The 2008 GFC had a long-term negative impact on performance in developing countries. Growth of per capita GDP was negative in the period 2015–2019 in Latin America and the Caribbean (LAC) and Sub-Saharan Africa (SSA) regions (Table 1).

Growth of per capita GDP in Europe and Central Asia (ECA) was only one fourth of what it was before the crisis. The effect on Asia was much smaller. Growth in East Asia and the Pacific (EAP) fell by a third, whereas it actually increased in South Asia (SA) (see Table 1). The external balance deteriorated in all regions (Table 2), deteriorating by about 2% of GDP, except in SSA and the Middle East and North Africa (MNA) where it deteriorated much more – by 4 percent and 8 percent of GDP, respectively.

Exports of goods and services (XGS) as a percentage of GDP fell in all regions and were lower in the period 2015–2019 compared to 2001–2007, except in LAC and SA (Appendix, Table A1). However, gross fixed capital formation (GFCF) was by and large maintained (Appendix, Table A2); it actually increased in EAP and ECA. Maintaining GFCF while growth of GDP is declining implies either that the structure of the economy is changing in the sense that more funds are invested in sectors with a higher capital output ratio or there is considerable excess capacity waiting to come into production when conditions improve. The capital intensive sector that has attracted investment is infrastructure, particularly large-scale projects.

In brief, the GFC resulted in a deterioration of the economic condition of developing countries with lower growth of per capita GDP, a decline in the share of XGS in GDP, and a worsening of external balance.

Economic performance of the BRICS countries mirrors that of developing countries. The rate of growth of per capita GDP in 2015–2019 was negative for Brazil and South Africa and almost zero for Russia, but declined only marginally in China and India (Table 3).

The relatively good growth performance of China and India is deceptive as the analysis of annual growth rates shows a considerable decline in growth rates in these two countries (Figure 1). Growth rates have been declining in China since 2007 and in India since 2016. This poor performance of the BRICS countries has not met expectations that high growth in BRICS would help maintain economic activity in the world economy. The poor growth performance can be related to the deterioration in the external balance (EB). The EB in the last period 2015–2019 was worse compared to the first period of 2001–2007 for all the BRICS countries (Table 4).⁷

The BRICS countries have, however, maintained high levels of investment (Appendix, Table A3). The G20 at the London summit in 2009 recommended higher public expenditure and easy money to counter the recessionary effects of the financial crisis. Such expansionary monetary and fiscal policies in BRICS resulted in high levels of government investment,⁸ as well as private investments due to lower interest rates. But such policies would also result in higher deficits in the EB, which is what we observe in BRICS.⁹

Despite the poor overall export performance (Appendix, Table A4), BRICS fared well in exports of information and computer technology (ICT) goods and services (Appendix, Tables A5, A6). BRICS’s good performance in exporting ICT goods and services augurs well for the future as trade in such services is growing more rapidly than trade in goods. But such exports were too small and the correlation between exports of ICT and growth of GDP was not significant.¹⁰ By and large, trade links of the BRICS economies with the world economy have weakened.

BRICS were expected to play an increasingly important role in the world economy as their share of both world GDP and trade was increasing. In the immediate aftermath of the crisis of 2008–2010, the share of each of the BRICS countries in world GDP increased leading some analysts to expectations that BRICS might lift the world economy out of the recession that accompanied the crisis (Table 7). But such hopes could not be fulfilled.

Even though over the longer term, namely between 2001–2007 and 2015–2019, their share of world GDP increased by almost 60% (Table 7), most of this increase was due to rapid growth in China and, to a lesser extent, in India. The relative size of GDP in Brazil, Russia and South Africa decreased between 2001–2007 and 2015–2019 (Table 7). Furthermore, the average income of residents of two of these countries, Brazil and South Africa, decreased relative to the average per capita GDP of the world, being almost 20% lower in relation to world per capita GDP in 2015–2019 compared to the period 2001–2007.

The BRICS countries, however, fared better in trade. Their share of world trade has increased and the share of trade in their GDP has also increased. BRICS substantially increased their share of world exports of goods and services in the periods 2001–2007 and 2015–2019; China’s and India’s share of world exports almost doubled (Appendix, Table A7). Brazil also increased its share of world trade in goods and services. The share of South Africa remained almost unchanged. The share of Russia, after an increase, substantially fell in the last period of 2015–2019, so that in the last period it was the same as in the initial period. (Appendix, Table A7).

The share of BRICS countries in world merchandise trade increased by almost 70%, more than their share of exports of goods and services (Appendix, Table A8). China more than doubled its share and it outperformed other BRICS countries. While India also increased its share substantially, the shares of Russia and South Africa remain almost unchanged. The share of BRICS countries in world service exports also increased (Appendix, Table A9), though the increase was less than for merchandise exports. While India had the largest share of world exports of services, China increased its share the most. Furthermore, the share of South Africa declined.

