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International Journal of Engineering Technology and Management Sciences Website: ijetms.in Issue: 1 Volume No.8 January - February – 2024 DOI:10.46647/ijetms.2024.v08i01.010 ISSN: 2581-4621
@2024, IJETMS | Impact Factor Value: 5.672 | Page 71
Specifying The Study Of Trade And Convergence
Of BRICS Economies In Post Pandemic Era
1Ravindra Kumar, 2Pavnesh Kumar, 3Leena Sharad Shimpi, & 4Om Prakash Verma
1
PhD Research Scholar, Department of Management Sciences, Mahatma Gandhi Central University Bihar.
1
ORCID ID
:
https://orcid.org/0000-0002-5496-9007
& 1Email: ravindra2019bbau@gmail.com
2
Professor, Department of Management Sciences, Mahatma Gandhi Central University Bihar.
3
Associate Professor, Department of Commerce, Babasaheb Bhimrao Ambedkar(Central) University
Lucknow,
UttarPradesh.
4PhD Research Scholar, Department of Commerce, Govt. V.Y.T. PG. Autonomous College,
Hemchand Yadav University, Durg, Chhattisgarh.
Abstract
This research paper examines how trade, income distribution, and convergence among the BRICS
countries have been affected by the formation of the BRICS economies. Trade and convergence rate
relationships have been examined using intra-trade organization, panel unit roots testing, and single
difference techniques. An estimated convergence meter between the major trading partners of the
BRICS countries and themselves has been calculated in the post-COVID-19 trade openness era.
The investigation's conclusions demonstrated that the BRICS countries came closer together over
the investigation's duration. However, no evidence of a connection to the formation of the post-
BRICS economic union appears to exist. The post-trade reform examination of the BRICS countries
produced different results with respect to trade and convergence. The panel unit roots test results
also show that, with the exception of the Indian economy and import-based groups, conditional
convergence are visible in the BRICS alliance and all export-based groups. Additionally, flawless
convergence has been confirmed in every BRICS nation. The paper so suggests that the BRICS
countries should participate in competitive trade and investment activities in the post-pandemic
globalization era.
Keywords
:
BRICS Nations; Intra Trade; Convergence; Indian Economy; Panel unit root tests; COVID-19
Introduction
There is no definitive link between trade and economic convergence. Numerous studies have
speculated on it, such as those by Jena and Barua (2020), Peron and Rey(2012), Liu (2009), Ben-
David (1996), Slaughter (2001), and Milutinović (2016). Evidence from theory and experimentation
have solidly established this connection. Furthermore, neo-classical theory is where the idea of
income convergence arose, according to Solow (1956). However, the significance of global trade is
over looked by this notion. The idea of endogenous development positions that trade results in
income convergence and technological transfers that generate knowledge spillovers, ultimately
reducing or widening the income gap between trading nations (Romer,1986;Lucas,1990). However,
because of declining marginal returns to capital, developing nations eventually overtake
industrialized ones in terms of growth rate. This is the neo-classical perspective. Nonetheless,
endogenous growth theory denied decreasing marginal returns to capital since countries saw
increasing returns to scale from investments in human and physical capital, such as education and
skills trainings. Additionally, the factor price equalization theorem, the international flow of
technology, and trade in capital items (e.g., Romer, 1986, Ben-David, 1997; Grossman & Helpman,
1990;Lucas,1996; Rodrik,1996; Slaughter, 1997) can be used to quantify the effect of trade on
income convergence.
An additional contention is that trade recognized for its ability to stimulate economic expansion.
International Journal of Engineering Technology and Management Sciences Website: ijetms.in Issue: 1 Volume No.8 January - February – 2024 DOI:10.46647/ijetms.2024.v08i01.010 ISSN: 2581-4621
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The factor price equalization theorem of trade theories states that free trade results in the
equalization of the factor price along with the distribution of wealth among nations. For example,
the Chinese economy is mostly driven by exports (e.g., Siddharthan & Narayanan, 2016). In
today's worldwide economy, trade is a vital tool for promoting economic progress. Furthermore,
trade may result in the creation or diversion of companies within the bloc. According to Lohani's
most recent publications(2020a), trade creation occurs between India and the BRICS nations.
