Economic Growth Scenarios Research Articles

Disaggregating time series on multiple criteria for robust forecasting: The case of long-term electricity demand in Greece

Electricity demand forecasting is an essential process in the operation and planning procedures of power systems that considerably influences the decisions of utility providers. Main aim of this paper is, first, to examine the relationship between a time series and influential multiple criteria, and, second, to provide long-term electricity demand forecasts in Greece. An original disaggregation or ordinal regression analysis methodological framework is outlined to optimally assess a robust additive value model which is as consistent as possible with a given time series. The accuracy and stability of this modeling approach is guaranteed through the calculation of statistical error measures and robustness analysis indices, respectively. For the case of Greece, the additive value forecasting model is inferred from data related to the training period 1999–2013. The proposed method has been applied for the forecasting of the annual total net electricity demand in the Greek interconnected power system during the following testing period 2014–2016. The model implies that the level of economic growth, represented by the national gross domestic product, imposes the greatest influence on the electricity demand followed by the energy efficiency progress and the weather conditions in the country. The ordinal regression models perform considerably better than the multiple linear (least-squares) regression model, in terms of prediction reliability, resulting into a minimum MAPE equal to 0.74%. The exact method has been also applied for the extraction of electricity demand projections till 2027 based on alternative economic growth scenarios, indicating a constant increase of the electricity demand in Greece.

RULING POLITICAL PARTIES TOWARD ECONOMIC GROWTH AND STABILITY: EVIDENCE FROM BANGLADESH

ABSTRACT The purpose of this study is to identify the economic growth and stability scenario under different ruling political parties since the inception of Bangladesh. The research is based on secondary data only. Data of the elected ruling parties at their tenure and data of overall GDP growth rate have been collected for the period of 1971 to 2017 from Bangladesh economic review. It has been evidenced from the research paper that economy of Bangladesh saw highest average GDP growth rate of 6.87 percent and highest economic stability with variation in growth rate by 0.28 percent during the two years (2006-2007) of then ruling caretaker government. Besides, it has been found that economy of Bangladesh witnessed the second highest average GDP growth rate of 6.26 percent during the last ten years’ ruling period of Awami League and the economy was also moderately stable with the deviation of growth by 0.66 percent. Trend analysis shows that frequently elected same ruling political party ensures higher economic growth and stability as the GDP growth rate of Bangladesh exceeded 7 percent during last three fiscal years (2016-2018) of ruling political party Awami League out of last 10 years of ruling as same elected party. This research paper will be supportive for the policy makers to take decision regarding good governance and political stability which will result higher but stable economic growth. Keywords GDP growth rate, political economics, sustainable growth.

Dynamic modeling of the policy effect and development of electric power systems: A case in Taiwan

Electric power is the cornerstone of economic growth, as well as one of the major energy sources for modern society. Economic growth, the demand for electricity, the security of fuel supplies, power-generating technologies, and the impact on the environment must be considered in the development planning and policy making of electric power. In fact, the planning of electric power development and the establishment of power generation capacity are complex and dynamic processes, which are influenced by national policies, citizens’ acceptance, and domestic and international energy sources. Hence, this study adopted system dynamics methodology to explore the development of policy-based electric power planning in Taiwan, analyzed its system structure, and simulated the impact of energy source policies on Taiwan's power supply according to different scenarios of economic growth. The findings of this study showed that the power supply in Taiwan is mainly influenced by four sub-systems with three important level variables, including the installed capacity of thermal power, installed capacity of nuclear power, and installed capacity of renewable energy. Currently, Taiwan plans to eradicate nuclear power by 2025 and replace it with renewable energies, which could result in power shortages and power rationing.

