Tools necessary for a successful transition to a fossil-fuel-free sustainable future

Bismark Ameyaw & Amos Oppong

It is indisputable that fossil fuels are unsustainable and environmentally-unfriendly. As part of her contribution to the December 2015 Paris accord, Ghana has set intended nationally determined contributions to help transform the world to a sustainable one. However, in transforming her economy characterized by numerous yet interrelated variables, certain efficient and effective tools are required. Here, we shed more light on some of the tools that play a pivotal role in ensuring a smooth transition from the environmentally-unfriendly and unsustainable economy to a sustainable one. Specifically, we concentrate on real-time reliable data, robust and scientific modelling and high accuracy forecasts as depicted in Figure 1.

Figure 1: Keys to a smooth transition to a sustainable future
  1. Real-time reliable data

From an econometric perspective, much data is key to deriving high-accuracy results. Data on Ghana on energy production and consumption (both by source and sector) and greenhouse gas emissions are limited. As at the time of drafting this bulletin yearly data on energy and emissions from credible sources such as World Bank country development indicators, the Central Intelligence Agency, EnerData, International Energy Agency, etc. span 1960 to 2015. Yearly as well as monthly data on energy, emissions and related causal variables starting from her date of independence (1957) to the late 1990s is almost not existing. The reliability and credibility of even the few sets of data on the country for energy, environment, economic indicators and living standards are frequently called into question by policymakers, the general public and pundits. Efforts made towards reporting and securing credible data on energy, environment, economic and living standards must be intensified and reporting data in real-time must be encouraged. Aggregating survey data collected by tertiary students and various researchers and research institutes of which all forms of irregularities are checked can be a good starting point towards creating regional (as well as districts and municipals) and sectoral (including sub-sectoral) real-time data. Such country- and sector-specific data would give policymakers a clearer and vivid picture of the state of the nation which could lead to proposing efficient and result-yielding policies.

 

  1. Robust models

There are numerous variables to consider when analyzing an energy, environment and economy case. The intricate yet pivotal relationships that exist between and among variables require robust models that are capable of capturing the complex inter and intra twists and reporting realistic outcomes. Globally, the Kaya and IPAT identities are well-established models that have been utilized in analyzing interrelationships among greenhouse gas emissions and population, gross domestic output, energy consumption and technology, among other variables. In order to capture the numerous and intricate relationships among energy, environment and output in the case of Ghana, the Kaya and IPAT models must be extended extensively to capture the unique characteristics of the country or entirely new robust models must be created. Given that such robust models are created and adopted, policymakers and leaders will be well-informed with rich facts as to which scenarios to consider when drafting emission-mitigation and efficient energy policies. It is worth noting that massive reliable data coupled with robust models could lead to efficient and effective energy-saving and emission-mitigation policies which spills-over to minimize misappropriation of scarce resources.

 

  1. High-accuracy forecasts

In drafting comprehensive policies, policymakers rely on energy and emission forecasts as benchmarks but the inaccuracies in past projections for the case of Ghana are substantially high. The inaccuracies are depicted in the high forecast errors of past projections. The inaccuracies are ascribed to modelling flaws and massive unrealized assumptions which form core parts in the underlying model. The massive reliable data coupled with robust models could guarantee high-accuracy forecasts as shown in Figure 1. High-accuracy forecasts, particularly business-as-usual, help to narrow the ever-expanding policy window and give policymakers a clearer picture of the consequences of policies implemented today. Thus, modellers are encouraged to critically model the intricacies and unique characteristics of the country to achieve high-accuracy forecast.

 

Bismark Ameyaw

BISMARK AMEYAW is a researcher at University of Electronic Science and Technology of China and a referee to a number of prestigious peer-review journals. He specializes in modelling and forecasting the dynamic links in energy policies and the economy. He writes, teaches and consults on management and econometric issues. He serves as an editorial board member and a reviewer for a number of prestigious international journals. You may contact him through: E-mail: kofiameyaw9@hotmail.com and 3101153683@qq.com

 

AMOS OPPONG is a researcher at University of Electronic Science and Technology of China and a referee to a number of prestigious peer-review journals. He specializes in modelling and forecasting the dynamic links in environmental, energy and the economy and policy analysis. He has rich research experience in diverse fields assisting research projects on mining, agriculture, sectoral energy demand, economy-wide energy demand and supply, trade, environmental cooperation, air pollution and climate change. You may contact him through: Email: 201714110129@std.uestc.edu.cn; oamos@rglobal.org