Argentine trade policies in the XX century: 60 years of solitude

Brambilla, Irene; Galiani, Sebastian; Porto, Guido Article Argentine trade policies in the XX century: 60 years of solitude Latin American Economic Review Provided in Cooperation with: Centro de Investigación y Docencia Económica (CIDE), Mexico City Suggested Citation: Brambilla, Irene; Galiani, Sebastian; Porto, Guido (2018) : Argentine trade policies in the XX century: 60 years of solitude, Latin American Economic Review, ISSN 2196-436X, Springer, Heidelberg, Vol. 28, Iss. 1, pp. 1-30, https://doi.org/10.1007/s40503-017-0050-9 This Version is available at: https://hdl.handle.net/10419/195252 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Argentine trade policies in the XX century: 60 years of solitude Irene Brambilla 1 •Sebastian Galiani 2 •Guido Porto 1 Received: 20 July 2017 / Revised: 15 September 2017 / Accepted: 4 October 2017 ÓThe Author(s) 2017. This article is an open access publication Abstract At the turn of the last century, the Argentine economy was on a path to prosperity that never fully developed. International trade and trade policies are often identified as a major culprit. In this paper, we review the history of Argentine trade policy to uncover its exceptional features and to explore its contribution to the Argentine debacle. Our analysis tells a story of bad trade policies, rooted in distributional conflict and shaped by changes in constraints, that favored industry over agriculture in a country with a fundamental comparative advantage in agriculture. While the anti-export bias impeded productivity growth in agriculture, the import substitution strategy was not successful in promoting an efficient industrialization. In the end, Argentine growth never took-off. Keywords Tariff protection Export taxes on agriculture Anti-export bias JEL Classification F13 F14 We thank Rafael Di Tella and Edward Glaeser for encouraging us to write this chapter. We appreciate the superb work done by Natalia Porto in the coordination of all the data collection effort. Nicolas Botan, Laura Jaitman, and Ivan Torre provided excellent research assistance. Comments from Alberto Porto and seminar participants at the ‘‘Argentine Exceptionalism’’ conference at Harvard University are greatly appreciated. &Guido Porto [email protected]no.unlp.edu.ar Irene Brambilla [email protected] 1 Universidad Nacional de La Plata and NBER, Calle 6 e 47 y 48, Oficina 532, La Plata 1900, Argentina 2 University of Maryland, College Park, USA 123 Lat Am Econ Rev (2018) 27:4 DOI 10.1007/s40503-017-0050-9 1 Introduction At the turn of the last century, the Argentine economy was on a promising path to prosperity, a prosperity which, in the end, never fully materialized. Argentina failed in many dimensions and various concurrent factors—addressed in different chapters of this book—help explain this debacle. Often, directly or indirectly, a major culprit is international trade. 1 This is the focus of our paper. We have two broad objectives: to uncover the exceptional features of the history of Argentine trade policy and to assess the contribution of these exceptional features to the economic performance of Argentina. In our analysis, we follow a descriptive approach based on two major sources of data: a compilation of quantitative and qualitative accounts from 1890 to 1966 taken from the literature on Argentine history, and a comprehensive (i.e., disaggregated) trade policy data set (on imports and exports) from 1966 to 2006 that we put together for this project. These data are used to document the high degree of antiexport bias of Argentine trade policy. We emphasize two manifestations of such bias: the burden imposed by economic policies on the agricultural export sector and the benefits granted to manufacturing sectors that typically competed against imports from the rest of the world—the model of import substitution. 2 To understand the Argentine anti-export bias and the import substitution policy, we provide an account of two major factors that help explain both the cross-sectional structure of protection as well as the overall trends in this structure of protection: the distributionalconflict and constraints, and how these shape theArgentine policy-making process. Broad differences in sectoral protection (industry versus agriculture or imports versus exports) are the result of distributional conflict between landowners, industrialists, and workers. The finer differences (at more disaggregated level of the import nomenclature, for instance) are also a consequence of distributional conflict (within the manufacturing sectors, for instance, or between unskilled and skilled labor) as well as of political economy considerations (lobbies or unions). The trends, in turn, can be understood with changes in the way that different governments weighed the distributional conflict and with changes in the constraints faced by those governments. The Great Depression and World War I and II, international commodity prices, international institutions (like the World Trade Organization), exchange