COMPARATIVE ADVANTAGE YAO PAN

COMPARATIVE ADVANTAGE YAO PAN

FREE TRADE: VIETNAM & EU 2/16

THEORIES OF INTERNATIONAL TRADE Trade based on differences: in technologies: Ricardo in factor endowments: Hecksher-Ohlin(H-O) èinter-industry trade Trade based on economies of scale and product differentiation: Krugman and others èintra-industry trade 3/16

Decomposition of trade (% total) Around 40% of trade flows are intra-industry but growing

OUTLINE Absolute versus comparative advantage Ricardo s model of international trade Empirical testing of comparative advantage Empirical testing of gains from trade

ABSOLUTE ADVANTAGE Adam Smith (1723-1790): countries should find out what they can produce more efficiently, and then specialize in what they do best while trading with other countries who are also doing what they're best at. Labour units required to produce one unit of output Wine Computer France 2 70 US 3 50

DAVID RICARDO (1772-1823) When a country can either import a commodity or produce it at home, it compares the cost of producing at home with the cost of procuring from abroad; if the latter is less than the first, it imports. Page 7

ASSUMPTIONS OF THE RICARDIAN TECHNOLOGY MODEL General (example) Two countries (EU and Kenya) Two final goods (Food and Chemicals) One factor of production (Labour) Constant returns to scale production functions Perfect competition Labor is mobile between sectors, but not between countries Costless trade in final goods (no impediments to trade) Technology differs between countries Page 8

TECHNOLOGY DIFFERENCES Production technology is summarized in a productivity table: Labour units required to produce one unit of output Food Chemicals EU 2 8 Kenya 4 24 The EU technology is more productive for both goods The EU has an absolute advantage in Food production: it requires less labor (2 units instead of 4) The EU also has an absolute advantage in Chemicals production: it requires less labor (8 units instead of 24) Page 9

Labor units required to produce one unit of output COMPARATIVE ADVANTAGE Food Chemicals EU 2 8 Kenya 4 24 An extra unit of Chemicals needs 8 labour in the EU This labour could have made 8/2 = 4 units of Food; the opportunity cost of Chemicals production in the EU is 4 Food An extra unit of Chemicals in Kenya needs 24 labour This labour could have made 24/4 = 6 units of Food; the opportunity cost of Chemicals production in Kenya is 6 Food The EU has a comparative advantage in Chemicals, Kenya in Food Page 10

PRODUCTION POSSIBILITY FRONTIER Definition: all possible combinations of efficient production points of final goods, given the available factors of production and the state of technology Example: Suppose the EU has 200 units of labour available and Kenya has 480 units available If all workers in the EU produce only Food, the EU can make 200/2 = 100 Food (and 0 Chemicals) If all workers in the EU produce only Chemicals, the EU can make 200/8 = 25 Chemicals (and 0 Food) Similarly, if all workers in Kenya produce Food total output is 480/4 = 120 Food (and 0 Chemicals); if they all produce Chemicals total output is 480/24 = 20 Chemicals (and 0 Food) Page 11

PRODUCTION POSSIBILITY FRONTIER Note that: The PPF depends on the available factors of production: if, e.g., more labour becomes available more goods can be produced The PPF depends on the state of technology: if new techniques become available, output increases with the same use of inputs Page 12

PRODUCTION POSSIBILITY FRONTIERS Food 120 100 Kenya The EU can produce (0 Chemicals, 100 Food) or (20 Chemicals, 0 Food), or any combination in between Kenya can produce (0 Chemicals, 100 Food) or (20 Chemicals, 0 Food), or EU any combination in between Page 13 Chemicals 20 25

AUTARKY FOR THE EU Food 100 Chemicals C EU EU 25 Opportunity cost of cheminal production=slope of ppf In autarky (without trade), perfect competition è Profit=(p-c) q=0 This implies relative price of cheminal p C /p F is equal to opportunity cost of Chemical production=4 EU can produce and consume at any point on or below the ppf. Say the EU consumes both goods and chooses point C EU ; Page 14

