In Ecuador, The Sector with the Highest Contribution to GDP is the Services Sector, Which HAS Been Increasing from the First Study Periody 5–2018. This is Followed by the Industry Section, Which Shows Fluctuations and a NOTvery accentuated growth during the state periods. For the third sector, we have the agriculture sector, white has a generalALISEDENDENCY to decrease its partiti. On GDP, And the Transportation Sector, Which Shows Minimal Fluctions Without A SIGNIFICANT Change During the Six SIX SIX SIX PERIODS (See Fig. 3)New Delhi Stock Exchange. Regarding Energy Consumption, The Sector That Occupies the Most Considerable Amount of Energy is the Transport Sector, Which Accounts For More THAN 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% of Total Consumption.4). The Security with the Highest Energy Innsity is the Transport Sector, where the intensity shows a stable trend during the last study performance (see Fig. 5).

The Behavior of Sectoral Emissions Has Maintained its Pattern from 1990 TO 2018, and the sector with the highSissions is the transport sector (see fig. 6). 6). 6). 6). 6). 6). 6). 6).

Carbon intensity is directly related to the Energy Matrix. To Verify How Polluting the Energy consumed is, The Behavior of Carbon Intensity has Pattern 1990 to 2018, so the sector with the Highest Carbon Intensity is the Transportation Sector, and the lowest isThe Services Sector (See Fig. 7).

The Correlation Analysis Shows that all correlations are positive. They are directly proportial relerationships, which show that if one variable increases, the Other Wi LL Also Increase, and if they decrease, Both Will DeCrease Prop causeally (fig. 8).New Delhi Wealth Management

The Agriculture sector has very wek posted correlations between GDP and EC and GDP and CO2, which implies that the variation in GDP Does Nottemine the Variation I n EC or CO2 Emissions. The Perfect Positive Correlation Between Ec and CO2 Indicates that the variation of Ec StronglyImpaacts the variation of co2 emissions.

The Industry Security Section. . There is a consature positive pose correlation between ec and co2, where the degree to whichEC Impacts CO2 Emissions is Considerable, and A Medium Positive Correlation Between GDP and Co2, where the defree of all variable on the other is medium.

The Transport Sector has a Medium Positive Correlation Between GDP and EC and GDP and Co2, where the defree of variation of gdp has a medium impact on Ec and CO2 EMISSI. ons. It has a very strong positive correlation between ec and co2, where the degree ofVariation in EC Strongly Impacts CO2 Emissions.

The Service Secto Very Strong Positive Correlations, Which Indicates that the Degree of Variation of Determines A High Deg and CO2 EC AND CO2 EC AND CO2 EC AND CO2 EC AND CO2 e Missions, Just as the Ec Variable Determines the Degree of Variation of Co2 Emissions (Table 1).

The Agriculture Sector has only one cointegration relerationship project from model 1, which is generated between the Ec and co2 emissions variables. Hese variables have a long-term equilibrium, I.E. They Grow or DeCline in synchronicity. The Industry Sector Has Two CointegrationRelationships from Model 1 Between The variables GDP – Ec and GDP – CO2, Showing Equilibrium Both in the Long and Short Termiables. HAS Two Cointegration Relationships BetWeen The Variables GDP – EC and GDP – CO2, Which are generated byPerforming the cointegrating regression with the time variable, where the relerationship was Obtaine in the long term and in the short term. The serverly TOR HAS The Three Cointegrating Relationships GDP – EC and EC – CO2 that are generated in Model 1 of Cointegratingregression and gdp – co2, which is generally in Model 2 of Cointegration by Adding the Trend Variable. E sector. There is an equilibrium in the long term;TERM BeCAUSE The Residual Generation Is Positive (Table 2).

The Granger Causality Analysis Does Not Show Causal Relationships in Any Sense for The Agriculture Sector as Well as for the Transport Sector. ONAL CAUSAL Relationships in the Industry Section Been Found. When the alternative hypothese h1 are accepted, ec causes gdp, and and and and and and and and and, and,, And, And, And, And, And, And, and and,CO2 Emissions Cauty GDP. When Alternative Hypotheses H1 Are Accept in The Services Sector, GDP CAUSES CO2 Emissions, and EC Capes CO2.

