Is Brazilian premature deindustrialization a case of Dutch disease?

ABSTRACT

The term “Dutch disease,” coined by The Economist (1977), describes how a commodity boom can overvalue a currency, undermine industrial competitiveness, and lead to deindustrialization. While traditionally linked to resource booms, an alternative theoretical view, advanced by Palma (2005) and the new developmentalist school, associates it in Latin America with post-1990s liberalizing reforms. This paper empirically tests whether Brazilian premature deindustrialization is driven by Dutch disease, a link not previously modeled within this latter theoretical framework. Using time series econometric models (1999-2024), we first examine whether the real exchange rate is influenced by Dutch disease variables. We then assess whether these factors explain Brazil’s premature deindustrialization, as hypothesized by Palma and new developmentalism. The findings support this interpretation, identifying Dutch disease – shaped by liberalizing reforms – as a key driver of Brazilian industrial decline. The paper closes with policy implications aimed at mitigating the structural impacts of Dutch disease.

JEL Classification: O1; O47; O.

KEYWORDS:
Dutch disease; natural and premature de industrialization; Brazil

INTRODUCTION

The term “Dutch disease”, coined by The Economist in 1977¹, refers to the economic crisis that hit the Netherlands in the 1960s after the discovery of vast natural gas reserves. With relatively unregulated markets, the surge in profitability drew resources away from manufacturing and toward the natural resource sector. The phenomenon was considered a “disease” because a commodity export boom triggered real currency appreciation, leading to a decline in manufactured exports, industrial contraction, and accelerated deindustrialization.

In the neoclassical model developed by Corden and Neary (1982), the phenomenon arises when a boom in one tradable sector – such as natural resources – diminishes profitability in other tradable sectors, like manufacturing, thereby altering the economy’s productive structure. Later, Jones and Neary (1984) demonstrated that non-tradable sectors, particularly low-productivity services, tend to benefit disproportionately, ultimately hindering long-term development.

An alternative interpretation, originally proposed by Palma (2005) and expanded by new developmentalism (Bresser-Pereira, 2008, 2020a, 2020b), argues that Dutch disease in developing economies arises not necessarily from commodity booms, but primarily from liberalizing economic reforms. In particular, trade liberalization and external financial openness since the 1990s have exacerbated structural dependence on commodities. These reforms undermined industrial policy instruments – such as import tariffs and managed exchange rates – that had previously supported industrialization. Brazil illustrates this pattern: following the liberalizing reforms of the 1990s, especially rapid trade liberalization and external financial openness, the share of commodities in total exports rose from 38.8% in 1990 to 65.8% in 2020, a shift accompanied by premature deindustrialization and economic stagnation (Nassif and Morceiro, 2026).

The main objective of this paper is to empirically test whether Brazil can be classified as a case of Dutch disease, addressing a critical gap in the literature. Although numerous studies have documented that Brazil represents one of the most severe cases of premature deindustrialization in the world economy², to the best of our knowledge, no research has yet provided an econometric demonstration of the mechanisms linking this structural decline to Dutch disease, as interpreted by Palma (2005) and new developmentalism – namely, as a consequence of the neoliberal economic reforms implemented in the 1990s.

As far as we know, the recent study by Bacha et al. (2025) is the only one to have positively tested for the existence of Dutch disease in Brazil. However, not only do they not consider trade and financial liberalization as causes of Brazilian deindustrialization, but they also choose to use the traditional concept of Dutch disease (i.e. one associated with a boom in the natural resource sector). Additionally, they dissociate Dutch disease from the real appreciation of the Brazilian currency, which ultimately contributes to the phenomenon of premature industrial decline.

The paper is organized as follows. Section 2 reviews the neoclassical and structuralist – new-developmentalist theoretical literature on Dutch disease. Section 3 examines key aspects of Brazilian economic policy, focusing in particular on exchange rate policy, and presents a set of economic indicators directly or indirectly linked to the Dutch disease phenomenon in Brazil. Section 4 employs time series models for the period 1999-2024 to first assess whether the real exchange rate is influenced by variables associated with Dutch disease, and then to analyze its relationship with deindustrialization, based on the frameworks of Palma and the new-developmentalist school. Section 5 draws the main conclusions and policy implications for Brazil.

THEORETICAL LITERATURE ON DUTCH DISEASE: NEOCLASSICAL VERSUS STRUCTURALIST AND NEW-DEVELOPMENTALIST APPROACHES

Dutch disease: the neoclassical model

Following the emergence of the problem in the Netherlands, Corden and Neary (1982) developed a neoclassical theoretical model to analyze the interrelationships between the affected variables and the long-term impacts on economic development. Their seminal work laid the foundation for what would become known as Dutch disease theory. The authors develop a model of a small open economy characterized by perfect competition and full employment, comprising two traded sectors – energy and manufactures – and one nontraded sector – services. The primary objective is to examine how the economy responds to a boom in the natural resource-based traded sector (energy).

The model explores various outcomes depending on key assumptions, such as the degree of intersectoral factor mobility or the presence of sector-specific factors, with labor being the only mobile input. A central mechanism of the model is the decomposition of the boom’s impact into two distinct channels: the movement effect and the spending effect. The movement effect captures the reallocation of resources following a productivity surge in the energy sector. This increase draws labor – and capital, if factors are mobile — away from manufacturing, directly reducing output and employment in that sector, thereby leading to deindustrialization. In contrast, the spending effect operates through real exchange rate appreciation. The resource boom raises national income, which in turn increases demand for nontraded services. This heightened demand drives up the relative price of nontraded goods compared to traded goods, resulting in an appreciation of the real exchange rate and further contributing to deindustrialization.

The central point is that both effects resulting from the natural resource boom give rise to deindustrialization: the first effect does so directly (“direct deindustrialization”), while the second operates indirectly, as it is mediated through real exchange rate appreciation. Corden and Neary (1982) suggest that the adverse effects of Dutch disease can be mitigated through policy measures such as exchange rate management and strategic allocation of government spending.

Corden (1984) revisits and expands upon the main arguments of the earlier Corden and Neary (1982) paper by incorporating additional macroeconomic considerations – such as domestic absorption effects, monetary rigidities, capital flows, expectations, and sectoral dynamics. Notably, Corden discusses and, to some extent, endorses protectionist responses to Dutch disease, although he characterizes them as a “second-best” policy option.

Jones and Neary (1984) reinforce the main conclusion of earlier studies. They show that following a natural resource boom, the manufacturing sector may experience a sharp contraction, as the boom disproportionately enhances the profitability of nontradable sectors – particularly traditional services such as commerce and retail – which typically exhibit lower productivity than manufacturing. This dynamic is labeled a “disease” because it compromises the country’s long-term development prospects.

