Chapter 10: International Trade and the Developing Countries

Chapter 10: International Trade and the Developing Countries Krugman, P.R., Obstfeld, M.: International Economics: Theory and Policy, 8th Edition, Pearson Addison-Wesley, 250-265 Frankel, J., and D. Romer (1999) Does trade cause growth? American Economic Review 89(3), 379-399 1

Preview Import substituting industrialization Trade liberalization since 1985 Export oriented industrialization Trade and development: the empirical evidence 2

Introduction Which countries are developing countries? The term developing countries does not have a precise definition, but it is a name given to many low and middle income countries. 3

Table 1: Gross Domestic Product Per Capita, 2005 (dollars) 4

Import Substituting Industrialization Import substituting industrialization was a trade policy adopted by many low and middle income countries before the 1980s. The policy aimed to encourage domestic industries by limiting competing imports. It was often accompanied with the belief that poor countries would be exploited by rich countries through international financial markets and trade. 5

Table 2: Effective Protection of Manufacturing in Some Developing Countries (percent) 6

Import Substituting Industrialization The principal justification of this policy was/is the infant industry argument: Countries may have a potential comparative advantage in some industries, but these industries can not initially compete with well-established industries in other countries. To allow these industries to establish themselves, governments should temporarily support them until they have grown strong enough to compete internationally. 7

Problems With the Infant Industry Argument 1. It may be wasteful to support industries now that will have a comparative advantage in the future. 2. With protection, infant industries may never grow up or become competitive. 3. There is no justification for government intervention unless there is a market failure that prevents the private sector from investing in the infant industry. 8

Infant Industries and Market Failures Two arguments for how market failures prevent infant industries from becoming competitive: 1. Imperfect financial asset markets Because of poorly working financial laws and markets (and more generally, a lack of property rights), firms can not or do not save and borrow to invest sufficiently in their production processes. If creating better functioning markets and enforcing laws is not feasible, then high tariffs would be a second-best policy to increase profits in new industries, leading to more rapid growth. 9

Infant Industries and Market Failures 2. The problem of appropriability Firms may not be able to privately appropriate the benefits of their investment in new industries because those benefits are public goods. The knowledge created when starting an industry may be not appropriable (may be a public good) because of a lack of property rights. If establishing a system of property rights is not feasible, then high tariffs would be a second-best policy to encourage growth in new industries. 10

Import Substituting Industrialization As a strategy to encourage manufacturing industries, import substituting industrialization in Latin American countries worked in the 1950s and 1960s. 11

Import Substituting Industrialization But economic development, not encouraging manufacturing per se, was the ultimate goal of the policy. Did import substituting industrialization promote economic development? No, countries adopting these policies grew more slowly than rich countries and other countries not adopting them. 12

Import Substituting Industrialization It appeared that the infant industry argument was not as valid as some had initially believed. New industries did not become competitive despite or because of trade restrictions. Import substitution industrialization involved costs and promoted wasteful use of resources: It involved complex, time-consuming regulations. It set high tariff rates for consumers, including firms that needed to buy imported inputs for their products. It promoted inefficiently small industries. 13

Trade Liberalization There is some evidence that low and middle income countries which had relatively free trade had higher average economic growth than those that followed import substituting industrialization. But this claim is a matter of debate. Regardless, by the mid-1980s many governments had lost faith in import substituting industrialization and began to liberalize trade. 14

Table 3: Effective Rates of Protection for Manufacturing in India and Brazil 15

Fig. 1: The Growth of Developing-Country Trade Source: World Bank 16

Trade Liberalization As with import substituting industrialization, economic development was the ultimate goal of trade liberalization. Has trade liberalization promoted development? The evidence is mixed. Growth rates in Brazil and other Latin American countries have been slower since trade liberalization than they were during import substituting industrialization, 17

Trade Liberalization But unstable macroeconomic policies and financial crises contributed to slower growth since the 1980s. Other countries like India have grown rapidly since liberalizing trade in the 1980s, but it is unclear to what degree liberalized trade contributed to growth. Some economists also argue that trade liberalization has contributed to income inequality, as the Hechscher-Ohlin model predicts. 18

Export Oriented Industrialization Instead of import substituting industrialization, several countries in East Asia adopted trade policies that promoted exports in targeted industries. Japan, Hong Kong, Taiwan, South Korea, Singapore, Malaysia, Thailand, Indonesia, and China are countries that have experienced rapid growth in various export sectors and rapid economic growth in general. These economies or a subset of them are sometimes called high performance Asian economies. 19

Export Oriented Industrialization These high performance Asian economies have generated a high volume of exports and imports relative to total production. By this standard, these economies are open economies. But it is debatable to what degree these economies established free trade. Although evidence suggests that these economies did have less restricted trade than other low and middle income countries, some trade restrictions were sometimes still in effect. 20