rates, and fiscal budget considerations affect the feasibility of the policies available to the government and thus shape trade policy. Our account is thus based on the interplay of endogenous domestic decisions and exogenous shocks, with roots in the inherent Argentine distributional conflict, thathindered the long-run economic growthof the country. These ideas provide the stylized facts about trade policy that motivate the modeling framework of the next chapter in the volume (by Sebastian Galiani and Paulo Somaini). The resulting anti-export bias and import substitution model had negative consequences for growth and economic performance. We document this by first looking at the evolution of agricultural productivity in the country (compared to the 1 The chapter by Taylor in this volume shows that international trade can account for around 25% of the income gap between Argentina and the developed world. 2 Due to the Lerner symmetry theorem, in fact, these are manifestations of the same phenomenon. 4 Page 2 of 30 Lat Am Econ Rev (2018) 27:4 123 US), and, second, by assessing the evolution of productivity in the Argentine industrial sector vis-a `-vis other countries. In the end, we show that the anti-agro bias impeded growth in agricultural productivity and the import substitution model failed at boosting productivity growth in industry. These are major factors that help explain why Argentina was unable to grow and achieve its once-tangible prosperity. The remainder of the paper is organized as follows. In Sect. 2, we document historic aggregate trade flows and describe the pattern of Argentine trade. In Sect. 3, we characterize the structure and evolution of import tariffs from 1870 to 2006. In Sect. 4, we document the Argentine anti-export policies by providing an account of export taxes from 1966 to 2006. In Sect. 5, we assess some of the consequences of bad trade policies. Section 6concludes. 2 Trade flows, trade patterns, and trade policy In this section, we present an overview of trade flows, trade patterns, and trade policy in Argentina. Argentina was initially an open economy, then it closed to trade, and finally opened up again in recent years. The trends in openness (the ratio of exports plus imports to GDP) from the 1900s to 2006 can be seen in Fig. 1. During the first globalization era, Argentina showed high openness ratios, which ranged from 30 to 40 percent for a period of almost 30 years. In contrast, trade openness significantly declined during the 1930s and 1940s, then slightly recovered at the end of the 1940s, and continued to decline throughout the 1950s and 1960s. From the 1970s to the early 2000s, the ratio of exports and imports to GDP remained relatively stable (with fluctuations) and, finally, strongly increased in recent years, especially after the 2001 crisis. Fig. 1 Trade openness exports ?imports as a share of GDP. Source: Own calculations with data from ECLAC, INDEC and Ferreres (2005) Lat Am Econ Rev (2018) 27:4 Page 3 of 30 4 123 Argentine comparative advantage lies primarily on agricultural goods, broadly defined so as to include both primary products as well as agro-manufactures. In fact, Argentina has historically been considered as one of the ‘‘grain yards’’ of the world. To a large extent, this is because the country is relatively abundant in land. Irwin (2002) argues that, in a sample of 25 developed and developing countries, Argentina had the highest ratio of productive land to population in 1890, followed by New Zealand, Australia, Canada, and the United States. Table 1, based on data compiled by Lai (1998), confirms this claim. Between 1875 and 1889, Argentina had the highest ratio of productive land per capita, 216.44 acres per capita. By the mid1940s, Argentina remained largely abundant in land, but showed much lower ratios compared to, for instance, Canada or Australia. The country also ranked high in the relative endowment of livestock. Based on data from the 1895 Argentine Census, we report in Table 2that, compared to eight other countries including the US and Australia, Argentina ranked first in horses, second in cattle, and third in sheep. The relative un-abundance of skilled labor and capital (compared to the developed world) also contributed to a specialization in agriculture, especially in the early years. To assess the stock of human capital, we look at literacy rates. Data from Sokoloff and Engerman (2000) are reported in Table 3. In 1900, 52% of the Argentine population was literate. The literacy rate was much higher than in other countries in the region, such as Brazil (25.6%), Chile (43%), Costa Rica (33%), and Table 1 Productive land per capita (in acres) Source: Lai (1998) Abundant in labor Moderately abundant in land Abundant in land 1875–89 United Kingdom 1.42 Trinidad (Caribbean) 5.66 Chile 25.43 Japan 1.76 Malaya 7.31 United States 34.91 Switzerland 2.33 Russia 7.48 Mexico 43.79 China 2.38 Siam/Thailand 8.65 Costa Rica 62.49 France 2.7 Malaysia 6.21 Canada 101.81 Spain 4.44 Brazil 102.27 South Africa 124.75 Australia 174.4 Argentina 216.44 1946–1949 Singapore 0.08 