Measurement of the population density and carbon dioxide emissions in African countries at different income levels
Last registered on February 16, 2016

Pre-Trial

Trial Information
General Information
Title
Measurement of the population density and carbon dioxide emissions in African countries at different income levels
RCT ID
AEARCTR-0001040
Initial registration date
February 16, 2016
Last updated
February 16, 2016 6:42 AM EST
Location(s)
Region
Primary Investigator
Affiliation
Middlesex University, London
Other Primary Investigator(s)
Additional Trial Information
Status
On going
Start date
2016-02-15
End date
2016-02-19
Secondary IDs
ISRCT
Abstract
Abstract

Most research on population and environment nexus concentrates on population growth and carbon dioxide emissions. Little research considers population density, and how it interacts with carbon dioxide emissions within a relationship. Thus, this research investigates the net impact of population density on carbon dioxide emissions across African countries and sees how this impact varies with per capita income. First, a conceptual framework of the structure of a relationship between population density, final consumption expenditure (annual growth), manufacturing sector and services sector value added as a component of GDP are synthesized from the IPAT to the STIRPAT model literature into an augmented STIRDCMS model. A panel equation modelling techniques were used to analyze the data. The empirical findings provided support for the conceptual framework, the findings suggest that the average effect of population density over CO2 emissions, when the population density change across time and between countries in LICA, increases by 1%, CO2 emissions increase by about 0.196% and reduce CO2 emissions by about 0.19% and 0.22% for LIMCA UICA respectively, holding all other predictors constant. An implication for both future researchers and decision makers are that this would expectedly heighten the awareness of the policy makers and the general public to equip a counterattack to possible severe environmental impacts in LICA. To the future researchers, this study can provide baseline information on the recent status of population density-CO2 emissions relationship. Furthermore, this study would be beneficial to the literature. It would provide the necessary information on the different driving forces of the environmental impacts in Africa.

External Link(s)
Registration Citation
Citation
Saka, Abdulrasaki. 2016. " Measurement of the population density and carbon dioxide emissions in African countries at different income levels." AEA RCT Registry. February 16. https://doi.org/10.1257/rct.1040-1.0.
Former Citation
Saka, Abdulrasaki. 2016. " Measurement of the population density and carbon dioxide emissions in African countries at different income levels." AEA RCT Registry. February 16. http://www.socialscienceregistry.org/trials/1040/history/6845.
Experimental Details
Interventions
Intervention(s)
The study investigates the role of population density on carbon dioxide emissions in African countries at different income levels.
Intervention Start Date
2016-02-15
Intervention End Date
2016-02-19
Primary Outcomes
Primary Outcomes (end points)
The key outcome variable of interest in this experiment is environmental impacts measured by carbon dioxide emissions per capita.
Primary Outcomes (explanation)
The outcome variable of this experiment was constructed by the World Bank, and sourced from the World Bank Indicators.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Most research on population and environment nexus concentrates on population growth and carbon dioxide emissions. Little research considers population density, and how it interacts with carbon dioxide emissions within a relationship. Thus, this research investigates the net impact of population density on carbon dioxide emissions across African countries and sees how this impact varies with per capita income. First, a conceptual framework of the structure of a relationship between population density, final consumption expenditure (annual growth), manufacturing sector and services sector value added as a component of GDP are synthesised from the IPAT to the STIRPAT model literature into an augmented STIRDCMS model. A panel equation modelling techniques were used to analyse the data. The empirical findings provided support for the conceptual framework, the findings suggest that the average effect of population density over CO2 emissions, when the population density change across time and between countries in LICA, increases by 1%, CO2 emissions increase by about 0.196% and CO2 emissions reduce by about 0.19% and 0.22% for LIMCA UICA respectively, holding all other predictors constant. An implication for both future researchers and decision makers are that this would expectedly heighten the awareness of the policy makers and the general public to equip a counterattack to possible severe environmental impacts in LICA. To the future researchers, this study can provide baseline information on the recent status of population density-CO2 emissions relationship. Furthermore, this study would be beneficial to the literature. It would provide the necessary information on the different driving forces of the environmental impacts in Africa.

Experimental Design Details
Most research on population and environment nexus concentrates on population growth and carbon dioxide emissions. Little research considers population density, and how it interacts with carbon dioxide emissions within a relationship. Thus, this research investigates the net impact of population density on carbon dioxide emissions across African countries and sees how this impact varies with per capita income. First, a conceptual framework of the structure of a relationship between population density, final consumption expenditure (annual growth), manufacturing sector and services sector value added as a component of GDP are synthesised from the IPAT to the STIRPAT model literature into an augmented STIRDCMS model. A panel equation modelling techniques were used to analyse the data. The empirical findings provided support for the conceptual framework, the findings suggest that the average effect of population density over CO2 emissions, when the population density change across time and between countries in LICA, increases by 1%, CO2 emissions increase by about 0.196% and CO2 emissions reduce by about 0.19% and 0.22% for LIMCA UICA respectively, holding all other predictors constant. An implication for both future researchers and decision makers are that this would expectedly heighten the awareness of the policy makers and the general public to equip a counterattack to possible severe environmental impacts in LICA. To the future researchers, this study can provide baseline information on the recent status of population density-CO2 emissions relationship. Furthermore, this study would be beneficial to the literature. It would provide the necessary information on the different driving forces of the environmental impacts in Africa.
Randomization Method
Randomization done by the World Bank.
Randomization Unit
Data collected from the World Bank were cross-sectional time series data.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
51 sovereign African countries.
Sample size: planned number of observations
Over 2000 planned number of observations, but depend on the model specifications.
Sample size (or number of clusters) by treatment arms
Manufacturing sector value added as a percentage of GDP, services sector as a percentage of GDP and final consumption government expenditure were controlled, population density as treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The empirical findings provided support for the conceptual framework, the findings suggest that the average effect of population density over CO2 emissions, when the population density change across time and between countries in LICA, increases by 1%, CO2 emissions increase by about 0.196% and CO2 emissions reduce by about 0.19% and 0.22% for LIMCA UICA respectively, holding all other predictors constant.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers