Part V: Introduction to Macroeconomics 19. The Wealth of Nations: Defining and Measuring Macroeconomic Aggregates 20.

Transcription

1 the Part V: Introduction to Macroeconomics 19. The Wealth of Nations: Defining and Measuring Macroeconomic s / 54

2 the Chapter / 54

3 the 1 2 the / 54

4 Chapter 20 the Q: Why is the average American so much richer than the average Indian? 4 / 54

5 the There are very large differences across countries in income or GDP per capita. We can compare income differences across countries using GDP per capita at current exchange rates or adjusted for purchasing power parity (PPP) differences. 5 / 54

6 the The aggregate production function links a country s GDP to its capital stock, its total efficiency units of labor, and its technology. Cross-country differences in GDP per capita partly result from differences in physical capital per worker and the human capital of workers, but differences in technology and the efficiency of production are even more important. 6 / 54

7 the 19.1 Around the Measuring Differences in Income per Capita We use the two terms, income per capita and GDP per capita, interchangeably in this course: Income per capita = GDP per capita = GDP Total population 7 / 54

8 the United States in 2010 GDP= $14.45 trillion Population= 310 million persons GDP per capita = $46,613 per capita 8 / 54

9 Question: How does U.S. GDP compare with GDP in Peru and Norway? the 9 / 54

10 the Peru in 2010 GDP = billion nuevo sols Total population = million people GDP per capita = 15,353 sols per person Norway in 2010 GDP = 2.57 trillion kroner Total population = 4.68 million people GDP per capita = 549,962 kroner per person Taiwan in 2010 GDP = 14,119,213 ( 百萬元 ) = 兆 NT$ Total population = 23,140,948 GDP per capita = 610,140 NT$ 10 / 54

11 the Question: How do we make GDP comparisons between the United States and Peru and Norway? Method #1: Convert GDP into U.S. dollars, using current exchange rates: GDP per capita = GDP per capita in local currency $ / local currency exchange rate. 11 / 54

12 the Peru GDP in 2010, Using Exchange Rates GDP per capita = Peru GDP per capita in sols $/sol exchange rate = 15,353 sols per person $/sol = $5,435 per person Norway GDP in 2010, Using Exchange Rates GDP per capita = Norway GDP per capita in kroner $/kroner exchange rate = 549,962 kroner per person $/kroner = $90,744 per person Taiwan GDP in 2010, Using Exchange Rates GDP per capita = 610,140 NT$ per person $/NT$ = $19,278 per person 12 / 54

13 GDP per Capita Rankings, Using Exchange Rates the 13 / 54

14 the There are two problems with using exchange rates to compare GDP across countries: Prices of goods and services can vary across economies. Exchange rates fluctuate throughout the year due to reasons beyond price changes. 14 / 54

15 the Question: How do we make GDP comparisons between the United States and Peru and Norway? Method #2: Convert Peru GDP by using the prices of goods and services in Peru relative to the prices of the same goods and services in the United States (purchasing power parity): GDP per capita = GDP per capita in local currency PPP adjustment 15 / 54

16 the Peru GDP in 2010, Using PPP Adjustment GDP per capita =Peru GDP per capita in sol $/peso PPP adjustment = 15,353 sol per person $/sol= $9,012 Norway GDP on 2010, Using PPP Adjustment GDP per capita = Norway GDP per capita in kroner $/kroner PPP adjustment = 549,962 kroner per person $/kroner= $59,946 Taiwan GDP on 2014, Using PPP Adjustment (IMF) GDP per capita = 687,816 NT$ per person $/NT$= $46,036 GDP per capita in 2014, using exchange rates, is $22, / 54

17 the The Big Mac Index In 1986, The Economist magazine proposed the Big Mac index as an alternative measure of exchange rates. This index is simply the ratio of prices of a Big Mac in two countries. The Big Mac index is a simple example of a purchasing power parity adjustment. Its shortcoming is that instead of a representative bundle of diverse goods, this index only compares a bundle consisting of a single good, the Big Mac, which is only a small fraction of people s consumption. 17 / 54

