ECON 206 Macroeconomic Analysis

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ECON 206 Macroeconomic Analysis Prof. Francesc Ortega s Class Guest Lecture by Prof. Ryan Edwards October 5, 2011 1

Our objectives today Growth: Cover the key facts about economic growth that we wish to understand later with models Examine the global extent of economic growth Understand how growth is a recent phenomenon Learn some tools: calculating growth rates and using ratio scales 2

A sketch of the U.S. around 1900 Life expectancy at birth, the average length of life starting from birth, was about 50 [today: 77] One out of every 10 infants died before his or her first birthday [today: 7 out of every 1,000] 90 percent of households did not have electricity, refrigerator, telephone, or a car [today most do] Fewer than 10 percent of adults had graduated from high school [today: 85 percent] 3

A sobering comparison Life expectancy at birth USA 1900 USA today Kenya today 50 77 50 Infant mortality 0.1 0.007 0.06 Real GDP per capita (1990 $) $4,100 $28,000 $1,000 4

If growth has been uneven across geographic boundaries, what about across time? Per Capita GDP (1990 dollars) Figure 3.1: Economic Growth over the Very Long Run Growth is a relatively recent phenomenon, only in the past 2 or 3 centuries 30000 25000 20000 U.S. Japan U.K. Growth arrived in different countries at different times 15000 10000 5000 2000 500 Today, a Great Divergence 0 500 1000 1500 2000 Brazil China Ethiopia Year Note: Data from Angus Maddison, The World Economy: Historical Statistics (Paris: OECD Development Center, 2003). 5

Per Capita GDP (2000 dollars) Figure 3.2: Per Capita GDP in the United States Since 1870, GDP per person in the U.S. has risen 15-fold: from about $2,500 to about $37,000 35000 30000 25000 20000 Another way to think about this is to compare your lifetime income with your parents 15000 10000 5000 2500 1860 1880 1900 1920 1940 1960 1980 2000 2020 Year Note: Data from 1870 to 1928 from Maddison, cited in Figure 3.1. Data from 1929 to 2004 from the Bureau of Economic Analysis. 6 You ll be about twice as rich, because incomes have been doubling every 35 years, or roughly once every generation

The math of growth In Figure 3.2, GDP per capita (yt) is increasing by an increasing amount The increases are roughly proportional to the level at any point, say by some proportion g y 2005 y 2004 = ḡ y 2004, y 2005 y 2004 y 2004 = ḡ. The left-hand side of the second equation, g, is the percentage change in GDP per capita, the growth rate. A little more math shows us: y t+1 = y t (1 + ḡ). 7

With a constant growth rate, level increases are larger and larger over time Calculating levels using growth rates over a period of time is mathematically a little complicated Example: With 6.5 billion people in the world today and a constant annual growth rate of 2%, how large will world population be in 100 years? Hint: It s not 6.5 billion + 2% x 6.5 billion x 100 years (which equals 6.5 + 13 billion extra = 19.5 billion) 8

With a constant growth rate n, population after one year is L 1 = L 0 (1 + n). ) After two years, it is L 2 = L 1 (1 + n). Combining these, we find that L 2 = L 0 (1 + n)(1 + n) = L 0 (1 + n) 2. So for some year t, L t = L 0 (1 + n) t. When L0 = 6.5 billion and n = 0.02, L100 = 47.1 billion considerably larger than 19.5 billion! 9

We will also need to compute annual growth rates but how? Rule of 70: if something is doubling every t years, you know that the growth rate is 70 t (With GDP per person, it s 70 35 years = 2%) Using the raw data: be a little careful! ( yt y t = y 0 (1 + ḡ) t ḡ = y 0 ) 1/t 1 You have to use a calculator or spreadsheet for this Note: this will give you 0.02 for 2% growth 10

Growth rate notation These are all the same: The annual growth rate of x (xt+1 xt) / xt = xt+1/xt 1, or if the data are spaced further apart in time, gx or g(x) g x = ( xt x 0 ) 1/t 1 All are numbers like 0.02 (which is 2%) per year 11

Properties of growth rates 1. Ratios become differences: If z = x/y, then g z = g x g y. 2. Products become sums: If z = x y, then g z = g x + g y 3. Powers become multiples: If z = x a, then g z = a g x (If this looks like logarithms to you, that s no accident!) 12

