CO2 EMISSIONS PANEL VAR APPROACH Snia Almeida Neves, Antnio Cardoso - - PowerPoint PPT Presentation

▶
co2 emissions panel var approach
SMART_READER_LITE
LIVE PREVIEW

CO2 EMISSIONS PANEL VAR APPROACH Snia Almeida Neves, Antnio Cardoso - - PowerPoint PPT Presentation

Feb 04, 2024 29 likes •202 views

15 th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION? THE INTERACTIONS BETWEEN CONVENTIONAL AND ALTERNATIVE ENERGY SOURCES IN TRANSPORT SECTOR, ECONOMIC GROWTH AND CO2 EMISSIONS PANEL VAR

slide-1
SLIDE 1

THE INTERACTIONS BETWEEN CONVENTIONAL AND ALTERNATIVE ENERGY SOURCES IN TRANSPORT SECTOR, ECONOMIC GROWTH AND CO2 EMISSIONS – PANEL VAR APPROACH

Sónia Almeida Neves, António Cardoso Marques, José Alberto Fuinhas NECE-UBI, and University of Beira Interior, Management and Economics Department; Covilhã, Portugal sonia.neves@ubi.pt

15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION? Vienna, 4th September 2017 1

slide-2
SLIDE 2

Energy dependence vs share of renewables

2

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017

Source: Own elaboration using EUROSTAT database Source: Own elaboration using EUROSTAT database

10 20 30 40 50 60 70 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Germany

Energy Dependence % RES share % 5 10 15 20 25 30 35 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Czech Republic

Energy Dependence % RES share %

15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

slide-3
SLIDE 3

Being the Transport Sector (TS) highly intensive in fossil fuels consumption, it is delaying the transition to a low-carbon economies.

In 2010 TS was responsible for:

  • 19% of the global energy used, being 96% from oil,
  • 60% of the global oil used, and
  • 23% of global CO2 emissions (source: World Energy Council, 2011).

In 2014, in the EU countries, TS was responsible for:

  • 33% of final energy consumption, being 94% from oil,
  • 25.5% of the GHG emissions (source: European Commission,2016)

3

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017

Transport Sector

15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

slide-4
SLIDE 4

4

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017 15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

Economic growth, CO2 emissions and TS energy consumption. e.g. (Chandran and Foon 2013; Saboori et

  • al. 2014)

Conventional and alternative TS energy sources

Panel Vector Autoregressive (Love and Zicchino 2006)

Contribution

slide-5
SLIDE 5

Objective

  • This paper aims to analyse the effects that are resulting from the

simultaneous use of the conventional and alternative TS energy sources on the economic growth and CO2 emissions.

  • CENTRAL QUESTIONS:
  • What are the consequences of the alternative TS energy sources
  • n the TS decarbonization?
  • Are both the conventional and alternative TS energy sources

contributing to the economic growth?

5

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017 15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

slide-6
SLIDE 6

Data

This study uses annual panel data from 1990 to 2014 for 21 high-income OECD countries.

Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Netherlands, Norway, Poland, Portugal, Spain, Sweden, Switzerland, United Kingdom, and the United States.

VARIABLES USED INCLUDES:

  • Gross Domestic Product per capita (LGDP)
  • TS fossil fuels (coal, crude, oil and natural gas) consumption per capita (LFOSSIL)
  • TS renewables fuels consumption per capita (LRES)
  • TS electricity consumption per capita (LELE)
  • CO2 emissions (LCO2)
  • Total energy consumption except which is consumed by TS per capita (LEN)

Hereafter, the prefixes “D” means the first differences and “L” means the natural logarithm.

6

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017 15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

slide-7
SLIDE 7

Data characteristics

Cross-section Dependence test (CD-test)

  • Suggests the presence of the cross-section dependence, however, DLELE only exhibits cross-

section dependence at 10% level of significance .

Panel Unit Root test

  • Second-generation unit root test (CIPS) was performed, and suggest that the variables are I(1).
  • For DLELE both first- and second-generation unit root test, and they are indicating that the

variables are I(1).

Correlation and multicollinearity

  • Correlation matrix values and the Variance Inflation Factor (VIF) were analysed, and confirm

that neither correlation or multicollinearity are deserving concern.

7

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017 15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

slide-8
SLIDE 8

Panel Data Vector Autoregressive (PVAR)

8

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017

Faced with variables potentially endogenous the use of Panel Data Vector Autoregressive (PVAR) is suitable. The estimator proposed by Love and Zicchino (2006) supports stationary endogenous variables as well as the unobserved individual heterogeneity.

, , 1 1 t t c d i f it it           

15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

Granger causality test Impulse Response Functions Forecast Error Variance

slide-9
SLIDE 9

9

The optimal number of the lags 1 were used because it minimizes all the selection criteria (MBIC, MAIC, and MQIC).

