1. E&D International Economics, 2 Lecture 12 Giorgia Giovannetti E-mail: giorgia.giovannetti@unifi.itgiorgia.giovannetti@unifi.it

2. Plan of the course/lectures Lectures (tentative) 14/9 Introduction: globalization 15/9 Introduction, 2 21/9 Ricardo: an introduction (Marvasi) 22/9 Measuring Globalization, Indicators 28/9 Measuring globalization and specialization, Indicators 2 29/9 Overview trade models 5/10 Overview trade models (Bernard et al 2007; 2011) 6/10 Overview- end (new new trade) 12/10 Trade models: Ricardo and comparative advantage 13/10 Ricardo and comparative advantage, 2 /H-O, intro 19/10 Trade models: H-O 20/10 Trade models: H-O,2/exercises 26/10 Trade and Imperfect competition 27/10 Trade and imperfect competition 2/11 Geography models/gravity 3/11 Hysteresis, Heterogeneous firms 9/11 Trade policy: TTIP 10/11 EU development Policy 16/11 EU development Policy 17/11 FDI and Multinationals: OLI theory 23/11 FDI and Multinationals Offshoring/trade in tasks 24/11 China and India (BRICS) 30/11 Granularity and aggregate shocks 1/12 212

3. No-Trade Equilibrium Production Possibilities Frontiers, Indifference Curves, and No-Trade Equilibrium Price FIGURE 4-2 (1 of 3) The Home production possibilities frontier (PPF) is shown in panel (a), and the Foreign PPF is shown in panel (b). Because Home is capital abundant and computers are capital intensive, the Home PPF is skewed toward computers. Summary Heckscher-Ohlin Model No-Trade Equilibria in Home and Foreign

4. No-Trade Equilibrium Production Possibilities Frontiers, Indifference Curves, and No-Trade Equilibrium Price FIGURE 4-2 (2 of 3) Home preferences are summarized by the indifference curve, U. The Home no-trade (or autarky) equilibrium is at point A. The flat slope indicates a low relative price of computers, (P C /P S ) A. Summary Heckscher-Ohlin Model No-Trade Equilibria in Home and Foreign (continued)

5. No-Trade Equilibrium Production Possibilities Frontiers, Indifference Curves, and No-Trade Equilibrium Price FIGURE 4-2 (3 of 3) Foreign is labor-abundant and shoes are labor- intensive, so the Foreign PPF is skewed toward shoes. Foreign preferences are summarized by the indifference curve, U* The Foreign no-trade equilibrium is at point A*, with a higher relative price of computers, as indicated by the steeper slope of (P* C /P* S ) A *. Summary Heckscher-Ohlin Model No-Trade Equilibria in Home and Foreign (continued)

6. Free-Trade Equilibrium Home Equilibrium with Free Trade FIGURE 4-3 (1 of 2) At the free-trade world relative price of computers, (P C /P S ) W, Home produces at point B in panel (a) and consumes at point C, exporting computers and importing shoes. Point A is the no-trade equilibrium. The “trade triangle” has a base equal to the Home exports of computers (the difference between the amount produced and the amount consumed with trade, (Q C2 − Q C3 ). Summary: Heckscher-Ohlin Model International Free-Trade Equilibrium at Home

7. Free-Trade Equilibrium Home Equilibrium with Free Trade FIGURE 4-3 (2 of 2) The height of this triangle is the Home imports of shoes (the difference between the amount consumed of shoes and the amount produced with trade, Q S3 − Q S2 ). In panel (b), we show Home exports of computers equal to zero at the no- trade relative price, (P C /P S ) A, and equal to (Q C2 − Q C3 ) at the free- trade relative price, (P C /P S ) W. Summary: Heckscher-Ohlin Model International Free-Trade Equilibrium at Home (continued)

8. Free-Trade Equilibrium Foreign Equilibrium with Free Trade FIGURE 4-4 (1 of 2) At the free-trade world relative price of computers, (P C /P S ) W, Foreign produces at point B* in panel (a) and consumes at point C*, importing computers and exporting shoes. Point A* is the no-trade equilibrium.) The “trade triangle” has a base equal to Foreign imports of computers (the difference between the consumption of computers and the amount produced with trade, (Q* C3 − Q* C2 ). Summary Heckscher-Ohlin Model International Free-Trade Equilibrium in Foreign