Suppose that x grows at rate gx = 0.10 while y grows at rate gy = 0.03. Then what is gz when... z = x y z = x/y z = y/x g z = g x + g y =.13 g z = g x g y =.07 g z = g y g x =.07 13

Again, if x grows at rate gx = 0.10 while y grows at rate gy = 0.03. Then what is gz when... z = x 2 z = y 1/2 z = x 1/2 y 1/3 g z = 2 g x =.20 g z =.5 g y =.015 g z = 1 2 g x =0.05 0.01 1 3 g y 14 =0.04

A real-world example Suppose you know the following: In 2010, you worked h = 20 hours a week for k = 50 weeks and earned w = $10 per hour So your total earnings E were equal to E = h k w With your earnings, you buy donuts priced at P = $2 per donut In 2011, times are tough! You can only get h = 18 hours per week for k = 50 weeks, and you didn t get a raise, so w = $10 But times are also tough for Dunkin Donuts, who have to cut donut prices to P = $1.80 to stay competitive in a down market 15

Questions you can answer using analytical tools, rather than a calculator hours h weeks k wage w price P 2010 20 50 $10 $2 2011 18 50 $10 $1.80 earnings E = h k w Q: Has your real wage (w r = w P) risen or fallen? Risen because w stayed the same while P fell. How much? g[w r ] = Q: Have your real earnings (R = E P) risen or fallen? g[w] g[p] = 0% ( 10%) = 10% because g[p] = 10% g[e P] = g[e] g[p] = g[h k w] g[p] = g[h] + g[k] + g[w] g[p] = 16 = 10% + 0% + 0% ( 10%) = 0% Your real wage rose by the same rate that your hours fell, so your real earnings are unchanged

A key example that will turn up soon: Suppose we know that Y t = A t K 1/3 t L 2/3 t. What is the growth rate of Y t in terms of the growth rates of At, Kt, and Lt? The growth rate of a product is the sum of the growth rates g(y t ) = g(a t ) + g(k 1/3 t ) + g(l 2/3 t ). 17

g(y t ) = g(a t ) + g(k 1/3 t ) + g(l 2/3 t ). The growth rate of a power is the power times the growth rate g(y t ) = g(a t ) + 1 3 g(k t) + 2 3 g(l t). We will later learn about this function; it tells us that growth in income (Y) comes from Growth in productivity (A) plus Growth in physical inputs (capital, K; and labor, L) 18

Plotting on a ratio scale (a.k.a. log scale) If the y-axis is scaled in terms of ratios or multiples of an amount rather than its levels, Then a series that grows at a constant rate... appears as a straight line on a ratio scale 19

On a ratio scale, equal spacings are constant ratios (here, 2:1 or doubling) GDP per person has grown at a fairly constant rate of 2% The slopes reveal faster or slower growth Figure 3.5: Per Capita GDP in the United States: Ratio Scale Per Capita GDP (ratio scale, 2000 dollars) 32000 16000 8000 4000 Flatter = slower growth Steeper = faster growth 2.0% per year 2000 1850 1900 1950 2000 2050 Year Note: This is the same data shown in Figure 3.2, but plotted using a ratio scale. Notice that the ratios of the equally-spaced labels on the vertical axis are all the same, in this case equal to 2. The dashed line exhibits constant growth at a rate of 2.0 percent per year. 20

Ratio scales allow us to see and tell stories about shifting growth rates much easier Per Capita GDP (ratio scale, 1990 dollars) Figure 3.6: Per Capita GDP since 1870 In 1870, the UK was the richest country 32000 16000 8000 U.S. Japan But the U.S. grew more rapidly! 4000 2000 1000 U.K. Germany Brazil China Postwar Germany and Japan caught up China is growing fast! 500 Ethiopia 1860 1880 1900 1920 1940 1960 1980 2000 Year Note: Data from Angus Maddison, The World Economy: Historical Statistics (Paris: OECD Development Center, 2003). Observations are presented every decade after 1950 and less frequently before that as a way of smoothing the series. 21

Here s where we see properties of growth rates in action: The growth rate of GDP/person... is equal to the growth rate of GDP minus the growth rate of person, a.k.a. population Figure 3.9: Population, GDP, and Per Capita GDP for the United States Ratio Scale Total GDP 3.5% Per Capita GDP Population 2.0% 1.5% 1860 1880 1900 1920 1940 1960 1980 2000 2020 Year Note: Data from Maddison (2003) and the Bureau of Economic Analysis. The average annual growth rate is reported next to each data series. 22