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BRINNER 1 10.ppt Business Investment Lecture 10 BRINNER 2 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 BRINNER 3 10.ppt Business Investment 20% 15% 10% 5% 19 99 19 97 19 95 19 93 19 91 19 89 19 87 19 85 19 83 0% -5% -10% 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?” BRINNER 4 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) BRINNER 5 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. BRINNER 6 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 BRINNER 7 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 12000 10000 6000 4000 2000 Real GDP Private Cap 19 99 19 97 19 95 19 93 19 91 19 89 19 87 19 85 19 83 19 81 19 79 19 77 19 75 19 73 19 71 19 69 19 67 19 65 19 63 19 61 0 19 59 $ Billion 8000 Accelerator Data: Change in Output vs Levels of Gross & Net Investment $1,600 $1,400 Recent shift to even higher investment relative to GDP is due to new technology opportunities $1,200 $1,000 $800 Note: Net Investment roughly matches the US change in GDP $600 $400 $200 19 99 19 97 19 95 19 93 19 91 19 89 19 87 19 85 19 83 19 81 19 79 19 77 19 75 19 73 19 71 19 69 19 67 19 65 19 63 19 61 19 59 $- $(200) Change in Real GDP Gross Investment Net Investment Accelerator Model Implications for the Business Cycle BRINNER 10 10.ppt 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 BRINNER 11 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 BRINNER 12 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 capitaloutput ratio • relative prices and productivity for capital , output, and labor determine this • the first basic extension is the Cobb-Douglas production model BRINNER 13 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 BRINNER 14 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 BRINNER 15 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 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 BRINNER 16 10.ppt Transitions between Targeted Equilibrium Points In BRINNER 17 10.ppt 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 BRINNER 18 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 BRINNER 19 10.ppt Historical Patterns in Aerial Work Platform Demand Growth and Volatility of Industry Sales AWP Sales Growth 15,000 21,000 10,000 14,000 5,000 7,000 Total Booms Straight Booms Scissors Total Units • • 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 0 1985 0 Articulated Booms 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 0% -20% -40% -60% -80% Total Booms Scissors Straight Booms Total Units 1999 28,000 1998 20,000 20% 1997 35,000 1996 25,000 40% 1995 42,000 1994 30,000 1993 49,000 1992 35,000 60% 1991 56,000 1990 40,000 80% 1989 63,000 1988 45,000 100% 1985 70,000 Year Over Year Growth Rate 50,000 Total Number of Units Number of Units by Product Line AWP Unit Sales Articulated Booms The cyclical volatility of scissors is similar to that of total booms, but slightly greater BRINNER 20 10.ppt Historical Patterns in Aerial Work Platform Demand Growth Rates in Sales and Served Markets Unit Growth vs. National Indicators Nonresidential Construction Industrial Production (excluding computers) Gross Domestic Product Total Units 80% 75% 60% • • 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 -20% Aerial Work Platforms Value of Semiconductor Shipments Sales of Electronics Sales of Semiconductors - Worldwide -40% 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 1999 1998 -60% 1997 1999 1998 1997 1996 1995 1994 -60% 1993 -20% 1992 -45% 1991 -15% 1990 -30% 1989 -10% 1988 -15% 1985 -5% 0% 1996 0% 1995 0% 1994 15% 1993 5% 20% 1992 30% 1991 10% 40% 1990 45% 1989 15% 1988 60% Unit Growth Rate 20% Year over Year Growth Rate 25% National Indicator Growth Rate Industry Growth Rates BRINNER 21 10.ppt Historical Patterns in Aerial Work Platform Demand Cyclical 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 BRINNER 22 10.ppt Historical Patterns in Aerial Work Platform Demand 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 $2million of construction Fleet = 2000 x Construction Stable construction growth produces matching equipment growth 10% of the fleet must be replaced every year. Replacement Sales = 10% x Fleet (prior year) thus = 10% x 2000 x Construction (prior year) Additional Capacity-Expanding Sales match Changes in Construction Expansion Sales = 2000 x (Construction-Construction (prior year)) Cycle in construction growth produces amplified equipment cycle Total Sales = Replacement + Expansion Sales = 200 x Construction + 2000 x (Construction-Construction (prior year)) Simplified Example to Highlight Source of Volatility Year 1 2 3 4 5 6 7 8 9 10 Construction ($ Billion) $ Billion(Excluding Inflation) Growth Rate Construction Equipment (units) Existing Fleet New Sales to meet 2 goals: Replacement Capacity Expansion Total Growth Rate 100 5% Requirements 2000 x Construction 10% 2000 x Construction Increase $ 105 $ 110 $ 121 $ 133 $ 133 $ 127 $ 127 $ 133 $ 140 5% 5% 10% 10% 0% -5% 0% 5% 5% 200,000 210,000 220,500 242,550 266,805 266,805 253,465 253,465 266,138 279,445 19,048 20,000 21,000 22,050 24,255 26,681 26,681 25,346 25,346 26,614 9,524 28,571 10,000 30,000 5% 10,500 31,500 5% 22,050 44,100 40% 24,255 48,510 10% 26,681 -45% (13,340) 13,340 -50% 25,346 90% 12,673 38,020 50% 13,307 39,921 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). BRINNER 23 10.ppt 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 Results in models without allowance for special 1999 gain Booms Scissors 45,000 40,000 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0 -5,000 -10,000 % explained (R-squared) =98.3% Standard error = 847 Units % explained (R-squared) =97.4% Standard error = 2858 Units Potential Rental Consolidation Shift: 1999 Actual - Estimate = 780 Units Potential Rental Consolidation Shift: 1999 Actual - Estimate = 3307 Units 1999 1998 1997 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 -2,000 1996 0 1995 2,000 1994 4,000 1993 6,000 1992 8,000 1991 10,000 Unexplained Deviations 1990 Unexplained Deviations 1989 12,000 Fitted (without special 99 allowance) 1988 Fitted (without special 1999 allowance) 1987 14,000 Hisorical 1986 Historical 16,000 1985 18,000