Table 4: Average Rates of Protection, 1985 (percent) 21

Export Oriented Industrialization It is also unclear if the high volume of exports and imports caused rapid economic growth or was merely correlated with rapid economic growth. Some economists argue that the cause of rapid economic growth was high saving and investment rates, leading to both rapid economic growth in general and rapid economic growth in export sectors. In addition, almost all of the high performance Asian economies have experienced rapid growth in education, leading to high literacy and numeracy rates important for a productive labor force. 22

Industrial Policies in East Asia Some East Asian economies have implemented industrial policies: policies intended to promote certain industries. Examples of industrial policies include not only tariffs, import restrictions, and export subsidies for import-competing industries and export industries, but also policies like subsidized loans for industries and subsidized research and development. But not all high performance Asian economies implemented these policies, and the ones that did had a wide variety of policies. 23

Industrial Policies in East Asia There is little evidence that countries with industrial policies had more rapid growth in the targeted industries than those that did not. There is some evidence that industrial policies failed: chemicals, steel, automobiles were promoted by the South Korean government in the 1970s, but the polices were later abandoned because they were too expensive and did not produce desired growth. 24

Trade and development: the empirical evidence We discuss the study by Frankel and Romer (1999). Does trade cause growth? American Economic Review 89(3), 379-399. Frankel and Romer examine the impact of trade on real income using an instrumental variable approach. First, we discuss possible reasons why countries do not gain from trade. We then describe the empirical approach used by Frankel and Romer (and many others). Then, we present the main results obtained by Frankel and Romer. Finally, we summarize the main arguments and results of other studies on the relationship between trade and income 25

Reasons Why Some Countries Do Not Gain from Trade An important source of gains from trade is the existence of cross-border knowledge spillovers. The ability to absorb foreign knowledge and technology depends on absorptive capacity. Several authors hypothesize that primary exports may be an obstacle to attaining a higher standard of living. Increased primary exports can lead economies to shift away from the competitive manufacturing sectors in which many externalities necessary for growth are generated, while the primary export sector itself does not have many linkages with, and spillovers into, the economy; Primary exports are subject to large price and volume fluctuations. Increased primary exports may therefore lead to increased GDP variability and macroeconomic uncertainty. 26

Reasons Why Some Countries Do Not Gain from Trade In a scenario of severe factor-market imperfections that limit both the mobility of factors between sectors and the flexibility of factor prices, increased trade may be associated with unemployment and, as a consequence, with income losses. The income effect of trade may also depend on the level of regulation The income effect of trade may depend on the quality of institutions. Institutions, such as property rights, lower transaction costs by reducing uncertainty and establishing a stable structure to facilitate interactions, thus helping to allocate resources to their most efficient uses. 27

General Approach in Cross-Country Studies Frankel and Romer (1999): ln(y i )=α+βt i +cs i +e i (1) ln(y i ) is the natural logarithm of income per person or income per worker in country i T i is the trade share of GDP (measured in logarithms or levels), and S i is country size, usually proxied by the logarithm of population and the logarithm of area. 28

General Approach in Cross-Country Studies ln(y i )=α+βt i +cs i +e i (1) Country size is included in the regression model for two reasons. (1) Country size serves as a proxy for the amount of trade within a country; the estimate of c can be used to assess whether countries also benefit from within-country trade. (2) Because larger (smaller) countries tend to have more (less) opportunities for trade within their borders, and therefore lower (higher) trade shares, it is necessary to control for country size in estimating the impact of international trade on income. Otherwise, S i would enter the error term, thereby inducing a negative correlation between e i and T i and thus a downward bias in the estimate of β. 29

General Approach in Cross-Country Studies ln(y i )=α+βt i +cs i +e i (1) Eq. (1) cannot be estimated by OLS, because of the likely endogeneity of trade, and because of omitted variables due to unobserved country-specific effects. 30

General Approach in Cross-Country Studies ln(y i )=α+βt i +cs i +e i (1) To overcome these problems, Frankel and Romer (1999) suggest an instrumental-variable (IV) approach. A valid instrument is correlated with the endogenous variable (T i ), but uncorrelated with the error term (e i ) and thus not associated with the dependent variable (ln(y i )) through any channel other than the endogenous variable. 31

General Approach in Cross-Country Studies ln(y i )=α+βt i +cs i +e i (1) To construct such an instrument, Frankel and Romer propose the following two-step procedure. The first step is to estimate a gravity equation for bilateral trade shares using distance between trading partners and country size as explanatory variables (components of trade, which are assumed to be independent of income). The second step involves calculating a predicted aggregate trade share for each country on the basis of the estimated coefficients of the gravity equation. This predicted trade share is then used as a geographybased instrument for trade in regression (1). 32

The Trade Instrument In the first step, Frankel and Romer (1999) estimate a gravity model of the form: log(trade ij /GDP i )= β 0 +β 1 log(dist ij )+β 2 log(n i )+ β 3 log(a i ) +β 4 log(n j )+ β 5 log(a j )+β 6 (L i +L j )+ β 7 BORDER ij + β 8 BORDER ij log(dist ij )+β 9 BORDER ij log(n i )+ β 10 BORDER ij log(a i ) +β 11 BORDER ij log(n j )+β 12 BORDER ij log(a j )+β 13 BORDER ij (L i +L j ) + e ij, TRADE is bilateral trade between countries i and j, DIST is the distance between i and j, N is population, A is area, L is a dummy for landlocked countries, and BORDER is a dummy for a common border between two countries. 33