Structuralist and new developmentalism arguments for Dutch disease

In a seminal revision, Palma (2005) argues that Dutch disease in many developing countries in Latin America (especially Brazil) need not stem from resource booms. Instead, he attributes the rising dominance of commodity sectors – encompassing primary and resource-based industrial goods – to liberalizing reforms adopted under “shock therapy” strategies, especially since the 1990s. These neoliberal reforms disrupted industrialization and the catching-up process, triggering premature deindustrialization.

In a follow-up study, Palma (2019, pp.925-930, boldfaces ours) refines his view:

“The recent deindustrialization of many countries in Latin America, unlike that of the Netherlands and the United Kingdom, was not triggered by the discovery of natural resources or the development of an export-oriented services sector. This deindustrialization – strongly marked by Dutch disease characteristics – was instead […] the result of a drastic process of trade and financial liberalization, carried out in a context of rapid institutional change, which led to an abrupt reversal of the industrialization process [based on import substitution agenda] that had previously been state-led [...]. Thus […], Dutch disease […] in most industrialized countries should be understood more as evolutionary [natural] deindustrialization processes – that is, in mature economies where manufacturing employment shifts to other sectors as part of the natural course of economic development […]. [In contrast, Dutch disease in Latin America – induced by economic policies and institutional changes – should instead be seen as a case of induced premature deindustrialization.”

Building on the Neary and Corden (1982) model but using the same historical-structural method adopted by Palma, the new developmental theory – advanced by Bresser-Pereira (2008; 2020a), Bresser-Pereira et al. (2014), among others³ – reframes the theory of Dutch disease. It explains the disease not only because of commodity booms but also, when the cost of production of exported commodities is very low, as a consequence of Ricardian rents – rents derived from those low costs – which can cause the disease even in the absence of a commodity boom. New developmentalism suggests that Latin America neutralized Dutch disease through import tariffs and other non-tariff barriers during its industrialization phase (1950-1980), but the disease resurfaced around 1990, when the region underwent liberalizing reforms. These reforms reduced protection via import tariffs, undervalued real exchange rates, and other industrial and macroeconomic policies tools, pushing economies back toward Ricardian natural comparative advantages, that is, a specialization on natural resource-based goods (commodities).

According to this view, countries that succeeded in industrializing and catching up (e.g. the United States) overcame Dutch disease through import tariffs, industrial policy, long-term public credit, and active exchange rate policy to avoid domestic currency overvaluation. In contrast, countries that underwent premature deindustrialization had initially mitigated the effects of Dutch disease but later abandoned these protective measures following fast trade and financial liberalization. As Bresser-Pereira (2020a, p.640) notes:

“The Dutch disease is a competitive disadvantage that blocks the industrialization of a developing country (for instance, Venezuela or Saudi Arabia) or causes deindustrialization of a middle-income or a rich country that previously neutralized the disease but, in a given moment, liberalized trade and so dismantled the mechanism that neutralized the disease (the case of Brazil).”

While retaining the classical mechanism (resource booms cause domestic currency appreciation in real terms), the new developmentalism approach expands it by introducing three distinct concepts of “equilibrium” real exchange rates and defines quantitatively the Dutch disease phenomenon as the difference between the current equilibrium, based on purchasing power parity (PPP), and the industrial equilibrium, which ensures the international competitiveness of domestic firms that adopt the best available technology in their respective sector. And defines the “extended Dutch disease” as the difference between the same current account equilibrium and the external debt equilibrium, which maintains the sustainability of external debt relative to GDP.

While the PPP-based equilibrium real exchange rate promotes current account balance and appears neutral across economic agents – including local producers competing with imports, exporters, and importers – it may fall short in supporting long-term industrialization. In contrast, the industrial equilibrium real exchange rate – which implies an undervalued domestic currency – enhances the global competitiveness of domestic firms operating with the best available technologies. When commodity prices surge and Dutch disease goes unaddressed, the nominal exchange rate tends to appreciate toward the current equilibrium rather than remaining closer to the industrial equilibrium. This shift undermines industrial development and reinforces dependence on primary exports.

According to the new developmentalism framework, sustainable development requires that five macroeconomic prices – profit rate, real exchange rate, real interest rate, real wage, and inflation – stay at “optimal” levels. Of these, the real interest and real exchange rates are paramount. The former influences investment by setting the opportunity cost of capital; the latter determines international competitiveness; all else being equal, both prices determine the long-term dynamics of economic growth. Overvalued real exchange rates disconnect investment from demand, deterring firms from deploying best available technologies. In other words, according to new developmentalism, with the domestic currency tendentially overvalued, entrepreneurs tend to face difficulties in accessing the existing effective demand. As a result, job creation increasingly benefits foreign producers, as domestic demand leaks into imports.

For Bresser-Pereira et al. (2014), the real exchange rate works as a switch that connects or disconnects companies that use the best available technology in their respective markets, confirming or rejecting their access to existing demand. Within this framework, only the industrial equilibrium real exchange rate aligns with sustained economic development. As emphasized by Bresser-Pereira et al. (2014), the exchange rate policy should be guided by competitiveness and economic growth goals, not merely by current account balance. Failing to do so risks trapping the country into a cycle of premature deindustrialization, external vulnerability, and long-term economic stagnation.

Brazil’s experience since the economic liberalizing reforms in the 1990s and even after adopting a floating exchange rate and inflation-targeting regime in 1999 illustrates this trajectory: persistent currency overvaluation, driven by policy-induced excessive capital inflows during the international liquidity bonanza, has accelerated premature deindustrialization and increased the economy’s exposure to external shocks. This has resulted in repeated episodes of capital flight and sharp currency depreciation (“overshooting”), triggering inflation, corporate insolvency, and financial instability, as will be further discussed ahead.

THE BRAZILIAN ECONOMY SINCE THE 1950S: FROM ACCELERATED GROWTH TO PREMATURE DEINDUSTRIALIZATION AND STAGNATION

From the post-World War II period until the late 1970s, the Brazilian economy stood out as one of the most dynamic in the world in terms of growth. This era was characterized by rapid industrialization: between 1948 and 1980, the manufacturing sector expanded at an average annual rate of 8.6%, while GDP grew by 7.4% per year. Labor productivity also rose sharply, registering an impressive average annual increase of 4.5% between 1950 and 1980 (Nassif, 2025). Moreover, during this period, Brazil began to shift away from its historical reliance on primary product exports, instead showing a growing capacity to generate domestic aggregate demand as a key driver of economic dynamism.