Thailand 5.2 Ethiopia 22.24 Japan 0.95 Malaysia 6.21 Argentina 29.4 Taiwan 0.98 United States 11.77 Brazil 29.96 United Kingdom 1.06 Chile 11.99 Canada 102.27 China 1.97 Costa Rica 16.18 Australia 130.36 Trinidad 1.98 South Africa 18.52 France 2.64 Russia 19.54 Indonesia 4.27 Mexico 19.96 Spain 4.29 4 Page 4 of 30 Lat Am Econ Rev (2018) 27:4 123 Mexico (22.2%). However, it was lower than in developed countries, namely the US (86.7%) and Canada (80%). In fact, the ratio of skilled-to-unskilled labor (computed as the rate of the literacy rate over its complement, the illiteracy rate) was actually 5.5 times higher in the US than in Argentina (and it was three times higher in Canada). Clearly, while Argentina appeared as relatively well endowed in skills in the early 1900 with respect to developing countries, skilled labor was relatively unabundant compared to the developed countries. To look at capital abundance, we build approximations to the capital to land ratio using the calculations of Argentine’s wealth reported in the National Census of 1914. For Argentina, we find that the ratio of industrial capital relative to the value of the agricultural resources (livestock plus land) was 0.10. This indicator was 0.39 for France (1909), 0.63 for the United States (1904), and 0.80 for Sweden (1908). This suggests a relatively scarcity of capital in the country. 3 Table 2 Livestock per capita 1895. Source: Argentine Census (1895) Cattle Horses Sheep Cattle/Pop. Rank Horses/Pop. Rank Sheep/Pop. Rank Australia 357 3 49 2 2995 1 New Zealand 132 4 34 4 2912 2 Argentina 542 2 111 1 1859 3 Uruguay 650 1 47 3 1602 4 United Kingdom 28 9 5 9 77 5 United States 76 5 24 5 68 6 France 34 7 7 8 54 7 Russia 29 8 23 6 52 8 Germany 35 6 8 7 27 9 Table 3 Literacy rate and skilled Labor. Source: Sokoloff and Engerman (2000) Year Literacy rate Skilled/unskilled Argentina 1900 52 1.1 Brazil 1900 25.6 0.3 Chile 1900 43 0.8 Costa Rica 1900 33 0.5 Mexico 1900 22.2 0.3 Uruguay 1900 54 1.2 Canada 1870 80 4.0 United States 1890 86.7 6.5 3 These figures are consistent with the industrialization index reported by Bairoch (1982). Bairoch’s index reveals, first, a relatively low level of industrialization in the developing world (especially Latin America), and, second, an increasing gap relative to developed countries. Gomez-Galvarriato and Williamson (2008) build a different industrialization index for 1910, which measures industrial performance using as a proxy net exports of cotton textile manufactures per capita (the index includes Lat Am Econ Rev (2018) 27:4 Page 5 of 30 4 123 The same pattern of factor endowments is seen in more recent year. We use data on the stock of skilled and unskilled labor, capital, and land compiled by Cusolito and Lederman (2009). Relative endowments in 2000 for a sample of the most relevant countries for our purposes are listed in Table 4. Argentina is currently relatively abundant in land: the country ranks fifth in the land/labor ratio. The capital/labor ratio is relatively low (Argentina ranks 47th), while the skilled-tounskilled ratio is also relatively low (Argentina ranks 41st). These observations reveal that the factor abundance of the country resides mostly in land and unskilled labor and that the sources of comparative advantage of Argentina, measured by its factor endowments, have remained unchanged since the late 1800s. This structure of factor endowments implies a historic specialization in goods mostly intensive in land and unskilled labor which are, to a large extent, agricultural goods. This can be seen by looking at the patterns of trade. For the early years, we rely on Vazquez Presedo (1971). In the 1900s, agricultural primary products accounted for most of Argentine’s exports. In fact, at the end of the 18th century and at the beginning of the 19th century, Argentina was the third exporter of wheat in the world (after the United States and Russia). Furthermore, the Argentine share of wheat exports among the eight major exporters doubled from 9 to 18% during the 1891–1910 period. In addition, the combined exports of Agriculture (primary products) and Processed Food (agro-manufactures) accounted for more than 90% of total Argentine exports in the early 1900s. Using more recent customs data, Fig. 2plots the trends in the share of exports of Agriculture (primary products), Processed Food (agro-manufactures), and Other Products from 1970 to 2006. Clearly, the share of agricultural exports declined in time. There were peaks of over 60% in 1971 and 1983, but the shares plummeted in the 1980s and 1990s, reaching a lowest value of less than 30% in 2006. The share of Processed Food was relatively stable throughout the period, with a slight increase starting in the mid-1980s. In consequence, the trend in the share of exports of Other Products is almost a mirror image of the trends in Agriculture, with a clear upward trend from around 25% in the early 1970s to nearly 50% in 2006. In Table 5, we present the average share of exports and imports from 1970 to 2006 at the 1-digit level of the Harmonized System. Looking at export shares