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American Journal of  Environmental
Economics (AJEE) 

Unraveling the Intricate Nexus of  Philippine Environment and Economy: 
An Empirical Analysis Using Multiple Regression

Leomar M. Sabroso1*, Jan Mariel A. Duyo2, Aristeo C. Salapa3

Volume 2 Issue 1, Year 2023
ISSN: 2833-7905 (Online)

DOI: https://doi.org/10.54536/ajee.v2i1.1640
https://journals.e-palli.com/home/index.php/ajee

Article Information ABSTRACT

Received: May 06, 2023
Accepted: May 23, 2023
Published: May 24, 2023

A progressive country has sacrificed many things to achieve its goals, including using natural 
resources leading to environmental degradation. This study aimed to find out the status of  the 
Philippines concerning environmental factors, specifically Carbon Dioxide (CO2) Emissions, 
and how it is intertwined with various economic aspects, explicitly Gross Domestic Product 
(GDP) per capita, Primary Energy Use, Renewable Energy Consumption, Population 
Growth, and Foreign Direct Investment. The study employed multiple regression analysis to 
measure the relationship between environmental conditions and economic growth factors. 
The data secondary data used in the study was obtained from World Bank (1990 – 2014). 
Results yielded that the impact of  GDP per capita has a positively significant relationship 
with carbon emission influencing a substantial increase. Consumption of  primary energy 
use by households or businesses has extensive environmental consequences, especially with 
substantial population growth. Moreover, the utilization of  renewable energy emerged as 
the most obvious approach the country should come up with to combat climate change and 
environmental deterioration as increased human activity necessitates the utilization of  the 
environment and natural resources. Researchers suggest significant investments in climate 
change adaptation and combating for the country, considering the Philippine’s strong 
potential for clean energy generation to avoid or even contend with the predicted ecological 
catastrophe by 2100.

Keywords

CO2 Emissions, GDP Per 
Capita, Primary Energy Use, 
Renewable Energy Consumption, 
Population Growth, Foreign 
Direct Investment, Philippines

1 University of  Mindanao, Philippines
2 Davao Doctors College, Philippines
3 University of  Southeastern, Philippines
* Corresponding author’s e-mail: leomar_sabroso@umindanao.edu.ph

INTRODUCTION
The environment is the most vital component of  
existence, and as a country, the environment has become 
increasingly crucial. Progress has greatly impacted our 
environment in one way or another. Human involvement 
and invention are aspects that contribute to a country’s 
advancement and economic development, leading to 
either prosperity or distraction (Beckerman, 1992). The 
world’s complexity also impacted the environment’s 
health, which was mostly influenced by mankind’s growth 
and development (Castiglione et al., 2015).
Similarly, the elements employed in industrialization are 
typically nonrenewable leaving residuals that may pose 
a hazard and result in negative externalities (Aydin, 
2019; Tiba & Omri, 2017). Environmental protection 
lags behind a country’s quicker economic development, 
thereby impacting the environment (Shi et al., 2019). 
Pollution is the main reason that leads to environmental 
degradation, which grows in the first stage but decreases 
in the second (Liu & Zhang, 2018) that presented the 
concept of  the Environmental Kuznet Curve and how 
it impacts the environment as the economy is booming 
(Abdollahi, 2020).
Environmental degradation in high income countries is 
lessen compared to middle-income and low-income such 
that usage of  nonrenewable shows significant increase 
in the latter (Naqvi et al., 2021). The gap between high-, 
middle- and low-income nation is evident as developed 
countries can invest and allocate resources to sustainable 
renewable infrastructures compared to developing 
nations where income and resources are limited (Arndt et 

al., 2018; Barger & Mattson, 2016; Elheddad et al., 2021)
The fundamental argument for reducing carbon dioxide 
emissions is the necessity for government action and 
policy ramifications (da Rocha Lima Filho et al., 2021; 
Nordmeyer, 2018). The disparity between economic 
progress and environmental degradation has been a point 
of  contention.

The Objective of  the Study
The main goal of  this study is to determine the relationship 
between the environmental conditions and the economic 
growth factors and confirm whether the hypothesis of  
EKC Theory worked in the Philippines. 