However, the share of exports of goods and services in GDP behaved differently for some of the BRICS countries than for the world in general. The share increased for the world, despite a dip in the period 2015–2019 (Appendix, Table A10). But among the BRICS countries, it increased only for India and South Africa, while for the other three countries, particularly China, it decreased.¹¹ In other words, only India and South Africa are becoming more export-oriented.

In the initial period of 2001–2007, the share of merchandise exports in GDP was higher for China, Russia, and South Africa than for the world (Appendix, Table A15). But this share decreased for the BRICS countries, with the exception of India and South Africa. By 2015–2019, only South Africa had a higher share of exports than the world on average. The share of service exports in GDP increased for the world and is much higher for the world than for the BRICS countries. The share of service exports in GDP increased for Brazil and India but remained unchanged for Russia and South Africa, and actually decreased for China.

One of the objectives of BRICS is to foster South-South economic cooperation in addition to expanding economic cooperation among themselves.¹² A major feature of the exports of developing countries is the growing share of developing countries in world trade and the increasing importance of South-South trade (Agarwal, 2013). The BRICS’s share in the total trade of the South increased from 28% in 2000 to 44% in 2017; the total trade of BRICS with South grew at a compounded annual growth rate of about 11% during 2000–2017 (Kumar, 2018).

Four of the BRICS countries send more of their exports to developing countries than the average for all G20 developing country members, and three of them send more of their exports to developing countries than the average for all developing countries (Appendix, Table A10).¹³

Annual data on macroeconomic variables are obtained from World Bank indicators for the sample period from 1992 to 2019. We investigate the relationship between growth of per capita GDP, the share of GFCF in GDP, and the share of external balance in GDP. In Model 1, we estimate the causal relationship between the variables of GDP per capita, external balance, and GFCF for each of the BRICS countries for the period from 1992 to 2019. Further, we also analyze this relationship by considering exports and imports separately in Model 2. These two models are specified as follows:

Model 1: PCI_𝑡−1 = 𝛼₀ + 𝛼₁𝐺𝐹𝐶𝐹_𝑡−𝑚 + 𝛼₁𝐸𝐵_𝑡−𝑚 + 𝜆₁𝐸𝐶𝑇_𝑡−1 + 𝜀_𝑡 (1),

Model 2: 𝑃𝐶𝐼_𝑡−1 = 𝛽₀ + 𝛽₁𝐺𝐹𝐶𝐹_𝑡−𝑚 + 𝛽₁𝑋_𝑡−𝑚 + 𝛽₁𝑀_𝑡−𝑚 + 𝜆₂𝐸𝐶𝑇_𝑡−1 + 𝜇_𝑡 (2),

where PCI – log of per capita GDP, GFCF – log of gross fixed capital formation, EB – log of (Imports/Exports), i.e. EB > 1 for current account deficit and EB < 1 for current account surplus, X – log of exports of goods and services, M = log of imports of goods and services, ECT = error correction term ε_t, µ_t = the stochastic error term and α₀, β₀ = constant or intercept term (t-m) = (year t – lag order), where m is the order of lag length.

All variables must be stationary to avoid the problem of spurious regression. The Augmented Dickey Fuller (ADF) reveals that all the variables are non-stationary at levels and stationary after taking the first difference (Tables A16 and A17).

Since the variables are non-stationary at levels and stationary at the first differences, the variables can be co-integrated. The Johansen test of cointegration suggests the existence of cointegrating equations in both Model 1 and Model 2 for all BRICS countries (Appendix, Table A18). The lag length for cointegration test is selected using standard criteria (Appendix, Table A19).

Therefore, we use the Vector Error Correction Model (VECM) to estimate the short-run and long-run relationship between the variables, as defined above in equations (1) and (2).

Short-run model looks like:

Model 1: ∆ 𝑃𝐶𝐼_𝑡−1 = 𝛼₀ + 𝛼₁ ∆ 𝐺𝐹𝐶𝐹_𝑡−𝑚 + 𝛼₁ ∆ 𝐸𝐵_𝑡−𝑚 + 𝜆₁𝐸𝐶𝑇_𝑡−1 + 𝜀_𝑡 (3),

Model 2: ∆ 𝑃𝐶𝐼_𝑡−1 = 𝛽₀ + 𝛽₁ ∆ 𝐺𝐹𝐶𝐹_𝑡−𝑚 + 𝛽₁ ∆ 𝑋_𝑡−𝑚 + 𝛽₁ ∆ 𝑀_𝑡−𝑚 + 𝜆₂𝐸𝐶𝑇_𝑡−1 + 𝜇_𝑡 (4).

