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Transcript
The lessons of growth theory …can make a positive difference in the lives of hundreds of millions of people. These lessons help us understand why poor countries are poor design policies that can help them grow learn how our own growth rate is affected by shocks and our government’s policies slide 0 Huge effects from tiny differences In rich countries like the U.S., if government policies or “shocks” have even a small impact on the long-run growth rate, they will have a huge impact on our standard of living in the long run… slide 1 Huge effects from tiny differences percentage increase in standard of living after… annual growth rate of income per capita …25 years …50 years …100 years 2.0% 64.0% 169.2% 624.5% 2.5% 85.4% 243.7% 1,081.4% slide 2 Huge effects from tiny differences If the annual growth rate of U.S. real GDP per capita had been just one-tenth of one percent higher during the 1990s, the U.S. would have generated an additional $449 billion of income during that decade slide 3 slide 4 International Evidence on Investment Rates and Income per Person Income per person in 1992 (logarithmic scale) 1 00 ,00 0 Canada Denmark Germ any U.S. 1 0,0 00 Mexico E gypt F inland B razi l P aki stan Ivory Coast U.K. Israel It al F rance y Singapore P eru Indonesi a 1 ,00 0 Zimbabwe India Chad 1 00 Japan 0 Uganda 5 Kenya Cam eroon 10 15 20 25 30 35 40 Investment as percentage of output (average 1960 –1992) slide 5 Income per person in 1992 (logarithmic scale) International Evidence on Population Growth and Income per Person 100,000 Germ any U.S. Denmark Canada Israel 10,000 U.K. It al y Japan F inland F rance Mexico Singapore E gypt B razi l P aki stan P eru Indonesi a 1,000 Cam eroon Ivory Coast Kenya India Zimbabwe Chad 100 0 1 2 Uganda 3 4 Population growth (percent per y ear) (average 1960 –1992) slide 6 Examples of technological progress 1970: 50,000 computers in the world 2000: 51% of U.S. households have 1 or more computers The real price of computer power has fallen an average of 30% per year over the past three decades. The average car built in 1996 contained more computer processing power than the first lunar landing craft in 1969. Modems are 22 times faster today than two decades ago. Since 1980, semiconductor usage per unit of GDP has increased by a factor of 3500. 1981: 213 computers connected to the Internet 2000: 60 million computers connected to the Internet slide 7 Policies to promote growth Four policy questions: 1. Are we saving enough? Too much? 2. What policies might change the saving rate? 3. How should we allocate our investment between privately owned physical capital, public infrastructure, and “human capital”? 4. What policies might encourage faster technological progress? slide 8 1. Evaluating the Rate of Saving Use the Golden Rule to determine whether our saving rate and capital stock are too high, too low, or about right. To do this, we need to compare (MPK ) to (n + g ). If (MPK ) > (n + g ), then we are below the Golden Rule steady state and should increase s. If (MPK ) < (n + g ), then we are above the Golden Rule steady state and should reduce s. slide 9 1. Evaluating the Rate of Saving To estimate (MPK ), we use three facts about the U.S. economy: 1. k = 2.5 y The capital stock is about 2.5 times one year’s GDP. 2. k = 0.1 y About 10% of GDP is used to replace depreciating capital. 3. MPK k = 0.3 y Capital income is about 30% of GDP slide 10 1. Evaluating the Rate of Saving 1. k = 2.5 y 2. k = 0.1 y 3. MPK k = 0.3 y To determine , divided 2 by 1: k 0.1 y k 2.5 y 0.1 0.04 2.5 slide 11 1. Evaluating the Rate of Saving 1. k = 2.5 y 2. k = 0.1 y 3. MPK k = 0.3 y To determine MPK, divided 3 by 1: MPK k k 0.3 y 2.5 y 0.3 MPK 0.12 2.5 Hence, MPK = 0.12 0.04 = 0.08 slide 12 1. Evaluating the Rate of Saving From the last slide: MPK = 0.08 U.S. real GDP grows an average of 3%/year, so n + g = 0.03 Thus, in the U.S., MPK = 0.08 > 0.03 = n + g Conclusion: The U.S. is below the Golden Rule steady state: if we increase our saving rate, we will have faster growth until we get to a new steady state with higher consumption per capita. slide 13 2. Policies to increase the saving rate Reduce the government budget deficit (or increase the budget surplus) Increase incentives for private saving: reduce capital gains tax, corporate income tax, estate tax as they discourage saving replace federal income tax with a consumption tax expand tax incentives for IRAs (individual retirement accounts) and other retirement savings accounts slide 14 3. Allocating the economy’s investment In the Solow