METHODOLOGY
This study employed a quantitative method (Creswell, 
2013; Greene, 2013; Perreault, 2011) which examines the 
link between factors that may be quantified to evaluate 
objective hypotheses. Multiple Regression Analysis 
measures the relationship between the dependent 
and independent variables. Independent variables are 
variables whose values are known that can explain 
the dependent variable (Dhakal, 2018; Frieman et al., 
2022). In other words, Multiple regression is a statistical 
method for examining the connection between numerous 
independent variables and a single dependent variable. 
Multiple regression analysis aims to predict the value of  
a single dependent variable by using known independent 
variables (Moore et al., 2006). 
Likewise, several studies have used multiple regression to 
measure the relationship between the environment and 

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Am. J. Environ Econ. 2(1) 24-28, 2023

economic development which elaborated the validity 
used in the study (Abdullah, 2015; Hosseini et al., 2019; 
Wijaya, 2021)
The study makes use of  the available secondary data from 
World Bank. These secondary data obtained was from the 

year 1990 to 2014 (a 25-year observation) in measuring the 
carbon dioxide emission (CO2) and the economic factors 
thereof  (Abdouli & Hammami, 2020). Furthermore, the 
variables used in the study and its descriptions are as 
follows:

Variables Description
Carbon Emission (CO2) Annual CO2 emissions (per capita)
Gross Domestic Product per Capita (GDP) GDP per capita (constant 2015 US$)
Primary Energy Use (PE) Energy use (kg of  oil equivalent per capita)
Renewable Energy Consumption (RE) Renewable energy consumption (% of  total final energy consumption)
Population Growth (PG), Population growth (annual %)
Foreign Direct Investments (FDI) Foreign direct investment, net inflows (% of  GDP)

Source: The World Bank (2021)

The gathered data was analyzed to regress and  measure 
the relationship between the variables. Each predictor 
value is weighed, the weights denoting their relative 
contribution to the overall prediction.
Y=α+β1X1i+β2X2i+β3X3i+β4X4i+ .….+βnXni
Here Y is the dependent variable, and X1,…,Xn are the 
n independent variables. In calculating the weights, a, 
b1,…,bn, regression analysis ensures maximal prediction 
of  the dependent variable from the set of  independent 
variables. This is usually done by least squares estimation 
(Moore et al., 2006).

Model Specification
The regressor econometric equation model of  the study 
is as follows:
Yi=β0+β1X1i+β2X2i+β3 X3i+β4X4i+β5X5i+μi
Where: 
Yi=  represents the carbon dioxide (CO2) emission of  the 
i-th country; 
Β0 = the intercept term; 
βis= efficiency parameters to be estimated; 
X1i = the gross domestic product per capita; 
X2i = primary energy use; 
X3i = renewable energy consumption; 
X4i= population growth; 
X5i= foreign direct investment; and 
μi = represents the error term.

RESULTS AND DISCUSSIONS
Multiple regression was run to predict Carbon emissions 
from GDP per Capita, Primary Energy Use, Renewable 
Energy Consumption, and Foreign Direct Investment. 
The r2 and the adjusted r2 value indicate that the 
proportion of  variance in the dependent variable can 
be explained by the independent variables with a value 
of  0.9864 and 0.9828, respectively, these independent 
variables explain 98% of  the variability of  the dependent 
variable. Furthermore, the output shows that the 
independent variables statistically significantly predict the 
dependent variable, F (5, 19) = 275.93, p < 0.000, thus, 
the diagnostic of  the regression model is a good fit of  
the data and four out of  the five independent variables 

statistically significant to the prediction, p < 0.05. 
Similarly, the findings illustrate that GDP per capita 
(8276.662, p < 0.0270) has a significant positive association 
with carbon emissions, implying that a percent increase in 
GDP per capita would result in higher carbon emissions. 
This is supported by Apergis and Payne’s (2014) analysis, 
which shows that per capita GDP and CO2 emissions 
have a long-run relationship, denoting that as GDP per 
capita rises, CO2 emissions will rise proportionately. 
Asumadu-Sarkodie and Owusu (2017), on the other hand, 
contradicted the findings, claiming that a percent rise in 
GDP per capita will reduce carbon dioxide emissions in 
the long run, based on EKC’s concept that in the long 
term, as a nation develops, the environmental effect 
reduces.
Furthermore, the Primary Energy Use (219898.9, p < 
0.0000) shows a significant increase in carbon emissions, 
proving that carbon emissions will increase as we continue 
using energy from coal, oil, natural gas, and other sources. 
According to Zhou and Gu (2020); Asumadu-Sarkodie 
and Owusu (2017); Dhakal (2009), the usage of  fossil 
fuels and other energy sources increases CO2 emissions 
from households, cities, provinces, and the country as 
a whole, considering non-renewables are used in the 
majority of  goods (Adams & Nsiah, 2019; Alharthi et 
al., 2021). Fisher and Irvine (2010), on the other hand, 
propose that the effect of  energy consumption to carbon 
emission might be reversed if  group-based interventions 
are applied. The intervention to address carbon emission 
is capable of  20% estimated reduction in a year and result 
in long-term changes in pro-environmental behavior.
Renewable Energy Use, on the other hand, has a negative 
significant association with carbon emissions (-4.93E+07, 
p < 0.0020), meaning that increasing renewable energy 
use will reduce carbon emissions which rendered as an 
aimed by every nation to combat climate change. This 
result is in line with Alharthi et al. (2021), who found 
that using renewable energy reduces carbon emissions 
significantly and would continue to do so as the amount 
expands. Moreover, the urgent need to transition from 
non-renewable to renewable energy consumption makes 
deploying energy-saving technologies even more crucial, 