first, we verify the downward trend in Agriculture and the slight increase in Processed Food. Furthermore, we observe that the shares of Mineral Products, Chemical Products, Plastics, and Transport increase in time. In contrast, Textiles, Footwear, and Leather become less important. Looking at imports shares, the main categories are Chemical Products, Machinery, and Transport Equipment. Clearly, Argentina exports mainly primary products and agro-manufactures, with an increasing participation in minerals and fuels, and imports instead capital goods and inputs. The overall trends in trade openness can be explained by both external factors (such as the Great Depression, World War I and II) and internal factors, such as Footnote 3 continued yarn, thread, and cloth of all sorts). According to this index, Argentina (net imports of 5:47$ per capita) and Australia (8:7$ per capita) recorded the highest dependence on imported cotton textile manufactures. 4 Page 6 of 30 Lat Am Econ Rev (2018) 27:4 123 Table 4 Relative factor endowments. Source: Cusolito and Lederman (2009) Country Capital/ labor Rank Land/ Capital Rank Land/ labor Rank Skilled/ unskilled Rank Argentina 55.5 28 3.5 25 1944.4 5 0.81 33 Australia 148.1 10 3.7 23 5495.5 1 2.76 6 Austria 165.2 6 0.2 63 379.7 42 2.35 11 Benin 3.0 65 35.4 7 1073.1 13 0.11 66 Bolivia 9.4 57 10.4 15 974.4 15 0.41 46 Brazil 35.1 33 2.3 31 801.2 23 0.28 57 Cameroon 4.3 62 29.0 10 1243.7 11 0.15 63 Canada 140.4 14 2.2 32 3069.7 3 3.92 4 Chile 57.8 26 0.6 55 343.7 46 1.07 24 China 14.5 51 1.4 36 204.1 58 0.62 37 Colombia 18.4 47 0.9 44 160.2 62 0.46 43 Costa Rica 19.9 44 0.8 46 160.1 63 0.43 44 Denmark 144.4 12 0.6 56 855.7 21 2.13 12 Dominican Rp 20.6 43 1.3 38 275.6 52 0.38 48 Ecuador 26.3 39 1.3 41 335.3 47 0.59 38 Egypt 11.1 55 1.4 37 154.7 64 0.56 40 El Salvador 11.9 54 2.5 29 293.7 51 0.24 58 Finland 144.5 11 0.6 54 886.6 19 2.38 10 France 152.2 9 0.5 59 712.5 30 1.25 20 Greece 85.7 23 0.7 49 584.6 34 0.90 29 Iceland 125.7 17 0.0 72 48.0 72 1.21 21 India 7.6 58 6.1 18 463.8 39 0.29 56 Indonesia 16.1 49 1.5 35 237.5 54 0.37 50 Ireland 104.4 21 0.6 52 663.9 31 1.78 15 Israel 138.7 15 0.1 67 150.6 65 1.61 16 Italy 153.1 8 0.2 62 369.9 43 0.88 31 Jamaica 24.5 40 0.7 50 165.0 61 0.73 35 Japan 184.8 5 0.0 71 72.8 71 2.56 8 Kenya 4.2 63 10.9 14 454.8 40 0.18 60 Korea Rep. 241.5 1 0.1 69 180.9 60 3.05 5 Malawi 1.6 69 30.7 9 495.4 37 0.05 69 Malaysia 57.6 27 0.4 61 209.6 57 1.02 25 Mexico 44.8 29 1.6 33 729.3 28 0.68 36 Mozambique 1.2 71 46.1 5 558.5 35 0.03 72 Nepal 7.0 59 4.3 22 300.4 50 0.18 61 The Netherlands 142.8 13 0.1 68 121.3 68 2.07 14 New Zealand 111.8 19 0.8 48 866.1 20 2.11 13 Nicaragua 15.4 50 8.8 16 1349.3 8 0.34 53 Norway 185.3 4 0.2 65 402.4 41 6.87 2 Lat Am Econ Rev (2018) 27:4 Page 7 of 30 4 123 import tariffs, quantitative restrictions, and export taxes. The focus of our chapter is on the role of trade policies, how they distort relative prices and how they affect trade volumes and trade patterns. To investigate these issues, we explore the history of import protection in Sect. 3and of export taxes in Sect. 4. As we will see, however, external and internal factors are interrelated and trade policy can sometimes be affected by changes in external conditions. 3 Tariffs (1890–2006) In this section, we provide an account of the history of Argentine tariff policy. Our objective is to derive a list of stylized facts that constitute the salient and exceptional features of interventions to imports in Argentina. We cover most of Argentine history, from 1890 to 2006. Due to differences in the quantity and quality of trade Table 4 continued Country Capital/ labor Rank Land/ Capital Rank Land/ labor Rank Skilled/ unskilled Rank Pakistan 10.3 56 5.1 20 527.8 36 0.20 59 Panama 36.3 32 1.3 40 471.3 38 0.93 28 Paraguay 18.8 46 7.9 17 1488.3 7 0.36 51 Peru 23.6 41 1.5 34 360.7 44 1.02 26 Philippines 16.1 48 1.3 39 209.6 56 1.16 23 Portugal 88.0 22 0.4 60 344.8 45 0.38 49 Romania 29.5 37 3.2 26 938.1 17 2.69 7 Senegal 2.9 66 24.8 11 721.1 29 0.09 68 Singapore 202.9 3 0.0 73 0.5 73 1.44 17 South Africa 19.8 45 4.3 21 854.0 22 1.38 19 Spain 113.4 18 0.7 51 751.7 26 0.88 30 Sri Lanka 12.3 53 1.0 43 117.1 69 0.81 32 Sweden 132.1 16 0.5 58 632.1 33 4.08 3 Switzerland 203.2 2 0.1 70 112.7 70 2.45 9 Togo 3.2 64 46.7 4 1506.6 6 0.16 62 Trinidad 62.8 24 0.2 64 140.0 66 0.95 27 Tunisia 33.9 35 2.9 27 981.3 14 0.30 54 Turkey 31.1 36 3.7 24 1150.5 12 0.29 55 Uganda 0.9 73 72.7 2 650.8 32 0.12 65 UK 111.0 20 0.2 66 219.3 55 1.39 18 Uruguay 39.9 30 2.4 30 961.0 16 0.81 34 USA 159.5 7 0.8 45 1309.6 9 8.71 1 Venezuela 35.0 34 0.8 47 274.2 53 0.38 47 4 Page 8 of 30 Lat Am Econ Rev (2018) 27:4 123 and never used again, except in the 1980s. In consequence, the 1980s were actually a period of reversal to protection, because the relatively flat trend in the average tariff came together with an increase in non-tariff barriers. The last episode of liberalization took place with President Menem in the 1990s. These reforms came in two stages. From 1989 to 1991, the average tariff declined from 30 to 18%, the dispersion