A Random Forest-Cellular Automata modelling approach to explore future land use/cover change in Attica (Greece), under different socio-economic realities and scales

This paper explores potential future land use/cover (LUC) dynamics in the Attica region, Greece, under three distinct economic performance scenarios. During the last decades, Attica underwent a significant and predominantly unregulated process of urban growth, due to a substantial increase in housing demand coupled with limited land use planning controls. However, the recent financial crisis affected urban growth trends considerably. This paper uses the observed LUC trends between 1991 and 2016 to sketch three divergent future scenarios of economic development. The observed LUC trends are then analysed using 27 dynamic, biophysical, socio-economic, terrain and proximity-based factors, to generate transition potential maps, implementing a Random Forests (RF) regression modelling approach. Scenarios are projected to 2040 by implementing a spatially explicit Cellular Automata (CA) model. The resulting maps are subjected to a multiple resolution sensitivity analysis to assess the effect of spatial resolution of the input data to the model outputs. Findings show that, under the current setting of an underdeveloped land use planning apparatus, a long-term scenario of high economic growth will increase built-up surfaces in the region by almost 24%, accompanied by a notable decrease in natural areas and cropland. Interestingly, in the case that the currently negative economic growth rates persist, artificial surfaces in the region are still expected to increase by approximately 7.5% by 2040.

Comparing the cost effectiveness of nature-based and coastal adaptation: A case study from the Gulf Coast of the United States.

Coastal risks are increasing from both development and climate change. Interest is growing in the protective role that coastal nature-based measures (or green infrastructure), such as reefs and wetlands, can play in adapting to these risks. However, a lack of quantitative information on their relative costs and benefits is one principal factor limiting their use more broadly. Here, we apply a quantitative risk assessment framework to assess coastal flood risk (from climate change and economic exposure growth) across the United States Gulf of Mexico coast to compare the cost effectiveness of different adaptation measures. These include nature-based (e.g. oyster reef restoration), structural or grey (e.g., seawalls) and policy measures (e.g. home elevation). We first find that coastal development will be a critical driver of risk, particularly for major disasters, but climate change will cause more recurrent losses through changes in storms and relative sea level rise. By 2030, flooding will cost $134–176.6 billion (for different economic growth scenarios), but as the effects of climate change, land subsidence and concentration of assets in the coastal zone increase, annualized risk will more than double by 2050 with respect to 2030. However, from the portfolio we studied, the set of cost-effective adaptation measures (with benefit to cost ratios above 1) could prevent up to $57–101 billion in losses, which represents 42.8–57.2% of the total risk. Nature-based adaptation options could avert more than $50 billion of these costs, and do so cost effectively with average benefit to cost ratios above 3.5. Wetland and oyster reef restoration are found to be particularly cost-effective. This study demonstrates that the cost effectiveness of nature-based, grey and policy measures can be compared quantitatively with one another, and that the cost effectiveness of adaptation becomes more attractive as climate change and coastal development intensifies in the future. It also shows that investments in nature-based adaptation could meet multiple objectives for environmental restoration, adaptation and flood risk reduction.

Analyzing and Simulating Urban Density: Exploring the Difference Between Policy Ambitions and Actual Trends in the Netherlands

This chapter explores the potential of geospatial analysis to characterize land use dynamics in urban areas and the surrounding urban fringe. It focuses on the difference between policy ambitions and reality with respect to urban densification. Policy ambitions for the containment of urban development are ambitious in the Netherlands, as is evident from the many local objectives to concentrate residential development within existing urban areas. These ambitions are formulated as target shares of the total net increase in housing stock that should be realized within designated urban area boundaries. Following a GIS-based analysis of local changes in housing stock between 2000 and 2008, we are able to describe actual intensification shares and residential densities in newly-developed urban areas. We observe that, especially in the already densely-populated western part of the country, the realized urban intensification shares are below the specified policy goals/ambition levels. Using these observations along with scenario-based projections of the regional increases in housing stock, we are able to determine the demand for new urban land in 2020. Using a land use simulation model, we simulate the urban development processes until 2020 according to two scenarios and two policy alternatives. In the first policy alternative, growth in the number of house units is based upon policy ambitions, while in the second scenario growth is based upon observed trends over the past decade. The results show that current policy ambitions related to urban intensification levels will greatly help in containing the substantial urban growth that is projected in the case of a high economic and population growth scenario. If urban development follows past trends, unabated, thus demonstrating relatively low urban intensification shares, large-scale urban extensions are likely to occur.