9. Free-Trade Equilibrium Foreign Equilibrium with Free Trade FIGURE 4-4 (2 of 2) The height of this triangle is Foreign exports of shoes (the difference between the production of shoes and the amount consumed with trade, Q* S2 – Q* S3 ). In panel (b), we show Foreign imports of computers equal to zero at the no-trade relative price, (P* C /P* S ) A *, and equal to (Q* C3 − Q* C2 ) at the free-trade relative price, (P C /P S ) W. Summary Heckscher-Ohlin Model International Free-Trade Equilibrium in Foreign (continued)

10. Free-Trade Equilibrium Equilibrium Price with Free Trade Because exports equal imports, there is no reason for the relative price to change and so this is a free-trade equilibrium. FIGURE 4-5 The world relative price of computers in the free-trade equilibrium is determined at the intersection of the Home export supply and Foreign import demand, at point D. At this relative price, the quantity of computers that Home wants to export, (Q C2 − Q C3 ), just equals the quantity of computers that Foreign wants to import, (Q* C3 − Q* C2 ). Summary: Heckscher-Ohlin Model Determination of the Free-Trade World Equilibrium Price

11. Free-Trade Equilibrium Pattern of Trade Home exports computers, the good that uses intensively the factor of production (capital) found in abundance at Home. Foreign exports shoes, the good that uses intensively the factor of production (labor) found in abundance there. This important result is called the Heckscher-Ohlin theorem. Summary: Heckscher-Ohlin Model

12. Differing Productivities across Countries Measuring Factor Abundance Once Again To allow factors of production to differ in their productivities across countries, we define the effective factor endowment as the actual amount of a factor found in a country times its productivity: Effective factor endowment = Actual factor endowment Factor productivity Summary Testing the Heckscher-Ohlin Model

13. Effects of Trade on Factor Prices How do the changes in pre-trade and post- trade relative prices affect the wage paid to labor in each country and the rental earned by capital? – Remember the relative price of computers in Home increase, causing them to export computers. – The relative price of computers in Foreign decreases, causing them to import computers.

14. Effects of Trade on Factor Prices Effect of Trade on the Wage and Rental of Home – We can use the relative demand for labor in each industry to derive an economy-wide relative demand for labor. – We can then compare it to the economy-wide relative supply of labor, L/K. – This will determine Home’s relative wage and what happens after the relative price of computers changes.

15. Effects of Trade on Factor Prices Economy-Wide Relative Demand for Labor – The quantities of labor and capital used in each industry add up to the total available labor and capital. K = K C + K S and L = L C + L S We can divide total labor by total capital to get the relative supply equal to the relative demand. Relative Supply Relative Demand

16. Effects of Trade on Factor Prices The relative demand is a weighted average of the labor-capital ratio to each industry. – This weighted average is obtained by multiplying the labor- capital ratio for each industry by K C /K and K S /K. These are the shares of total capital employed in each industry. The equilibrium relative wage is determined by the intersection of the relative supply (L/K) and the relative demand curves. – Remember the amounts of labor and capital do not depend on the relative wage.

17. Effects of Trade on Factor Prices The relative demand is an average of the labor curves for each industry. The relative demand curve therefore lies between these two curves. Where the curves intersect gives the wage relative to the rental: W/R.

18. Effects of Trade on Factor Prices Point A describes an equilibrium in the labor and capital markets—it combines these two markets into a single diagram by showing the relative supply equal to the relative demand.

19. Effects of Trade on Factor Prices Increases in the Relative Price of Computers – P C /P S increases at Home. – Production shifts away from shoes to computers. Shoe production decreases and computer production increases. – Labor and capital both move from shoe production to computer production. – Relative labor supply does not change. – Since capital has shifted to the computer industry, the relative demand for labor changes. The terms used in the weighted average, K C /K and K S /K, change.