in tariff rates was also reduced, and all non-tariff barriers were pulled down. The second stage in the Menem reform was the adoption of Mercosur—a regional trade agreement among Argentina, Brazil, Paraguay, and Uruguay—between 1994 and 1996. The intrazone tariff among members was in most cases reduced to zero. The common external tariff (extrazone) was negotiated between members and implied a further reduction in tariffs in some cases and a reversion to protection in others (as in the case of food products in Argentina, for example). In our data, we account for Mercosur by weighting the intrazone tariff by the share of imports coming from Mercosur (which underestimates the average tariff). There was a slight decline in tariffs after 1996, only fairly noticeable in the average trends. There was also a slight reversal to protection in the 2000s, after the crisis of 2001. However, this reversal was short lived, since tariff levels returned to the previous levels in 2003–2004. A major factor shapes Argentine trade policy: the distributional conflict. By distributional conflict, we mean the natural tension in the country between the sector with comparative advantage, Agriculture, and factor ownership. Agriculture is intensive in land, which is mostly owned by richer landowners. Industry is the domain of workers. In this scenario, free trade, ceteris paribus, worsens the distribution of income in Argentina, and this provides a distributional root for protection and anti-export bias. There are, of course, many other factors that complement the distributive concern in the determination of trade policy. These factors affect the economic environment and constraints that shape the context into which trade policy is dictated. In Argentina, key factors are the level of international commodity prices, the evolution of international institutions, the exchange rates, and the fiscal resource needs of the government in office. The story about the interplay between the distributional conflict inherent to the Argentine society and external shocks is developed in the next chapter by Galiani and Somaini. They model a three-sector economy (agriculture, manufacturing, and nontradable services) that uses three factors: land, labor, and capital. Factor owners (workers, landlords, and capitalists) have different preferences over trade protection (i.e., tariffs or export taxes). The model identifies several distinctive dynamic patterns that are broadly consistent with the evolution of the Argentine economy and the trade policy described in our chapter. The authors show that, for very high terms of trade, the economy can specialize in agriculture and services (thus importing manufactures) in a political equilibrium that supports free trade policy. This story is consistent with our account of the period 1930–1943 in Argentina. However, as the terms of trade worsen, the economy begins a gradual but persistent industrialization process that carries support for protectionism until it becomes a viable political equilibrium (consistent with the post 1943 period in Argentina). In the model, however, protection has reinforcing effects, because the additional flow of capital and labor to the secondary sector raises even more demands for protectionism. This Lat Am Econ Rev (2018) 27:4 Page 15 of 30 4 123 describes an import substitution strategy that might drive the economy towards near autarky. In Argentina, this is consistent with the situation of the economy towards the early 1970s. The emergence and the strengthening of the IS model in Argentina strongly correlate with the overall level of protection after the 1930s and up to the late 1960s and 1970s. The debacle of the import substitution model can be traced back to changes in the economic conditions and environment. There are at least three factors that made the model become increasingly unsustainable. First, there was an increasing pressure to eliminate inefficient policies that impeded GDP growth. As highlighted in Galiani and Somaini in this volume, the abrupt change in the trends in tariff protection after the oil crisis points to dynamic factors such as the increasing cost of technology adoption in the manufacturing sector as well as the fiscal constraints to finance subsidies to the manufacturing sector. Second, population growth, unions, and unbalanced consumption growth towards services were over time debilitating the protectionist coalition. Third, a major factor that explains the trends in tariff reforms in Argentina in recent years was the increasing need to participate in world fora and to comply with the Uruguay Round and the WTO accession. 