Freight Demand Forecasting Considering Economic Growth Factors

This work proposes a methodology to project future freight demand for all commodity types that begin and end in each geographical region and the amount of freight that moves between all origin and destination pairs. Following the traditional four-step demand forecasting framework, the procedure corresponds to trip generation and trip distribution analysis for interregional freight demand. Using future economic growth factors from macroeconomic and input-output models, the amounts of freight production and attraction in each analysis zone are forecasted and taken as given. Subsequently, an iterative matrix balancing method is applied to determine the estimated freight shipment demand for all origin and destination zone pairs. The proposed algorithm is applied to generate predicted future freight demand within the United States from 2010-2050 in five-year increments based on the national freight demand data from 2007. Four different scenarios are proposed that consider variations in both global economic growth and environmental regulation. This study will assist transportation planners and decision makers in public and private sectors to assess how future freight delivery demand on the national scale considering various future global economic growth and environmental policy scenarios will affect various issues such as air quality and human health problems.

Scenario-Based Simulation on Dynamics of Land-Use-Land-Cover Change in Punjab Province, Pakistan

The dramatic changes in land use are associated with various influencing factors such as socioeconomic, climatic, geophysical and proximity factors. Hence, understanding the driving mechanisms of land use changes is crucial to determine the pattern of future changes in land use. The aim of this study is to project the future land use and land cover changes from 2010 to 2030 in Punjab province under three scenarios: Business-as-Usual scenario (BAU), Rapid Economic Growth scenario (REG) and Coordinated Environmental Sustainability scenario (CES). This article used the previously developed Dynamics of Land System (DLS) model to simulate the land use changes in response to the driving mechanisms. The results indicate that cultivated land and built-up areas would expand while areas of water and grassland would face contraction under all three scenarios. Nevertheless, future land demand varies in different scenarios. Under the CES scenario; forest area would expand in the future while large reduction in unused land would be observed. Under the REG scenario, augmented expansion of built-up areas and drastic decrease in forest areas would be the main features of land use changes. Our findings in the scenario analysis of land use changes can provide a reference case for sustainable land use planning and management in Punjab province.

The Waste Footprint of French Households in 2020: A Comparison of Scenarios of Consumption Growth Using Input‐Output Analysis

SummaryThis study aims at quantifying and analyzing the waste footprint of French household consumption in 2020 with respect to different scenarios of economic growth. Three models are jointly used: (1) a multiregional unilateral input‐output model extended to waste, to quantify waste generation from economic activities induced by household consumption; (2) a coefficient‐based model dedicated to quantifying postconsumer waste as a function of household consumption; and (3) the New Econometric Model of Evaluation by Sectorial Interdependency and Supply (NEMESIS), a macroeconometric model used to elaborate different scenarios of growth in household consumption in the period 2008–2020. Three scenarios consider changes primarily in terms of household consumption volume, while one scenario additionally considers changes in the composition of consumption according to the past‐30‐year trend. First, this study suggests that if the trend in changes of composition is maintained, it will lead, by 2020, to a “relative” decoupling between French household consumption and waste footprint with respect to dry recyclables, mixed wastes, and organic wastes and to an “absolute” decoupling with respect to mineral wastes. Second, this study provides a mapping of the changes in French household waste footprints from 2008 to 2020 as a function of scenarios, with indications of where these changes would actually occur in the economy (waste from economic activities or postconsumer waste) and geographically (in France or abroad). In particular, for most of the scenarios considered, changes in French household consumption from 2008 to 2020 primarily induce changes in organic and mineral waste generation abroad rather than in France.

