The Brazilian productive structure and policy responses in the face of the international economic crisis: An assessment based on input-output analysis

Accepted Manuscript Title: The Brazilian productive structure and policy responses in the face of the international economic crisis: an assessment based on input-output analysis Author: Roberto Alexandre Zanchetta Borghi PII: DOI: Reference:

S0954-349X(17)30236-9 http://dx.doi.org/10.1016/j.strueco.2017.08.001 STRECO 670

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Please cite this article as: Zanchetta Borghi, Roberto Alexandre, The Brazilian productive structure and policy responses in the face of the international economic crisis: an assessment based on input-output analysis.Structural Change and Economic Dynamics http://dx.doi.org/10.1016/j.strueco.2017.08.001 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

The Brazilian productive structure and policy responses in the face of the international economic crisis: an assessment based on input-output analysis

Roberto Alexandre Zanchetta Borghi1 Given Name: Roberto Alexandre Family Name: Zanchetta Borghi Affiliation address: University of Cambridge Centre of Development Studies St Edmund’s College, Mount Pleasant, Cambridge/UK, CB3 0BN Email: [email protected] Phone number: +55-19-996261545 Highlights 

Post-2008 Brazilian policies comprised different instruments and several sectors.

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Input-output analysis assesses the potential role of sectors in economic recovery.

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Industrial sectors present stronger linkages but are losing ground in the economy.

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There is more evidence for supporting some of the benefited sectors than others.

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Sustained recovery requires industrial development to tackle external constraints.

Abstract This paper addresses the Brazilian productive structure and the major economic policies undertaken in the face of the international economic crisis. Input-output techniques are applied to Brazilian national accounts and present a picture of the potential role of different sectors in the recovery of the economy. Considering the country’s economic performance at the time, post-2008 economic policies adopted in Brazil are discussed, with emphasis given on the tax break policy, inserted into a broader policy scope. Results show that industrial sectors have stronger linkages in terms of production and employment maintenance in the economy but have been losing ground in the productive structure. Among them, there is evidence in favour of supporting more some sectors, such as the automobile and the construction industries, rather than others, such as white goods appliances and furniture, but especially the need of recovering industrial development as a whole for sustained economic growth.

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Permanent address: Av. Nossa Senhora de Fátima, 805, apt. Acapulco 91, Campinas/SP, Brazil, 13076903.

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Keywords: Brazilian productive structure; industrial sectors; international crisis; economic policies; input-output analysis. JEL Code: D57; E65; O25; O54.

1. Introduction The Brazilian economy experienced an important growth cycle between 2004 and 2008. The economy grew, on average, 4.8% per year in real terms2. International conditions contributed to the growth cycle as well as domestic changes in economic policy orientation. From the international perspective, the recovery of international liquidity, the increasing commodity prices and the rising Chinese demand for commodities in the early 2000s were among the key factors that made huge trade surpluses and capital inflows possible for Brazil, resulting in large foreign reserves accumulation. From the domestic perspective, changes in economic policy towards consumption, investment and income distribution enlarged the potential of domestic demand to grow. Major policy changes included: (a) the expansionary monetary policy that reduced interest rates although they still remained one of the highest in the world; (b) the credit expansion that lower interest rates caused, together with the deliberate policy that the Brazilian National Development Bank (BNDES) adopted to support investment growth in a recognition of industrial policy as an important instrument for promoting economic growth; (c) infrastructure, investment and industrial programmes, such as the National Programme for the Acceleration of Growth (PAC) and the Industrial, Technological and Foreign Trade Policy (PITCE); (d) the strong and systematic increase in real minimum wages as well as formal employment creation in large scale; and (e) the expansion of income transfer programmes, such as “Bolsa Família”, benefiting poor families and regions. Macroeconomic policy, however, was attached to the inflation targeting regime, governmental budget surpluses and floating (but managed) exchange rates, policies adopted in Brazil since 1999. They coexisted in the mid-2000s with the efforts to implement industrial and social policies. Favourable international conditions and the combination of credit expansion, real income gains and intense employment creation resulted in increasing prospective demand and higher expectations for both private investments and domestic consumption. Once made, investment and consumption decisions reinforced the boom in the business cycle. At the same time, nonetheless, high inflows of foreign resources from both capital inflows and high exports, mostly of primary goods, led to a strong appreciation of the national currency over the period. While, on the one hand, overvalued currency contributed to a rise in real wages and a boost to domestic consumption, on the other, it started to increasingly affect the competitiveness of the domestic industry through rising imports of industrial goods and, therefore, challenge the continuity of domestic economic growth. This structural imbalance regarding the industrial sector was partially hidden during Brazil’s booming phase, as industry was growing fast to meet domestic demand and external accounts were benefited by high commodity exports and capital inflows. The 2

Data from the Brazilian Central Bank, available at: http://www.bcb.gov.br/ (Accessed in: June 2016). See also Figure 1 of this paper in section 4.

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economy was growing, most people were employed, and income inequality was declining. The imbalance would become clear, however, after the outbreak of the international economic crisis in 2008. The reversal of international conditions in the following years would reveal the rising external constraints on growth. The international economic crisis severely affected Brazil’s growing economy at the end of 2008 and especially in the following year. In response to the economic downturn, the Brazilian government adopted several countercyclical policies to address the maintenance of domestic output and employment levels. Most policies were implemented in two rounds: in 2008/2009 as a response to the world recession, and in 2011/2012 as an attempt to face the economic turmoil related to the low domestic dynamism and the negative international conditions. One of the most immediate policy responses was the implementation of tax reduction on several industrialised goods, comprising different sectors, such as the automobile, construction and white goods appliances industries. These measures were aligned with the new sets of industrial policy, the Productive Development Policy (PDP) and the “Brasil Maior” Plan, which were implemented in 2008 and 2011, respectively. Several stimuli, including broader tax exemption, were offered to a large pool of industries based on various instruments and criteria at different moments after 2008. There was also credit expansion led by public commercial banks and the BNDES towards the government housing policy, the restructuring of private companies incurring losses during the crisis, and the financing of new investments. Among other initiatives, the government began to impose taxes on capital inflows, in order to control currency appreciation and volatility. From a Keynesian perspective, demand stimuli, e.g. by means of tax reduction and credit expansion, may positively impact the economy as a whole, given the multiplier effects of initial stimuli to some sectors on the economic structure (Keynes, 1936). In addition, from a Hirschmanian perspective, multiplier effects depend on the productive structure and the relative importance of particular sectors, whose linkages with other sectors may lead to greater effects from initial stimuli (Hirschman, 1958). Initial countercyclical policies took these arguments into consideration and were successful in boosting the overall economy in 2010, shortly after the economic slump in the year before, when negative GDP growth was registered. However, the deterioration of both external and domestic conditions put the economy back into a situation of low dynamism thereafter. Other rounds of the same stimuli did not prove as effective as before. What the aforementioned countercyclical policies mostly neglected was the low competitiveness of the industrial sector combined with the rising external constraints on growth. From a Keynesian perspective, à la KaldorThirlwall, the external sector plays a crucial role in securing a sustainable recovery from the crisis. Policies aimed at demand recovery and employment expansion cannot ignore the behaviour of the current account, especially given the constraints it may pose on sustaining growth in difficult times of the international markets (Kaldor, 1966 and 1971; Thirlwall, 1979 and 2002; McCombie and Thirlwall, 2004). This paper discusses the Brazilian productive structure and its compatibility with major economic policies undertaken in the face of the international economic crisis. Inputoutput methodology is used to present a picture of the importance of different sectors in