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particularly in Asia’s emerging economies (Hanif  et al., 
2019). This transition is crucial because it directly impacts 
environmental quality (Balsalobre-Lorente & Leito, 
2020). Consequently, by implementing energy-efficient 
technologies, organizations can effectively address this 
need while conserving energy, enhancing efficiency, and 
fostering their own growth, profitability, and sustainability 
(Hossain & Pk, 2023).  However, according to Nguyen 
and Kakinaka (2019), not all countries may expect a 
reduction in CO2 emissions when they use renewable 
energy; it was noted that low-income countries, when 
compared to their high-income counterparts, increase 
CO2 emissions as they increase renewable energy use. 
The relationship between population growth and carbon 
emission has shown highly significant (0.9601143, p 
< 0.0000) which means that through the increase in 
human activities, carbon emission increases. The findings 
coincide with the study of  (Dong et al., 2018; Knapp & 
Mookerjee, 1996; Sulaiman & Abdul-Rahim, 2018) in 
which in the short-run the human activities contribute 
to the increase in the carbon emission however  (Ohlan, 

2015; Pratama, 2021) would suggest otherwise that not 
only in the short-run can carbon emission be increase 
because of  population growth but also in the long-run. 
Several authors have claimed that population growth 
positively significantly intensify carbon emission (Lawal, 
2019; Masoud Abouie-Mehrizi, 2012; Rahman et al., 
2020). Contrary to the findings, (Begum et al., 2015) stated 
that population growth does not have any significant 
association or sufficient evidence that it can positively 
affect carbon emission.  
Foreign investment has no significant influence on 
carbon emissions, pertaining to the results. Other 
literature review has discovered a strong link between 
FDI and CO2, with estimations determining that FDI has 
a beneficial impact on CO2 emissions (Ewane & Ewane, 
2023; Hou, et al., 2021; Wu & Zhang, 2021; Zhou et al., 
2018). Gunarto (2020) verifies that there is no significant 
relationship between FDI and CO2 emissions, indicating 
that it is not a contributor to the country’s CO2 emissions, 
in accordance with the study’s inferences that FDI has no 
significant influence on CO2 emissions.

Table 1: The Estimation Result Between CO2  and Economic Factors
Carbon Emission Coef. Std. Err. t P>t
Constant -1.09E+08 1.36E+07 -8.01 0.0000***
GDP per Capita 8276.662 3445.604 2.4 0.0270**
Primary Energy Use 219898.9 18984.41 11.58 0.0000***
Renewable Energy Consumption -4.93E+07 1.39E+07 -3.54 0.0020***
Foreign Direct Investment -852065.7 673231.3 -1.27 0.221
Population Growth 0.9601143 0.1047229 9.17 0.0000***
F(5, 19) 275.93
Prob > F 0.0000***
R-squared 0.9864
Adj R-squared 0.9828
Root MSE 2.00E+06    

Note: *P <0.10, **P < 0.05, ***P < 0.01

CONCLUSION
Based on the obtained results, the following conclusion 
was drawn: 

1. The impact of  GDP per capita has a positively 
significant relationship with carbon emissions influencing 
a substantial increase. As the nation grows and develop, 
the result of  that realization is detrimental to the 
environment.

2. Consumption of  primary energy use by any 
particulars such as household or businesses have extensive 
consequences to the environment. As a developing 
country, the high volume of  energy consumption 
used by the different sectors heightens environmental 
degradation.

3. The utilization of  renewable energy was the most 
obvious approach humans could come up with to 
combat climate change and environmental deterioration. 
Increased usage of  renewable energy reduced the 

country’s carbon emissions.
4. Increased human activity necessitates the utilization 

of  the environment and natural resources whenever the 
population grows. These human activities exacerbate 
negative impacts on the environment and intensify 
carbon emissions.

RECOMMENDATION
In line with the outcomes discovered in the study, the 
area of  renewable energy would be an interesting factor 
to delve deeper into. With a negative relationship with 
carbon emissions, it would be an important environmental 
dynamic for the country to invest in, considering the 
Philippines strong potential for clean energy generation. 
Additionally, with the worrying predictions of  the 
country’s ecological catastrophe by 2100 if  significant 
investments to climate change adaptation is not made by 
2020, more studies in the field of  climate change solution 

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should be prioritized, leaning more towards gearing 
the agricultural and industrial sectors in developing 
equipment, policies, and practices that encourage 
sustainability for future generations. 

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