Sectoral Disaggregation Research Articles

Spatial diffusion of the socio-economic effects from the deployment of energy technologies in Spain

ABSTRACT The paper covers an application to spatial economic analysis, based on a multiregional input-output model. Considering the challenges of the energy sector, this method is applied to analyse the spatial diffusion of the effect, of Spanish investment in different energy technologies covering several energy policy scenarios, in terms of added value and employment. Sector disaggregation is also analysed. Results show that renewable energy sources offer excellent opportunities for economic and employment growth at the global level. Spanish renewable energy deployment has positive spillover effects in China and Germany, but its impact on Spanish social and economic development is not significant.

Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL

Abstract. To design a monitoring network for estimating CO2 fluxes in an urban area, a high-resolution observing system simulation experiment (OSSE) is performed using the transport model Graz Mesoscale Model (GRAMMv19.1) coupled to the Graz Lagrangian Model (GRALv19.1). First, a high-resolution anthropogenic emission inventory which is considered as the truth serves as input to the model to simulate CO2 concentration in the urban atmosphere on 10 m horizontal resolution in a 12.3 km × 12.3 km domain centred in Heidelberg, Germany. By sampling the CO2 concentration at selected stations and feeding the measurements into a Bayesian inverse framework, CO2 fluxes on a neighbourhood scale are estimated. Different configurations of possible measurement networks are tested to assess the precision of posterior CO2 fluxes. We determine the trade-off between the quality and quantity of sensors by comparing the information content for different set-ups. Decisions on investing in a larger number or in more precise sensors can be based on this result. We further analyse optimal sensor locations for flux estimation using a Monte Carlo approach. We examine the benefit of additionally measuring carbon monoxide (CO). We find that including CO as tracer in the inversion enables the disaggregation of different emission sectors. Finally, we quantify the benefit of introducing a temporal correlation into the prior emissions. The results of this study have implications for an optimal measurement network design for a city like Heidelberg. The study showcases the general usefulness of the inverse framework developed using GRAMM/GRAL for planning and evaluating measurement networks in an urban area.

Industry-mix effects at different levels of sectoral disaggregation: a decomposition of inter-country differences in energy costs

Industry-mix effects at different levels of sectoral disaggregation: a decomposition of inter-country differences in energy costs

Gains from trade and their quantification: Does sectoral disaggregation matter?

Gains from trade and their quantification: Does sectoral disaggregation matter?

A reassessment of industrial growth in interwar Turkey through first-generation sectoral estimates

This study presents the first sectorally disaggregated estimates of the industrial output growth for Turkey between World War I and II. These estimates indicate that at the aggregate level the existing official index overestimates the output growth. Secondly, the sectoral disaggregation shows that the industrial growth was balanced, as both textiles and food-processing branches, which comprised most of the value-added, grew significantly. Local industries expanded against the only modest gains in per capita consumption of manufactured goods and incomes. Output growth was positively correlated with higher initial import penetration and nominal protection rates, which implies that trade protectionism helped favorable relative prices induce domestic expansion. On the other hand, both import-competing and domestic-market-oriented sectors significantly expanded, which suggests that import repression and increasing domestic demand drove industrial growth.

Labour Productivity in a Central and Eastern European Secondary City – Evidence from Regional and Firm-Level Data

Abstract Our article examines the changes in the economic position of a Hungarian secondary city, Pécs, and its region in the post-crisis period from a labour productivity perspective. Our aim is to contrast results based on data of the city’s largest local firms from the Orbis Europe enterprise database with the results based on the EuroStat regional database. We assess local trends in a sectoral disaggregation and focus on the period between the two crises. Our results suggest that Pécs and its region face a persistent difficulty in attracting external resources and in retaining and generating endogenous resources.

The impact of COVID-19 and associated policy responses on global food security.