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017

First order PVAR were estimated

Table 1 : Lag order selection criteria Lag CD J J pvalue MBIC MAIC MQIC 1 0,421 153,928 0,002

  • 492,880
  • 62,072
  • 232,295

2 0,616 88,856 0,087

  • 342,349
  • 55,144
  • 168,892

3 0,706 33,963 0,566

  • 181,640
  • 38,037
  • 94,911

15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

Lag order selection criteria

slide-10
SLIDE 10

Stability condition

10

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017 15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

  • 1
  • .5

.5 1 Imaginary

  • 1
  • .5

.5 1 Real

Roots of the companion matrix

slide-11
SLIDE 11

Granger causality test

11

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017

Table 2: Granger Causality test DLELE DLCO2 DLEN DLRES DLFF DLGDP DLELE does not cause

  • 1,406

11,388*** 20,566*** 5,650** 5,265** DLCO2 does not cause 0,012

  • 0,047

4,626** 13,396*** 13,548*** DLEN does not cause 1,016 9,144***

  • 4,600***

5,430** 19,377*** DLRES does not cause 1,880 0,578 0,460

  • 2,789*

5,790** DLFF does not cause 7,840*** 5,124** 12,453*** 12,206**

  • 29,012***

DLGDP does not cause 3,159* 67,235*** 26,748*** 15,627*** 10,530***

  • ALL

10,258* 112,266*** 81,295*** 43,411*** 32,499*** 54,461*** Notes: ***, **, and * denotes statistical significance at 1%, 5%, and 10% respectively.

15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

slide-12
SLIDE 12

Summary of the causalities

12

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017 15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

slide-13
SLIDE 13

Vienna, 4th September 2017 13

Main achievements and their implications

Introduction Data and Methodology Results Discussion Conclusions

15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

sonia.neves@ubi.pt

  • DLFF ↔ DLGDP – The positive bidirectional causality shows the importance of

this sector for the entries dynamics of the economy as well as their intensity

  • n the fossil fuels use.
  • DLRES ↔ DLGDP – The renewable fuels is hampering the economic growth.

This outcome could come from excessive costs associated. The reduction of the economic growth also implies the reduction of the renewable fuels consumption.

  • DLELE ↔ DLGDP - The TS electricity consumption affects the economic

growth positively. The economic growth causes the TS electricity consumption

  • nly at 10% level of significance. This means that the penetration of the

electricity within the TS are not significantly dependent from the economic performance.

slide-14
SLIDE 14

Vienna, 4th September 2017 14

Main achievements and their implications

Introduction Data and Methodology Results Discussion Conclusions

15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

sonia.neves@ubi.pt

  • DLFF ↔ DLRES– Although the renewables fuels only causes the fossil

fuels at 10% level of significance, there is evidence that the renewable fuels could contribute to reduce the fossil fuels consumption.

  • DLRES ↔ DLELE – There is evidence of the negative bidirectional causality.

This show us a kind of the substitution effect between electricity and renewable fuels.

  • DLELE ↔ DLFF – The electricity

use are contributing to reduce the dependence on the fossil fuels.

slide-15
SLIDE 15

Vienna, 4th September 2017 15

Main achievements and their implications

Introduction Data and Methodology Results Discussion Conclusions

15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

sonia.neves@ubi.pt

  • DLCO2 ≠ DLELE – The electricity consumption not contributes to reduce

the CO2 emissions, neither vice-versa.

  • DLCO2 → DLRES – The renewables fuels have been promoted for the

environmental protection. However, it has not had any direct impact on the CO2 emissions.

  • DLCO2 ↔ DLFF – This results corroborates with the amply documented in

the literature wherein the TS is highly harmful to the environment .

slide-16
SLIDE 16

Answering the questions

What are the consequences of the alternative TS energy sources on the TS decarbonization?

  • Both the electricity and renewables fuels must be pursued to decarbonize the
  • TS. Although they are not having any direct impact on the CO2 emissions

reduction, actually, they contributes to reducing the fossil fuels consumption. Are both the conventional and alternative TS energy sources contributing to the economic growth?

  • The electricity use on TS is contributing to the economic growth, but the

renewable fuels are hampering it. On the shift pathways to low-carbon TS the alternative energy sources plays a fundamental role. However, the negative effect of the renewable fuels on the economic growth must deserve further attention.

16

Introduction Data and Methodology Results Discussion Conclusions

sonia.neves@ubi.pt

Vienna, 4th September 2017 15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION?

slide-17
SLIDE 17

THE INTERACTIONS BETWEEN CONVENTIONAL AND ALTERNATIVE ENERGY SOURCES IN TRANSPORT SECTOR, ECONOMIC GROWTH AND CO2 EMISSIONS – PANEL VAR APPROACH

Sónia Almeida Neves, António Cardoso Marques, José Alberto Fuinhas NECE-UBI, and University of Beira Interior, Management and Economics Department; Covilhã, Portugal sonia.neves@ubi.pt

15th IAEE European Conference 2017 HEADING TOWARDS SUSTAINABLE ENERGY SYSTEMS: EVOLUTION OR REVOLUTION? Vienna, 4th September 2017 17