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the domestic productive structure and, therefore, their potential role in the recovery of the economy. 56-sectors 2008 make and use tables for the Brazilian economy, released by the Brazilian Institute of Geography and Statistics (IBGE), are applied to estimate the input-output matrix for the year when most policy decisions were made at the first time since the crisis had started. Output and employment multipliers, employment generator, Hirschman-Rasmussen backward and forward linkages as well as backward, forward and total normalised pure linkages are calculated, in order to identify the leading economic sectors of the Brazilian economy, i.e. those sectors with stronger linkages in terms of production and employment maintenance in the economy. Complementary data on Gross Domestic Product (GDP) growth by major economic sectors, industrial share in total GDP and external accounts are also used. This analysis allows for an assessment of policies adopted for economic recovery, and results could prove useful in shaping different economic policies, such as fiscal and industrial policies, to promote growth and employment. The paper is divided into three sections. The first section addresses the post-2008 economic policies adopted in Brazil, with emphasis given on the tax break policy, inserted into a broader policy scope, in response to the international crisis. The second section presents a methodological revision of the literature on input-output matrices as well as the indices applied to the analysis. The third section discusses key features of the Brazilian productive structure based on the previous indicators. Concluding remarks follow. 2. Brazilian economic policies in the face of the international economic crisis Brazilian economic policy response to the international economic crisis was relatively quick and comprised a set of instruments of different nature – fiscal, industrial, credit, monetary, and social – over the years to contain the negative effects of the international crisis on the domestic economy. These policies aimed at securing the levels of output and employment in the economy, and as a whole were successful during the first years3. This section discusses the major directives implemented on each area, giving particular emphasis on the fiscal-industrial initiatives of tax exemption on several industrialised goods of different sectors. Policy response came more rapidly from fiscal policy decisions. The reduction of the value-added tax (VAT) on industrialised goods4 was one of the broadest and most immediately implemented measures aiming at stimulating demand, particularly final consumption, and therefore restoring production and employment levels in the Brazilian economy. The three most favoured sectors at the beginning of this policy were the automobile, construction and white goods appliances industries. Subsequently, capital goods and furniture industries were also included.

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Quarterly national account data point to a GDP growth of 9.3%, 8.8%, 6.9% and 5.3% in the first, second, third and fourth quarters of 2010 in relation to the respective quarters of the year before. The more significant results in the beginning of the year were, to a large extent, related to the basis of comparison, since the economic performance in 2009 was already improving at the end of the year, making the economic recovery observed in the beginning of 2010 more expressive in comparison with the one observed at the end of the year. Data available at: http://www.ibge.gov.br/home/ (Accessed in: January 2014). 4 The acronym in Portuguese for the tax on industrialised goods is IPI (“Imposto sobre Produtos Industrializados”).

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As most of other policies, this policy was implemented in two rounds in recent years: in 2008/2009 as a prompt response to the world recession, and in 2011/2012 as a further attempt to face the economic turmoil associated with a slowdown in the domestic economy and the negative international conditions, especially coming from the Euro area and the reversal of commodity prices. The policy may be understood not only as a fiscal stimulus by reducing tax rates on particular goods, but also as a part of broader industrial initiatives undertaken by the Brazilian government at the same time, given that sectors benefited from different and combined fiscal and monetary stimuli. The two main industrial programmes were the Productive Development Policy (PDP) and the “Brasil Maior” Plan, respectively implemented in 2008 and 20115. Stimuli offered to various industries included, among other instruments, wide tax exemption, of not only the aforementioned VAT reduction but also of other levies and subsidies on different types of goods, as well as the expansion of credit lines, especially of BNDES, to industries under certain criteria aiming at enhancing investment, export, innovation, and energy efficiency levels. The adoption of the new automotive regime, as discussed below, illustrates some of these concerns during the second round of policy implementation and shows how tax policy was framed by a broader scope of initiatives. For the automobile sector6, a differentiated policy on tax reduction regarding various types of vehicles (e.g. passenger cars up to 1,0 engine, from 1,1 to 2,0 engine and light commercial vehicles) and fuels (e.g. ethanol or dual-fuel and petrol) was established in December 2008. VAT changes for different vehicles lasted, after several extensions, until the early 2010, when tax rates returned to their previous original levels. Initially planned to stand until March 2009, reduced tax rates were extended until June and, then, September 2009, when it was decided that they should return gradually through monthly increases until January 2010 to their levels prior to the crisis. For ethanol or dual-fuel vehicles, the tax rate returned to the previous original level in April 2010. The second round of this policy to the automobile sector involved new tax reductions and policy extensions valid from May 2012, and was in conformity with the new automotive regime. According to the new automotive regime, launched in September 2011 and valid from December 2011 to December 2012, carmakers should use at least 65% of national or regional content in vehicle manufacturing, besides investing in research and development and making at least 6 of 11 productive stages in the country. A 30-percentage point increase in tax rates would apply on all vehicles not aligned with the new regulation. In October 2012, as part of the industrial, technological and foreign trade directives expressed in the “Brasil Maior” Plan, the “Inovar-Auto” (“Programme of Incentive to the Technological Innovation and the Intensification of the Productive Chain of Automotive Vehicles”) was implemented. It established new rules for the sector during the period between 2013 and 2017. Companies should accomplish 3 out of 4 On these plans, see CNI (2009) and ABDI (2014). Other detailed information on the “Brasil Maior” Plan at: http://www.brasilmaior.gov.br/ (Accessed in: June 2016). 6 For details of the evolution of the policy for this sector, see federal decrees n. 6,687 of December 11, 2008, n. 6,809 of March 30, 2009, n. 6,890 of June 29, 2009, n. 7,017 of November 26, 2009, n. 7,660 of December 23, 2011, n. 7,716 of April 3, 2012, n. 7,725 of May 21, 2012, n. 7,879 of December 27, 2012, and n. 8,168 of December 23, 2013. See also Anfavea (2010), Galvão (2009), Valor Econômico (2009), Prado (2012), Martello (2012) and Beck (2013). 5

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prerequisites to deduct the 30-percentage point VAT increase. The rules were: (i) to invest at least 0.15% of the gross operating income in innovation in 2013, which would increase up to 0.5% until 2017; (ii) to invest at least 0.5% of the gross operating income in engineering, which would rise up to 1% until 2017; (iii) to make 8 of 12 productive stages of light vehicles and 10 of 14 productive stages of heavy vehicles in the country, which would increase to 10 of 12 and 12 of 14 productive stages until 2017 for light and heavy vehicles, respectively; (iv) to improve the level of energy efficiency of vehicles following Brazilian patterns of energy-save for 25% of manufactured vehicles in 2013 and 100% of vehicles in 2017. The construction industry had the VAT rate on many of its goods reduced to zero from April 2009 onwards. Such was the case for the following construction materials: cement, paint and varnish, mortar and concrete for construction, non-coated steel gratings for mortar or concrete structures or works, non-refractory overlays, hinges, baths, shower cabins, sinks, and electric shower. Other construction materials also had VAT reduction, such as concrete additives, putty, painting apparel, and circuit breakers. As it occurred in the automobile industry, the fiscal incentive was extended for several times, including in June 2009, December 2010, August 2011 and December 20127. The construction sector was not only benefited by tax exemptions but also by other policies, in particular credit-social policy. The government launched in March 2009 the programme “Minha Casa, Minha Vida”, a government-subsidised housing programme aiming at building new houses that could be financed by households with monthly household income up to R$ 1,600.00. Houses were financed by the public commercial bank Caixa Econômica Federal. After the programme extension, households with monthly income up to R$ 5,000.00 also became eligible for credit and public loans were expanded. The goal was to build 2.4 million new houses until 2014. This programme was an important drive to stimulate the construction sector during the crisis, in addition to the social objective of providing home for many people8. The industry of white goods appliances also had the VAT reduced in April 2009, as part of the efforts to stimulate final demand and avoid unemployment. The VAT reduction policy for the sector was extended in June and once again in October 2009, when more energy-efficient goods obtained a higher tax exemption. Reduced tax rates ranging between 0% and 20% according to the type of good stood until January 2010, when tax rates returned to their original levels. By the end of 2011, the government adopted a second round of the tax reduction policy on goods related to this sector. The aim was to maintain domestic activity in the face of the adverse international landscape. At this time, however, the incentive was implemented for energy-efficient appliances only. The policy was extended in March 2012, and tax rates were gradually increased in February, July and October 2013, but they still lasted thereafter at a lower level in comparison with original levels9.

