was developed through a panel data model to identify the determinant variables of inclusive economic growth.

Annual data of the main macroeconomic and social variables were used for a sample of 14 Latin American

countries (Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Honduras, Mexico,

Panama, Paraguay, Peru, and Uruguay); the study horizon comprises 25 years, between 1995 and 2019. The

following variables were found to have a direct influence on inclusive economic growth: public spending and

international trade; the study also showed that inflation, unemployment, and the presence of crises have a

negative impact on inclusive economic growth. Moreover, an additional public expenditure of 1% implies an

increase of 0.100% in inclusive economic growth, and for each positive variation of 1% in international trade,

inclusive economic growth responds with an increase of 0.144%.

introduced in 2000 by Kakwani & Pernia, [1], to

refer to growth that favors the most vulnerable by

enabling them to participate actively in economic

resources need to be made available so they can be

distributed equitably and fairly to expand

opportunities for future generations, [2]. In contrast,

Jalles & Mello, [3], consider that although economic

growth brings prosperity, the benefits are not always

evenly distributed in society; in this line, the authors

exemplify the experience of Latin America, which,

although it has maintained steady growth between

1990 and 2000, this did not imply an improvement

in income distribution in the region. According to

growing behavior of inequality existed in the world;

inequality using the income ratios of the percentiles

and deciles of the population. The most important

data on inequality worldwide is the one gathered

and compiled by Piketty and his collaborators, [6],

published in the World Inequality Database (WID),

describing the participation of 1% and 10% of the

population with higher incomes as well as the

participation of 50% of the population with lower

2021, 25.2% of the income generated in Latin

America accounted for 1% of the population with

the highest income (Top 1%), compared with 21.5%

in 2000; that is to say, an increase of 3.7 percentage

units is appreciated. On the other hand, it can be

seen that the 10% of the population with higher

incomes (Top 10%) of Latin America absorbed

58.5% of the income generated in 2021, which was

a nearly identical percentage to the year 2000.

Likewise, in 2021, 8.8% of the income generated in

in 2021; however, in this period, 1% of the

population with the highest income in Latin

America increased their participation to 25.2% in

the income distribution, a level relatively higher

than the rest of continents, [7].

been able to reverse the distribution of income;

similarly, to be an improvement in economic growth

and the trend towards equal per capita income, the

investment must be made in human capital, thus

achieving sustainable human development over

time.

inequality, and environmental factors in Latin

America, which demonstrate that, despite the

economic growth seen over the years, and the

1.1.1 Socio-economic and Environmental

Situation in Latin America

1.1.1.1 Poverty and Multidimensional Poverty

According to the World Bank, [20], countries that

is a dynamic phenomenon, being that people who

manage to live on USD 6 a day, which is slightly

above the poverty line, are 40% likely to become

poor again. Informality or unprotected low-

productivity jobs make it harder for people to escape

poverty or not fall into it. Along these lines, Deaton,

[21], affirms that poverty has not improved by

comparison with the growth of countries, stating

that there is an inconsistency in the data available on

poverty and reality, as many wealthy families do not

according to the poverty incidence rate to 1.90

dollars per day (% of the population) between 1990

and 2019 for the regions of Europe and Central

Asia, East Asia and the Pacific, South Asia, Middle

East and North Africa, Sub-Saharan Africa, and

Latin America and the Caribbean. It can be seen that

East Asia and the Pacific is the region that has best

managed to reduce their poverty levels. At the same

time, Latin America did the same, reducing the

poverty incidence rate from 15.2% in 1990 to 3.7%

[26], mention that according to this index, in Latin

America, about 38 million people lived in

multidimensional poverty before the pan-demic, a

figure that represented 7.2% of the population of the

region; this means that approximately 7 out of every

100 Latin Americans experience at least 4 of the 10

hardships measured at once Furthermore, according

to Santos, [27], the multidimensionality in poverty

in the Latin American region highlights the

incidence of the COVID-19 pandemic, as people

that the solution to deal with the health, education

and living standards dimensions of the IPM does not

depend solely on monetary transfers.