8 We now turn to the cross-sectional variation in tariffs and look at the evolution of tariffs for different groups of products (at the 2-digit level). Table 7lists the average tariff for the four broad stages of liberalization described above. Footwear has always been the most protected sector. Textiles and Leather have also received consistently higher levels of tariff protection. The case of Food Processing is interesting, because the sector ranked third in 1966–1970 but subsequently lost protection relative to Textiles (starting in 1971) and Stones, Machinery, Metals, Plastics, and Transport Equipment up until the 1990s. From 1991 to 2005, however, the sector recovered protection and it ranked fourth. There has also been some variation in the ranking of low-protected industries. Minerals were the least protected sectors during the first two periods, but it was replaced by Agriculture after 1977. In addition, Minerals, and Chemicals were at the bottom of the distribution throughout all the stages of liberalization. An interesting case is the Wood sector which moved between the middle and top of the distribution during the first three periods but became the third least protected industry starting in 1991. There is a somewhat analogue story with Machinery, which was always in the middle of the ranking except during the 1980s (when it became the third most protected industry). Figures 5,6give a better sense of the relative structure of protection across time periods. We show the evolution in tariffs for each major product group (solid line) relative to Agriculture (broken line). In general terms, tariffs have been cut in all sectors, though clearly in different degrees. While the historical sectoral differences in protection levels persist today (the most protected industries in the 1960s are still the most protected in the 2000s, and likewise for the least protected), the liberalization process has caused sectoral tariffs to converge to a large extent. 8 Of course, this does not preclude the taxation of exports, as we show in the next section, and hence the possibility of continuing with a protectionist model. 4 Page 16 of 30 Lat Am Econ Rev (2018) 27:4 123 Table 7 Tariff Statistics for periods of 1966 to 2005. Source: Argentine trade policy data collected by the authors. See text Sector 1966-1970 1971–1976 1977–1979 1980–1990 1991–2005 Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. Footwear 151 69 158 2.152 69 21 38 6 15 4 Leather 139 89 130 3.623 58 28 28 3 11 3 Processed Food 127 67 121 3.201 35 23 25 4 10 3 Textiles 126 63 126 1.894 53 15 34 5 13 4 Stone 109 56 102 2.236 48 16 31 4 10 3 Wood 91 40 84 2.918 35 15 28 3 8 2 Machinery 89 32 73 2.411 43 20 20 4 11 2 Metals 87 41 76 2.517 42 11 28 3 10 2 Plastics 83 32 67 1.441 40 12 25 2 10 2 Agro 79 57 56 0.227 13 3 19 2 5 2 Transport 77 32 63 2.641 40 11 29 4 10 4 Chemical 76 37 61 1.759 30 11 22 2 8 2 Mineral 69 48 46 2.411 26 7 24 4 2 1 Fig. 5 Relative sectoral protection against agriculture. Source: Argentine trade policy data collected by the authors. See text Lat Am Econ Rev (2018) 27:4 Page 17 of 30 4 123 Another feature revealed by Figs. 5and 6is how agriculture was left unprotected, relative to other sectors in the economy. The sectors with significantly higher tariff levels than the agricultural sector were Textiles, Footwear, Processed Food, and Leather (Fig. 5). Instead, Transport, Machinery, Metals, Plastics, Minerals, Chemicals, and Wood also show higher tariffs than Agriculture, but the differences are much less pronounced (Fig. 6). The only exception is the Mineral sector which had less protection during certain periods (before 1976 and after 1991). The cross-sectional structure of tariffs can also be explained by the distributional conflict and how it evolves in time (due to changes in the way which the conflict is assessed by different governments or to changes in the trends in the constraints faced by those governments). We argue that the structure of protection in Argentina, which has favored industrial manufactures like textiles or footwear over agromanufactures, can be accounted for by two interrelated theories, lobbies (and political economy) and unions. The political economy argument is based on the protectionists lobby literature developed by Grossman and Helpman (1994, 2001). In this theory, industries are organized in lobbies which make contributions to the government in exchange for protection. The government, in turn, receives these contributions and maximizes social welfare. The outcome is a set of equilibrium sectoral tariff rates that balances the power of the lobbies and the efficiency losses in different industries. There is a little evidence of the role of industry lobbies in Argentina. Olarreaga and Soloaga (1998) show that active lobbying can explain the exceptions to both the intrazone Fig. 6 Relative sectoral protection against agriculture. Source: Argentine trade policy data collected by the authors. See text 4 Page 18 of 30 Lat Am Econ Rev (2018) 27:4 123 and the common external tariff in Mercosur. However, Olarreaga et al. (1999) show that terms of trade, as well as political economy factors, explain the formation of the common external tariff of Mercosur members. Another powerful explanation of sectoral tariffs, especially in Argentina, is unions. This setting, explored in Galiani and Porto (2010), exploits the power of unions as a determinant of tariffs. In Galiani and Porto, unions have the power to appropriate part of the tariff rent, which is then distributed to unskilled labor. In the Argentine data, their results suggest that the trends in the structure of protection, and the impacts on the trends in the structure of wages, can be explained by combining long-run forces, as in a Heckscher–Ohlin model, with short-run departures like unions. 