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See Salles (2009) and federal decrees n. 6,809 of March 30, 2009, n. 6,890 of June 29, 2009, n. 7,394 of December 15, 2010, n. 7,542 of August 2, 2011, and n. 7,879 of December 27, 2012. 8 More details about the programme are available at: http://www.caixa.gov.br/ and http://www.cidades.gov.br/index.php (Accessed in: January 2014). 9 See federal decrees n. 6,825 of April 17, 2009, n. 6,890 of June 29, 2009, n. 6,996 of October 30, 2009, n. 7,660 of December 23, 2011, n. 7,705 of March 25, 2012, and n. 8,035 of June 28, 2013. See also Goy et al. (2009), Martello (2012) and Beck (2013).

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Other sectors were also benefited by similar tax policies but not as promptly as the aforementioned industries, whose benefits started either in the end of 2008 or in the early 200910. The furniture industry was benefited by VAT reduction in November 2009. The policy initially lasted only until March 2010. Tax rates on wood, steel and plastic furniture as well as on pieces of wood used in furniture manufacturing were reduced to zero, while other goods, such as wallpaper, lamps and lampshades, had also their tax rates partially reduced. This initiative was repeated a second time in April 2012 and, as in the case of white goods appliances, several extensions were applied with slight increases in tax rates in February, July and October 2013, besides January 2014, although still remaining at a reduced level11. The sector of capital goods was also granted tax exemption on more than 70 items used in manufacturing. The measure started in the mid-2009. Planned to last until December 2009, it was extended several times, until June 2010, December 2010, December 2011, December 2012, December 2013, and June 2014, when the government decided to permanently reduce to zero the VAT on capital goods, such as trucks, buses, machines and other equipment used for production12. In addition to the VAT measure, the sector of capital goods was benefited by the “Investment Maintenance Programme” (PSI), a BNDES programme established in July 2009 aiming at offering long-term credit to local producers for their purchases of capital goods and machinery, as well as export and innovation financing. This initiative also favoured the automotive sector, as it covered the acquisition of heavy vehicles. Credit lines were offered at subsidised interest rates, even lower than those of conventional BNDES programmes for acquisition of capital goods, such as BNDES Finame. As other policies, the PSI was extended repeatedly at the end of every year since 2009. It had a positive impact on investment recovery in the early stages but its effectiveness seemed to have decreased over time. In 2015, under political turmoil and severe governmental budget constraints, stricter rules were applied to the programme, including reduced amount of resources and higher interest rates. It lasted until December 201513. Credit expansion by public commercial banks and the BNDES was an important instrument to stimulate the economy, especially in the light of the credit crunch faced by financial markets shortly after the outbreak of the international crisis in 2008. Public banks Banco do Brasil and Nossa Caixa, for example, offered R$ 8 billion to carmakers’ finance companies in November 2008 in order to encourage vehicle financing operations. Caixa Econômica Federal, another large public bank, expanded loans following the government housing policy previously discussed. BNDES raised credit lines, not only introducing the PSI but also reducing long-term interest rates on other loans and programmes. BNDES also played a key part in the restructuring of private companies that were facing severe financial constraints once unable to refinance their debts at the market, given the 2008 credit crunch. Several companies made big 10

There was, for example, the reduction to zero of other levies, such as the Social Integration Programme (PIS) and the Contribution to the Financing of Social Security (COFINS) on wheat, flour and bread from the mid-2009 to the end of 2010 (Galvão, 2009). 11 See federal decrees n. 7,017 of November 26, 2009, n. 7,705 of March 25, 2012, n. 8,035 of June 28, 2013, n. 8,116 of September 30, 2013, and n. 8,169 of December 23, 2013. See also Lima (2009), Martello (2012) and Beck (2013). 12 See federal decrees n. 6,890 of June 29, 2009, n. 7,017 of November 26, 2009, n. 7,222 of June 29, 2010, n. 7,394 of December 15, 2010, and n. 7,543 of August 2, 2011. 13 See more on the PSI at Machado et al. (2014), Soto (2015b) and Martello (2015).

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losses, especially from foreign exchange derivatives as the national currency strongly devalued at the outbreak of the crisis, and as a result were in urgent need of funding14. No longer after the sharp devaluation, the national currency was again rapidly appreciating. In order to control further currency appreciation and volatility, the government imposed capital controls, as from 2009 capital inflows to the country were already rebounding. Brazil reinstated the tax on financial transactions (IOF) on portfolio equity and debt inflows in October 2009, increasing it twice on debt inflows a year later, in October 2010, when also extended to derivatives markets. In 2011, reserve requirements were imposed on banks’ short foreign exchange positions in the cash market. However, at the time the policy was implemented the exchange rate had almost returned to pre-crisis levels, thus limiting the policy effectiveness in alleviating appreciation pressures15. The exchange rate remained overvalued until 2012. A devaluation process started thereafter at gradual pace, because of changing international conditions and reduced capital inflows, but escalated after mid-2014 in the light of rising political turmoil and uncertainty in the country until its peak in the early 201616. Monetary policy did not respond as promptly as fiscal stimuli and credit expansion to the beginning of the crisis. In comparison to other economies, particularly developed economies, where interest rates were quickly reduced to near 0% levels, the Brazilian Central Bank took considerable time to adopt an expansionary monetary policy. The annual basic interest rate (Selic) in Brazil remained at 13.75% until the end of 2008. There were two rounds of decreasing interest rates afterwards. The first round started in 2009 and Selic rate went down to 8.75% per year by July 2009. This level was maintained until April 2010, when due to economic recovery and fears of inflationary pressures a new cycle of rising interest rates began. By July 2011, the annual interest rate was back to a 12.5% level. The worsening of domestic and international conditions triggered new policy packages to face the crisis, as already mentioned, and new reductions of the interest rate in a movement accompanied by public banks. The annual interest rate achieved the lowest level of 7.25% in October 2012 but it was not sustained for long. In April 2013, monetary authorities decided to increase interest rates again, initiating a long process of rising interest rates that reached 14.25% per year by July 2015 in a moment of deep economic slowdown and governmental budget deficits17. The speedy recovery of domestic demand after the outbreak of the crisis counted not only on fiscal, industrial, credit and monetary stimuli but also on the continuity of social policies. The maintenance of previous important initiatives, such as income transfer through the “Bolsa Família” programme as well as systematic increases in minimum wages, also contributed to sustain consumption levels, preventing the economy from negative effects of the crisis in the early stages. The launch of new programmes, such as the housing programme “Minha Casa, Minha Vida”, also played a part both in stimulating sectoral activity and in generating employment and income in the economy. However, as other policy measures, despite contributing to offset immediate drop in 14

See Resende (2008) and Farhi and Borghi (2009). See more details at IMF (2011). 16 For a long series of the exchange rate, see the Brazilian Central Bank data at: http://www.bcb.gov.br/ (Accessed in: June 2016). 17 See the Brazilian Central Bank data on the annual basic interest rate at: http://www.bcb.gov.br/Pec/Copom/Port/taxaSelic.asp (Accessed in: June 2016). See also Modenesi et al. (2012) and AKB (2013) for more on the monetary policy and other economic policies of the period. 15

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economic activity in the face of the crisis, they were unable to sustain a long-term recovery. Finally, as part of fiscal stimuli implemented at later stages, a payroll tax break reduction covering several sectors was adopted from 2011 onwards. The 20% social security levies that companies were used to pay on their annual payroll were changed to 1.5% or 2.5% social security levies on companies’ gross revenues, depending on their sectoral activity. Levies were further reduced to 1% and 2% for most industrial and services sectors, respectively. In 2015, the government started to revert the reduction of some payroll tax breaks, given the country’s widening budget gap. Social security levies on companies’ gross revenues were increased to 2.5% and 4.5% for companies paying, respectively, 1% and 2% contributions before. The measure was part of the initiatives of the “Brasil Maior” Plan implemented in 2011 and expanded thereafter as some of the efforts to jumpstart the Brazilian economy under adverse conditions. However, as other subsidies and tax exemptions, it implied lower tax revenues, particularly when economic activity was no longer responding accordingly to fiscal stimuli, leading to fiscal deficits and a reversal of most previous countercyclical policies18. 3. Input-output theoretical framework and methodology This section discusses first the theoretical framework based on the input-output analysis that is used subsequently to address the identification of leading economic sectors in the Brazilian productive structure in terms of output and employment. This theoretical part is followed by a discussion of methodological issues of estimating the Brazilian inputoutput matrix for 2008. 3.1. Theoretical framework The theoretical framework of this study is based on the input-output analysis (Leontief, 1941). According to this approach, total output in the economy (X) can be expressed as the sum of output for intermediary consumption of different sectors (Z) and for final demand (Y). The matrix of interindustry flows (Z) and the total output allow for the calculations of the matrix of technical coefficients (A). The technical coefficient ( aij ) measures, in monetary terms, how much of goods the sector j has used from the sector i for its total output. In other words, it shows the proportion of inputs purchased by sector j from sector i in relation to the total output of sector j, as expressed in (1). Z ij (1) aij  Xj It follows that: X  AX  Y

(2)

The solution to this equation gives the total output necessary to meet the final demand: 1 (3) X  I  A Y where I  A1  L is known as the Leontief inverse or the total requirements matrix.