model, there’s one type of capital. In the real world, there are many types, which we can divide into three categories: – private capital stock – public infrastructure – human capital: the knowledge and skills that workers acquire through education How should we allocate investment among these types? slide 15 4. Encouraging technological progress Patent laws: encourage innovation by granting temporary monopolies to inventors of new products Tax incentives for R&D Grants to fund basic research at universities Industrial policy: encourage specific industries that are key for rapid tech. progress (subject to the concerns on the preceding slide) slide 16 CASE STUDY: The Productivity Slowdown Growth in output per person (percent per year) 1948-72 1972-95 Canada 2.9 1.8 France 4.3 1.6 Germany 5.7 2.0 Italy 4.9 2.3 Japan 8.2 2.6 U.K. 2.4 1.8 U.S. 2.2 1.5 slide 17 Explanations? Measurement problems Increases in productivity not fully measured. – But: Why would measurement problems be worse after 1972 than before? Oil prices Oil shocks occurred about when productivity slowdown began. – But: Then why didn’t productivity speed up when oil prices fell in the mid-1980s? slide 18 Explanations? Worker quality 1970s - large influx of new entrants into labor force (baby boomers, women). New workers are less productive than experienced workers. The depletion of ideas Perhaps the slow growth of 1972-1995 is normal and the true anomaly was the rapid growth from 1948-1972. slide 19 The bottom line: We don’t know which of these is the true explanation, it’s probably a combination of several of them. slide 20 CASE STUDY: I.T. and the “new economy” Growth in output per person (percent per year) 1948-72 1972-95 1995-2000 Canada 2.9 1.8 2.7 France 4.3 1.6 2.2 Germany 5.7 2.0 1.7 Italy 4.9 2.3 4.7 Japan 8.2 2.6 1.1 U.K. 2.4 1.8 2.5 U.S. 2.2 1.5 2.9 slide 21 CASE STUDY: I.T. and the “new economy” Apparently, the computer revolution didn’t affect aggregate productivity until the mid-1990s. Two reasons: 1. Computer industry’s share of GDP much bigger in late 1990s than earlier. 2. Takes time for firms to determine how to utilize new technology most effectively The big questions: Will the growth spurt of the late 1990s continue? Will I.T. remain an engine of growth? slide 22 Money supply measures, April 2002 _Symbol C Assets included Amount (billions)_ Currency $598.7 M1 C + demand deposits, travelers’ checks, other checkable deposits 1174.0 M2 M1 + small time deposits, savings deposits, money market mutual funds, money market deposit accounts 5480.1 M3 M2 + large time deposits, repurchase agreements, institutional money market mutual fund balances 8054.4 slide 23 slide 24 slide 25 slide 26 slide 27 The social costs of inflation …fall into two categories: 1. costs when inflation is expected 2. additional costs when inflation is different than people had expected. slide 28 The costs of expected inflation: 1. shoeleather cost def: the costs and inconveniences of reducing money balances to avoid the inflation tax. i real money balances Remember: In long run, inflation doesn’t affect real income or real spending. So, same monthly spending but lower average money holdings means more frequent trips to the bank to withdraw smaller amounts of cash. slide 29 The costs of expected inflation: 2. menu costs def: The costs of changing prices. Examples: – print new menus – print & mail new catalogs The higher is inflation, the more frequently firms must change their prices and incur these costs. slide 30 The costs of expected inflation: 3. relative price distortions Firms facing menu costs change prices infrequently. Example: Suppose a firm issues new catalog each January. As the general price level rises throughout the year, the firm’s relative price will fall. Different firms change their prices at different times, leading to relative price distortions… …which cause microeconomic inefficiencies in the allocation of resources. slide 31 The costs of expected inflation: 4. unfair tax treatment Some taxes are not adjusted to account for inflation, such as the capital gains tax. Example: 1/1/2001: you bought $10,000 worth of Starbucks stock 12/31/2001: you sold the stock for $11,000, so your nominal capital gain was $1000 (10%). Suppose = 10% in 2001. Your real capital gain is $0. But the govt requires you to pay taxes on your $1000 nominal gain!! slide 32 The costs of expected inflation: 4. General inconvenience Inflation makes it harder to compare nominal values from different time periods. This complicates long-range financial planning. slide 33 Additional cost of unexpected inflation: arbitrary