20. Effects of Trade on Factor Prices Increases in the Relative Price of Computers – The relative demand for labor is now more weighted toward computers. – The relative demand for labor is now less weighted toward shoes.

21. Effects of Trade on Factor Prices Initial equilibrium before change in relative price of computers The increase in the relative price of computers causes the relative demand curve to shift left—toward computers The real wage falls which increases the amount of workers per unit of capital in both industries

22. Effects of Trade on Factor Prices From this, the labor-capital ratio rises in both shoes and computers. How does this happen? – More labor per unit of capital is released from shoes than is needed to operate that capital in computers. – As the relative price of computers rises, computer output rises while shoe output falls. – Labor is “freed up” to be used more in both industries.

23. Effects of Trade on Factor Prices We can use our earlier equation for relative supply and demand to show the response to the increase in the relative price of computers, P C /P S. Relative Supply No change Relative Demand No change in total

24. Effects of Trade on Factor Prices The relative supply has not changed, so the relative demand cannot change overall. Individual components of the relative demand change, but counteract each other to keep total relative demand the same. – More capital used in the computer industry so, K C /K rises while K S /K falls. Output of computers rises and output of shoes falls. – Labor/capital ratio in both industries increases. – The relative demand continues to equal relative supply.

25. Effects of Trade on Factor Prices Determination of the Real Wage and Real Rental. – Who gains and who loses from the change in the relative price of computers? – We need to determine the change in the real wage and real rental. The change in the quantity of shoes and computers that each factor of production can purchase.

26. Effects of Trade on Factor Prices Change in the Real Rental – Because the labor/capital ratio increases in both industries, the marginal product of capital increases. There are more people to work with each unit of capital. – The rental rate of capital is determined by its marginal product. R = P C *MPK C R = P S *MPK S – Capital can move freely between industries in the long run. The rental rate will be equalized across industries.

27. Effects of Trade on Factor Prices Change in the Real Rental – Both marginal products of capital increase. – Rearranging the previous equation we get: MPK C = R/P C and MPK S = R/P S – R/P C measures the quantity of computers that can be purchased with the rental. – R/P S measures the quantity of shoes that can be bought with the rental. – Since the MPK C and MPK S both increase, R/P S and R/P C must increase as well. – Therefore, capital owners are clearly better off when the relative price of capital increases.

28. Effects of Trade on Factor Prices Change in the Real Rental – Therefore, capital owners are clearly better off when the relative price of capital increases. – Computers are the capital intensive industry and the relative price of capital has increased. An increase in the relative price of a good will benefit the factor of production used intensively in producing that good.

29. Effects of Trade on Factor Prices Change in the Real Wage – Again we make use of the fact that the labor/capital ratio increases in both industries. – The law of diminishing returns tells us the marginal product of labor must decrease in both industries. – As before the wage is determined by the marginal product of labor and the price of goods. W = P C *MPL C and W = P S *MPL S – Rearranging MPL C = W/P C and MPL S = W/P S

30. Effects of Trade on Factor Prices Change in the Real Wage – W/P C is the quantity of computers that can be purchased with the wage. – W/P S is the quantity of shoes that can be purchased with the wage. – MPL C and MPL S decrease, so W/P C and W/P S decrease. – Labor is clearly worse off due to the increase in the price of computers.

31. Effects of Trade on Factor Prices The Stolper-Samuelson Theorem: In the long run when all factors are mobile, an increase in the relative price of a good will increase the real earnings of the factor used intensively in the production of that good and decrease the real earnings of the other factor. Therefore, in the Heckscher-Ohlin model: The abundant factor gains from trade, and the scarce factor loses from trade.