The Trade Instrument log(trade ij /GDP i )= β 0 +β 1 log(dist ij )+β 2 log(n i )+ β 3 log(a i ) +β 4 log(n j )+ β 5 log(a j )+β 6 (L i +L j )+ β 7 BORDER ij + β 8 BORDER ij log(dist ij )+β 9 BORDER ij log(n i )+ β 10 BORDER ij log(a i ) +β 11 BORDER ij log(n j )+β 12 BORDER ij log(a j )+β 13 BORDER ij (L i +L j ) + e ij, The equation includes two measures of size: log population and log area, dummy variables for landlocked countries and common borders, interaction terms of all of the variables with the common-border dummy, because a large part of countries trade is with their immediate neighbors and because the goal is to identify geographic influences on overall trade. 34

The Trade Instrument Frankel and Romer aggregate the fitted values from the bilateral trade equation. They first rewrite the above equation log(trade ij /GDP i )= a X ij + e ij, where a is the vector of coefficients, and X ij is the vector of right-hand side variables. The estimate of the geographic component of country i s overall trade share is then Instrument = Σe â Xij 35

Results, Frankel and Romer, IV estimates Table (included observations: 98) Coefficient Std. Error t-statistic Prob. C 1.620810 3.484226 0.465185 0.6429 TRADE 2.960762 1.340939 2.207977 0.0297 LOG(POPULATION) 0.351181 0.145084 2.420532 0.0174 LOG(AREA) 0.201787 0.176904 1.140657 0.2569 36

Results, Frankel and Romer, IV estimates Table (included observations: 150) Coefficient Std. Error t-statistic Prob. C 4.961235 2.035972 2.436789 0.0160 TRADE 1.966313 0.912417 2.155061 0.0328 LOG(POPULATION) 0.191747 0.088080 2.176961 0.0311 LOG(AREA) 0.086371 0.097830 0.882866 0.3788 37

Results of Other Studies Rodríguez and Rodrik (2001) argue that the Frankel and Romer findings simply reflect the impact of geography on income, rather than the impact of trade on income, since the geography-based instrument is correlated with other geographic variables that affect income through non-trade channels, such as morbidity, agricultural productivity, and institutions. Rodríguez and Rodrik (2001) re-estimate the Frankel- Romer regression, adding additional controls for geography (such as distance from the equator, the percentage of a country s land area that lies in the tropics, and regional dummies), and find that the IV coefficient estimates on trade become statistically insignificant once additional geography variables are included. 38

Results of Other Studies Several other studies also include institutional variables in the IV regression. These are intended to explicitly control for potential income effects of the geography-based trade instrument that can be associated with the effects of geography on income through institutions. Frankel and Rose (2002), as well as Noguer and Siscart (2005), for example, estimate Eq. (1) with and without additional controls for both geography and institutions. They detect a large and statistically significant effect of trade on income that is robust to the inclusion of additional control variables. 39

Study Frankel and Romer (1999) Hall and Jones (1999) Rodríguez and Rodrik (2001) Frankel and Rose (2002) Irwin and Tervio (2002) Dependent variable Trade/GDP nominal Independent variable ln(trade/gdp) ln(trade/gdp) nominal real Geographical controls Institutional controls ln(gdp per worker) 1.97 / 2.96 No No ln(gdp per worker) 0.185 Yes Yes ln(gdp per capita) 1.97 No No ln(gdp per capita) 0.21 / 0.34 Yes No ln(gdp per capita) 1.59 / 1.96 No No ln(gdp per capita) 1.13 / 1.28 Yes No ln(gdp per capita) 0.68 Yes Yes ln(gdp per capita) 0.65 / 4.91 No No ln(gdp per capita) -7.19 / 1.30 Yes No 40

Study Alcalá and Ciccone (2004) Rodrik et al. (2004) Noguer and Siscard (2005) Felbermayr (2005) Dependent variable Trade/GDP nominal Independent variable ln(trade/gdp) nominal ln(trade/gdp) real Geographical controls Institutional controls ln(gdp per worker) 0.394 / 1.013 Yes Yes ln(gdp per worker) 1.002 / 1.482 Yes Yes ln(gdp per capita) -0.87 / 0.02 Yes Yes ln(gdp per worker) -0.42 / -0.30 Yes Yes ln(gdp per capita) -0.94 / -0.77 Yes Yes ln(gdp per capita) 2.59 / 2.96 No No ln(gdp per capita) 0.89 / 1.22 Yes No ln(gdp per capita) 0.82 / 1.23 Yes Yes ln(gdp per capita) -0.344 Yes No 41

Tariffs and Growth DeJong and Ripoll (2006) find that the effects of tariffs on growth are negative for rich countries, but positive for poor countries. 42