18 Even though PPP adjustments raise the income levels of the developing countries, there are still very large disparities in income per capita across countries. GDP per Capita Rankings, Using PPP Adjustment the 18 / 54

19 the Exhibit 20.1 Income per Capita in 2010 (PPP-adjusted 2005 constant dollars) 19 / 54

20 the Exhibit 20.2 A Map of Income per Capita 20 / 54

21 the in Income per Capita The age structure and labor participation rates vary across countries. These variations impact income per capita. Therefore, we may want to consider: Income per worker = GDP Number of people in employment 21 / 54

22 GDP per Capita vs. GDP per Worker the 22 / 54

23 the Exhibit 20.3 Income per Worker in 2010 (PPP-adjusted 2005 constant dollars) 23 / 54

24 the Productivity Ultimately, it is productivity differences that drive income per capita and income per worker differences across countries. Productivity is the value of goods and services that a worker generates for each hour of work. 24 / 54

25 the 25 / 54

26 the and the Standard of Living There is be a positive relationship between income per capita (and income per worker) and various measures of standard of living. The next three slides present evidence of this relationship, using absolute poverty rates, life expectancy, and the Human Development Index to measure the standard of living. 26 / 54

27 the Exhibit 20.4 The Relationship Between Poverty and Income per Capita in 2010 (PPP-adjusted 2005 constant dollars) Absolute poverty: one dollar a day per person poverty line. This measure has now been updated to $1.25 in 2005 U.S. dollars. 27 / 54

28 the Exhibit 20.5 The Relationship Between Life Expectancy and Income per Capita in 2010 (PPP-adjusted 2005 constant dollars) 28 / 54

29 the Exhibit 20.6 The Relationship Between the Human Development Index and Income per Capita in 2010 (PPP-adjusted 2005 constant dollars) 29 / 54

30 the 20.2 the Productivity Differences Productivity differences are the ultimate drivers of income per capita and income per worker differences across countries. There are three reasons productivity differs across countries: Human capital Physical capital 30 / 54

31 the Human Capital Human capital: The stock of skills embodied in labor to produce output. This stock of skills, or total efficiency units of labor, is written: H = L h where L is total number of workers, h is the average efficiency or human capital of workers 31 / 54

32 the Physical Capital Physical capital: The stock of business structures (plants) and equipment (machines) used for production. : Superior knowledge in production or more efficient production processes so that more output can be produced with the same amount of human and physical capital. 32 / 54

33 the The How exactly do increases in a factor of production lead to increases in productivity and GDP? Macroeconomists use the aggregate production function to model the relationship between aggregate GDP and its factors of production. 33 / 54

34 the The aggregate production function is: Y = A F(K, H) where Y is GDP K is the physical capital stock H is the total efficiency units of labor F( ) is a mathematical function A is an index of technology 34 / 54

35 the The aggregate production function has the same two properties as the production function of an individual firm. 1. More is better An increase in either physical capital or total efficiency units of labor, holding the other factor constant, leads to an increase in GDP. 2. Law of diminishing marginal product The marginal contribution of either physical capital or total efficiency units of labor to GDP diminishes when we increase the quantity used of that factor (holding all other factors of production constant). 35 / 54

36 the Exhibit 20.7 The with Physical Capital Stock on the Horizontal Axis (with the total efficiency units of labor held constant) 36 / 54

37 the Exhibit 20.8 The with the Efficiency Units of Labor on the Horizontal Axis (with physical capital stock held constant) 37 / 54

38 the 20.3 With more advanced technology, more output can be produced with the same amount of physical capital and total efficiency units of labor. Therefore, technology will shift the production function upward. 38 / 54

39 the Exhibit 20.9 The Shift in the Resulting from More Advanced 39 / 54

40 the Dimensions of has two very distinct components. Today, we have knowledge about how to produce many new goods, such as smart phones and tablets. This knowledge also enables us to perform certain tasks more efficiently. Part of this knowledge is in the human capital of the workers. An important part of this knowledge is embodied in the physical stock of firms. 40 / 54