The external debt crisis of the 1980s marked the beginning of a shift toward a period of low economic dynamism and a reversal of Brazil’s industrialization process, leading the economy into a state of near stagnation. Figure 1 illustrates the growth trajectories of GDP and the manufacturing sector since 1948, along with their respective trend lines, clearly highlighting this turning point. From the 1980s onward, the manufacturing sector experienced a sustained decline in its growth rate, a trend that deepened following the 2008 global financial crisis. Since 2010, industrial growth has outpaced overall economic growth in only three years.

Figure 1
Evolution of GDP and Manufacturing Industry in Brazil (1948-2024) – In index number 1980=100

Complementing Figure 1, Figure 2 depicts the evolution of the manufacturing sector’s share in total value added, measured at constant 2018 prices. Since the mid-1980s, this share has declined almost continuously, with the downturn becoming significantly more pronounced from the 2010s onward. By 2023 – the most recent year for which data are available – manufacturing accounted for just 10.9% of GDP, a level even lower than that recorded in 1947.

Figure 2
Brazilian manufacturing sector as a proportion of GDP (1947-2023, in percentage) – at 2018 prices

This section argues that the virtuous growth cycle observed in the post-war period was underpinned by a profound structural shift toward more capital-intensive sectors, driven by an economic policy strategy aimed at closing the gap between Brazil’s per capita income and that of the developed world. This strategy was strongly influenced by the thinking of the Economic Commission for Latin America and the Caribbean (ECLAC), which maintained that income expansion in non-industrialized economies depended heavily on overcoming the persistent deterioration in the terms of trade for their exported goods. For agrarian-exporting countries like pre-war Brazil, sustained per capita income growth required a transition toward industrialization, led and coordinated by the state. The state’s role was to identify and promote strategic sectors capable of driving industrialization and productivity growth (Bértola and Ocampo, 2010).

The state-led industrialization strategy was implemented through a policy of import substitution, which involved imposing high import tariffs and other non-tariff barriers on consumer goods to protect infant domestic industries, alongside subsidies to encourage industrial exports. However, the strategy was largely dismantled in the 1990s with the onset of trade and financial liberalization, marking a significant shift in Brazil’s development model toward the principles of the Washington Consensus. Between 1981 and 2024, the average annual GDP growth rate fell to 2.1%, while the manufacturing sector expanded by only 0.6% per year.

The uncritical adoption of liberal economic policies significantly reduced the state’s policy space to pursue a development and industrialization agenda in Brazil. Deindustrialization, therefore, should be understood as the outcome of a deliberate policy choice, one that replaced the active use of protectionist measures aimed at transforming the productive structure with a non-interventionist approach, grounded in the belief that free markets would allocate resources efficiently through static comparative advantage⁴.

The consequences of this policy choice in economies still undergoing development include deindustrialization, as they tend to specialize in sectors with “natural” comparative advantages, thereby reinforcing the symptoms of the so-called “Dutch disease”. For this reason, when deindustrialization occurs before the economy has completed a stage of mature industrialization, it is referred to as premature, and the economy loses its dynamism and competitiveness.

Table 1 shows the evolution of Brazil’s productive structure since the post-war period. It was in the 1970s that the manufacturing industry reached its peak share, accounting for nearly 30% of total value added. This share declined sharply from the 1990s onward, and by the 2010s, it had fallen to less than half of its value in the 1970s.

Table 1
Share of main sectors of Brazilian economic activities in total value added (current prices) Selected periods from 1951 to 2020 (in percentage)

Periods	% Share of main sectors of activity – 1951-2020
	Agriculture	Total industry (including manufacturing)	Manufacturing	Services
1951-60	22.5	26.3	20.2	51.1
1961-70	15.7	32.6	25.8	51.5
1971-80	11.5	38.1	29.4	50.0
1981-90	10.0	39.9	28.8	49.7
1991-00	7.3	32.5	17.6	60.3
2001-10	5.7	27.2	16.2	67.1
2011-20	5.3	23.3	12.4	71.4

During the thirty years of virtuous growth in the Brazilian economy (1950-1980), the industrial sector’s structure became more complex, with a greater concentration in capital-intensive sectors. The dynamism in terms of the growth rate of Brazilian manufacturing, as mentioned, resulted from the shift in the composition of subsectors within the industrial matrix – that is, from the increasing weight of the more dynamic industries.

As described in the theoretical literature on structural change processes, the faster an economy grows, the more efficient it is at reallocating productive resources from low-productivity activities – typically associated with the production of low-value-added goods, such as those intensive in natural resources – to activities that produce higher-value-added goods. Table 2, drawing on data from the Industrial Censuses, presents the shifts in the relative shares of manufacturing subsectors. These subsectors are categorized according to Pavitt’s (1984) classification, which groups industries based on their factor inputs and the key characteristics that shape how they compete in the market.

In 1970, the industrial structure was dominated by scale-intensive and resource-based sectors. By 1980, the share of resource-based industries had declined, while specialized suppliers, scale-intensive, and labor-intensive sectors had gained ground. In other words, up to the early 1980s, the evolution of Brazil’s productive structure reflected steady progress through the stages of industrialization, with the domestic production of both consumer and capital goods becoming increasingly internalized.

Table 2
Share of Brazilian manufacturing subsectors, selected Years (in percentage)

Group of sectors of activity of the manufacturing industry	% share in total manufacturing			Difference in percentage points
	1970	1980	2000	1980--1970	2000--1980	2000--1970
Resource-based	32.6	29.7	38.4	-2.9	8.7	5.8
Labor-intensive	15.9	17.2	11.5	1.3	-5.7	-4.4
Scale Intensive	37.1	38.6	33.2	1.5	-5.4	-3.9
Specialized Suppliers	9.9	11.7	11.2	1.8	-0.5	1.3
Science-Based	4.5	2.8	5.8	-1.7	3.0	1.3

From 1980 to 2000, a period marked by the onset of premature deindustrialization – when manufacturing’s share of total value-added declined from 30.3% in 1980 to 15.3% in 2000 – the three industry groups that had previously gained weight lost ground in their share of total manufacturing. In other words, the decline of the manufacturing industry in the country’s productive matrix occurred due to the relative loss of importance of sectors that were more capital-intensive and technologically sophisticated.

In 2000, the science-based group showed a gain in share; however, this gain was concentrated in a single product (the production of medium-sized aircraft). The progression of the deindustrialization process becomes evident in 2000 when comparing the sectors’ shares in the two extreme years of the table: from 1970 to 2000, labor-intensive and scale-intensive sectors retreated in the productive structure, losing a combined total of 8.3 percentage points, while the natural resource-intensive sector advanced by 5.8 percentage points.

From successful industrialization to the abandonment of state-led development

The industrialization process driven by import substitution relied heavily on broad protectionist measures to support infant industries. Two policies were particularly instrumental in enabling this productive transformation: first, the protection of priority industries through high tariffs and market reserves for domestic production, reinforced by the “National Similar Law”⁵; and second, an exchange rate policy that provided preferential rates for the import of capital goods and various intermediate inputs.