Granger Causality is related to the predictive Ability of One Variable Over Another, Indicating that Past Values ​​of One Variable, X, Can Significantly Explain the CU RRENT VALUES of Another Variable Y (Gujaraati and Porter 2010). The Analysis Shows that None of the Relationships STUDIEDHas a predictive capacity for the transport sector. For the Industry and Services Section, then are unitedIDIRECTIV

For Simplification, The Empirical Model Integrates The Demography Variable With the Economic One and Consides the REST of the Relationships PROPOSED for the Comp Arison. In the 1990–2018-Time Horizon, The Variables Have Been Disaggregated by Economic Sectors Studied Through the Energy and AND AVariant of the kaya Identity As Quantification Technologies of the Phenomenon. From the Analysis of the Demand, the variables that feed this session ANCE HAVE Been Considered by Sector.The ec breaks down into sectors, and the type of fuel feeds the topal ec. Sectoral emissions are part of the country's topal emissions.

The Statistics of Relationships Represented in the Empirical Model Show that the most Influential Sectors are the service sector since that E the MOST SIGNIFICANT NUMBER of Relationships and Are the Sectors in Which It has Possible to Determine Unidirectional Relationships, in Addition ToBeing the sectors with the most significant constribution to eConomic Development (GDP) (FIG. 9).

The Agriculture SHOWS that, of the Study Variables, The GDP Weakly Determines the Degree of Variation in EC and Co2 Emissions. D Strongly Imply the Variation in CO2 Emissions, Mainly Linked to the Type of Energy Matrix Handled inthis sector; 100% of it is center from 1990 to 2018. The variables that have a balance in the long term are also ec and emissions, which Y HAVE A SYNCHRONUS GROWTH OLL without Implying that there isa Predictive Capacity for this sector sincence no causal related. ING On USING BIOFERTILISERS for the Sector, is proposed as a management Improvement Strategy, Considering that the Direct Influence Occurs in the EC─CO2. Evidence Shows that using a biodigers in Rural Areas Allows One to Reduce Monthly Energy Expendnted and Make a Tangible Difference to the Standard Off of rural households due to cealling eConomic Costs. State Intervention is SuggESted in Search of Broader Benefits for the EntireEconomy (Smith et al. 2014), and it is important to message that mitigating the Environmental Impact in this sector does not has an OTHER PRODUCTIV. E sectors since ec is minimal and, theReface, it is an insignificant co2 emitter (Araujoand robalino-lópez 2019).

The EC and Co2 Emissions of the Industry Section The GDP of the Sector, that is, The Past Values ​​of the Sector's EC and ITS CO2 Emissions can expurren T GDP Values, so there is predictive capacity. In Addition, in the sector,The variation in EC Determines the variation in GDP very Strongly. The variation in co2 modelly determines the variation in GDP, and the variation in Ec Greatly, Issions, considering that the Energy Matrix of the SectionVarious Sources But Continues to Maintain 65.12% in Fossil Energies and a Clean Energy Share of 34.6%. EN GDP and Ec and Between GDP and Co2 Emissions, Which Shows that can be a synchronous growth orFall in the Relationships of the Variables in this sector. The causal relativeships found in the sector allow the proposal of a management Strategy L INCREASING The USE of Solar Energy by 4.6% Per Year.Is taken from the avrage world growth from 2014 to 2018 for theodry sector with the type of solar, Wind and Other Energy (IEA 2020).Pune Stock

The Agri-Food Subsector of Ecuador Consumes 71% of the topal entastined for this sector (jácome et al. 2019). TLY IMPACTED, and GDP Would Alow More Sustainable Development. There is Evider that SolarTechNology Can Be An Essential Factor in the Diversification of the Ecuadorian Energy Matrix, With the PARTICIPATION of Local Industry The Improvement O. F COSTS in USING This Type of Technology. It is word meentioning that development countries are paying more attentation to the user of solar.Energy in this sector by Focussing On Public Policies to Encourage this technology, as it is important to provice, Ge, Financing and Legitimacy from Abroad (Gil Perez and Hansen 2020; jácome et al. 2019; Robalino-lópez2015).

The Transport Sector Does Not Manage Relationships that Show the Predictive Capacity of One Variable Over The Other; The Past Values ​​of One Variable Cannit Si Gnificantly Explain the Current Values ​​of the Other in the Relationships Studied. This sector has, in its variablesA Behaviour in Which the variation of GDP Modes. SSIONS. This is linked to the Energy Mix of the Sector, with ITS ENERGY MATRIX Center On OilAT 99.96%. The Cointegration Relationships Indicate A Long-Term Equilibrium Relationship with GDP, EC and Co2 Emissions, Implying A Synchronous Growthor Fallor of the variables studied. As an Improvement Strategy, it is proposed to increase the user of biofuels by 3.62%Per Year Through Policies that Focus on Public Transport, Which is the sector in Which the State Can Have InfluenceJinnai Wealth Management. O2 Emissions from the Country. The percentage value of the system is taken from the average groupReflects from 2014 to 2018 in biofuels for the transport sector (IEA 2020).