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On the payroll tax break policy, see Dias (2015) and Soto (2015a).

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From the Leontief model, several impact analyses can be made in order to measure the effects of changes in demand on output, employment, value-added, among other variables. The direct coefficient (k) for each of these variables is given by the ratio between the value of the variable K used for generating the total output of each sector and the total output of the corresponding sector, as follows: Kj (4) kj  Xj From these direct coefficients expressed in a diagonal vector ( kˆ ) and the Leontief inverse (L) it is obtained, by sector, the total amount directly and indirectly generated of variable K for each monetary unit produced for final demand. This is the idea of generator, which relates the output for final demand to a given variable in the economy. Hence, the generator of a variable K for each sector can be calculated through the sum of each column of the matrix GK obtained as shown by (5). GK  kˆ  L (5) The ratio between the generator of each sector and its respective direct coefficient gives the sectoral multiplier of variable K. The multiplier relates the direct effect of a given variable on its total (direct and indirect) effect in the economy, as equation (6) shows. (6) MK j  GK j k j Based on this, the output multiplier, the employment multiplier and the employment generator can be calculated19. For the purposes of this paper, only multipliers of type I are used. Their effects consider only the linkages between sectors as a response to interindustry demand, i.e. they do not deal with household consumption as endogenous to the model20. The input-output model allows, additionally, for calculations of other indicators highlighting the linkages between sectors and the linkage power of each sector in the economy, such as Hirschman-Rasmussen backward and forward linkages as well as backward, forward and total normalised pure linkages21. The analysis of these indices contributes to the assessment of key sectors in the economy22. Whilst the term forward linkage is used to indicate the interconnection of a particular sector with sectors to which it sells its output, i.e. how much of its output is demanded by other sectors, the term backward linkage refers to the interconnection of a particular sector with those sectors from which it purchases inputs, i.e. it measures how much a sector demands from other sectors in the economy.

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Output multiplier and output generator are identical. Consequently, the output multiplier for each sector can also be obtained by the sum of each column of matrix L. It indicates, for each sector, the amount of production directly and indirectly generated in the economy for each unit of final demand. The bigger the multiplier of one sector in comparison to the multipliers of other sectors is, the greater its impacts on the rest of the economy will be, thus pointing to its importance to stimulate total output. 20 With household consumption as endogenous to the model, multipliers of type II would be obtained as they would include the income or induced effect (Miller and Blair, 2009; Guilhoto, 2009). 21 About these indices, which are presented below, see Miller and Blair (2009), Guilhoto and Sesso Filho (2005), Guilhoto (2009), and Liu et al. (2010). 22 McGilvray (1977) discusses the notion of key or leading sectors in the economy, which may consider its insertion into a broader aim of economic policy in the face of the needs at each time.

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Considering the elements lij of matrix L and defining L* as the average of all elements of L and L* j as the sum of a column of L, the Hirschman-Rasmussen backward linkage can be calculated as:

BL j  L* j n L*

(7)

For the calculation of the forward linkage index it is used the direct-output coefficients matrix (F), which consists of allocation coefficients (as opposed to technical coefficients) obtained from the matrix of interindustry flows (Z) as expressed in (8). Instead of dividing each column of Z by the total output of the sector associated with that column, each row of Z is divided by the total output of the sector associated with that row. (8) F  xˆ 1  Z Similar to the calculation of the Leontief inverse, the Ghosh matrix or output inverse (G) can be obtained: (9) G  ( I  F ) 1 Considering the elements g ij of matrix G and defining G * as the average of all elements of G and Gi* as the sum of a row of G, the Hirschman-Rasmussen forward linkage can be calculated as: (10) FLi  Gi* n G * According to Miller and Blair (2009), sectors could be distributed over a four-way classification depending on their backward and forward linkage results as: (a) generally independent of (or not strongly connected to) other sectors, when both linkages measure less than 1; (b) generally dependent on (or connected to) other sectors, when both linkages measure greater than 1; (c) dependent on interindustry supply, when only the backward linkage is greater than 1; and (d) dependent on interindustry demand, when only the forward linkage is greater than 1. It is important to highlight, however, that Hirschman-Rasmussen indices do not consider the size of the sector in the economy represented by its different levels of production. Such approach is made by the GHS methodology, which results from a number of decompositions of the Leontief inverse (Guilhoto, 2009). Considering the block matrix of technical coefficients (A), as shown by (11), composed of square matrices of direct technical coefficients of sector j and of the rest of the economy ( A jj and Arr , respectively), and of rectangular matrices of direct inputs purchased by sector j from the rest of the economy and of direct inputs purchased by the rest of the economy from sector j ( Arj and A jr , respectively), it is possible to decompose the Leontief inverse as in (12).  A jj A  Arj

A jr   Arr 

(11)

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 L jj L  ( I  A) 1    Lrj

L jr   jj  Lrr   0

0   j  rr   0

0  I   r   Arj  j

A jr  r  I 

(12)

where

 j  ( I  A jj ) 1

(13)

 r  ( I  Arr ) 1

(14)

 jj  ( I   j A jr  r Arj ) 1

(15)

 rr  ( I   r Arj  j A jr ) 1

(16)

From (3) and (12), it follows that:  X j    jj      Xr   0

0   j Y j   j A jr  r Yr     rr   r Arj  j Y j   r Yr 

(17)

This process gives the pure backward and forward linkages (PBL and PFL, respectively): PBL   r Arj  j Y j

(18)

PFL   j A jr  r Yr

(19)

The PBL indicates the impact of sector j’s total output on the rest of the economy, regardless of the input demand that sector j produces for its own use or requires from other sectors, and vice-versa. The PFL indicates the impact of total output of the rest of the economy on sector j. It is possible as well to calculate the pure total linkage (PTL) as the sum of PBL and PFL expressed in current values: (20) PTL  PBL  PFL Dividing the pure linkages of each sector by the average value of pure linkages in the economy as a whole, one may find the normalised pure linkages in order to compare sectors given their relative size in the economy. Backward (PBLN), forward (PFLN) and total (PTLN) normalised pure linkages can be calculated as follows:  n  (21) PBLN i  PBLi   PBLi n   i 1   n  (22) PFLN i  PFLi   PFLi n   i 1   n  (23) PTLN i  PTLi   PTLi n   i 1  3.2. Methodology For the purposes of this study, 56-sectors 2008 make and use tables for the Brazilian economy, released by the Brazilian Institute of Geography and Statistics (IBGE), are employed to estimate the Brazilian input-output matrix for the year when countercyclical policy decisions started to be made at the first time since the beginning