Concerning import policy, tariffs and surcharges were complemented by import controls implemented through both explicit and implicit non-tariff barriers. Regarding exchange rate policy, in response to external financing difficulties in the early 1950s, Instruction 70 of the Superintendency of Currency and Credit (SUMOC) was introduced in 1953. This measure established a multiple exchange rate system that categorized productive sectors into five priority levels, ranked from highest to lowest. The system served a dual purpose: conserving scarce foreign reserves and, more importantly, functioning as a mechanism of industrial protection⁶.

One of the most distinctive features of Brazil’s industrialization process was the persistence of high inflation. To preserve export competitiveness amid accelerating price levels, the government adopted a policy of crawling peg – known as mini-devaluations – beginning in 1968. This regime remained in place, with few interruptions, until March 1990. In addition to chronic inflation, domestic infrastructure bottlenecks underscored the need for increased public investment. The significant acceleration of industrialization during the 1950s was largely driven by the implementation of the Target Plan (Plano de Metas) under President Juscelino Kubitschek (1956-1961). The plan outlined a proactive role for the state in investing in key infrastructure and basic sectors, while also promoting private investment.

Another significant boost to Brazilian industrialization came with the implementation of the Second National Development Plan (II PND), carried out between 1975 and 1979. Launched in 1975, the plan aimed to deepen the process of import substitution, with a strategic focus on key industrial (especially intermediate goods) and energy sectors. The external shocks of 1979-1980 – characterized by a second spike in international oil prices and rising interest rates on foreign debt – abruptly ended Brazil’s period of rapid economic growth. Mounting balance of payments imbalances and accelerating inflation soon plunged the country into what would later be termed the “lost decade” of the 1980s.

The external debt shock of the early 1980s prompted Brazil to abandon, during the 1990s, the developmentalist strategy it had pursued since the post-war era. Throughout the decade, difficulties in renegotiating the debt persisted, exacerbating domestic imbalances such as mounting inflationary pressures and a protracted fiscal crisis.

The acceleration of inflation during the 1980s was largely driven by the pervasive indexation mechanisms – both formal and informal – that shaped Brazil’s monetary and financial transactions. After multiple unsuccessful attempts to contain inflation through heterodox economic plans in the 1980s and early 1990s, price stability was finally achieved in 1994 with the introduction of the Real Plan (Plano Real).

From that point onward, Brazil deepened its economic liberalization⁷. Trade liberalization had already advanced rapidly between 1990 and 1994⁸, while the external financial opening began in 1992. This shift marked a new development strategy centered on integrating the Brazilian economy into global markets. Trade liberalization was rightly seen as a necessary step to increase domestic competition and revive labor productivity, which had stagnated since the mid-1980s. However, it was implemented in the form of “shock therapy”: most non-tariff barriers were abruptly removed, nominal import tariffs were sharply reduced, and capital account liberalization proceeded rapidly. Although trade openness also served as a tool for price control during the fight against high inflation under the Real Plan, its abrupt implementation posed significant adjustment challenges.

Financial liberalization, meanwhile, was expected to attract capital inflows that could help finance balance of payments deficits. Collectively, the neoliberal reforms of the 1990s dismantled many of the protective instruments – such as domestic industry protection, active exchange rate policies, and public investment, which, according to Bresser-Pereira (2020b), had helped neutralize the effects of Dutch disease during the period of accelerated industrialization. However, the most consequential shift for the Brazilian manufacturing sector was the change in exchange rate policy, which became the primary anchor for the country’s price stabilization strategy⁹.

While the Real Plan succeeded in curbing high inflation, the adoption of a (semi-) fixed exchange rate regime – under conditions of free capital mobility and a high reliance on external savings – proved ultimately unsustainable. The Brazilian economy faced successive speculative attacks during the Mexican crisis (1995), the Asian financial crisis (1997), and the Russian crisis (1998), all of which disrupted capital inflows and intensified external vulnerability. These pressures culminated in the abandonment of the (semi-)fixed exchange rate regime in January 1999. The transition to a floating exchange rate regime triggered a sharp depreciation, with the currency overshooting before eventually stabilizing. This floating regime, adopted in early 1999, remains in effect today.

The macroeconomic policy “tripod”: Floating exchange rate, inflation targeting, and primary surplus targets

With the adoption of a floating exchange rate regime in January 1999, Brazil transitioned to an inflation-targeting framework as its new monetary anchor. At a theoretical level, this shift was expected to restore monetary policy autonomy within a context of price stability (Mundell, 1960). Between 2003 and the onset of the global financial crisis in 2008, Brazil benefited from highly favorable terms of trade – fueled by a boom in commodity prices for its exports and an environment of ample global liquidity. These factors contributed to a sustained overvaluation of the Brazilian currency. Remarkably, this trend of real appreciation continued even after the end of the commodity boom – apart from a brief interruption following the 2008 crisis – lasting until the recession of 2015-2016. This persistence can largely be attributed to the interplay between a conservatively managed inflation-targeting regime and a floating exchange rate system, operating within a global environment of sustained liquidity.

As evidenced by Brazil’s experience over the past two and a half decades, prolonged currency overvaluation has had harmful effects on the country’s productive structure. It has contributed to premature deindustrialization and intensified the external constraint on growth. Figure 3 illustrates the relationship between current account balances as a percentage of GDP (right axis) and the real effective exchange rate (left axis). Two key patterns emerge: first, Brazil’s current account deficits are closely linked to periods of real currency appreciation; second, when these deficits become unsustainable, adjustment tends to occur abruptly – either through sharp currency depreciations, as seen in 1999, or through a combination of depreciation and deep recession, as was the case during the 2015-2016 downturn.

Figure 3
Real effective exchange rate index and current account (CA) balance/GDP in Brazil: 1999-2024 (in percentage)

Following the severe recession of 2015-2016, Brazil underwent a sluggish economic recovery between 2017 and 2019, which was then disrupted by the onset of the COVID-19 pandemic in 2020. Since that time, the real effective exchange rate has tended toward undervaluation. This recent trend largely reflects elevated risk premia resulting from a series of global shocks since 2020. Still, given the limited policy space to implement autonomous macroeconomic measures, a return to a period of abundant global liquidity could once again lead to an overvaluation of the Brazilian real.

In short, Brazil’s subordinate integration into international financial markets has shaped an exchange rate management dynamic characterized by high domestic interest rate differentials relative to external rates and substantial holdings of international reserves. These tools have been used to buffer capital flow volatility and, in turn, to limit the inflationary impact of sudden currency depreciations.