According to a different study by Lohani (2020b), incremental IIT trade and intra-industry trade
(IIT) happened at a higher level of aggregation. Furthermore, the data from the marginal IIT index
demonstrated that IIT has increased over time in the BRICS countries. Furthermore, IIT has been
assisting the BRICS nations in enhancing their trade ties. The economy of the BRICS nations have
yet another important focus of this research. We attempted to monitor the convergence of income
and trade among the BRICS nations in this study. In order to assess income convergence across the
BRICS countries, this study looks into the following questions in light of trade and income ties:
First, are the BRICS nations' trade and income trends consistent with one another? Second, since
the formation of the organization, have trade or financial integration with in the BRICS countries
changed in any way? Last but not least, are there any signs of trade or income convergence among
the main BRICS trading partners? Furthermore, since the foundation of the BRICS union, have
there been any changes in trade as well as revenue convergence with each of the BRICS countries'
principal trading partners? Thus, this essay has attempted to respond to the questions raised above.
Furthermore, the concept of income convergence was expanded upon by Barro and Sala-i-
Martin(1991), Solow(1956), and others in their earlier research.
Afterthen, Ben-David(1996) and Slaughter(2001), employed comparison-in-difference and single
difference experimental techniques to try and investigate the relationship between trade and income
convergence. But the difference-in-difference approach is not included in this investigation. This
study uses the single difference technique, as per Ben-David (1997), in order to keep things straight
forward. According to Carlino and Mills (1993) and Das et al. (2019) have shown that panel unit
roots tests are utilized to verify for both conditional and absolute convergence.
Review of Literature
Numerous research (e.g., Barro & Sala-i-Martin, 1991; Quah, 1993; Sachs & Warner,1995; Sala-i-
Martin, 1996) attempted to use cross-country regression to investigate the relationship between
trade and per capita income. Several economists, however, disagree with this approach; Ben-
David(1996),for example, rejected it, therefore took into account of BRICS nations, including
trading partners as well as trading nations. As mentioned in works like Ben-David (1993, 1996) and
Ben-David and Kimhi (2004), which both explicitly address the trade and convergence argument,
using the single difference methodology to assess the trade and convergence relationship offers an
alternative way of examining this effect. Additionally, Hakro and Fida(2009) assessed intra-group
convergence, and Slaughter (2001) computed convergence adopting the difference-in-difference
approach. Ben-David (1993), also employed the single difference equation approach to study the
post-World War-II trade liberalization phase, namely the loosening of qualitative limitations with
regard to the chosen set of countries. National income convergence is driven, the report claims, by
the relationship amongst trade liberalization and trade volume between EFTA and EEC nations.
Ben-David (1996) also looked at trade and income convergence in nations with significant trading
partners. In particular, when it comes to trade in products, the analysis found that per capita income
and key trading partners were convergent.
Ben-David (2001), went on to compare and contrast the findings of Slaughter's (2001) study,
offering an examination of the countries has been chosen for both the intervention group and the
control group, in addition to the sample years of data , employed as concerned. As such, this study
established the foundation for further investigations into trade and income convergence. Ben- David
and Kimhi (2004) also looked at the volume, pace, and wealth disparity of trade with the main
trading partners or group (the 25 richest nations) of the NAFTA, EFTA, and EEC trade
International Journal of Engineering Technology and Management Sciences Website: ijetms.in Issue: 1 Volume No.8 January - February – 2024 DOI:10.46647/ijetms.2024.v08i01.010 ISSN: 2581-4621
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blocs.Therefore,135 import-side pair nations and 125 export-side pair nations make up the study
samples in this regards. Using the single differential technique, the investigation was carried out at
both intra-group and bilateral integration. According to the study's findings, developing nations
export to developed nations. The findings thus pointed to a rise in the rate of convergence (among
the participating nations) as a result of trade concerned. Additionally, Cyrus(2004), examined the
relationship between trade and cross-national income disparity using a variety of methods,
including Granger causality tests, random effect models, and fixed effect models. The results
indicated that trade eventually lessens wealth inequality. Zhang examined the ASEAN economies in
a study that was published in 2001, based on empirical evidence, the key forces behind East Asian
cooperation between 1960 as well as 1996 were trade and market forces that were influenced by
foreign direct investment. Additionally, Puyana and Romero's (2004), research findings showed that
the NAFTA countries were separating and that there was no consistent indication of economic
convergence or integration.
However, Choi (2009), discovered that as trade intensity ratios increased in tandem with a nation's
closeness to another and linguistic similarity, per capita income began to converged. Hakro and
Fida (2009), have conducted a study on a few South Asian nations. The difference-in-difference
method and intra-trade convergence were applied. The findings demonstrated that trade
liberalization significantly influenced convergence. Fascinatingly, throughout the post-liberalization
era as per capita income quickly converged. Liu (2009), found however, that the causal relationship
between trade and per capita income is reversed. The fact that income convergence for 165 nations
occurred in unique product categories between 1965 and 2000 (at five-year intervals) lends
credence to the idea that trade drives income convergence. Peron and Rey (2012), however, found
that there was not a comprehensive convergence in the Indian Ocean Zone from 1950 to 2008.