We analyze the impact of the COVID-19 pandemic and associated policy responses on the global economy and food security in 80 low- and middle-income countries. We use a global economy-wide model with detailed disaggregation of agricultural and food sectors and develop a business-as-usual baseline for 2020 and 2021 called "But-for-COVID" (BfC). We then shock the model with aggregate income shocks derived from the IMF World Economic Outlook for 2020 and 2021. We impose total-factor productivity losses in key sectors as well as consumption decreases induced by social distancing. The resulting shocks in prices and incomes from the CGE model simulations are fed into the USDA-ERS International Food Security Assessment (IFSA) model to derive the impact of the pandemic on food security in these 80 countries. The main effect of the pandemic was to exacerbate the existing declining trend in food security. Food insecurity increases considerably in countries in Asia through income shocks rather than prices effects. We also review trade policies that were put in place to restrict imports and exports of food, and we evaluate their potential for further disruption of markets focusing on the food-security implications.

World carbon pricing database: sources and methods

This note describes the sources and methods used to construct the World Carbon Pricing Database (WCPD). This database contains a harmonized record of the sectoral coverage and prices associated with carbon pricing mechanisms implemented worldwide at the national and subnational levels over the period 1990–2020. The dataset follows IPCC 2006 sectoral disaggregation, which allows for a straightforward integration with other datasets following the same structure.

Using emissions trading schemes to reduce heterogeneous distortionary taxes: The case of recycling carbon auction revenues to support renewable energy

We examine the economic impacts of using the revenues from environmental taxation to reduce a pre-existing distortionary tax in a multisector economy where the environmental regulation and pre-existing distortionary tax apply heterogeneously across polluting sectors. With a numerical framework including a detailed sectoral disaggregation, we quantify these in the specific case of the European Union where carbon pricing coexists with electricity levies employed to support renewable energy. We find that using auction revenues from the EU Emissions Trading System (ETS) to reduce the national levies results in a 1.8% ETS carbon price increase but a 5.9% drop in the non-ETS carbon constraint. While the energy intensive sectors often benefit from electricity levy exemptions, the combination of these exemptions and of the recycling of carbon auction revenues to support renewable energy makes the ETS sectors worse off than if carbon revenues are transferred to households. In aggregate, the recycling option analysed here results in a GDP gain due to its impacts on the non-ETS sectors, the reduction of the electricity levy and associated distortionary effects.

The role of the agricultural sector in Ghanaian development: a multiregional SAM-based analysis

Ghana shows remarkable differences in employment and welfare between the southern and northern regions. The promotion of policy focus on the development of the northern regions requires the elaboration of specific databases describing the regional economies. Hence, this work outlines the construction of a Social Accounting Matrix (SAM) for Ghana for the year 2015 with a high disaggregation of sectors, household income groups and education levels across 10 administrative regions. Linear multisectoral models have been applied to this SAM to estimate socio-economic impacts of potential final demand policies down to a regional level in the Ghanaian economy. Further on, the structural path analysis is used to investigate the role played by different agriculture commodities in transmitting income to different types of households. The results allow for an identification of the most suitable sectors to be promoted due to their ability to generate the highest increases in output, employment and value added in the rest of the economy, as well as those with a significant impact on household income generation. As a result, the primary sector will play a key role in the economic and employment growth of the country. Notably, sorghum and millet, pulses, tobacco, cotton and fibres can be considered favourable crops for development in the Northern region.

USEEIO v2.0, The US Environmentally-Extended Input-Output Model v2.0

USEEIO v2.0 is an environmental-economic model of US goods and services that can be used for life cycle assessment, footprinting, national prioritization, and related applications. This paper describes the development of the model and accompanies the release of a full model dataset as well as various supporting datasets of national environmental totals by US industry. Novel methodological elements since USEEIO v1 models include waste sector disaggregation, final demand vectors for US consumption and production, a domestic form of the model that can be used to separate domestic and foreign impacts, and price adjustment matrices for converting outputs to purchaser price and in various US dollar years. Improvements in modeling national totals of industry and environmental flows are described. The model is validated through reproduction of national totals from input data sources and through analysis of changes from the most recent complete USEEIO model that can be explained based on data updates or method changes. The model datasets can all be reproduced with open source software packages.