32. Effects of Trade on Factor Prices Changes in the Real Wage and Rental: A Numerical Example – Suppose we have the following data: – ComputersSales Revenue = P C Q C = 100 Earnings of labor = WL C = 50 Earnings of capital = RK C = 50 – ShoesSales Revenue = P S Q S = 100 Earnings of labor = WL S = 60 Earnings of capital = RK S = 40

33. Effects of Trade on Factor Prices Shoes are more labor-intensive than computers. – The share of total revenue paid to labor in shoes (60%) is more than the share in computers (50%). When trade opens, the relative price of computers, P C, increases while the price of shoes, P S, does not change. – Computers: % increase in price = ΔP C /P C = 10% – Shoes: % increase in price = ΔP S /P S = 0%

34. Effects of Trade on Factor Prices Our goal is to see how the increase in the relative price of computers translates into long run changes in the wage and rental. Rental on capital is calculated by taking total sales revenue in each industry, subtracting the payments to labor, and dividing by the amount of capital:

35. Effects of Trade on Factor Prices Since the price of computers has risen, ΔP C > 0 and ΔP S = 0. Using this in the last equations:

36. Effects of Trade on Factor Prices We can rewrite the last equation in percentage changes:

37. Effects of Trade on Factor Prices Plugging in data from before Our goal is to find out by how much rental and wage change given changes in the relative price of the final goods  Solve for 2 unknowns with 2 equations

38. Effects of Trade on Factor Prices After solving we get: – (ΔW/W) = -(20%/0.5) = -40% – When the price of computers increases by 10%, the wage falls by 40% – Labor can no longer afford to buy as many computers or shoes. – The real wage, measured in terms of either good, has fallen, so labor is worse off.

39. Effects of Trade on Factor Prices We can also see: – (ΔR/R) = -(ΔW/W)(60/40) = 60% – Rental on capital increases by 60% when the price of computers rises by 10% – Owners of capital can afford to buy more of both computers and shoes. – The real rental measured in terms of either good has gone up, and capital owners are clearly better off.

40. Effects of Trade on Factor Prices General Equation for the Long-Run Change in Factor Prices – In the long run we can summarize as follows: – For an increase in P C ΔW/W < 0 < ΔP C /P C < ΔR/R Real wage falls, real rental increases – For a decrease in P C ΔR/R < ΔP C /P C < 0 < ΔW/W Real rental rate falls, real wage increases – For an increase in P S ΔR/R < 0 < ΔP C /P C < ΔW/W Real rental falls, real wage increases

41. Effects of Trade on Factor Prices These equations relating the changes in product prices to change in factor prices are sometimes called the “magnification effect.” – They show how changes in the prices of goods have magnified effects on the earnings of factors. – Even modest fluctuations in the relative prices of goods on world markets can lead to exaggerated changes in the long-run earnings of both factors. This shows why some are opposed to trade and some support it.

42. Extending the Heckscher-Ohlin Model The HO model can be made more realistic by allowing for more than two goods, factors, and countries. – This is the first modification to the model. As the second modification, we will allow the technologies used to produce each good to differ across countries.

43. Extending the H-O Model Many Goods, Factors, and Countries – The predictions of the HO model depend on knowing what factor a country has in abundance, and which good uses that factor intensively. – When there are more than two goods, it is more complicated to evaluate factor intensity and factor abundance. Measuring the Factor Content of Trade – How do we measure the factor intensity of exports and imports when there are thousands of products traded between countries? – How can we use this to test the HO model?

44. Extending the H-O Model Measuring the Factor Content of Trade – Using Leontief’s test, we can look at similar data. – We can multiply his numbers shown in Table 4.2 by the actual value of U.S. exports and U.S. imports. This gives values for “total exports” and “total imports.” – These values are called the factor content of exports and factor content of imports. They measure the amounts of labor and capital used to produce exports and imports. – By taking the difference between the factor content of exports and factor content of imports.

45. Extending the Heckscher-Ohlin Model Factor Content of Trade for the United States, 1947 This table extends Leontief’s test of the Heckscher-Ohlin model to measure the factor content of net exports. The first column for exports and for imports shows the amount of capital or labor needed per $1 million worth of exports from or imports into the United States, for 1947. The second column for each shows the amount of capital or labor needed for the total exports from or imports into the United States. The final column is the difference between the totals for exports and imports. Seen yesterday

46. Extending the Heckscher-Ohlin Model Measuring the Factor Content of Trade – Since both these factor contents are positive, we see that the U.S. was running a trade surplus. – The U.S. exported large amounts of goods to help countries of Europe rebuild after WWII. – The fact that the factor content of net exports for both capital and labor are positive will be important as we move forward.