redistributions of purchasing power Many long-term contracts not indexed, but based on e. If turns out different from e, then some gain at others’ expense. Example: borrowers & lenders • If > e, then (r ) < (r e) and purchasing power is transferred from lenders to borrowers. • If < e, then purchasing power is transferred from borrowers to lenders. slide 34 Additional cost of high inflation: increased uncertainty When inflation is high, it’s more variable and unpredictable: turns out different from e more often, and the differences tend to be larger (though not systematically positive or negative) Arbitrary redistributions of wealth become more likely. This creates higher uncertainty, which makes risk averse people worse off. slide 35 slide 36 Recent episodes of hyperinflation 10000 percent growth 1000 100 10 1 Israel 1983-85 Poland 1989-90 Brazil Argentina Peru Nicaragua Bolivia 1987-94 1988-90 1988-90 1987-91 1984-85 inflation growth of money supply slide 37 slide 38 Business Cycles Business Cycles – Business cycles are 2-year to 5-year fluctuations around trends in real GDP and other related variables – A recession is a large fall in the growth of real GDP and related variables • A depression is an especially large recession slide 39 Business Cycles slide 40 Real GDP Growth in the United States 10 Percent change from 4 quarters 8 earlier Average growth rate = 3.5% 6 4 2 0 -2 -4 1960 1965 1970 1975 1980 1985 1990 1995 2000 slide 41 Recessions in the U.S. since World War II Year and quarter of peak in RGDP Number of quarters until trough in RGDP Change in RGDP, peak to trough (%) 1948:4 2 -1.7 1953:2 3 -2.7 1957:3 2 -3.7 1960:1 3 -1.6 1970:3 1 -1.1 1973:4 5 -3.4 1980:1 2 -2.2 1981:3 4 -2.9 1990:2 3 -1.5 No simple regular or cyclical pattern: output changes very considerably in size and spacing slide 42 Behavior of the Components of Output in Recessions Component of GDP Consumption Durables Nondurables Services Average Share in GDP (%) Average Share in fall in GDP in recessions relative to normal growth (%) 8.4 25.8 29.5 15.6 11.2 9.1 4.7 10.7 0.7 20.9 11.7 40.6 Net Export -0.4 -12.3 Gov’t Purchases 20.6 3.3 Investment Residential Business Fixed Inventories Fluctuations are distributed very unevenly over the components of output slide 43 Cyclical Behavior of Key Macroeconomic Variables Procyclical variable – An economic variable that moves in the “same” direction as aggregate economic activity industrial production, consumption, investment, employment, real wage, inflation, stock prices Countercyclical variable – An economic variable that moves in the “opposite” direction as aggregate economic activity unemployment slide 44 Supply shocks A supply shock alters production costs, affects the prices that firms charge. (also called price shocks) Examples of adverse supply shocks: Bad weather reduces crop yields, pushing up food prices. Workers unionize, negotiate wage increases. New environmental regulations require firms to reduce emissions. Firms charge higher prices to help cover the costs of compliance. (Favorable supply shocks lower costs and prices.) slide 45 CASE STUDY: The 1970s oil shocks Early 1970s: OPEC coordinates a reduction in the supply of oil. Oil prices rose 11% in 1973 68% in 1974 16% in 1975 Such sharp oil price increases are supply shocks because they significantly impact production costs and prices. slide 46 CASE STUDY: The 1970s oil shocks The oil price shock shifts SRAS up, causing output and employment to fall. In absence of further price shocks, prices will fall over time and economy moves back toward full employment. P P2 LRAS B SRAS2 A P1 SRAS1 AD Y2 Y Y slide 47 CASE STUDY: The 1970s oil shocks 70% 12% Predicted effects of the oil price shock: • inflation • output • unemployment 60% …and then a gradual recovery. 10% 50% 10% 40% 8% 30% 20% 6% 0% 1973 4% 1974 1975 1976 1977 Change in oil prices (left scale) Inflation rate-CPI (right scale) Unemployment rate (right scale) slide 48 CASE STUDY: The 1970s oil shocks 60% Late 1970s: As economy was recovering, oil prices shot up again, causing another huge supply shock!!! 14% 50% 12% 40% 10% 30% 8% 20% 6% 10% 0% 1977 1978 1979 1980 4% 1981 Change in oil prices (left scale) Inflation rate-CPI (right scale) Unemployment rate (right scale) slide 49 CASE STUDY: The 1980s oil shocks 40% 1980s: A favorable supply shock-a significant fall in oil prices. As the model would predict, inflation and unemployment fell: 10% 30% 8% 20% 10% 6% 0% -10% 4% -20% -30% 2% -40% -50% 1982 1983 1984 1985 1986 0% 1987 Change in oil prices (left scale) Inflation rate-CPI (right scale) Unemployment rate (right scale) slide 50