Development of a Multi-sector Bounded-Neighbourhood Model with intersectoral commodity-money interactions

The article presents an approach to the development of an extended multi-sector bounded-neighbourhood with differentiated types of resources and intersectoral commodity-money interactions with implementation in the AnyLogic simulation tools. A feature of this approach is, firstly, a high degree of sectoral disaggregation (e.g., 42 types of economic activity are considered), and secondly, the three-level architecture of the proposed multi-agent system, which includes high-tech and low-tech resources as workplaces differentiated by types of economic activity (branches of the economy), and also multiple agents-individuals: natives and migrants with their own rules of behaviour and characteristics, and agents-sectors that provide the necessary structure of employment. We study the issues of software implementation of such a multi-level system in the AnyLogic, as well as the influence of the most important parameters of the model, in particular, such as the inflow rate of new migrants, dimensionality of forming industry clusters (i.e., a number of workplaces), level of wages by branches of the economy, etc. on the employment structure and the dynamics of gross domestic product, respectively.

Foreign-domestic substitution, import penetration and CGE modelling

ABSTRACT Foreign-domestic substitution elasticities (the so-called ‘Armington elasticities’) determine the degree of competitiveness in demand between similar products produced in different countries and are key parameters in a variety of numerical models of international trade. Armington elasticities are part of the explanation of the large increases in market shares of foreign products relative to locally produced ones in Australia, for example. The existing literature provides only limited evidence on these elasticities for Australia with the most disaggregated produced some time ago in 1977 by Alaouze and colleagues. This paper provides up-to-date parametric estimates of Armington elasticities for Australia with a reasonable degree of sectoral disaggregation. We use 22-years of data for 20 types of merchandise commodities, using OLS, panel and restricted-panel approaches. Our estimates range from 0.30 to 2.26, with higher elasticities for Transport and Equipment products and lower ones for Energy and Minerals. We illustrate the use of our elasticities with a trade-policy simulation using a computable generable equilibrium model of the Australian economy. We analyse the sensitivity of the results to the Armington elasticities by also using the previous estimates of Alaouze and colleagues. We find an overestimation of economic effects when using the old Armington values.

Adensamento produtivo e esgarçamento do tecido industrial brasileiro

Resumo A industrialização brasileira por substituição de importações proporcionou níveis elevados de adensamento produtivo, contudo, esses níveis reduziram-se após a abertura comercial. Porém, os estudos existentes utilizaram desagregação setorial que não permite identificar nichos produtivos adensados ou esgarçados dentre dos setores manufatureiros. Este trabalho mapeou e analisou, pela primeira vez para o Brasil, o grau de adensamento produtivo de todas as 258 classes industriais a partir de dados inéditos obtidos do IBGE. Assim, o estudo identificou os nichos mais e menos adensados, possíveis alvos das políticas públicas. Resultados relevam que as classes de baixa e média-baixa tecnologia continuam predominantemente adensadas, porém, metade das classes industriais de alta e média-alta tecnologia possui esgarçamento produtivo moderado a elevado, sendo algumas classes tecnológicas já maquiladoras. Conclui-se que o esgarçamento das classes industriais mais tecnológicas pode retardar o desenvolvimento brasileiro, sobretudo quanto à Ciência, Tecnologia e Inovação.

On the accuracy of gravity-RAS approaches used for inter-regional trade estimation: evidence using the 2005 inter-regional input–output table of Japan

In contrast to international trade, it is still difficult to find regional trade statistics within a nation. Given that the gravity model continues to be very popular, we test two gravity-RAS approaches used for interregional trade estimation: a standard one and an extended version, which additionally estimates intra-regional flows. We assess the accuracy with the help of two measures and for different sectoral aggregation levels. For that, we use the survey-based 2005 interregional input–output table of Japan as a benchmark. Results show high overall accuracy levels for the standard approach, better than when using international data, albeit with heterogeneous errors for sectors and regions. We further find that the results of a multiregional input-output model are highly sensitive to the trade estimation approach and that errors slightly increase for increasing sectoral disaggregation levels. Results from an experiment based on a random number generator show how RAS influences results.