Furthermore, the wealthiest countries remain poorer while the wealthier countries get comparatively
richer when wealthy countries like Singapore, Malaysia, Australia, Mauritius, Thailand, and
Singapore exit the convergence club.
While bilateral and trade agreements had minimal impact on most countries, opening up the market
contributed to an increase in the flow of manufactured goods. Additionally, Dey and Neogi (2015),
examined the convergence of income within China and the other SAARC nations. Between 1970
and 2011, the sigma and unconditionally beta convergence methods were employed. The ideas that
the addition of China might accelerate the rate of financial convergence and that economic
cooperation had enabled the region's per capita GDP to converge more quickly were backed by the
study's outcomes. On the other hand, Milutinović (2016), examined the relationship between
international trade and income convergence for the member states of the European Union and
discovered that, in 2001, 2005, 2009, and 2013, a significant amount of bilateral trade had an
impact on income convergence. In order to evaluate the economic progress of various nations,
Gnangnon (2019), also looked at economic growth, transitional convergence (TCC), and trade
policy space (TPS). Between 1995 and 2015, 150 countries made up the study's sample size. After
applying the system GMM model to the data analysis, it was shown that (tps) significantly impacted
(tc) and had a favorable effect on economic growth.
In addition, the (tc) increases in tandem with the (tps). Further using the convergence hypothesis,
Das et al. (2019), discovered that the BRICS countries catching up had no effect on any of the two
sub-periods. However, the first sub-period showed conditional convergence. The survey also
asserted that there has been a gradual decline in the economic differences between the BRICS
countries. Furthermore, between 1995 and 2019, Jena and Barua (2020), looked at the contributions
that trade and government spending—both inside and outside the EU—had to the convergence of
per capita income in the EU. A panel data model was used to construct and mediate the in-equality
indices. The findings showed how trade openness and government spending affected the EU's
eventual convergence in per capita income.
Because of external trade and government spending, the gap in per capita income amongst EU
members has also narrowed. Furthermore, there has been no disruption to the convergence trend
International Journal of Engineering Technology and Management Sciences Website: ijetms.in Issue: 1 Volume No.8 January - February – 2024 DOI:10.46647/ijetms.2024.v08i01.010 ISSN: 2581-4621
@2024, IJETMS | Impact Factor Value: 5.672 | Page 74
caused by the financial crisis. Lastly, trade and convergence for the BRICS countries had only been
the subject of a few numbers of studies, including Das et al. (2019). However, the current study
encourages more investigation because it minimizes the significance of commercial growth and
trade barriers.
Objective of the Study
To Examine the trade and income convergence relationship, in BRICS Economies in post
pandemic era
To Evaluate the intra trade bloc and post-liberalization scenario, with reference to BRICS
countries
Research Methodology
This research had been done on the basis of secondary data. A time series chronology of per capita
GDP for the years 1991–2022, expressed in constant 2010 values, was made available by the World
Bank in the World Development Indicator (WDI, 2019), WTO and International Chambers of
Commerce (ICC). From1991 to 2022, the International Monetary Fund's yearly releases of the
Directorate of Foreign Trade Statistics (DOTS) provided the trade flow data at nominal prices
(IMF,2022).
Data Analysis and Discussion
The rates of economic growth of the BRICS economies varied from 1991 to 2022. As per the
Figure -1, shows the gradual narrowing of the economic growth disparities across the BRICS
countries. The worldwide recession of 2008–2009, which saw significant drops in economic growth
in South Africa, Brazil, and Russia, were also depicted on this graph. Conversely, the economies of
Brazil, Russia, and South Africa all had slower growth than those of China and India.
Figure;1: GDP Growth Rate of BRICS Countries,(Year1991–2022).
Figure-1. BRICS Countries' GDP Growth Rate,1991–2022.
Source of Data; The author (self-calculation using the World Bank data base wdi as of March 2022).