However, as argued by the new developmentalist literature (Bresser-Pereira, 2020a), the strategic price that guides resource allocation toward the manufacturing sector is the real exchange rate. In economies with comparative advantages in natural resource exploitation, like Brazil, the real exchange rate tends to appreciate over time. In Brazil’s case, the liberal turn in economic policy entailed the dismantling of mechanisms that had previously countered the effects of Dutch disease. Combined with unrestricted capital mobility, this shift has led to a persistently overvalued real exchange rate, undermining competitiveness in the long term.

Table 3 illustrates the evolution of Brazil’s international trade pattern over selected years. The share of primary goods in total exports rose sharply – from around 15% in 2000 to nearly 50% in 2023 – signaling an increasing reliance on products tied to static comparative advantages. During the same period, manufactured exports declined by more than 30 percentage points. All categories of manufactured goods experienced steep contractions, with the sole exception of resource-based products, which saw a modest increase. These trends reflect a clear pattern of premature deindustrialization.

Table 3
Share of goods’ total exports and imports – Selected years from 2000-2023 (in percentage)

	Exports				Imports
	2000	2010	2020	2023	2000	2010	2020	2023
Primary Goods (Agriculture and Mining)	14.6	34.8	46.5	48.3	12.3	13.1	7.7	9.5
Manufacturing	83.3	63.1	53.5	51.5	87.3	85.9	91.3	90.0
Resource-based	18.4	21.3	20.7	20.2	3.8	3.1	4.2	3.9
Labor-intensive	9.1	4.1	2.5	2.0	4.5	5.8	6.3	5.3
Scale Intensive	29.8	21.1	18.3	18.0	23.6	26.8	20.1	25.4
Specialised Suppliers	14.0	8.3	5.5	5.9	19.0	19.0	21.0	18.8
Science-Based	12.0	8.4	6.4	5.3	36.4	31.1	39.7	36.6
Not classified	2.0	2.1	0.0	0.3	0.4	1.0	1.0	0.5
TOTAL	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0

On the import side, the composition remained relatively unchanged between 2000 and 2023. The most notable trend was a growing dependence on imported manufactured goods, further highlighting the erosion of Brazil’s domestic manufacturing base within its overall productive structure.

In summary, the analysis presented in this subsection highlights Brazil as a textbook case of premature deindustrialization and re-primarization of its export basket, hallmarks of a chronic Dutch disease condition. This hypothesis will be tested in the following section.

BRAZILIAN PREMATURE DEINDUSTRIALIZATION AND DUTCH DISEASE: EMPIRICAL EVIDENCE BASED ON ECONOMETRIC ESTIMATES

This section aims to econometrically assess, through monthly statistics, whether Brazil’s premature deindustrialization, over the period 1999-2024, can be attributed to Dutch disease dynamics. The empirical strategy is divided into two stages. In the first stage, we estimate the determinants of the Brazilian real exchange rate. The goal is to examine whether a Dutch disease proxy variable, alongside other explanatory variables drawn from the theoretical literature, plays a statistically significant role in explaining the behavior of the real exchange rate. In the second stage, we assess whether the real exchange rate, together with other relevant variables, helps explain changes in the share of the manufacturing sector in GDP, an indicator of industrialization or deindustrialization.

More specifically, in the first stage, we test whether the real exchange rate is significantly influenced by variables associated with Dutch disease, such as commodity price indices and interest rate differentials (as a proxy for external financial openness). If so, we proceed to the second stage, where the objective is to test whether deindustrialization – proxied by the seasonally adjusted fixed-base industrial production index – is correlated with the real exchange rate and additional explanatory variables aligned with the new developmentalist interpretation of Dutch disease. These include not only commodity price indices but also variables capturing the effects of liberalizing reforms, such as nominal import tariffs and a proxy for external financial openness. If these variables are found to be statistically significant, the results would support the hypothesis that Brazil’s premature deindustrialization is driven by Dutch disease mechanisms, as interpreted by the new developmentalist literature.

Determinants of the long-term real exchange rate in Brazil (1999-2024)

This subsection estimates a model for real exchange rate determination, intending to identify the variables that have influenced its long-term behavior in Brazil over recent decades. Special emphasis is placed on variables highlighted by new-developmentalist theory – namely, the commodity price index (as a proxy for Dutch disease) and the interest rate differential – alongside additional variables selected based on the methodological framework developed in our earlier work (Nassif et al., 2017)¹⁰.

The econometric specification of the model for determining the long-run trajectory of the real exchange rate is given by:

(1) $\text{LogRERt}=\text{c}0+\beta 1\text{LogYt}+\beta 2\text{LogCAt}+\beta 3\text{LogClt}+\beta 4\text{LogDIFt}+\beta 5\text{LogIRt}+\beta 6\text{LogCRt}+{ϵ}_{\text{t}}$

All variables are expressed in logarithms:

RER is the real effective exchange rate.

Y is real GDP per capita in U.S. dollars.

CA is the current account balance as a share of GDP.

CI is the current commodity price index.

DIF is the interest rate differential between the domestic short-term interest rate (Selic/Over) and the U.S. short-term interest rate (2-year T-note, for the international rate).

IR is the stock of Brazil’s international reserves as a share of GDP.

CR is Brazil’s sovereign risk premium, represented by the JP Morgan EMBI Brazil Sovereign Foreign Currency index.

ε is the error term, and the subscript t denotes time (in our econometric model, monthly observations).

The dataset covers the period from January 1999 to December 2024, and the detailed specification of the sources is in the first part of Table A1 in the Appendix¹¹.

The first step in the empirical analysis involved conducting unit root tests using the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) procedures. The results indicated that all the series are integrated of order one, meaning they are non-stationary in levels but stationary in first differences.

Since the variables are non-stationary and share the same order of integration, the Johansen (1988) cointegration approach can be employed to investigate whether a stable long-run relationship exists among them. As the test indicated the presence of one cointegrating vector among the series, it is possible to confirm the existence of a long-term equilibrium relationship among the model’s variables.

Given that the series are non-stationary and cointegrated, Equation (1) can be estimated using both Ordinary Least Squares (OLS)¹² and the Vector Error Correction models (VEC). Table 4 presents the results of the econometric model.