AUTARKY FOR KENYA Food 120 Kenya Similarly, suppose Kenya consumes at the point C K in 100 autarky C K The relative price of Chemicals in autarky is then 4 Food in the EU and 6 Food in Kenya If costless trade is possible the EU will produce and export C EU EU Chemicals and Kenya will produce and export Food Page 15 Chemicals 20 25

GAINS FROM TRADE Food Pr K Suppose the trade equilibrium price p C /p F = 5 EU C K The EU will produce at Pr EU and might consume at C EU Provided Kenya (which produces at Pr K ) is willing to Kenya C EU consume at C K They trade Page 16 Chemicals Pr EU

GAINS FROM TRADE Food Pr K EU C K Since both countries are now able to consume at a point strictly beyond reach in autarky, both countries gain from trade (reach higher welfare) C EU Kenya Page 17 Chemicals Pr EU

INTERNATIONAL WAGES Absolute cost advantageèwage/welfare Assume (1) EU (Kenya) specialized in chemical (food) (2) exchange rate=1 (3) wage in Kenya is numeraire, Weu is EU wage Food price in Kenya=1*4=4(perfect competition) For EU not to produce food: Food price in EU=2*Weu>4èWeu>2 Chemical price in EU=8*Weu(perfect competition) For Kenya not to produce chemical: Chemical price in Kenya=24>8*WeuèWeu<3 Page 18

RICARDIAN MODEL SUMMARY Technological differences between countries are the classical driving force for international trade flows. Only comparative costs, not absolute costs, are important for determining the direction of trade flows. Absolute costs are important for determining a country s welfare level (wage). Allowing for more countries and more goods is easy, allowing for more than one factor of production is not Page 19

COMPARATIVE ADVANTAGE: EMPIRICAL TEST Comparative advantage, meaning differences in relative autarky prices, is the basis for trade Why? If two countries have the same autarky prices, then after opening up to trade, the autarky prices remain equilibrium prices. So there will be no trade... The law of comparative advantage: Countries tend to export goods in which they have a CA, i.e. lower relative autarky prices compared to other countries (International price autarky price) is positively correlated with net export è Does this hold in the data? Page 20

COMPARATIVE ADVANTAGE: EMPIRICAL TEST Bernhofen and Brown (JPE, 2004) exploit the (nearly) closed economy of Japan in 1858, and its subsequent opening up to trade in 1859, as a natural experiment to test for Law of CA. Attractive features of this setting: - Rare example of a closed economy - Relatively simple economy - Subsequent opening up was plausibly exogenous to economic change in Japan (non-autarky was forced upon Japan by USA). Page 21

Japan Opening Up: Source: Sugiyama (1988, table 3-4)

Graphical results

HOW LARGE ARE THE TRADE GAINS? Frankel and Romer (1999) Extremely influential paper (one of AER s most highly cited articles in recent decades). Takes a huge question ( Does trade cause growth? ) and answers it with more attention to the endogenous nature of trade than previous work. Key idea: instrument for a country s trade (really, its openness ) by using a measure of distance: how far that country is from large/rich potential trade partners. Page 24

HOW LARGE ARE THE TRADE GAINS? First-stage: instrument trade volume (import+export) Part I: Key idea: bilateral trade flows fall with bilateral trade costs and variables like bilateral distance Dij, and whether two countries share a border Bij, appear to be correlated with trade costs. Gravity equation: Page 25

First-Stage Results (Part I)

FIRST-STAGE (PART II) Now FR (1999) aggregate the previously estimated gravity regression over all of country i s imports from all of its bilateral partners to obtain Zi The constructed variable Zi is then used as an instrument for how much a country is actually trading, Ti Page 27

First-Stage Results (Part II)

FR(1999): SECOND-STAGE Now, finally, FR (1999) run the regression of interest Does trade cause growth? : Ln(GDPi/POPi)=a + b Ti + c POPi + d Ai + ui Here, GDPi/POPi is GDP per capita and Ai is area FR run this regression using both OLS and IV (Zi for Ti) Page 29