12

of the crisis23. As the use table is at consumer prices, it is necessary to deduct from its values the respective margins of commerce, transport, net taxes of subsidies, imports and import taxes in order to achieve the national supply at basic prices. In this regard, it is used the methodology of Guilhoto and Sesso Filho (2005), which provides coefficients establishing a link between the value of good i sold to each sector or each component of final demand j at market prices and the total value of good i sold to all sectors and components of final demand in the economy. These coefficients allow for distributing over the matrix the values of aforementioned variables so that they can be deducted from consumer prices. It should be noted that values for imports and import taxes may not be allocated to exports. Their coefficients are calculated in a similar way, but only deducting exports from total demand before distributing over the matrix. After obtaining the national supply at basic prices, it was chosen to deal with total requirements matrix in industry-by-industry technology model. It assumes that the mix of production of a given sector may change but its market share in goods it produces remains constant, thus resulting that the sector may change its mix of production in order to keep its market share in those markets it operates (Guilhoto, 2009). For this reason, the market share matrix (D), obtained from the make table, is multiplied by the national supply matrix at basic prices, resulting in its change from commodity-byindustry to industry-by-industry. The next step consists in reducing the total number of sectors although maintaining a desegregation level compatible with the analysis under study. Based on aggregation proposed by Carvalho and Kupfer (2007) and considering the similarities of sectors’ productive structures, the 56-sectors matrix was converted into a 30-sectors matrix24. From the complete input-output matrix with 30 sectors, the matrix of technical coefficients, the Leontief inverse, output and employment multipliers, employment generator, Hirschman-Rasmussen backward and forward linkages as well as backward, forward and total normalised pure linkages were calculated. This analysis shows a picture of the Brazilian productive structure and allows for the identification of the most dynamic sectors in terms of production and employment in the economy. Complementary data on GDP growth by major economic sectors, industrial share in total GDP and Brazilian external accounts, released by the Brazilian Central Bank and the World Bank, are also used. Results provide an assessment of the relative importance of sectors within the policy framework adopted in the face of the international economic crisis25. 4. The Brazilian productive structure and leading economic sectors

23

Make and use tables released by IBGE with this level of desegregation, which is the greatest available for the Brazilian economy, show the household appliances sector. This does not happen within IBGE’s more aggregate tables. The sector, however, includes all types of goods and not necessarily only those benefited by the VAT tax policy, namely the white goods appliances. 24 See Appendix A for the correspondence between the original 56-sectors matrix and the calculated 30sectors matrix. 25 From the theoretical framework and methodology discussed above, complementary analyses on this topic could be made aiming at comparing input-output matrices with and without the inclusion of, for instance, tax policy initiatives or calculating the effects of a positive change in final demand due to reduced tax rates on output, employment and tax revenues.

13

This section discusses the results of the input-output analysis for the Brazilian economy in 2008, considering them within a wider perspective on the evolution of sectoral GDP growth and external accounts. Input-output methodology sheds light on the importance of different sectors in the productive structure and contributes to broaden the understanding of their potential role in the recovery of the economy. The relative importance of sectors to the domestic economic dynamics is assessed from different perspectives. It reveals sectors whose activities may affect to a greater extent the overall economic activity in terms of the selected variables, namely output, employment and interindustry linkages. Figure 1 shows that the Brazilian economy was growing considerably fast before the 2008 international economic crisis and was severely struck by it in 2009. The industrial sector was the most affected sector by the crisis. However, the set of countercyclical policies adopted at that time proved to be successful in recovering the economy in 2010, especially pulled by industrial growth. The worsening of international conditions led to a new round of policy implementation after 2011. Brazil maintained positive growth rates but at a lower level until 2013. Despite policy initiatives, industry was performing worse in comparison with the primary and services sectors. The deterioration of domestic economic conditions, especially in the face of increasing political turmoil in year of presidential elections, resulted in a 0% growth rate in 2014. In the following year, most countercyclical policies were discontinued in favour of austerity policies, given governmental budget constraints. As a result, the overall economy dropped almost 4% and the industrial sector, more than 6%. It is important to note that the industrial sector as a whole and the manufacturing sector in particular have been losing share in the Brazilian GDP. Indeed, this process dates back to the stagflation period of the 1980s and the economic liberalisation of the 1990s. In the early 1980s, industry corresponded to more than 40% of total GDP and manufacturing only, to about one-third of total GDP. The GDP composition considerably changed after the 1990s, accelerating a process of decreasing industrial and manufacturing share in the Brazilian GDP and a concomitant rising share of the services sector26. Figure 2 shows that the industrial share in GDP was inferior to 30% in the 2000s and the manufacturing share was equivalent to approximately half of this proportion. The growth cycle in the mid-2000s was accompanied by a rising share of industry, especially manufacturing, in Brazil’s GDP, reflecting high industrial growth rates at that moment. Nonetheless, this process was not sustained for long. Policy responses to the crisis gave a stimulus to the industry as a whole but the manufacturing share in GDP kept a downward trajectory, revealing that construction and extractive industries accounted more for the temporary industrial recovery than manufacturing itself. The industry share in total GDP declined to less than 24% in 2014 and the manufacturing share to less than 12%, the lowest level ever.

26

Data from the World Bank, World Development Indicators, available at: http://databank.worldbank.org/data/ (Accessed in: June 2016).

14

It is true that the growth cycle Brazil experienced in the 2000s benefited from large amount of exports, especially of primary goods, and capital inflows, alleviating temporarily balance of payments pressures on growth. The resulting overvalued exchange rates, however, increasingly affected the industrial competitiveness, particularly of the manufacturing industry, which, as seen, is losing ground in the Brazilian GDP. After the 2008 international crisis, the movement of rising imports and the external constraints on growth became clear. Part of demand recovery that economic policies promoted in Brazil was met by increasing imports. The decline in international commodity prices after 2011/2012 aggravated the situation, once affecting Brazil’s exports. As the new round of policy implementation at that time and new surges of domestic demand resulted in demand leakage to foreign markets, trade balance and current account balance sharply worsened, placing considerable challenges for a sustainable recovery from the crisis (see Figure 3). Output and employment multipliers, employment generator, Hirschman-Rasmussen backward and forward linkages as well as backward, forward and total normalised pure linkages provide, from different perspectives, the relative importance of sectors in the Brazilian productive structure to address the negative effects in the face of the crisis. Despite the decreasing share of industrial sectors in total GDP, the analysis of output multipliers show that they still are the main sectors able to stimulate the total output (or production) from a given change in final demand. Food and beverages, automobile and oil refining industries presented the highest output multipliers, which were greater than 2.35 in the Brazilian economy in 2008. In other words, these sectors may have deep productive linkages in the economy as a whole. Some of the sectors benefited by economic policies, such as household appliances and capital goods, figured in the 6th and 8th position, respectively, while others, including the furniture and construction industries, appeared only at the 18th and 20th position (see Figure 4).

The problem, however, consists in the fact that the Brazilian economy, despite showing an important industrial structure, is largely based on non-industrial sectors, particularly services. These sectors present a much lower capacity to stimulate production in the economy, as the analysis of output multipliers made clear, but account, as in the case of services, for more than 60% of total GDP. Regarding the employment generator, i.e. the amount of employment directly and indirectly generated through a variation in final demand, a greater impact may be observed in agriculture and livestock. In this sector, an additional R$ 1 million of final demand would correspond to 76 new direct and indirect jobs that would be necessary to carry out the production to meet this demand. The food and beverages industry was also important in generation of employment, holding the 4th position with an employment generator close to 50 jobs (see Figure 5). This indicator partially reflects sectors’ structural characteristics. In general, capitalintensive sectors tend to appear in the lower tail of the distribution as they usually require less additional amount of labour (or workforce) to meet demand variations. On the contrary, labour-intensive sectors, such as clothing and footwear, textiles, wood, tobacco and some services, present higher employment generators, since increases in

15

final demand tend to be met by an increase in the amount of additional employment as well27. The furniture industry, later benefited by the tax incentives policy and considered as a labour-intensive sector, did not present, however, a very high employment generator, standing behind the construction sector. Automobile, household appliances and capital goods industries, in turn, took only the 20th, 22nd and 23rd places, respectively (see Figure 5). The employment multiplier indicator complements the employment analysis. It shows a major importance of the oil refining sector. Nonetheless, it should be noted a distortion in this case. On the one hand, this sector employs few workers – its direct coefficient of employment is the lowest among all other sectors in the economy – and, on the other hand, it has significant productive linkages as already seen, thus resulting in a high amount of indirect employment. For these reasons, the ratio between direct and total employment expressed by the employment multiplier was expressive in comparison with other sectors28. According to this indicator, the automobile industry held the 4th position, household appliances industry was at the 10th and construction, at the 27th (see Figure 6). It is also worth highlighting that the construction industry and other sectors taking the last places of this distribution, such as other services, agriculture and livestock, commerce, clothing and footwear, and education and health, showed the highest direct coefficients of employment29. In other words, they were the main sectors accounting for direct employment in the economy, given that they had the largest amount of directly employed workforce to the sectors’ total output. As a result of the focus on direct generation of employment, their employment multipliers tended to be lower than in other sectors.