Initiative for Infrastructure Integration in South America: Way Toward Regional Convergence

ABSTRACTThis paper studies how the public provision of transportation infrastructure impacts output convergence and trade integration in a two-country dynamic general equilibrium model in which the transportation cost between countries is endogenously determined by the stock of public infrastructure in both countries. Because of its particular conception, the so-called ‘Initiative for the Integration of Regional Infrastructure in South AmericaIIRSA’ serves as the case of study. Data from Argentina and Brazil is thus used to solve the model. Two main results emerge. First, increasing public investment in infrastructure provides an impetus to commercial integration but does not necessarily generate output convergence. Second, the model shows that the only way for the two countries to achieve output convergence (in a win–win economic growth scenario) is to coordinate their increments on public infrastructure, as proposed by IIRSA.

Projections of Future Land Use in Bangladesh under the Background of Baseline, Ecological Protection and Economic Development

Land is one of the important input resources in a highly populous and land-scarce country such as Bangladesh. When different factors change (such as, geophysical, proximity, socioeconomic and climatic), there are dramatic changes in the spatial pattern of land uses. Thus, shedding light on the dynamics of land use and land cover changes has great importance for finding the changing pattern of land use in Bangladesh. In the present study, we predicted the land use and land cover changes from 2010 to 2030 under baseline, ecological protection priority and economic growth scenarios in Bangladesh. On this basis, we applied a previously developed Dynamics of Land Systems (DLS) model to simulate the changes in land uses according to the driving mechanisms. The findings indicate that cultivated land declines and built-up area expansion is common under all three scenarios. However, the future land use demand shows differences under different scenarios. The results under the ecological protection priority scenario shows that forest area and grassland will increase more, while under economic growth scenario, built-up area will expand dramatically in the future. The present research results furnish meaningful decision-making information for planners to conserve and/or exploit land resources in Bangladesh in a more sustainable manner.

Co-Benefits of CO2 and NOx Emission Control in China’s Cement Industry

Over the past 30 years, China’s cement industry has experienced rapid development. In this study the authors estimate the emissions trend, emissions control policies, and costs of the policies in China’s cement industry under various economic growth scenarios. First, the authors develop a bottom-up energy system — multi-pollutant abatement planning (MAP) model for China’s cement industry based on the existing productivity, a set of retrofitting options and new investments, alternative fuels, and various available emission control technologies. Second, the authors identify key drivers of cement demand to develop scenarios for future cement demand (2012–2030) and corresponding output peak time under high/low economic growth conditions. Third, the authors consider three scenarios including current policies without carbon control (BAU), moderately low carbon scenario (MLC), and radically low carbon scenario (RLC). The scenarios are being built up with different emission control goals and also compared by costs with estimation of marginal abatement cost curve for cement industry. Finally, based on the estimates the authors suggest a cost-efficient green/low carbon development roadmap for China’s cement sector, considering best available technological options and policy instruments. The study estimates the benefits of co-controlling air pollutants and CO2 emissions, and proposes an innovative mechanism to deal with air pollution and climate change.

Regional Oil Extraction and Consumption: A Simple Production Model for the Next 35 years Part I

The growing conflicts in and about oil-exporting regions and speculations about volatile oil prices during the last decade have renewed the public interest in predictions for the near future oil production and consumption. Unfortunately, studies from only 10 years ago, which tried to forecast the oil production during the next 20–30 years, failed to make accurate predictions for today’s global oil production and consumption. Forecasts using economic growth scenarios overestimated the actual oil-equivalent liquid production, while models which tried to estimate the maximum future conventional and unconventional oil production/year, using official and public country reserve data and/or private oil industry oil reserve databases, often underestimated the current conventional oil production in some larger oil-producing countries. In this paper, a new approach to model the maximal future regional and thus global oil production (part I) and the consequences for the regional oil consumption (part II) during the next decades is proposed. Our analysis of the regional oil production data during past decades shows that, in contrast to periods when production was growing and growth rates varied greatly from one country to another, remarkable similarities are found during the plateau and decline periods of different countries. As a result, we propose to model the oil production decline phase in all oil-producing regions with a universal decline function which assumes that a few years with a stable production will be followed by about 5 years with a 3 %/year decline and 6 %/year afterwards. This plateau and decline function was found to describe accurately the oil production of the past 15 years from Western Europe (EU+Norway), Mexico and Indonesia. Following this model, the particular production phase of each major oil-producing country and region is determined essentially only from the recent past oil production data. Accordingly, we find that the conventional oil production in all regions, outside of the Middle East OPEC countries, will start the 3 %/year decline phase between the years 2015 and 2020. Using these data, the model is then used to predict the production from all major oil-producing countries, regions and continents up to the year 2050. The limited regional and global potential to compensate this decline with unconventional oil and oil-equivalents is also presented.