4 The anti-export bias Only relative prices matter and thus the anti-export bias in trade policy can arise by protecting the import competing industry or by directly taxing the export sector. In consequence, we now explore the structure of export taxes and the most recent evolution from 1966 to 2006. Compiling data on export taxes were actually harder than compiling data on import tariffs, because WITS does not carry information on export taxes and the whole series from 1966 to 2006, only available via the Guı ´a Pra ´ctica, had to be manually typed. From 1966 to 1990, Argentina utilized the NADE nomenclature (Nomenclatura Arancelaria y Derechos de Exportacio ´n) and, from 1991 to 2006, the Harmonized System. Concardances between these two nomenclatures had to be manually built, as well. Trends in export taxes are reported in Fig. 7. The solid line shows averages across all sectors and the broken lines are the 5th and 95th percentile of the export tax Fig. 7 Average export taxes. Source: Argentine trade policy data collected by the authors. See text Lat Am Econ Rev (2018) 27:4 Page 19 of 30 4 123 rates. These are not intended to be confidence bands for the mean, but to give a sense of the extreme values applied in practice. The first salient feature of our data is the presence of long episodes of active policies of export taxes in the recent past, an undeniable manifestation of the antiexport bias. The second salient feature is that the intensity of taxation varies and that export taxes do not follow a clear trend over time. As we will see, they depend, to a large extent, on the Presidency in office and on its attitude towards free trade, exports, and the distributive conflict. From a relatively low base in the early 1970s, export taxes reached a peak of nearly 15% in the mid-1970s. During this early period, many sectors enjoyed no taxes (the 5th percentile is zero, for instance, from 1970 to 2001), but others were hit very hard with tax rate peaks of over 40% in the mid-1970s. These are high rates by almost any standards. Export taxes were reduced significantly at the end of the 1970 and early 1980s, when the Military was in power. Instead, they increased with the advent of Democracy in 1983. However, while the average export tax remained positive throughout all the 1980s, both these averages and the extreme values never reached the higher levels of the mid-1970s. A striking change occurs in the 1990s. Consistent with the liberalization period of Menem and Cavallo, export taxes were completely eliminated and the sector remained fully liberalized until the Presidency of Kirchner, when export taxes were actively utilized again. They remain in heavy use today. Moreover, it is interesting to note that while historically there have been sectors with zero taxes (see 5th percentile), after 2002, all sectors faced positive export taxes. The trends in averages clearly mask lots of details. Export taxes in Argentina tend to be concentrated in a few sectors at very high levels. The agricultural sector has been traditionally the most taxed sector throughout time along with mineral products. We explore this in Figs. 8and 9. There are six panels in each Figure. Each panel compares the Agricultural sector (broken line) with other major sectors (solid line). In Fig. 8, we see that the Agricultural sectors fared very badly relative to Chemicals, Plastics, Textiles, Footwear, Machinery, and Transport, all sectors with very low levels of taxation. The comparison sectors in Fig. 9are instead sectors that face some level of export taxes. While the Agricultural sector is still more heavily taxed, all sectors show positive taxes and, in addition, show similar trends in time. An additional piece of evidence that shows the hurdles faced by the agricultural sector is given in Table 8. We counted the numbers of years, from 1966 to 2006, in which each sector had positive export taxes. Interestingly, the Agricultural sector and Processed Food (together with Chemicals) faced positive export taxes for 33 out of 40 years. In contrast, Footwear, Machinery, and Transport are among the leastoften taxed sectors, with 7 and 13 years, respectively. While the overall anti-export bias in undeniable, there are interesting differences within agriculture. To see this, we plot the trends in average export tax for the four most important sectors in agriculture, Cereals and Oil Seeds, Dairy, and Meat in Fig. 10. Clearly, export tax rates within the agricultural sector move in accordance with the general tendency described above. However, Cereals and Oil Seeds were often taxed at a much higher rate than Dairy and Meat. In the peak of the mid-1970s, 4 Page 20 of 30 Lat Am Econ Rev (2018) 27:4 123 Fig. 8 Average export taxes at 2-digit groups. Source: Argentine trade policy data collected by the authors. See text Fig. 9 Average export taxes at 2-digit groups. Source: Argentine trade policy data collected by the authors. See text Lat Am Econ Rev (2018) 27:4 Page 21 of 30 4 123 the average export tax on Cereals and Oil Seeds was close to 40%, while it was 10% for Dairy and 20% for Meat. In contrast, the most recent export tax intervention of the 2000s had heavily affected Dairy, as well. It is important to notice that, within these high averages, there are individual products that faced extreme tax rates; a notorious case is soybeans (in the Oil Seeds group) with current tax rate of 35%. 