Table 4
Determinants of the long-term real exchange rate in Brazil – (1999-2024) Dependent Variable: Real exchange rate (RER)

Variable	Variable	OLS Coefficient (t-statistic)	VEC Coefficient (t-statistic)
Constant	C	14.35*** [6.49]	-16.76
Log of GDP per capita	lnY-3	-0.19*** [-4.56]	-0.74*** [-5.94]
Log of Commodity Price Index	lnCI	-0.23* [-1.68]	-0.15*** [3.65]
Log of Current Account Balance / GDP	lnCA	0.05*** [4.52]	0.07*** [-3.46]
Log of Interest Rate Differential	Ln(DIF)-3	-0.10*** [-6.04]	-0.07* [-1.79]
Log of International Reserves / GDP	lnIR	0.28*** [9.53]	0.35*** [6.32]
lnCR (Log of Brazil Risk Premium)	lnCR	0.22*** [7.70]	0.32*** [4.58]

• Note on OLS model: R-squared: 0.67; Adjusted R-squared: 0.66; Durbin-Watson: 1.67; F-statistic: 102; Prob (F-test): 0.00; Number of observations: 309 after adjustments. Variables Y and DIF were included with 3 lags.
• Note on VEC model: 3 lags; Number of observations: 302 after adjustments. All variables were included with one lag. Order of the variables in the VEC: RER, DIF, IR, CA, Y, CI, and CR.
• ^***
  Notes: Significant at 1%;
• ^**
  Significant at 5%;
• ^*
  Significant at 10%.

The results presented in Table 4 indicate that all explanatory variables are statistically significant and display the expected signs, underscoring their relevance in explaining Brazil’s long-term real exchange rate (RER) behavior¹³. In both the OLS and VEC models, the logarithm of GDP per capita exhibits a significant negative relationship with the RER, suggesting that higher income levels are associated with real appreciation, an outcome consistent with the Balassa-Samuelson effect (see Obstfeld and Rogoff, 1996, p.212).

The commodity price index also shows a negative coefficient, indicating that increases in commodity prices lead to an appreciation of the real exchange rate. This result aligns with the Dutch disease hypothesis in both neoclassical and developmentalist theories and is statistically significant in both models, though at the 10% level in the OLS estimation.

In the OLS model, the current account balance, international reserves, and the country risk premium are all statistically significant and positively signed. This suggests that stronger external balances and higher reserve accumulation tend to depreciate the RER, while higher risk premiums are associated with depreciation, findings that align with theoretical expectations. Meanwhile, the interest rate differential is negative and significant in both specifications, supporting the view that higher domestic interest rates attract capital inflows and lead to real exchange rate appreciation, a result consistent with Palma’s and the new-developmentalist interpretation of Dutch disease.

The consistency of these results across both models, coupled with robust t-statistics, reinforces their economic and statistical significance. Taken together, the findings provide strong empirical support for core propositions of the new-developmentalist approach regarding the structural drivers of currency overvaluation in developing economies. Specifically, the negative and significant relationship between the commodity price index and the RER confirms the presence of Dutch disease dynamics: rising commodity prices lead to foreign exchange inflows that appreciate the domestic currency. Likewise, the significant negative effect of interest rate differentials on the RER suggests that high domestic interest rates – used as a strategy to attract foreign capital and stabilize inflation – further contribute to currency appreciation.

Overall, these results reinforce the new-developmentalist argument that both external factors (such as commodity dependence and reliance on external savings) and internal factors (such as monetary policy stance) systematically contribute to the persistent overvaluation of the real exchange rate in Brazil. This overvaluation, in turn, reflects deeper structural vulnerabilities rooted in Dutch disease dynamics.

Determinants of premature deindustrialization in Brazil in the period 1999-2024: a case of Dutch disease?

The present subsection empirically investigates premature deindustrialization, incorporating additional variables, besides the real exchange rate, to capture the dimensions of trade liberalization and financial openness. These new variables capture the broader context of Palma’s and the new developmentalist reinterpretations of Dutch disease. The goal is to assess how changes in external and monetary policy regimes from 1999 onwards have shaped industrial competitiveness through their effect on the real exchange rate, and consequently on the allocation of domestic resources.

The econometric specification of this model is constructed on a monthly basis and is presented in Equation (2). Once again, the details on the construction of the variables can be found in the second part of Table A1 in the Appendix.

(2) ${\text{LogIND}}_{\text{t}}={\text{c}}_{\text{0}}+{\beta }_1{\text{LogRER}}_{\text{t}}+{\beta }_2{\text{LogTLI}}_{\text{t}}+{\beta }_3{\text{LogFIN}}_{\text{t}}+{ϵ}_{\text{t}}$

All variables are expressed in logarithms and calculated as follows:

IND is a proxy for deindustrialization, represented by the seasonally adjusted fixed-base industrial production index¹⁴.

RER is the real effective exchange rate¹⁵.

TLI is the proxy for trade liberalization, specifically the nominal import tariff adjusted by the monthly industrial production (fixed-base series)¹⁶.

FIN is the proxy for external financial openness, constructed as the sum of monthly gross financial flows as a percentage of trade flows¹⁷.

ε is the error term, and the subscript t denotes time (in our econometric model, monthly observations).

The dataset also covers the period from January 1999 to December 2024, and the detailed specification of the sources is in the second part of Table A1 in the Appendix.

In addition to the OLS estimation, we employed a Vector Error Correction (VEC) model, which accounts for potential endogeneity bias by treating all variables as endogenous within the system. This approach acknowledges the simultaneous determination of variables and estimates a system of equations that captures both short- and long-run dynamics, thereby mitigating the effects of structural endogeneity. As Enders notes, “because the VEC model is a system of equations in which each variable is treated as endogenous, it helps mitigate endogeneity concerns that often affect single-equation models” (2015, p.390). The econometric strategy follows the same approach as in the previous section, beginning with unit root tests, cointegration analysis, and the estimation of both OLS and VEC models.

As previously noted, all series have one unit root and share a common cointegration vector. The results of the econometric models are presented in Table 5.

Table 5
Determinants of premature deindustrialization in Brazil (1999-2024) Dependent Variable: Industrial Production Index (IND)

Variable	Variable	OLS Coefficient (t-statistics)	VEC Coefficient (t-statistics)
Constant	C	6.49*** [8.18]	-16.76
Log real exchange rate	LnRER-1	0.25*** [15.62]	0.74*** [5.94]
Log trade liberalization proxy	LnTLI-6	-0.21*** [-7.27]	-0.15*** [3.65]
Log external financial openness proxy	LnFIN-1	-0.04*** [-3.66]	-0.07*** [-3.46]

• Note on OLS model: R-squared: 0.67; Adjusted R-squared: 0.66; Durbin-Watson: 1.75; F-statistic: 197; Prob (F-test): 0.00; Number of observations: 306 after adjustments.
• Note on VEC model: 4 lags; Number of observations: 307 after adjustments. All variables were included with one lag. Order of the variables in the VEC: IND, RER, TLI, and FIN.
• ^***
  Notes: Significant at 1%;
• ^**
  Significant at 5%;
• ^*
  Significant at 10%.