Figure -1, depicts the income distribution between the major trading partners of the BRICS
countries as well as within the BRICS bloc, both of which have declined overtime. Income
GDPYoYGrowthratein %
Figure-1; YoY, GDP Growth Rates of BRICS Nations
20
15
10
5
0
-5
-10
-15
-20
Year
Brazil
China
India
Russia SouthAfrica
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
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dispersion is calculated using the mean dispersion among groups, such as intra-bloc and important
trading partner groups that comprise in the BRICS countries in the present year. As explained in the
article on the creation of the trading group and list of countries (Tables 1-3), show the main trading
partners of the BRICS countries. The 2010 research period, which began after the BRICS were
founded, is divided by the vertical line. Furthermore, after trade liberalization was enacted in each
of the BRICS countries, the income inequality with those countries' main trading partners has
decreased, as seen by this graph.
Moreover, China initiated commercial liberalization in 1987, and South Africa, Brazil, and India
soon followed in 1991–1992. Nevertheless, following its 1991 independence from the USSR,
Russia started to liberalize its trade policy in1992. As a result, in1991 is seen as the year that the
BRICS nations liberalized period consistency. According to this mathematical equation,
I
i
,
t
I
t
I
i
,
t
1
I
t
1
where Ii,t refers to country i’s log per capita GDP in year t and It denotes average log per capita
GDP of a trading group in year t. reflects coefficient of convergence (divergence) of the model.
1
indicates convergence whereas
1
shows divergence.
The Hadri (2000), LM test's null hypothesis statement states that all panels are therefore stationary,
whereas the alternative hypothesis statement states that at least one panel has a unit root or is non-
stationary. This research utilizes the assertions made by Carlino and Mills (1993), to test for
convergence in panel unit roots tests method by accounting for the differences between the average
per capita GDP of the group of countries and the per capita GDP of the country. The test had been
applied to the panel unit roots since the group of nations is both homogeneous and heterogeneous.
Xe
,
i
,
t
1
Xe
,
i
,
t
2
Xe
,
i
,
t
Be
e
,
i
, ---------------(2)
where
1
represents coefficient of pre-BRICS situation,
e
1
e
2 ,
represents post BRICS
situation
and 2 represents the marginal effect whether post-BRICS situation is
“higher/lower” than the pre- BRICS situation.
The unit root test was carried out because the data are belongs to time series. Tests for unit roots
such as the augmented Dickey-Fuller (ADF) tests were carried out. As a pool regression, we
examined the individual unit root test. Ben-David's (1996), study also employed this examination
results. In this case, X is replaced by Z. To ascertain if the convergence process is stochastic,
conditional, or absolute, the panel unit root test was utilized. It was also used to assess the stability
of the variation in per capita GDP across national borders. If the changes in GDP per capita are
constant, it suggests convergence. Conversely, if it is non-stationary, it indicates that the differences
in GDP per capita are diverging. If more than two countries are included in the analysis, it is also
anticipated that the average income of the BRICS countries will converge with the countries that are
trading partners.
The panel unit root test eliminates the possibility of misleading regression issues that come from
single regression on the pertinent cross-sections in addition to offering results with higher statistical
correctness. Conditional convergence hypothesis arises from panel unit root tests that take into
account fixed individual effects; absolute convergence hypothesis arises from panel unit root tests
that take into account them without fixed individual effects (see Carlino & Mills, 1993; Das
etal.,2019).
In addition, the structure of the panel time series data examined in this article , denoted by huge T
and small N, where T stands for "time" and N for the total number of cross sections or observations
in the panel data framework. Consequently, we also looked at the data's panel unit root tests. As a
result, the results are more trust worthy.
To confirm the panel unit roots testing, first-generation panel unit roots tests were employed. Thus,
International Journal of Engineering Technology and Management Sciences Website: ijetms.in Issue: 1 Volume No.8 January - February – 2024 DOI:10.46647/ijetms.2024.v08i01.010 ISSN: 2581-4621
@2024, IJETMS | Impact Factor Value: 5.672 | Page 76
cross-sectional independence is assumed by the unit root tests of the first generation panel. In this
study, we tested the stationarity of panel unit roots using four different methods: the Levin, Lin, and
Chu (henceforth LLC; Levin et al., 2002), Im et al.,2003), and FisherType tests. The Maddala and
Wu (1999), tests assumed that the data had a unit root in the model Pesaran, Shin, and Im
(henceforth IPS). However, an alternative hypothesis statement was distinct. Assuming the
alternative hypothesis, the tests by Maddala and Wu (1999), LLC (2002), IPS (2003), and Fisher
Type assume that a portion of the panels is stationary. Additionally distinguished are the IPS (2003)
and Fisher Type tests, which are similar to the Maddala and Wu(1999) tests. The ADF were utilized
to estimate the aggregate p-value for each time series unit root test, and the Maddala and Wu
(1999), test was used to average the panel over each unit π. In contrast, ADF or PP were applied to
every panel. The three tests listed above may reject the unit roots null hypothesis even in cases
when one series was stationary.