The cointegrating equations (long-run model) when PCI is normalized to unity looks like:

Model 1: 𝐸𝐶𝑇_𝑡−1 = 𝑃𝐶𝐼_𝑡−1 − 𝜑₁𝐺𝐹𝐶𝐹_𝑡−1 − 𝜑₂𝐸𝐵_𝑡−1 + 𝜑₀ (5),

Model 2: 𝐸𝐶𝑇_𝑡−1 = 𝑃𝐶𝐼_𝑡−1 − 𝛾₁𝐺𝐹𝐶𝐹_𝑡−1 − 𝛾₂𝑋_𝑡−1 − 𝛾₃𝑀_𝑡−1 + 𝛾₀ (6),

where 𝛼₀, 𝛽₀, 𝜑₀, 𝛾₀ = constant or intercept term.

The VEC residual autocorrelation test confirms that there is no autocorrelation, i.e. the errors are not serially correlated (Table A21). The Jarque-Bera test of normality confirms that the errors are normally distributed (Table A22).

The results of the short-run regression are presented in Appendix (Table A19). As far as the Granger causality test for short-run causality is concerned, we cannot reject the null hypothesis that there is no causal relationship between per capita GDP (PCI) and other variables in the short run-in Model 1 (Appendix, Tables A23). In Model 2, we find a significant short-run causality between per capita GDP and other variables for some BRICS countries (Appendix, Table A24).

Now we summarize the short-run causality (Table 8). China is a case of traditional growth dynamics; investment leads to growth. Neither domestic savings nor the external balance is constraints. Russia demonstrates an internal demand constraint, as investments lead to an increase in exports. South Africa demonstrates a bi-direction relationship between GFCF and growth of per capita income, a typical multiplier accelerator relation; investment-led and growth-led imports, which supports the conclusion on growth-led trade made by Rani and Kumar (2019). India shows a dominant external constraint; increased imports lead to growth, substantiating the conclusion of Maitra (2020). In India, imports positively affect exports, which is indicative of the share of import content in exports, as the exports and production of the industrial sector in India are heavily dependent on imports of petroleum, capital goods and other essential inputs (Maitra, 2020). Brazil has basically performed poorly since the 1982 debt crisis, despite different policy regimes, and this is reflected in the fact that there is no causality leading to growth, substantiating the result of Srinivasan (2016) and contrasting the results of Bakari et al. (2019).

Since the coefficient of the error correction term is negative and significant for Brazil, India and China (Models 1 and 2), this indicates that there is a convergence towards the long-run dynamics compared to short-run. Thus, long-run relationship exists between per capita GDP and other variables in these countries. However, there are no long-run relationships in Russia and South Africa.¹⁵ The cointegration equations for countries where long-run relationships between GDP and other macro variables exist are presented in Appendix (Tables A25 and A26) and a summary of the results is shown in Table 9.

In the long run, Brazil, China and India show a classical relationship between GFCF and growth. In addition, in Brazil, we find that the external balance adversely affects GDP but positively affects GFCF, as the government seeks to re-ignite growth when the external balance is favorable. While exports have a positive effect on per capita GDP as the external constraint is relaxed, imports have a negative effect on per capita GDP in Brazil; this supports the findings of Bakari et al. (2019). In China, investment has a positive effect both on growth and the external balance, reflecting its export-oriented development strategy. In India, investment has a positive effect on GDP. Exports have a positive effect on per capita GDP, but imports have a negative effect on per capita GDP, reflecting that for almost the entire period, the country has run an external deficit and has a long history of external crises in 1967, 1966–1968, 1973, 1981 and 1991. The negative impact of import on per capita GDP in the long run in India contradicts the findings of Maitra (2020) and Marjit and Santra (2016). Imports positively affect exports, which is indicative of the import content in exports and the dependence of Indian exports on imported inputs not only in the short run but also in the long run (Maitra, 2020).

To summarize, we find that GFCF has a positive effect on per capita GDP in Brazil, India and China in the long run. In all three countries, exports have a positive effect on per capita GDP but imports have a negative effect, a typical import multiplier effect. Per capita GDP, in turn, has a positive and significant effect on exports in Brazil. The external balance adversely affects GDP and positively affects GFCF in Brazil, while it has little effect on either GDP or GFCF in China and India. Imports trigger exports in Brazil and India, whereas in China, exports trigger imports. GFCF has a negative effect on exports in Brazil and India. Domestic output does not respond rapidly to GFCF demand, and output is diverted to meet investment demand. GFCF crowds out exports.