The results indicate that a more undervalued real exchange rate is positively and significantly associated with the growth dynamics of Brazil’s manufacturing sector over the analyzed period. This finding is consistent with the new developmentalist theory, which posits that maintaining a competitive real exchange rate – defined as a stable rate at the industrial equilibrium level – is crucial for sustaining industrial dynamism in developing economies.

Furthermore, the real exchange rate coefficients were not only statistically significant but also exhibited the greatest explanatory power regarding Brazil’s premature deindustrialization. This reinforces the interpretation that the phenomenon is closely linked to the effects of Dutch disease.

In addition, the proxy variables for trade liberalization and external financial openness were also significant in explaining premature deindustrialization in Brazil. Taken together with the persistent trend of real exchange rate overvaluation, these findings lend strong support to the hypotheses advanced by Palma (2005) and new-developmentalist scholars: that Dutch disease has been the principal driver of Brazil’s premature deindustrialization in recent decades.

CONCLUSION AND POLICY IMPLICATIONS

Most empirical studies agree that Brazil has experienced one of the most severe cases of premature deindustrialization in the global economy. However, to our knowledge, Bacha et al. (2025) is the only study that empirically examines whether this process is linked to Dutch disease. While their results confirm such a connection, their analysis is grounded in the neoclassical framework, which attributes Dutch disease to only commodity price booms. This interpretation led the authors to the misleading conclusion that Brazil’s deindustrialization stems from supply-side issues, such as weak human capital or low trade openness¹⁸.

In contrast, our main contribution is to apply the interpretation advanced by Palma (2005) and the new developmentalist school, which sees Brazil’s premature deindustrialization as a form of Dutch disease rooted not only in resource booms but also in neoliberal reforms. These reforms, implemented between 1990 and 1994 and centered on rapid trade and external financial liberalization, dismantled the intuitive and pragmatic mechanisms that had previously neutralized the disease – chiefly domestic protection through import tariffs and non-tariff barriers as well as capital controls and exchange rate policy. As a result, much of the manufacturing industry became non-competitive, protections for domestic industry were weakened, macroeconomic policy space was constrained, and the economy was exposed to high real interest rates and chronically currency overvaluation, volatile exchange rates, contributing to decades of (premature) deindustrialization¹⁹.

Our findings confirm Palma’s and the new-developmentalist hypotheses: Dutch disease has been a key driver of Brazil’s premature deindustrialization in recent decades. Based on this evidence, we draw two important economic policy implications.

The first implication is that, to halt the process of deindustrialization and resume a path of sustained economic development, the Brazilian government must remain committed to industrial policies focused on innovation and the diffusion of technological progress. Notably, as the global economy advances toward replacing current carbon-intensive technologies with low-carbon alternatives, Brazil faces significant opportunities at a time when the global playing field is still relatively level. The country has substantial potential not only to expand its energy diversification through environmentally sustainable technologies (e.g. solar and wind power), but also to scale up the industrial transformation of so-called critical minerals – lithium, copper, rare earth elements, cobalt, and nickel. These minerals are essential inputs for high-tech sectors such as semiconductors, electric vehicle batteries, solar panels, computers, smartphones, and national defense, all of which are expected to experience rising long-term demand. However, the way these strategic minerals will be utilized in the future – pure extractivism versus industrial and technological transformation – will determine whether they become a blessing or a curse for us. As Pessoa warns in his doctoral dissertation, if these windows of opportunity are not promptly and effectively seized, Brazil risks becoming locked into a model of green extractivism in the absence of appropriate industrial policy, replicating a core-periphery dynamic and “renewing and reinforcing a colonial relationship, one that can be understood as green [neo]colonialism” (2025, p.46).

The second policy implication is that it is long past time for Brazilian governments –regardless of their political-ideological orientation – to reposition the macroeconomic regime (monetary, fiscal, and exchange rate policies) as supportive of industrial policy. Brazil’s macroeconomic policy, based on the so-called macroeconomic tripod, tends to trap the economy in a tendency of high real interest rates and currency overvaluation. The results of our research show that this trap has contributed to the weakening of Brazil’s manufacturing sector in recent decades. It is true that, since the COVID-19 pandemic crisis, the Brazilian real has remained undervalued, but this recent cycle reflects a succession of external shocks such as the pandemic itself, the Ukraine war, and the instability caused by the Trump administration’s trade war. Once the current international instability subsides and global conditions improve, the absence of changes in Brazil’s macroeconomic regime could lead the Brazilian currency to resume its tendency toward overvaluation.

This requires adjustments to the macroeconomic policy framework, such that: i) the inflation-targeting regime becomes more flexible, balancing the objectives of price stability with sustained GDP growth; ii) fiscal policy moves away from the assumption of expansionary austerity – which, by presupposing the permanent freezing of real government expenditures, lacks empirical support – and instead embraces fiscal responsibility, where public spending (including interest payments on public debt) is programmed to ensure long-term sustainability of the gross public debt-to-GDP ratio while also enabling adequate investment in physical and human capital (infrastructure, education, health, and social programs); and iii) the floating exchange rate regime follows the lead of several Asian countries, rejecting passive “dirty float” approaches in favor of a managed float system. In such a regime, the central bank actively employs a range of instruments – spot and futures market interventions, and, in exceptional cases, ad hoc capital controls – to keep the real exchange rate at a competitive level (i.e. at the industrial equilibrium – that is, at the “optimum” rate), avoiding currency overvaluation.

Taken together, these recommendations function as mechanisms to neutralize Dutch disease in Brazil. In practice, they are essential for reversing deindustrialization, restoring economic development, and enabling the country to catch up to income and welfare levels comparable to those of developed nations.

• Note
  The authors thank Fabrício J. Missio, Luiz Carlos Bresser-Pereira and Edmar L. Bacha for their comments and suggestions, while disclaiming any responsibility on their part for the remaining errors.

Data Availability Statement

The entire dataset supporting the results of this study is available upon request from the authors.