47. Extending the H-O Model Measuring Factor Abundance – How should we measure factor abundance when there are more than two factors and two countries? – To determine whether a country is abundant in a certain factor, we compare the country’s share of that factor with its share of world GDP. – If the share of a factor > share of world GDP. The country is abundant in that factor. – If the share of factor < share of world GDP. The country is scarce in that factor.

48. Extending the H-O Model Country Factor Endowments, 2000

49. Extending the H-O Model Capital Abundance – 24% of the world’s physical capital is located in the U.S., 8.7% is located in China, 13.3% in Japan, etc. – The final bar in the graph shows each country’s % of world GDP. The U.S. had 21.6% of world GDP, China had 11.2%, Japan had 7.5%, etc. We can conclude that the U.S. was abundant in physical capital in 2000. – Japan and Germany were also abundant in physical capital. – The opposite holds for China and India—their shares of world capital are less than their share of GDP. They are scarce in capital.

50. Extending the H-O Model Labor and Land Abundance – We can use a similar comparison to determine whether each country is abundant or not in R&D scientists, in types of labor distinguished by skill, in arable land, or any other factor of production. – For example: U.S. is abundant in R&D scientists: 26.1% of the world’s total as compared to 21.6% of the world’s GDP. The U.S. is also abundant in skilled labor but is scarce in less-skilled labor and illiterate labor. India is scarce in R&D scientists: 2.5% of world’s total as compared to 5.5% of the world’s GDP.

51. Extending the H-O Model Labor and Land Abundance – The U.S. is also scarce in arable land which is surprising since we think of the U.S. as a major exporter of agriculture. – Another surprise is that China is abundant in R&D scientists. – These findings seem to contradict HO model. – It is likely that the productivity of R&D scientists and arable land are not the same in both countries. – In this case, shares of GDP are not the whole story. – We need to allow for differences in productivity.

52. Extending the H-O Model Differing Productivities Across Countries – Remember that Leontief found that the U.S. was exporting labor-intensive products even though it was capital- abundant at that time. – One explanation is that labor is highly productive in the U.S. and less productive in the rest of the world. Then the effective labor force in the U.S. is much larger than if we just count people. Effective labor force is the labor force times its productivity. – We can now look at differing productivities into the HO model.

53. Extending the H-O Model Measuring Factor Abundance Once Again – Effective Factor Endowment is the actual factor endowment times the factor productivity. – The amount of effective labor in the world is found by adding up the effective factor endowments across all countries. – To determine if a country is abundant in a certain factor, we compare the country’s share of that effective factor with share of world GDP. If share of an effective factor is less than its share of world GDP then that country is abundant in that effective factor. If share of an effective factor is less than its share of world GDP, then that country is scarce in that effective factor.

54. Extending the H-O Model Effective R&D Scientists – The effectiveness of an R&D Scientist depends on what they have to work with. – On way to measure this is through a country’s R&D spending per scientist. – If more spending, then scientist will be more productive. – Take the total number of scientists and multiply that by the R&D spending per scientists – Figure 4.10 shows these shares. – With these productivity corrections, the U.S. is more abundant in effective R&D scientists and China is lower.

55. Extending the H-O Model Effective Arable Land – We also need to do a correction for arable land. – Effective arable land is the actual amount of arable land times the productivity in agriculture. – The U.S. has a very high productivity in agriculture where China has a lower productivity. – We repeat the same calculations from figure of 2000 The 4 th bar graph shows each country’s share of effective arable land, corrected for productivity differences – The numbers before and after the correction are very close. The U.S. is neither abundant nor scarce in effective arable land.

56. Extending the Heckscher-Ohlin Model “Effective” Factor Endowments, 2000

57. Food Imports Close to Matching Level of Exports It is expected that by about 2010, U.S. imports of agricultural goods will be about equal to exports. That is what the HO model would predict, given our finding that the U.S. is neither abundant nor scarce in effective land.

