semiconductors
Three alternate government indicators of semiconductor growth are charted above; none have grown as rapidly as aerial work platforms
Historical Patterns in Aerial Work Platform DemandGrowth Rates in Sales and Served Markets
• One of the primary served markets, nonresidential construction, is 3-4 times more volatile than the total US economy, as measured by either manufacturing production or GDP
• Offsetting this liability is the persistently stronger growth of the aerial work platform industry. Unit growth is charted against the right scale, 3 times the left scale used for the national indicators
Industry Growth RatesUnit Growth vs. National Indicators
Yea
r ov
er Y
ear
Gro
wth
Rat
eU
nit Grow
th Rate
Nat
iona
l Ind
icat
or G
row
th R
ate
BRINNER21
10.ppt
Historical Patterns in Aerial Work Platform DemandCyclical Forces Driving Sales around the Rising Penetration Trend
• Durable equipment sales are inherently the most cyclical markets in an economy• New equipment purchases serve two goals
» Replace worn-out or obsolete equipment to maintain existing total production capacity. In your markets, production capacity is required to match construction activity or manufacturing / commercial operations
Replacement demands are relatively steady, tending to approximate a percentage of the pre-existing fleet of equipment accumulated over a decade
However, even replacement budgets are cyclical, becoming more generous in prosperous markets and lean in soft markets
» Expand capacity to meet higher production levels These are highly cyclic sales, in that if construction is simply flat, no new equipment is
required for expansion In other words, the level of such sales tracks the growth in customer production
• Equipment sales lag served markets by approximately a year, reflecting two factors:» Businesses typically extrapolate from recent experience, expecting strong markets to continue
and weak to stay soft, rather than making independent forecasts» Capital budgets are created at the beginning of a year, then executed through the year
• This lag tends to produce cycles of excess or insufficient capacity, producing volatile orders to the equipment supplier
BRINNER22
10.ppt
A simple model of equipment sales in your industry, using construction as an example:The customer’s desired fleet is proportional to nonresidential construction: one AWP per $2million of construction
Fleet = 2000 x Construction
10% of the fleet must be replaced every year.Replacement Sales = 10% x Fleet (prior year)
thus = 10% x 2000 x Construction (prior year)
Additional Capacity-Expanding Sales match Changes in ConstructionExpansion Sales = 2000 x (Construction-Construction (prior year))
Total Sales = Replacement + Expansion Sales= 200 x Construction + 2000 x (Construction-Construction (prior year))
Historical Patterns in Aerial Work Platform Demand
Simplified Example to Highlight Source of VolatilityYear 1 2 3 4 5 6 7 8 9 10
Construction ($ Billion)$ Billion(Excluding Inflation) 100 105$ 110$ 121$ 133$ 133$ 127$ 127$ 133$ 140$ Growth Rate 5% 5% 5% 10% 10% 0% -5% 0% 5% 5%
Construction Equipment (units) Requirements
Existing Fleet2000 x
Construction 200,000 210,000 220,500 242,550 266,805 266,805 253,465 253,465 266,138 279,445 New Sales to meet 2 goals: Replacement 10% 19,048 20,000 21,000 22,050 24,255 26,681 26,681 25,346 25,346 26,614
Capacity Expansion
2000 x Construction
Increase 9,524 10,000 10,500 22,050 24,255 - (13,340) - 12,673 13,307 Total 28,571 30,000 31,500 44,100 48,510 26,681 13,340 25,346 38,020 39,921 Growth Rate 5% 5% 40% 10% -45% -50% 90% 50% 5%
Your actual industry cycles, although large, are muted by the year-to-year inertia in customer capital budgeting decisions and by he ongoing rising penetration of such equipment in construction and manufacturing.
As in this example, cycles in the fleet of units parallel cycles in the served construction market (as shown earlier).
Stable construction growthproduces matching equipment growth
Cycle in construction growthproduces amplified equipment cycle
BRINNER23
10.ppt
-2,000
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
19
85
19
86
19
87
19
88
19
89
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90
19
91
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92
19
93
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96
19
97
19
98
19
99
Historical
Fitted (without special 1999 allowance)
Unexplained Deviations
Historical Patterns in Aerial Work Platform Demand Cyclical Forces Driving Sales around the Rising Penetration Trend
Using your trade association data from 1985 through 1999, models reflecting this structure have been estimated for scissor and total boom sales
Additional factors are the trend gains in penetration in served markets and the potential sales gain in 1999 due to consolidation of the rental industry
With regard to lags in response, sales are driven by the level and change in construction spending in the current and prior two years
The estimates confirm a far greater sensitivity of lifts to manufacturing activity; boom sales are almost totally driven by nonresidential construction
% explained (R-squared) =98.3%Standard error = 847 Units
Potential Rental Consolidation Shift:1999 Actual - Estimate = 780 Units
% explained (R-squared) =97.4%Standard error = 2858 Units
Potential Rental Consolidation Shift:1999 Actual - Estimate = 3307 Units
Results in models without allowance for special 1999 gain
-10,000
-5,000
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
19
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90
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19
99
Hisorical
Fitted (without special 99 allowance)
Unexplained Deviations
Booms Scissors