• 1
  See The Economist (1977).
• 2
  See Iasco-Pereira and Morceiro (2024); Morceiro and Guilhoto (2023); Morceiro and Tessarim (2024); Nassif et al. (2018); Nassif et al. (2015); Nassif et al. (2020); Rodrik (2016), among others.
• 3
  For readers interested in a more detailed new developmentalist analysis of Dutch disease, see Nassif (2025, ch. 6).
• 4
  Franco’s (1998) article is the most accurate expression of the defense of this external integration strategy.
• 5
  According to the National Similar Law (in effect since 1938, but enforced in practice from 1968 onward), importers could request tariff exemptions provided that no similar product was manufactured domestically. Although the legal provisions required that government officials compare the price, quality, and delivery time of domestically produced goods with those of their international counterparts, in practice, the Foreign Trade Office (CACEX) made decisions on an ad hoc basis, routinely denying import requests whenever the mere existence of domestic production could be confirmed. For details, see Nassif (1995).
• 6
  In addition to the regulatory instruction, Instruction 113 of the Superintendency of Currency and Credit (SUMOC) was established in January 1955, which, among other measures, allowed the import of equipment and production goods without foreign exchange coverage.
• 7
  The import substitution-based development strategy also exhibited microeconomic weaknesses, such as excessive dependence on the technology and capital of multinational enterprises (notably capital goods and durable consumer goods industries), and limited innovative capacity. In manufacturing subsectors characterized by high capital-labor ratios, the absence of a well-calibrated balance between domestic protection and external competitive pressure led to industries operating at suboptimal scales, with average costs significantly above international levels. Nonetheless, despite these microeconomic inefficiencies, the growth performance of the Brazilian economy during the period remains indisputable. Rather than addressing these structural weaknesses through targeted reforms and a reorientation of industrial policy, the country shifted to a neoliberal strategy in the early 1990s.
• 8
  Brazil’s trade liberalization officially began in 1988 with a significant reduction in nominal import tariffs, particularly in the manufacturing sector. However, the reform had limited practical impact due to the continued presence of numerous non-tariff barriers – such as import restrictions on thousands of goods (included in the so-called “Anexo C”), many of which were blocked amid the exchange rate crisis. As a result, the initial phase of trade liberalization proved largely ineffective. For further details, see Nassif (2003).
• 9
  Kume (1996) observes that the acceleration of trade liberalization occurred concurrently with increased exchange rate exposure, driven by the appreciation of the Brazilian real against the dollar.
• 10
  A detailed discussion on the determinants of the real exchange rate can be found in Nassif et al. (2017).
• 11
  The entire database used in this study is available upon request from the authors.
• 12
  According to Hamilton (1994), when the variables in the model exhibit these properties, OLS remains a super-consistent estimator. For a formal demonstration, see Hamilton (1994, p. 587).
• 13
  For a detailed justification of the expected signs of these variables, see Nassif et al. (2017).
• 14
  The observed data for our dependent variable – the share of manufacturing value-added in total value-added (that is, the GDP) – is only available on a quarterly or annual basis. To address this limitation, we use a proxy variable for deindustrialization (IND): the monthly Physical Production Index for the manufacturing industry, published by the Brazilian Statistical Office (IBGE). This index is assumed to reflect changes in the industrial structure, as its weighting system is based on the value-added contribution of each product to the total value-added of the manufacturing sector. As a chained monthly index, it dynamically captures relative gains and losses in the weight of each product and, accordingly, determines the growth dynamics of the manufacturing industry. Over a long-time span, as the growth of the manufacturing industry accelerates (or decelerates), its contribution to total value-added increases (or decreases).
• 15
  Note that in the real exchange rate determination model analyzed earlier, the main variable associated with Dutch disease (the commodity price index) proved significant in explaining the long-term trajectory of the real exchange rate. This implies, therefore, that the use of the original (observed) RER should serve as one of the explanatory variables in the model of premature deindustrialization (Equation (2)).
• 16
  The variable TLI is built based on a measure of the import tariff. An import tariff is levied on the CIF (cost, insurance, and freight) value of the imported product, expressed in the local currency according to the exchange rate specified in the import contract. The nominal tariff statistics refer to the average of the entire tariff universe reported for each year. As our models are run on a monthly database, we chose not to replicate the nominal import tariffs twelve times, but to adjust them monthly according to the level of the monthly fixed base industrial production index (seasonally adjusted). When comparing the adjusted monthly tariffs with the annual average tariffs, we found that the values are not, of course, identical, but rather close. For database, see Appendix, Table A1.
• 17
  The variable FIN, constructed based on the indicator proposed by Lane and Milesi-Ferretti (2007), was also used by Bresser-Pereira et al. (2020) as a proxy variable for external financial openness. For details, see Bresser-Pereira et al. (2020, footnote 4).
• 18
  This conclusion was more explicit in the first version of the mentioned article. See Bacha et al. (2024).
• 19
  “Intuitively”, because between 1950 and 1980 – Brazil’s period of rapid growth – policymakers were not yet aware of the concept of Dutch disease.

REFERENCES

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Appendix

Table A1
Description of the data source

	Variables in Equation (1)
RER	Actual real effective exchange rate (June 1994 = 100) – Central Bank of Brazil (http://www.bcb.gov.br), series 11752.
Y	Real GDP per capita in US Dollars – elaborated by taking the annual Brazil GDP per capita in U.S. dollars (from Central Bank of Brazil series 21776) and transforming it on a monthly basis using Brazil’s U.S. dollar GDP (series 4385). Population estimated by the Brazilian Institute of Geography and Statistics (IBGE) – http://www.bcb.gov.br.
CI	Commodity price index – IMF commodity net export price index, individual commodities weighted by the ratio of net exports to GDP, rolling weights.
CA	Current account balance as a share of GDP – Central Bank of Brazil series 23079.
DIF	Short-term interest rate differential – difference between Central Bank of Brazil monthly interest rate series for SELIC from IPEADATA; and the U.S. T note 2 years, from IPEADATA (transformed to a monthly base).
IR	Stock of Brazil’s international reserves as a share of GDP – Central Bank of Brazil (series 3546) and Brazil’s GDP in U.S. dollars (series 4192).
CR	Brazil’s risk premium – EMBI Brazil sovereign foreign currency – Standard & Poor’s monthly series, IPEADATA. From July 2024 onwards, updated series applying the variation of CDS 5 years from https://br.investing.com/rates-bonds/brazil-cds-5-years-usd-streaming-chart/.

	Variables in Equation (2)
IND	Monthly Industrial Production index, seasonally adjusted, fixed-base 2002 = 100, Brazilian Institute of Geography and Statistics (IBGE).
RER	Actual real effective exchange rate (June 1994 = 100) – Central Bank of Brazil (http://www.bcb.gov.br), series 11752.
TLI	Trade liberalization – elaborated as nominal tariff adjusted for the monthly fixed base industrial production index (seasonally adjusted). Source for the nominal tariff: Database computed by Marta Castilho, kindly provided to the authors, and used in Castilho et al. (2025).
FIN	Financial openness – elaborated as the sum of gross financial flows as a percentage of trade flows. IPEADATA for gross trade flow and Central Bank of Brazil for the gross flow of IDE (12 months moving average).

• Editor responsible for the evaluation process:
  Luiz Carlos Bresser-Pereira

Publication Dates

• Publication in this collection
  10 July 2026
• Date of issue
  2026

History

• Received
  24 Feb 2025
• Accepted
  23 June 2025