58. Extending the H-O Theorem We have now abandoned many of the assumptions we previously made. – We allow for many goods, factors, and countries. – We also allow for factors to differ in productivity. – If a country is abundant in an effective factor, then the factor’s content in net exports should be positive. – If a country is scarce in an effective factor, then that factor’s content in net exports should be negative.

59. Extending the H-O Theorem The est is as follows – Sign of (country’s % share of effective factor minus the % share of world GDP) equals Sign of (Country’s factor content of net exports). – For example, Table 4.2 shows that for capital the U.S. had a positive factor content of net exports. – Using 35 countries, the U.S. share of GDP of those countries was 33%. – Given the timing after WWII, we can assume that the U.S. share of world capital was more than 33%. – Therefore, the U.S. was abundant in capital and since that factor’s content of net exports was positive, it passes the sign test.

60. Extending the H-O Theorem The Test – The U.S. share of population for the 35 countries was about 8%. – This is less than the U.S. share of GDP, 33%. – Therefore, the U.S. was scarce in labor. – But labor’s factor content of net exports was positive. – The sign of U.S. factor abundance in labor is thus the opposite of the sign of its factor content of net exports. The sign test seems to fail for the U.S. in 1947 in labor. – However, the U.S. share of the population is not the right way to measure the U.S. labor endowment.

61. Extending the H-O Model One way to measure productivity is to use wages paid to workers. A plot of wages of workers in various countries and the estimated productivity of workers in 1990 is shown in figure. You can see these are highly correlated. The effective amount of labor found in each country equals the actual amount of labor times the wage. The amount of labor in each country times the average wages gives total wages paid to labor.

62. Extending the H-O Theorem Doing this for 30 countries and comparing it to the U.S. we find that the U.S. was abundant in effective labor. Given that the U.S. was abundant in effective factor, then labor also passes the sign test, in addition to capital. There is no “paradox” in the U.S. pattern of trade. This explanation for Leontief’s paradox relies on taking into account the productivity differences in labor across countries. – As Leontief himself proposed, once we take into account differences in the productivity of factors across countries, there is no “paradox” after all.

63. Why does India Import Cotton Textiles? From the 17 th century until the early 19 th century, India was a major world producer of cotton textiles and exported those goods to Britain and elsewhere. By the early 19 th century, however, Britain had overtaken India as the world’s dominant producer of cotton textiles and was exporting to India. India still produced raw cotton needed to manufacture cotton cloth—the raw cotton was exported to Britain.

64. Why does India Import Cotton Textiles? A similar trade pattern held for China and Egypt. These countries are all labor abundant rather than land abundant, therefore it is puzzling why they seem to be net exporters of land and net importers of labor.

65. Why does India Import Cotton Textiles? Two explanations 1.Britain’s rise as the world’s leading exporter of cotton textiles was related to technological improvements. However India was able to gain access to this technology. Then the importing of textiles is contrary to the HO model.

66. Why does India Import Cotton Textiles? 2.The poor countries used this new technology to make textiles inefficiently.  Large differences in efficient use of technology across countries remained.. This inefficiency applied more strongly to labor than it did to other factors such as land. Estimates from 1910 and 1990 show that labor was not necessarily the abundant factor in India once we take into account its low productivity. India could be considered land-abundant if land and labor are measured by their “effective” amounts. This can explain the switch from exporter to importer.

67. Conclusions The HO framework is one of the most widely used models in explaining trade patterns. It isolates the effect of different factor endowments across countries and determines the impact of these differences on trade patterns, relative prices, and factor returns. By focusing on the factor intensities among goods, the HO model also provides clear guidance as to who gains and who loses from trade.

68. Conclusions The HO model predicts real gains for the factor used intensively in the export good, whose relative price goes up with the opening of trade, and real losses for the other factor. We have investigated some empirical tests of the HO theorem. These tests originated with Leontief’s paradox, the finding that U.S. exports just after WW II were relatively labor intensive.

69. Conclusions With the test reformulated to use factor amounts embodied in net exports and the effective factor endowments in each country, it was found that the U.S. was abundant in effective labor and presumed it was in capital. The U.S. had positive factor content of L and K in net exports, consistent with the sign test of the extended HO model.