This analysis of output and employment multipliers and generators is followed by an assessment of the degree of dependence and interconnections between sectors provided by Hirschman-Rasmussen forward and backward linkages. As previously mentioned, sectors could be classified as key sectors, dependent on interindustry supply, dependent on interindustry demand or relatively independent of others. Figure 7 points as key sectors in the Brazilian economy in 2008 those sectors situated in the upper right quadrant, such as oil refining, chemical, automotive, steel, metallurgy, non-metallic minerals, wood, paper, textiles, and alcohol industries. Under this approach, construction industry would lie in the group of sectors generally independent of others, shown at the lower left quadrant. Among sectors strongly dependent on interindustry supply, situated in the lower right quadrant, it could be stressed both food and beverages as well as the automobile industry as presenting the highest backward linkages in the economy. This indicates 27

An important remark for an analysis of economic policy, not considered by this indicator though, refers to the quality of employment, which could be assessed in terms of labour conditions and average wage levels for each sector. 28 It should be noted, additionally, that demand increases for the oil refining sector may not be translated into very large generation of employment as observed from its relatively low employment generator. This is especially because of sector peculiarities, above all the fact of being a highly capital-intensive sector together with those sectors linked to it. 29 Check the values for direct coefficients of employment in Appendix B.

16

their strong interconnections with other sectors on which they are dependent and, probably, a strong capacity of pulling other industries. Other sectors included in the tax incentives policy, such as household appliances and capital goods industries, were also in the same quadrant with the 6th and the 8th highest Hirschman-Rasmussen backward linkage in the economy in 2008, respectively. Among sectors strongly dependent on interindustry demand, located at the upper left quadrant, the oil and gas extraction industry presented the highest forward linkage.

Given that Hirschman-Rasmussen indices do not take into account the relative size of each sector in the economy as a whole, which is an important feature of the analysis of leading economic sectors, normalised pure linkages were also calculated. From previous evidence, services sectors are expected to rank higher because, despite lower linkages, they present larger output share in the economy. Backward linkages pointed to food and beverages, public administration, education and health, construction and automobile industries as sectors with a greater pure impact of their production on demanding other sectors in the economy, as shown by Figure 8. The household appliances industry only appeared in the 26th position, possibly due to its relatively small size in the economy.

Forward linkages, in turn, indicate those relatively more important sectors as input suppliers for the production of other sectors in the economy. Figure 9 shows the predominance of services-related sectors. As the production of most sectors initially favoured by economic policies is generally directed to final demand, they tended to register weaker forward linkages. Construction, capital goods and furniture industries held the 18th, the 21st and the 25th position, respectively. The automobile and household appliances industries were only in the antepenultimate and penultimate places. As a result of the combination of these indices, the total normalised pure linkage is obtained, according to which the main economic sectors considering both their forward and backward linkages would be some sorts of services labelled as other services, then followed by the food and beverages industry (see Figure 10). Under this classification, the construction industry held the 9th position and the automobile industry, the 11th. Capital goods industry was at intermediate position (15th place), whereas furniture and household appliances sectors were only in the 25th and the 29th position, respectively.

5. Concluding remarks This paper discussed the major economic policies adopted by the Brazilian government after the 2008 international crisis and key features of the Brazilian productive structure. Input-output analysis provided a picture of the relative importance of different sectors in the productive structure from many perspectives, contributing to identify leading economic sectors and to assess their potential role in economic recovery in terms of output and employment that can be considered within a wide scope of policy initiatives. Policy response to the crisis began relatively quick, covered several sectors in the economy, and comprised different sets of instruments, including fiscal, industrial,

17

credit, monetary and social policies, that could stimulate domestic demand and contain the negative effects from abroad. Most countercyclical policies were implemented in two rounds, particularly in 2008/2009 and in 2011/2012. Policies were successful in securing the levels of output and employment in the economy at the first moment. They resulted in short-term demand recovery and accomplished their initial objectives. Brazil registered high growth rates already in 2010. However, policy effectiveness reduced over time. Adopted again in 2011/2012 and lasting until 2014, most countercyclical policies did not prove so effective in this second round as before to stimulate economic activity. Although they were unable to promote a sustainable recovery, they contributed at least to prevent an economic downturn in the early stages. Input-output results showed more evidence in favour of supporting some of the benefited sectors, in particular the automobile and the construction industries, rather than others, such as white goods appliances and furniture industries. The automobile industry presented, in general, a significant importance in all different assessments, especially in output and employment multipliers, Hirschman-Rasmussen backward linkage and backward normalised pure linkage. The capital goods industry, key for the promotion of domestic investment, was in an intermediate position and registered better relative performance in terms of output multiplier and backward linkages. The construction industry was particularly more relevant in the backward normalised pure linkage than in other analyses. However, it is also an extremely important sector in directly generating employment. For the household appliances sector, in which white goods appliances are included, highlights came from its output multiplier. Despite this fact, there was no clear indication of stronger interconnections with the rest of the economy. Most of its indices were lower than indices of other industrial sectors. The furniture industry, later benefited by tax policy, showed only intermediate positions with no special performance from different perspectives. To some extent, the temporal implementation of the tax break policy was associated with the relative importance of sectors in the economy, as for example the automobile industry was one of the first to be favoured after the crisis had started. Results also showed that the food and beverages industry was one of the leading economic sectors from different perspectives. The identification of these sectors can prove useful in shaping different economic policies in order to promote economic activity, although the reasons to pick particular sectors for certain economic policies are much beyond the analysis above and usually involve issues of political economy to coordinate interests of each sector. The paper also made clear that industrial sectors present stronger linkages in terms of production and employment maintenance in the economy but they have been losing ground in the Brazilian productive structure. To a large extent, the decreasing effectiveness of policy initiatives was related to the low competitiveness of the industrial sector as a whole and the rising external constraints on growth. Demand stimuli intensified imports, enlarging trade and current account deficits in a moment of deterioration of international markets and placing further challenges for a sustained economic recovery. This process indicates that the promotion of long-term economic growth also requires other policies that address this structural imbalance through the recovery of industrial development and make it competitive at international level.

18

Otherwise, new growth attempts are likely to be constrained again by external accounts. Acknowledgements The author wishes to thank Joaquim J. M. Guilhoto for comments on a first draft of this paper, two anonymous reviewers for their comments, and Capes, Brazilian Ministry of Education, for supporting his studies.

19

References Abdi, 2014. Contribuições para a política de desenvolvimento industrial, de inovação e de comércio exterior – período 2011/2014. Brasília, Agência Brasileira de Desenvolvimento Industrial (ABDI). Akb, 2013. Dossiê da crise IV: a economia brasileira na encruzilhada. São Paulo, Brazilian Keynesian Association (AKB). Anfavea, 2010. Anuário da indústria automobilística brasileira 2010. São Paulo, Brazil, Associação Nacional dos Fabricantes de Veículos Automotores (Anfavea). Beck, M., 2013. Governo aumenta IPI de móveis e veículos em janeiro, mas mantém o da linha branca. O Globo, Rio de Janeiro, Brazil, December 31. Carvalho, L., Kupfer, D., 2007. A transição estrutural da indústria brasileira: da diversificação para a especialização. XXXV Encontro Nacional de Economia da Anpec, Recife, Brazil, December. Cni, 2009. Política de desenvolvimento produtivo: avaliação e perspectivas. Brasília, Confederação Nacional da Indústria (CNI), August. Dias, M., 2015. Dilma sanciona desoneração da folha e veta alíquota para setor de vestuário. Folha de S. Paulo, Brasília, Brazil, September 1. Farhi, M., Borghi, R. A. Z., 2009. Operations with financial derivatives of corporations from emerging economies. Estudos Avançados, University of São Paulo, 23 (66), May-August, 169-188. Galvão, A., 2009. Governo decide prorrogar corte de IPI por até seis meses. Valor Econômico, Brasília, Brazil, June 30. Goy, L., Veríssimo, R., Fernandes, A., 2009. Corte no IPI da linha branca é prorrogado até janeiro de 2010. Agência Estado, Brazil, October 29. Guilhoto, J. J. M., 2009. Análise de insumo-produto: teoria, fundamentos e aplicações. São Paulo, Brazil, FEA-USP. Guilhoto, J. J. M., Sesso Filho, U. A., 2005. Estimação da matriz insumo-produto a partir de dados preliminares das contas nacionais. Economia Aplicada, 9 (2), AprilJune, 277-299. Hirschman, A. O., 1958. The strategy of economic development. New Haven, Yale University Press. Imf, 2011. Recent experiences in managing capital inflows – cross-cutting themes and possible policy framework. Washington, International Monetary Fund, February. Kaldor, N., 1966. Causes of the slow rate of economic growth of the United Kingdom. Cambridge, Cambridge University Press. Kaldor, N., 1971. Conflicts in national economic objectives. Economic Journal, 81 (321), March, 1-16. Keynes, J. M., 1936. The general theory of employment, interest and money. The collected writings of John Maynard Keynes, vol.VII. Cambridge, Cambridge University Press for the Royal Economic Society, 2013. Leontief, W. W., 1941. The structure of American economy, 1919-1929: an empirical application of equilibrium analysis. Cambridge, Harvard University Press. Lima, D., 2009. Analista apoia isenção de IPI dos móveis e diz que outros setores precisam de ajuda. Agência Brasil, Brazil, November 27.