Dynamic modelling of the potential habitat loss of endangered species: the case of the Canarian houbara bustard (Chlamydotis undulata fuerteventurae)

In this work, we apply a dynamic modelling approach to analyse the habitat loss of the Canarian houbara bustard (Chlamydotis undulata fuerteventurae). This tool allows us to assess the effects of the socio-economic and environmental interactions on the factors threatening the habitat and to carry out a prospective analysis. The results show a potential habitat loss of around 13 % during the period 1996–2011, the land uptake and increase in new roads and tracks being the factors contributing most. After model testing, a set of scenarios was explored. Under the business as usual (BAU) scenario, around 20 % of the habitat would be lost by the end of the period considered (2012–2025). The impact of the economic growth scenario on the habitat would mean an additional loss of around 21 % with respect to BAU, whereas under the recession scenario, the loss might be around 6.5 % lower than BAU. The policy of restoration of gavias—traditional farming systems—would suppose an additional loss of almost 6 %, relative to BAU. If this policy took place under economic growth conditions, it might mean an additional loss of almost 28 % relative to BAU. These results point to the existence of a potential trade-off between the recuperation of ecosystem services offered by restored gavias and the conservation of the houbara habitat, which must be addressed within the management processes, as well as to the need for compensatory measures to guarantee the conservation goals.

Analyzing energy savings potential of the Chinese building materials industry under different economic growth scenarios

As a vital industry providing raw materials to construction, building materials industry plays an essential role in China's energy consumption growth during urbanization. The objective of this study is to investigate the transition of future energy demand and energy savings potential of the Chinese building materials industry. The co-integration method is applied to identify the influencing factors of the sectoral energy use. Considering that economic growth is the driving force for the sectoral energy demand, this paper develops multiple scenarios to comprehensively analyze the transition of sectoral energy use and map various possibilities. Results indicate that although sectoral energy consumption peaks varied among different scenarios, the predicted sectoral energy use, which would account for a smaller share in national energy usage in the future, shows a similar downward trend after the first rise. Results also demonstrate that the sectoral energy savings potential is considerable. Policy implications are summarized as follows: (1) the relatively rapid economic growth stage provides an opportunity for the sector to conserve energy and reduce emissions; (2) technological progress ensures continuous improvement in sectoral energy efficiency; (3) the sector should speed up industrial restructuring and upgrading to deal with higher energy costs promoted by energy pricing reform.

Future Raw Material Supply: Opportunities and Limits of Aluminium Recycling in Austria

In order to promote sustainable production by using secondary raw material from existing material stocks, complementary to primary raw material, information about the future availability of secondary resources constitutes a prerequisite. In this study, a dynamic material flow model of historic aluminium (Al) flows in Austria is combined with forecasts on future Al consumption to estimate the development of old scrap generation and in-use stocks until 2050. In-use stocks are estimated to increase by 60 % to 515 kg/cap. by 2050 assuming a scenario of moderate economic growth. Old scrap generation in 2050 would thereby more than double (up to 30 kg/cap.) in comparison to the 2010 amounts. Despite this substantial increase in old scrap generation, industrial self-supply from old scrap will probably not exceed 20 %, and final consumption self-supply of Al will not exceed 40 % given present conditions. Opportunities and limits of increasing self-supply through higher collection rates and lower scrap export levels are investigated in this study as the European Raw Material Initiative considers enhanced recycling to be a key measure to ensure future resource supply. Based on these analyses, a self-sustaining Al supply from post-consumer Al is not expected if current trends of Al usage continue. Therefore, comprehensive resource policy should be based on a profound understanding of the availability of primary and secondary resources potentials and their dynamics.