As an illustration of this, consider the following equation :
Zit it it it …………..(3)
Here πit represents a random walk, that is, it ijt 1 it and it and it are zero mean
i.i.d. normal errors.
Analysis of Empirical Results
Intra-trade Results
The computation of intra-Bloc income convergence among the member countries based on intra-
trade volume is shown in (Table -3). Essentially, the BRICS countries are grouped according to the
disparity in their GDP per capita. Birth rates of intra-group trade blocs or post-BRICS economic
blocs (
1
2
0) show the negative sign (see Table- 3). This implies that convergence
has been observed. The coefficient is not statistically significant, though. In addition, the pre-
BRICS coefficient has a negative value
(
1
0
)
, and this confirms that convergence is
taking place in the pre-BRICS scenario. . However, the post-bloc formation
(
2
0
) the
size is extremely little and statistically negligible, and the coefficient shows a positive
sign. Convergence is generally occurring in the pre-BRICS context. Consequently, we
will need to wait a few more years to see the income convergence in connection to
trade in order to collect data indicating convergence among the BRICS states in the
post-BRICS alliance. Additionally, trade integration contributed to the reduction of
the wealth gap among the BRICS countries even prior to the formation of the
organization.
Export-based Results of BRICS Countries
An examination of each country's trade with its principal trading partners has been done in order to
monitor the effects of trade liberalization on the BRICS economies. Between1990 and 1992, almost
all of the BRICS economies liberalized their trade policies, with the exception of China, which
started doing so in 1979. As a result, we decided to use it in the year 1991 as the cutoff year for
anonymity. In 2010, the BRICS economic union came into full force. Consequently, beginning
2010, we have incorporated an intervention dummy variable in the post-BRICS phase to examine
the pace of integration of the BRICS economies with the global economy.
Import-based Results of BRICS Countries
International Journal of Engineering Technology and Management Sciences Website: ijetms.in Issue: 1 Volume No.8 January - February – 2024 DOI:10.46647/ijetms.2024.v08i01.010 ISSN: 2581-4621
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The import-based group results for the BRICS nations revealed that (Table -2), pre-BRICS bloc
coefficient is trending downward.
(
0 ) );
The data indicates that the economies of all the BRICS countries, with the exception of Brazil and
Russia, are
showing signs of convergence.
Table1.Results shows of Intra-BRICS Nations.
Treatment country Period of study
(
)
(
)
(
)
Intra- BRICS 1991-2022
-0.028*** -0.003 0.01
Source of Data
: calculated by authors
Note :
At the 1% and significance levels, respectively, are indicated by ***.
Table-2: Results is based on of Export-based BRICS Nations.
Treatment
country
Period of study
(
)
(
)
(
)
Brazil
1991-2022
-0.022***
-0.000***
0.015***
Russia
1991-2022
-0.024***
0.000***
0.018***
India
1991-2022
0.976***
-0.000***
0.007***
China
1991-2022
-0.025***
-0.000***
-0.001***
South Africa
1991-2022
-0.020***
-0.000***
0.003***
Source of Data: Authors Calculations
Note: Significance at 1% level is indicated by***, respectively.
Disparity with important import allies from 1991 until 2020. Beneficial outcomes are also
demonstrated by the post-BRICS bloc coefficient sign
(
2
0
)
; This shows that the economies of the
other BRICS countries—aside from the first two—are separating, despite the economies of Russia and
India BRICS countries converging with important import partners. Nevertheless, analyses are available
because the magnitudes of the coefficients vary from small to high. This indicates that, aside from Brazil and
South Africa, the economies of the BRICS are approaching large import partner countries in a similar
manner, whereas those of the latter two are following different
paths shows that post-BRICS bloc formation coefficients are negative
( (
< 0 ).
Panel Unit Roots Tests Analysis Results
Tests of panel unit roots have been used to identify the stochastic convergence process. Applying
the test, we ran the tests both with and without an intercept to ascertain the presence of absolute
convergence, sometimes referred to as the" catching-up process," and conditional convergence. The
income differential (or gap) data contains a unit root, which is why the findings are also computed
at the initial difference. The data's homogeneity has thus been examined at first difference. ADF
and panel unit roots tests of stationary, among other unit root tests, are shown in (Tables:1-3) with
their respective results. The series became stationary at first difference order, as indicated by the
results of the ADF individual unit root test (Table-3), while the panel stationary or panel unit root
test indicated that the series was stationary at the level and first difference. Therefore, compared to
individual unit root testing, panel unit root or stationary tests are more successful. Moreover,
employing panel unit root tests on intra-bloc findings, absolute and conditional convergence were
identified. That is why the BRICS nations are catching up to their trading partners throughout the
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course of the period (refer toTable-2).