1.1.1.2 Inclusion, Exclusion, and Inequality

Krasota & Melnyk, [28], claim that inequality has

always existed in societies; and that, along with

development, inequality has been responsible for

dividing society into different strata. The authors

demonstrated that socio-economic inequality is an

inequalities, and maintaining growth through equal

opportunities for the whole society. Social inclusion

guarantees equal access to social services and

economic resources and the participation of all

members of society in the political, social,

economic, and civic aspects of life, [28].

that social exclusion happens when people are

marginalized from participating in social activities.

Along these lines, Cruz-Saco, [31], mentions that

opportunities; for example, not getting the

opportunity to get a job will not allow us to receive

a salary and, therefore, this will lead to other

deprivations leading to greater poverty and what it

entails. Finally, the author adds that the success of

Western countries is because they were able to

concluded that the highest levels of the GINI index

are observed in Latin American countries. Also,

there are other indicators, such as the Theil index,

proposed by Henry Theil in 1967, which measures

inequality, having as an advantage that it can be

broken down into subgroups; this is because it takes

the basis of the concept of entropy; also, this index

"complies with the additive decomposition

property," characteristic that differentiates it from

other indices by allowing "to know what percentage

inequality, among them that it is independent of

population size and scale and can be broken down

into each of its elements. In this line, according to

INEI, [41], Latin American countries have very high

rates of exclusion generated by inequality in income

distribution and poverty; because of this, these

countries are characterized by their disintegrated

and fragmented societies.

1.1.1.3 Environmental Factors

enables strong growth and prevents climate change

from having a negative impact on the future

economy. Kamah, Riti & Bin, [43], demonstrated

that inclusive growth and environmental quality

have an inverted U-shape relationship, which means

that environmental quality deteriorates at an early

stage of inclusive growth. However, environmental

quality improves as inclusive growth increases after

reaching the threshold point. On the other hand, Ge

& Li, [44], demonstrated that environmental

mention that one of the most important renewable

energy markets in the world is located in Latin

America thanks to its abundance of geothermal

energy, sun exposure, water resources, wind, and

biomass; however, the region lacks technology and

resource verification, although taxes are also

important; however, the author adds that low levels

of tax collection and transfers constrain the

redistributive impact of the Fiscal policy in

developing economies. For its part, Stiglitz, [34],

states that a better-regulated financial system and

more progressive taxes are needed to achieve

greater equity and strengthen economic

performance. Along these lines, Lee, Park & Lee,

[51], point out that fiscal policy is an effective tool

systems; however, in developing countries, these

systems are less developed, and therefore, they have

a lower redistribution, mainly due to a lower ratio

between tax revenues and GDP. Also, there is

greater dependence on indirect taxes and less

comprehensive social safety nets. Nevertheless,

many economies have used tax policies to achieve

inclusive growth and, through them, have achieved

distributive and progressive effects, [52]. An

important piece of evidence about the influence of

income, property, goods and services, international

trade, and social contributions taxes.

are different ways in which inequality damages the

economy, mainly considering that high inequality

weakens aggregate demand; adding that this

situation is aggravated by the deficient actions of the

monetary authorities in dealing with weak demand;

a hyper-expansive monetary policy due to the

reduction of interest rates and the relaxation of

wages, consumption, and total spending among

households. In this line, Furceri et al., [55], found

that an expansive monetary policy decreases income

inequality. On the contrary, a contractive monetary

policy increases it, its impact being much greater

than the expansive policy’s. However, expansionary

Heshmati et al., [52], consider that the main drivers

of income inequality are international trade policies,

globalization, education, labor market reform, and

technological change, adding that there is no

panacea for achieving inclusive growth.

real income and trade opening of its members and

other Latin countries, [61]. As a basis for this event,

the analysis is performed in the subperiods 1995-

corresponds to inclusive economic growth (Y),

measured as the difference between real economic

growth (2010=100) and the percentage change in

the net Gini coefficient, and independent variables

including public expenditure (X1), represented by

the percentage change in real public expenditure

(2010=100), inflation (X2) calculated as the

generalized least squares (GLS):

β1>0, β2<0, β3<0, β4>0, β5<0

Finally, to decide between (3) and (5), the Hausman

test is used, whose null hypothesis is that the

estimators of random effects and fixed effects do not

differ substantially and implies that the random

effects model is more efficient.