41 the Advances in technology result mostly from purposeful, optimizing decisions by entrepreneurs and firms. Firms and the government in the United States spent $430 billion (or 2.8% of GDP) in research and development (R&D) to find new ways of applying science to production methods and to develop new and improved goods and services. 41 / 54

42 the One example of how purposeful activity like R&D can increase the technology of the economy is Moore s Law. Named after Intel cofounder Gordon Moore, Moore s Law predicts that the number of transistors packed on a computer chip (i.e., the processing speed) should double every two years. Exhibit Moore s Law 42 / 54

43 the Entrepreneurship A particular important reason why efficiency of production and productivity might differ across economies relates to entrepreneurship. Various factors might influences whether the individuals with a comparative for entrepreneurship become entrepreneurs. When they fail to do so, the efficiency of production of an economy is lower. 43 / 54

44 the Monopoly and GDP Monopolies and barriers against the entry of new companies are some of the reasons why a country has not achieved more significant growth. Telecommunications sector in Mexico is a private monopoly under the ownership of Carlos Slim. It not only charges higher prices than other countries but also invests less than other comparable countries. 44 / 54

45 the Exhibit Underinvestment in Information and Communication in Mexico Relative to Countries with Comparable Income 45 / 54

46 Chapter 20 the Q: Why is the average American so much richer than the average Indian? Answer: Exhibit presents data on income per worker, human capital per worker (schooling), and physical capital per worker relative to the United States. 46 / 54

47 the Exhibit The Contribution of Human Capital, Physical Capital, and to Differences in Income per Worker In column 2, income per worker in the United States is actually 9 times that in India (82,359/9,010 = 9). In column 5, income per worker in the United States would be 3.5 times that in India (82,359/24,071 = 3.5) if an Indian worker had the same technology. This translates into an almost threefold increase in income per worker (24,071/9,010 = 2.7). 47 / 54

48 Chapter 20 the Q: Why is the average American so much richer than the average Indian? Answer: The average American is so much richer than the average Indian mostly because of better technology in the United States. 48 / 54

49 the We write the aggregate production function in a specific form called the Cobb-Douglas production function. We then use the Cobb-Douglas production function to solve for the hypothetical value of GDP per worker of India, in which India possesses U.S. technology. 49 / 54

50 the The aggregate production function can be written in many different functional forms. Economists like to use a specific form called the Cobb-Douglas production form: Y = A F(K, H) = A K 1/3 H 2/3 The coefficients to which K and H are raised sum to one. This feature generates two important properties of the Cobb-Douglas production function. 50 / 54

51 1. There are constant returns to scale in K and H. the A F(2K, 2H) = A (2K ) 1/3 (2H) 2/3 = A 2 1/3 2 2/3 K 1/3 H 2/3 = 2Y 2. In competitive markets, one-third of income is paid to physical capital and two-thirds to labor. This is roughly consistent with the empirical fact. Y wh r K = H H Y K K = 2/3 1/3 51 / 54

52 the Using the Cobb-Douglas production function, we can solve for GDP per worker, y: y Y L = A K 1/3 H 2/3 1 L 1/3 L ( ) 2/3 K 1/3 ( ) H 2/3 = A L L ( ) K 1/3 = A h 2/3 L since H = L h. G D P per worker = T echnology (Capital per worker) 1/3 (Human Capital per worker) 2/3 52 / 54

53 the U.S. level of technology: A U S = India level of technology: A I N DI A = y U S ( ) 1/3 KU S 2/3 L U S h U S y I N DI A ( K I N DI A L I N DI A ) 1/3 h 2/3 I N DI A GDP per worker of India in which India possesses U.S. technology is therefore: y I N DI A with U S T echnology ( ) K 1/3 I N DI A = A U S h 2/3 I N DI A L I N DI A 53 / 54

54 the Using data on U.S. technology and Indian capital per worker and human capital, we can now estimate the hypothetical value of GDP per worker of India in which India possesses U.S. technology: y I N DI A with U S T echnology = 575 (19, 975) 1/3 (1.91) 2/3 = $24, / 54