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Liu, H., Polenske, K. R., Guilhoto, J. J. M., 2010. China and Brazil productive structure and economic growth compared: 1980s to 2000s. 57th Annual North American Meetings of the Regional Science Association International, Denver, November. Machado, L., Grimaldi, D. S., Albuquerque, B. E., Santos, L. O., 2014. Additionality of countercyclical credit: evaluating the impact of BNDES’ PSI on the investment of industrial firms. Working Paper, Banco Nacional de Desenvolvimento Econômico e Social (BNDES), November. Martello, A., 2012. Governo prorroga IPI mais baixo para carros, linha branca e móveis. G1, Brasília, Brazil, December 19. Martello, A., 2015. Após 6 anos, programa com juro menor para investimento chega ao fim. G1, Brasília, Brazil, December 30. McCombie, J. S. L., Thirlwall, A. P., 2004. Essays on balance of payments constrained growth: theory and evidence. London and New York, Routledge. McGilvray, J. W., 1977. Linkages, key sectors and development strategy, in: Leontief, W. W. (Ed.), Structure, System and Economic Policy. Cambridge, Cambridge University Press, pp. 49-56. Miller, R. E., Blair, P. D., 2009. Input-output analysis: foundations and extensions, second ed. Cambridge, Cambridge University Press. Modenesi, A. M., Prates, D. M., Oreiro, J. L., Paula, L. F., Resende, M. F. C. (Eds.), 2012. Sistema financeiro e política econômica em uma era de instabilidade: tendências mundiais e perspectivas para a economia brasileira. Rio de Janeiro and São Paulo, Elsevier and Brazilian Keynesian Association (AKB). Prado, M., 2012. Novo regime automotivo permitirá que montadoras escapem de alta do IPI. Folha de S. Paulo, Brasília, Brazil, April 3. Resende, T., 2008. Montadoras terão R$ 4 bi do governo de SP. Folha de S. Paulo, São Paulo, Brazil, November 12. Salles, Y., 2009. Governo prorroga IPI reduzido para carros e desonera material de construção. Folha de S. Paulo, São Paulo, Brazil, March 30. Soto, A., 2015 (a). Brazil reduces payroll tax breaks to cut swelling budget gap. Reuters, February 27. Soto, A., 2015 (b). Brazil cuts funds for PSI loan program as deficit swells. Reuters, October 23. Thirlwall, A. P., 1979. The balance of payments constraint as an explanation of international growth rate differences. Banca Nazionale del Lavoro Quarterly Review, 128, 45-53. Thirlwall, A. P., 2002. The nature of economic growth: an alternative framework for understanding the performance of nations. Cheltenham, Edward Elgar. Valor Econômico, 2009. Governo prorroga IPI reduzido para carros flex até março de 2010. Valor Econômico, Brasília, Brazil, November 25.

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Figure 1. Real GDP annual growth rates by sector, Brazil, 2000-2015 (%) 12.5

10.0 7.5 5.0 2.5

0.0 -2.5 -5.0

Primary sector

Industry

Services

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

-7.5

GDP

Source: own elaboration based on Brazilian Central Bank data available at: http://www.bcb.gov.br/ (Accessed in: June 2016).

Figure 2. Industry and manufacturing share, Brazil, 2000-2014 (% GDP) 30 25 20 15 10 5

Industry

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

0

Manufacturing

Source: own elaboration based on the World Development Indicators, World Bank data, available at: http://databank.worldbank.org/data/ (Accessed in: June 2016). Note: Industry includes extractive industries, manufacturing, construction and utilities, corresponding to divisions 10-45 of the International Standard Industrial Classification (ISIC), revision 3. Manufacturing, which corresponds to ISIC divisions 15-37, is reported as a separate subgroup in this chart.

22

0.0

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

20

15

5

0

-5

-15

-20

Financial services and real estate

Commerce

Public administration

Education and health

Other services

Information services

Utilities

Oil and gas extraction

Mineral extraction

Agriculture and livestock

Construction

Exports (l.a.) Trade balance (r.a.)

Transport and storage

Furiniture

Paper, stationery and printing

Textiles

Wood

Alcohol

Non-metallic minerals

Clothing, leather and footwear

Metallurgy

Electrical and communication equip.

Steel

Capital goods

Chemicals

Household appliances

Automotive

Tobacco

Oil refining

Automobile

Food and beverages

Figure 3. External accounts, Brazil, 2000-2014 (% GDP) 5

4

10 3

2

1

0

-1

-10 -2

-3

-4

-5

Imports (l.a.) Current account balance (r.a.)

Source: own elaboration based on the World Development Indicators, World Bank data, available at: http://databank.worldbank.org/data/ (Accessed in: June 2016). Note: l.a. = left axis; r.a. = right axis.

Figure 4. Output multiplier, Brazil, 2008

2.5

2.0

1.5

1.0

0.5

Source: own calculations based on the estimated Brazilian input-output matrix for 2008. See Appendix B.

23

Agriculture and livestock

0 Financial services and real estate

Utilities

Steel

Oil refining

Oil and gas extraction

Mineral extraction

Automotive

Capital goods

Household appliances

Chemicals

Automobile

Electrical and communication equip.

Metallurgy

Public administration

Information services

Paper, stationery and printing

Non-metallic minerals

Transport and storage

Furniture

Education and health

Construction

Alcohol

Commerce

Tobacco

Wood

Textiles

Food and beverages

Other services

Clothing, leather and footwear

Figure 5. Employment generator, Brazil, 2008 80

70

60

50

40

30

20

10

Source: own calculations based on the estimated Brazilian input-output matrix for 2008. See Appendix B.

24

Oil refining

0 Commerce

Agriculture and livestock

Other services

Construction

Education and health

Clothing, leather and footwear

Transport and storage

Furniture

Public administration

Textiles

Wood

Non-metallic minerals

Metallurgy

Information services

Financial services and real estate

Capital goods

Mineral extraction

Paper, stationery and printing

Electrical and communication equip.

Automotive

Household appliances

Utilities

Chemicals

Alcohol

Food and beverages

Steel

Automobile

Tobacco

Oil and gas extraction

Figure 6. Employment multiplier, Brazil, 2008 80

70

60

50

40

30

20

10

Source: own calculations based on the estimated Brazilian input-output matrix for 2008. See Appendix B.

25

Figure 7. Hirschman-Rasmussen forward and backward linkages, Brazil, 2008 1.6 Oil and gas extr.

1.4

Chemicals Oil ref. Non-met. min. Wood Steel Inf. serv. Transp. Paper M etallurgy Agric. Textiles Automotive Alcohol M in. extr. Utilities

FL

1.2

1.0 Fin. serv. and real estate

Other serv. Commerce

Elect. and com. equip.

0.8

Food and beverages

Capital goods Furniture Pub. adm.