Panel unit root tests conducted on export-based groups, however, showed that all import-based
groups emerged with absolute convergence, whereas all other groups—aside from the Indian
example—showed conditional convergence. Export-oriented groups were therefore falling behind
the BRICS countries in the post-liberalization era (see Table -3). On the other hand, conditional and
absolute convergences were observed fore very import-based group according to panel unit root
tests.
Table-3. Results of Export-based Groups by. Panel Unit Roots Test
Random Walk
Country
Group
LLC
MW
IPS
Hadri
At Level
At 1st Diff.
Level
At 1st Diff.
At Level
At 1st Diff.
At Level
At 1st Diff.
Brazil
2.81*** 4.88***
31.76*** 69.59***
India
10.31*** 8.12***
167.66*** 122.92***
China
11.84*** 4.35***
172.43*** 60.71***
Russia
5.52*** 22.37***
86.01*** 522.31***
South Africa
7.89*** 4.84***
163.71*** 66.15***
Intercept only
Brazil
2.21*** 5.26***
7.02 65.11***
1.14
5.42***
37.67*** 2.15**
India
0.93 0.11
18.53 11.91
2.05
2.78
43.01*** 43.53***
China
3.38*** 6.07***
29.51*** 67.64***
1.98
5.79***
35.84*** 2.92***
Russia
3.61*** 19.81***
57.74*** 577.31***
0.88
23.80***
42.09*** 1.25
South Africa
0.23 6.34***
4.91 110.67***
3.81
7.24***
47.15*** 6.25***
Intercept and trends
Brazil
1.81**
4.15***
24.01**
48.45***
1.24
4.05***
14.76***
6.27***
India
2.42***
2.05**
47.96***
41.76***
2.64***
2.21***
22.84***
21.68***
China
1.42*
5.20***
14.59
63.05***
0.13
5.24***
16.95***
2.97***
Russia
1.42*
17.05***
84.95***
521.65***
4.07***
23.82***
12.23***
0.24
South Africa
1.24*
5.93***
16.57
97.65***
0.21
6.24***
25.79***
9.42***
Source of Data : authors calculations.
Note ;- Here the symbol*, **, and*** indicate significance at 10%, 5%, and 1% levels, respectively, and the values
are from the
statistical test.
Conclusion
The main goal of this research paper was to examine the convergence of trade and per capita
income for the BRICS countries. The intra-bloc influence and the impact of major trading partners
on the per capita income of the nations have been examined in relation to trade's effects on
convergence rates using the single difference technique. The convergence statistics between the
BRICS nations and their principal trading partners were calculated from 1991 to 2022, the post-
trade liberalization period of the BRICS nations. The BRICS countries converged at that time, the
paper had been indicated the results. However, the data concerning the formation of the post-
BRICS economic bloc suggests a very small relationship.
Every country in the BRICS group had a different outcome from the post-trade liberalization
analysis. One indication that the Chinese economy is convergent in the fact that, unlike the other
BRICS economies, all of them have diverging economies when it comes to their main export
partner nations. The economies of all the BRICS, with the exception of South Africa and Brazil,
International Journal of Engineering Technology and Management Sciences Website: ijetms.in Issue: 1 Volume No.8 January - February – 2024 DOI:10.46647/ijetms.2024.v08i01.010 ISSN: 2581-4621
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are, nevertheless, convergent with important import partner countries, indicating a divergence as
well. In this concerned the panel unit roots tests on intra-bloc groups validate both conditional
convergence and absolute convergence (catching up during the period). While the results for the
other export-based groups—aside from the Indian instance—show conditional convergence, all
export-based groups exhibit absolute convergence. All import-based groups appear to exhibit both
conditional and absolute convergence, according to the results of the BRICS import-based groups.
Following liberalization, the BRICS countries are currently catching up to export- and import-based
companies. In conclusion, the study supports Michel Temer , the president of Brazil, when he
officially announced, "BRICS countries aim to achieve economic convergence on these issues."
Xinhua, reported in the year 2017 in this concerned scenario.
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