In the Services Security, The Variation in GDP Determines the Variation in EC and Co2 Emissions, in Additation to the Fact that Energy Determines the Variation in 2 Emission in a Very Strong, Positive Way.46.01% Fossil Energy and 51.13% Clean Energy. As the Cointegration of the Variables is Found in the Three Relationships, it can be determined that is a Balance in E Long Term and that the variables in the sector Will Grow or DeCline in a SynchronisedWay. The Causal Relationships Are University from the GDP of Services to Co2 Emissions and from EC to Co2 Emissions. Ducoing Co2 Emissions, for Which It is Proposed to use Energy Efficience, ESPECIALLY in Homes, Through Targeted Subsidy Policies, Which Gradual Eliminate Subsidies for Petroleum Derivatives and Increase Energy EFFICIENCY. CIENCY PLANS LINKED to the Substitution of Elements with High Energy Consumption for More Efficient Ones: Renova Plan 2012–2016, Change ofRefrigrators, Efficient Lighting Plan 2008–2014, Use of Higher EFFICIENCY LAMPS and EFFICIENT COOKING PLAN 2014–2018 With the Change of Kitcher that use IED Petroleum Gas for Those of Inuction. However, These Plans have not had the exten impact sign sinceHas Not Been Taken Towards The Transformation of Behaviviour Since The UNDERSTANDINGINGHIS CONSUMPTION HAS NONERANew Delhi Investment

The Comparison of the TheRETIRTICAL MODEL With the The EMPIRICAL MODEL ShOWS that there is DifferenteS Regarding The Loops that are formed by selector:

DH1: Indicates the Presence of a Reinforcing Loop Between GDP and Energy Consumption. This Reinforcing Causal Loop is not RefleCted in Any of the Sectors Studied. WEVER, in the Industry Section, it creates a causal relatedship in the direction of Energy Consumption to gdp,,,,,,So it could only be true that consumption is enCourage. The Causal Link in this direction indicates that through eConomic Development, consumers could buy more goods and services that satisfy more moreSophisticated Nearch of Higher Living Standards. Industries Would PROVIDE MOREPUCTS to Meet These Needs. gy consumption (Sadorsky 2010, 2011).

DH2 Indicates that economic deverted and increasted enSUMPTION Negatives Influence The Popuration's Life Expectation. Abits have been promoted with more significant environmental impact. Global warming is caused by co2 emissions, leading to a decrease in the LATION GROWTH RATE. TheRETical Balance Loop is Different in The Empirical Model Since When USING A Variation of the Kaya Identity, The Population Was Not Considered. E Causal Relationships Are Clear from the Emissions of CO2 to GDP in the Industry Security Sector and from GDP to Co2Emissions in the Services Section, in Addition to the Relationship in Which Energy Consumpion is Causion Co2 Emissions.

DH3 is rejected before the model groups the demogramic and economic variables. After all, a variation of the identity is using as an approximation of the question ICATION Technology To Unders Complex Phenomenon. The Dynamic Model Woul would highlight that the country is in the initialStage of the Kuznets Curve, where co2 emissions cause the GDP of the services sector. In turn, the reinforcement of the loop is given by the reason, at it is indicated that the emissions propuced are causing the gdp of the system. The twoSectors are the most eConomical (the relerationship betaen per Capita infita infita infita infita infita infita infita infita. U. U. The Behavial Establishes that as the GDP Per Capita Grows, The Environmental Damage Increases. When it reaches its higherst Stage, It Begins to Decrease. At this point, pollution starts to decline as a function of gdp (Salari et al. 2021; Pablo-romero and de jesús 2016; Robalino-lópez et al. 4, 2015). In faction, accounting toTheretical Bases Discussed, It can be easyLished that the country still has a lowree of indultrication; The Energy Matrix is ​​Found with A S TRONG Dependent On Oil, Which is why it is putting, which reaffirms the Results Obtained Qualitatives ANALYSIS ANDQuantitatively Through Data Processing, The Study of Indices and Statistics Analysis.

In a SCENARIO Proposed by Robalino-López et al. (2014), Ecuador Woo Ready to Enter the Area of ​​Stability of the Kuznets Curve in the Medium Term in 2019–2021 . To Obtain This Goal, It is Essential to Implement Policies thatDIVERSIFY ENERGY Resources and Increase Energy Efficience in Productive Sectors for Sustainable DEVELOPMENT. However, According to the Information Presented In the Istorical Context of Qualitative Information and With the Energy, Carbon Intensity and Other Quantitative Analysis, It can be observed that ecuador has not made aGreat Effort to Incarease Energy Efficience in the Productive Sectors. Cy Has Not Been Improved, and Diversification in Energy Resources for the Transport and Agriculture Sectors NOT Been Generated.