OLS and IV results

HOW LARGE ARE THE TRADE GAINS? These are big effects, that surprised many people Possible explanations: Countries that are close to big countries are rich not just because of trade, but because of spatially correlated true determinants of prosperity (omitted variable bias) Openness is proxying for lots of true treatment effects of proximity to neighbors: multinational firms, technology transfer, knowledge spillovers, migration, political spillovers. Not just Trade. The dynamic effects of openness accumulated over a long period of time, are larger than the static one-off effects of opening up to trade. Page 31

FOLLOW-ON WORK FROM FR(1999) Because of importance of question, and surprising findings, FR (1999) generated a lot of controversy and follow-on work. Rodrik and Rodriguez (2000) were most critical. Fundamental message (that has now also been confirmed for many cross-country studies, in all fields) is that these regressions are not that robust. - Inclusion of various controls can change the results a great deal. - Different measures of openness yield quite different results. Page 32

FOLLOW-ON WORK FROM FR(1999) In two recent papers, James Feyrer has revamped interest in the cross-country approach by using panel data and an IV based on a time-varying component of distance (enables the inclusion of fixed effects to mitigate omitted variable bias). Feyrer (2009) Paper 1: Trade and Income Exploiting Time Series in Geography Feyrer (2009) Paper 2: Distance, Trade, and Income The 1967 to 1975 Closing of the Suez Canal as a Natural Experiment Page 33

FEYRER (2009) PAPER 1 Uses panel of country-level GDP and trade data from 1960-1995 Exploits fact that marginal cost of shipping via air fell faster over this period than marginal cost of shipping via sea. This will make trade costs (or distance ) fall over time. And importantly, trade costs between country pairs will be affected very differently by this: - Germany-Japan sea distance is 12,000 miles, but only 5,000 air miles. ( Treatment ) - Germany-USA sea and air distances are basically the same. ( Control ) Feyrer uses this variation to get a time-varying instrument for trade openness, and then pursues a FR 1999 approach. Page 34

US Trade by Mode of Transport Consistent with a change in relative cost of using each mode Figure: Air Freight Share of US Trade Value (excluding North America) Source: Hummels (2007), pp133.

IV (Column 1-4) & OLS (Column 5-6) Results:

FEYRER (2009) PAPER 2 IV coefficient in Feyrer (2009) Paper 1 is still large. Perhaps, therefore, omitted variable bias was not as big an issue as previously thought. But a fundamental question of interpretation remains: - Is openness capturing channels related purely to the trade of goods, or is it possible that this variable is (also) proxying for other elements of international interaction (FDI, migration, knowledge flows) made cheaper by the rise of air travel? Page 37

FEYRER (2009) PAPER 2 Feyrer (2009) Paper 2 exploits the closing and reopening of the Suez Canal between 1967 and 1975 to dig deeper: Page 38

The Suez Canal provides the shortest sea route between Asia and Europe and currently handles about 7.5% of world trade. The closure of the canal was a substantial unexpected shock to world trade

FEYRER (2009) PAPER 2 Feyrer (2009) Paper 2 exploits the closing and reopening of the Suez Canal between 1967 and 1975 to dig deeper: (Unstated) logic: No one is doing FDI or migration by sea during this period, so only thing a change in sea distance can affect is trade. Short-run shock. Can trace the timing of the impact. Very nice feature that it turns off and on: Should expect symmetric results from static trade models, but asymmetric results if driven purely by (eg) spread of knowledge. Page 40

Trade and Sea Distance:

Page 42 FEYRER (2009) PAPER 2: IV RESULTS

CONCLUSION CA seems to hold, in one place where tested. GT appear to vary considerably across estimates. - But GT are hard to measure. There are aspects of welfare (e.g. change in the number of varieties available) that are not captured in the studies we ve seen above, but which might be important (or not!). - Also very hard to get exogenous change in ability to trade.

AREAS FOR FUTURE RESEARCH Are there other ways (or places) in which to test CA? Can we find more natural experiments that affect regions abilities to trade, to shed more light on the size of GT? How well do the measures that statistical agencies use to measure economic welfare correspond with the concepts of welfare in the models we have seen? See Burstein and Cravino (2011) for a discussion.