Spatiotemporal Characteristics, Determinants and Scenario Analysis of CO2 Emissions in China Using Provincial Panel Data

This paper empirically investigated the spatiotemporal variations, influencing factors and future emission trends of China’s CO2 emissions based on a provincial panel data set. A series of panel econometric models were used taking the period 1995–2011 into consideration. The results indicated that CO2 emissions in China increased over time, and were characterized by noticeable regional discrepancies; in addition, CO2 emissions also exhibited properties of spatial dependence and convergence. Factors such as population scale, economic level and urbanization level exerted a positive influence on CO2 emissions. Conversely, energy intensity was identified as having a negative influence on CO2 emissions. In addition, the significance of the relationship between CO2 emissions and the four variables varied across the provinces based on their scale of economic development. Scenario simulations further showed that the scenario of middle economic growth, middle population increase, low urbanization growth, and high technology improvement (here referred to as Scenario BTU), constitutes the best development model for China to realize the future sustainable development. Based on these empirical findings, we also provide a number of policy recommendations with respect to the future mitigation of CO2 emissions.

Modelling energy supply options for electricity generations in Tanzania

The current study applies an energy-system model to explore energy supply options in meeting Tanzania’s electricity demands projection from 2010 to 2040. Three economic scenarios namely; business as usual (BAU), low economic consumption scenario (LEC) and high economic growth scenario (HEC) were developed for modelling purposes. Moreover, the study develops a dry weather scenario to explore how the country’s electricity system would behave under dry weather conditions. The model results suggests: If projected final electricity demand increases as anticipated in BAU, LEC and HEC scenarios, the total installed capacity will expand at 9.05%, 8.46% and 9.8% respectively from the base value of 804.2MW. Correspondingly, the model results depict dominance of hydro, coal, natural gas and geothermal as least-cost energy supply options for electricity generation in all scenarios. The alternative dry weather scenario formulated to study electricity system behaviour under uncertain weather conditions suggested a shift of energy supply option to coal and natural gas (NG) dominance replacing hydro energy. The least cost optimization results further depict an insignificant contribution of renewable energy technologies in terms of solar thermal, wind and solar PV into the total generation shares. With that regard, the renewable energy penetration policy option (REPP), as an alternative scenario suggests the importance of policy options that favour renewable energy technologies inclusion in electricity generation. Sensitivity analysis on the discount rate to approximate the influence of discount rate on the future pattern of electricity generation capacity demonstrated that lower values favour wind and coal fired power plants, while higher values favour the NG technologies. Finally, the modelling results conclude the self-sufficiency of the country in generating future electricity using its own energy resources.

Initiative for Infrastructure Integration in South America: Way Toward Regional Convergence

This paper studies how the public provision of transportation infrastructure impact output convergence and trade integration in a two-country dynamic general equilibrium model in which the transportation cost between countries is endogenously determined by the stock of public infrastructure in both countries. Because of its particular conception, the so-called "Initiative for the Integration of Regional Infrastructure in South America (IIRSA)" serves as the case study. Data from Argentina and Brazil is thus used to solve the model. Two main results emerge. First, increasing public investment in infrastructure provides an impetus to commercial integration but does not necessarily generate output convergence. Second, the model shows that the only way for the two countries to achieve output convergence (in a win-win economic growth scenario) is to coordinate their increments on public infrastructure, as proposed by IIRSA.

Forecasting carbon dioxide emissions

This study extends the literature on forecasting carbon dioxide (CO2) emissions by applying the reduced-form econometrics approach of Schmalensee et al. (1998) to a more recent sample period, the post-1997 period. Using the post-1997 period is motivated by the observation that the strengthening pace of global climate policy may have been accelerated since 1997. Based on our parameter estimates, we project 25% reduction in CO2 emissions by 2050 according to an economic and population growth scenario that is more consistent with recent global trends. Our forecasts are conservative due to that we do not have sufficient data to fully take into account recent developments in the global economy.