0.6

Clothing and footwear Construction Household Tobacco appliances

Educ. and Health

Automobile

0.4 0.4

0.6

0.8

1.0

1.2

1.4

1.6

BL

Source: own calculations based on the estimated Brazilian input-output matrix for 2008.

Figure 8. Backward normalised pure linkage, Brazil, 2008 4.0 3.5 3.0 2.5 2.0 1.5 1.0

Wood

Non-metallic minerals

Alcohol

Textiles

Tobacco

Household appliances

Mineral extraction

Oil and gas extraction

Paper, stationery and printing

Steel

Utilities

Information services

Furniture

Metallurgy

Oil refining

Automotive

Chemicals

Clothing, leather and footwear

Agriculture and livestock

Electrical and communication equip.

Transport and storage

Financial services and real estate

Commerce

Capital goods

Automobile

Other services

Construction

Public administration

Food and beverages

0.0

Education and health

0.5

Source: own calculations based on the estimated Brazilian input-output matrix for 2008. See Appendix C.

26

0.0

Tobacco

Household appliances

Automobile

Clothing, leather and footwear

Education and health

Furniture

Alcohol

Public administration

Wood

Capital goods

Textiles

Mineral extraction

Construction

Electrical and communication equip.

Non-metallic minerals

Paper, stationery and printing

Automotive

Food and beverages

Metallurgy

Steel

Oil and gas extraction

Oil refining

Utilities

Information services

Transport and storage

Agriculture and livestock

Financial services and real estate

Chemicals

Commerce

Other services

Figure 9. Forward normalised pure linkage, Brazil, 2008 3.5

3.0

2.5

2.0

1.5

1.0

0.5

Source: own calculations based on the estimated Brazilian input-output matrix for 2008. See Appendix C.

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Other services

0.0 Tobacco

Household appliances

Wood

Alcohol

Textiles

Furniture

Mineral extraction

Non-metallic minerals

Clothing, leather and footwear

Paper, stationery and printing

Electrical and communication equip.

Automotive

Steel

Metallurgy

Oil and gas extraction

Capital goods

Utilities

Oil refining

Information services

Automobile

Education and health

Construction

Public administration

Transport and storage

Agriculture and livestock

Chemicals

Financial services and real estate

Commerce

Food and beverages

Figure 10. Total normalised pure linkage, Brazil, 2008 3.0

2.5

2.0

1.5

1.0

0.5

Source: own calculations based on the estimated Brazilian input-output matrix for 2008. See Appendix C.

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Appendix A. Map of sectoral aggregation Origina Agriculture and forestry Livestock and fishing Oil and gas extraction Iron Others of extractive industry Food and beverages Tobacco Textiles Clothing Leather and footwear Wood goods - excluding furniture Cellulose and paper materials Newspapers, magazines and CDs Oil refining Alcohol Chemical goods Resin manufacturing Pharmaceutical goods Pesticides and herbicides Perfumery, hygiene and cleaning Paint, lacquer and varnish Other chemical goods and derivatives Latex and plastics Cement Other goods of non-metallic minerals Steel and derivatives Metallurgy of non-iron metals Metal goods - excluding machinery and equipments Machinery and equipments, including maintenance and repairs Household appliances Office and computer equipments Electrical machinery, devices and materials Electronic material and communication equipments Medical-hospital and optical instruments/devices Passenger cars and light commercial vehicles Trucks and buses Autoparts Other transport equipments Furniture Production and distribution of electricity, gas, water, sewerage and urban cleaning Construction Commerce Transport, storage and mail Information services Financial intermediation, insurance, pension and related services Real estate and rent Maintenance and repairs Hotels and restaurants Services to companies Private education Private health Services to households and associations Domestic services Public education Public health Public administration and social security

Destinationb Agriculture and livestock Agriculture and livestock Oil and gas extraction Mineral extraction Mineral extraction Food and beverages Tobacco Textiles Clothing, leather and footwear Clothing, leather and footwear Wood Paper, stationery and printing Paper, stationery and printing Oil refining Alcohol Chemicals Chemicals Chemicals Chemicals Chemicals Chemicals Chemicals Chemicals Non-metallic minerals Non-metallic minerals Steel Metallurgy Metallurgy Capital goods Household appliances Electrical and communication equipments Electrical and communication equipments Electrical and communication equipments Electrical and communication equipments Automobile Automobile Automotive Automotive Furniture Utilities Construction Commerce Transport and storage Information services Financial services and real estate Financial services and real estate Other services Other services Other services Education and health Education and health Other services Other services Education and health Education and health Public administration

Source: own classification based on Carvalho and Kupfer (2007).

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a b

Original sector of the 56-sectors matrix. Corresponding sector in the 30-sectors aggregated matrix.

Appendix B. Values of output multiplier, employment generator, employment multiplier and direct coefficient of employment, by sector, Brazil, 2008 Sectors

Output multiplier

Employment generator

Employment multiplier

Public administration 1.51 21.12 1.68 Agriculture and livestock 1.75 75.62 1.23 Alcohol 1.96 39.40 6.38 Food and beverages 2.43 48.27 7.11 Automobile 2.40 16.29 16.70 Automotive 2.15 15.63 3.65 Commerce 1.43 41.53 1.22 Construction 1.76 39.26 1.38 Education and health 1.51 34.93 1.42 Household appliances 2.11 16.17 3.76 Oil and gas extraction 1.73 12.16 22.74 Mineral extraction 1.74 13.03 3.11 Tobacco 2.23 41.67 21.08 Wood 1.96 42.50 2.03 Capital goods 2.06 15.92 2.83 Electrical and communication equipments 2.02 16.58 3.65 Metallurgy 2.01 18.03 2.11 Non-metallic minerals 1.98 25.39 2.03 Furniture 1.92 34.68 1.64 Other services 1.64 56.43 1.26 Paper, stationery and printing 1.93 22.59 3.12 Chemicals 2.09 16.19 4.81 Oil refining 2.35 11.23 72.32 Information services 1.70 21.59 2.28 Financial services and real estate 1.33 8.73 2.75 Utilities 1.72 9.88 3.98 Steel 2.03 11.12 8.80 Textiles 1.94 43.27 1.80 Transport and storage 1.79 26.53 1.62 Clothing, leather and footwear 2.00 60.74 1.55 Source: own calculations based on the estimated Brazilian input-output matrix for 2008.

Direct coefficient of employment 12.58 61.27 6.17 6.79 0.98 4.28 33.96 28.43 24.60 4.30 0.53 4.19 1.98 20.99 5.62 4.54 8.56 12.54 21.16 44.92 7.23 3.37 0.16 9.48 3.18 2.48 1.26 24.00 16.36 39.14

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Appendix C. Values of backward, forward and total normalised pure linkages, by sector, Brazil, 2008 Sectors Backward Forward Public administration 2.991 0.176 Agriculture and livestock 0.950 2.362 Alcohol 0.179 0.169 Food and beverages 3.822 0.970 Automobile 2.304 0.033 Automotive 0.580 0.878 Commerce 1.575 2.690 Construction 2.310 0.514 Education and health 2.656 0.081 Household appliances 0.193 0.009 Oil and gas extraction 0.258 1.255 Mineral extraction 0.302 0.376 Tobacco 0.201 0.000 Wood 0.056 0.239 Capital goods 1.223 0.298 Electrical and communication equipments 0.890 0.520 Metallurgy 0.474 1.026 Non-metallic minerals 0.080 0.665 Furniture 0.485 0.129 Other services 2.273 3.031 Paper, stationery and printing 0.319 0.771 Chemicals 0.828 2.659 Oil refining 0.774 1.523 Information services 0.415 1.922 Financial services and real estate 1.079 2.560 Utilities 0.350 1.532 Steel 0.384 1.089 Textiles 0.151 0.371 Transport and storage 1.111 2.099 Clothing, leather and footwear 0.786 0.053 Source: own calculations based on the estimated Brazilian input-output matrix for 2008.

Total 1.586 1.655 0.174 2.399 1.170 0.729 2.131 1.414 1.371 0.101 0.755 0.339 0.100 0.148 0.761 0.705 0.749 0.372 0.308 2.651 0.545 1.742 1.148 1.167 1.818 0.940 0.736 0.261 1.604 0.420

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