9 The combination of export taxes liberally applied, especially on the agricultural sector, and a significant protection granted to the manufacturing sector are the result of the distributional conflict outlined in Sect. 3. In the end, Argentine trade policy shows a clear anti-export, anti-agriculture bias. Table 8 Number of years with positive export taxes 1966–2006. Source: Argentine trade policy data collected by the authors. See text Sector Years Agro 33 Processed Food 33 Chemical 33 Leather 30 Wood 28 Textiles 28 Mineral 26 Metals 26 Transport 26 Stone 24 Plastics 17 Footwear 13 Machinery 7 Fig. 10 Agricultural groups. Source: Argentine trade policy data collected by the authors. See text 9 In 2006, when our data end, taxes on soybeans are ‘‘only’’ 22.5%. 4 Page 22 of 30 Lat Am Econ Rev (2018) 27:4 123 5 Some of the consequences In this section, we briefly discuss some of the consequences of Argentine trade policies. Since these policies have numerous impacts on various outcomes, it is impossible to provide a comprehensive assessment. Instead, we present evidence to support the broad claims of our analysis: i) the historical debacle of Argentina can in part be explained by bad trade policies; and ii) their manifestation is a marked antiexport bias and an inefficient import substitution model. 10 5.1 Agriculture To document the implications of trade policies on agricultural performance, we explore here various outcomes, including the volume of exports and the share of Argentine agricultural production on world production, an index of agricultural production, and the performance of yields in Argentine agriculture (vis-a ´-vis the US). In Panel a) of Fig. 11, we show the evolution of Argentine exports (largely composed of agricultural exports—both primary products and agro-manufactures). Exports grew steadily until the late 1930s and early 1940s, when, concurrently with the IS model, they plummeted. Exports recovered in the 1980s and early 1990s, and after the mid-1990s, they skyrocketed, especially due to technology adoption in agricultural. Panel b) of Fig. 11 uncovers interesting features of these trends. We report the share of corn, wheat, and soybean production of Argentina in world production. We see that the shares of corn and wheat grew steadily from the early 1900s until around the 1930s. The shares abruptly collapsed in the late 1930s and early 1940s up until around the 1950s. From the 1950s to the 2000s, the production shares of corn and wheat stagnated: they showed a slightly increasing trend from 1950 to the mid-1970s, a slightly declining trend from the 1970s to the 1990s, and a slightly increasing trend in the 1990s. The trends in the production shares of soybeans are different. Soybeans were only adopted in Argentina in the 1972–1973, almost 20 years later than in the US. The story, told by Reca (2007), gives an interesting portrait of Argentine history. Whereas soybean production had been heavily encouraged in the US since the 1930s, the Argentine agricultural sector always resisted its adoption and the Argentine government never took actions to promote it—it was considered an ‘‘exotic plant.’’ The scenario changed in 1972–1973, only by chance. Argentina used to import balanced animal feed from fish flour produced in Peru (from the ‘‘anchoveta peruana,’’ a type of anchovies). A change in sea currents in the Pacific Ocean caused a disruption in anchoveta production in 1972 and a scarcity of balanced feed in Argentina. As a result, soybeans were finally adopted in 1973–1974 after a joint initiative of the balanced feed industry and the Argentine Secretary of Agriculture. Soon after adoption, Argentina became a major producer, at an increasing rate. With the exception of a small dip at the end of the 1990s, the 10 See the chapter by Lucas Llach (2009) in this volume for a detailed account of the relative performance of Argentina vis-a `-vis other countries. Lat Am Econ Rev (2018) 27:4 Page 23 of 30 4 123 share of Argentine soybean production in world production has been increasing continuously, reaching over 15% in the 2000s. To further illustrate the performance of the agricultural sector, we built an index of Cattle, Corn, Soybean, and Wheat Production in Argentina for the 1914–2007 (a) (b) Fig. 11 Evolution of Argentine agriculture. Source. Panel a): CEPAL (ECLAC) office in Buenos Aires. Panel b): Owncalculations based on Ferreres (2005) until 1960, and FAOSTAT from 1961 to2006 4 Page 24 of 30 Lat Am Econ Rev (2018) 27:4 123