The Missing Trade Elasticities and the Floating Size of the Gains from Trade

Multi-sector variants of standard gravity models typically predict much larger gains from trade than their one-sector counterparts. This paper explores to what extent this result is due to the relevant cross-sector variation observed in trade elasticity and to what extent it is instead an artifact of (discretionary) sectoral disaggregation. Numerical calculations are performed based on standard sufficient statistics for a specific class of gravity models (i.e. perfect competition models). Results suggest that, for benchmark values of the trade elasticity that applies to the one-sector specification, heterogeneous elasticities across sectors are, by far, the main source of the gains magnification effect, at least under standard levels of sectoral disaggregation at which input-output tables are commonly publicly available. Yet, when using more disaggregated data from tables available for the U.S. only, the effect of sectoral deconstruction per se substantially increases, leaving the issue on the true size of the gains still widely open.

Input-output modeling analysis with a detailed disaggregation of energy sectors for climate change policy-making: A case study of Saskatchewan, Canada

Systematically evaluating the emission intensity and total emission of industries is indispensable for understanding energy and environmental sector performance in general and to support scientific climate change policy-making. In this study, an environmentally extended input-output (EEIO) model with a detailed disaggregation of energy sectors is developed to investigate the life-cycle environmental impacts of different industries. A special case study of the Province of Saskatchewan, Canada, is conducted to illustrate the potential benefits of its use in the environmental policy-making field. The I–O table is transformed and disaggregated based on the energy use patterns and the underlying economic structure. Key GHG emissions, including CO2, CH4 and N2O, are considered and the CO2 equivalent intensities of different economic sectors are calculated. An in-depth analysis of key industries is conducted to further investigate the interactions between different industries. It is founded that the Province of Saskatchewan is a trade exposed and emission intense economy. The emission intensity of agriculture is higher than the mean level, and is difficult to reduce due to the large farm machines used in agricultural production. Fossil-fuel electric power generation, as an intermediate input, has a strong effect on other industries and is a key factor for emission reduction.

Macrologistics instrumentation: Integrated national freight-flow and logistics cost measurement

The objective of this research is to aid macrologistics decision-making through the development and interpretation of national freight-flow and logistics cost measurements, i.e. macrologistics instrumentation. This provides the systemic view of the national freight logistics landscape that is required to address logistics challenges within the context of a country's socio-economic objectives. The results highlight that South Africa's macrologistics costs exceed that of trading partners, with road transport the dominant cost contributor. Investing in domestic intermodal solutions will reduce both transport and externality costs. This, in turn, will improve the competitiveness of domestic and international freight, and support economic and ecological development objectives. Rail branch line densification will improve market access for rural economies and reduce logistics costs while supporting social development objectives. These applications provide examples of data-driven policy development and infrastructure investments. The level of spatial and sectoral disaggregation in the South Africa's Freight Demand ModelTM, and the flow-level link with a logistics costs model, within the context of the national input-output model, is to the best of our knowledge unique. This link to economic aggregates in the South Africa's Freight Demand ModelTM input data bridges logistics' analytical gap to macroeconomic decision-making.

Szoki technologiczne związane z wykorzystaniem energii w modelu CGE dla gospodarki Polski

1. Agencja Rynku Energii [2011], Sytuacja techniczno-ekonomiczna sektora elektroenergetycznego. IV kwartały 2010. Google Scholar

Measuring energy efficiency - structural and index decomposition analysis

Aim: The aim is to recognize the main determinants of the energy efficiency improvement in transport in Poland in the years 2000-2014 using structural and index decomposition analysis, and to identify areas where there is still potential for further reduction of energy consumption.Design / Research methods: Techniques used to analyse changes in energy use are: structural decomposition analysis and index decomposition analysis. Each of these two methods is characterized by distinctive, unique techniques and approaches, as they have developed quite independently. Index decomposition analysis measures the impact of energy efficiency gains on the level of energy consumption, at the most detailed sector disaggregation level allowed by the available data. Whereas structural decomposition analysis allows to analyse the impact of the external factors, such as technological, demand, and demographic effects, on the fluctuations of the total energy consumption. The similarities and differences between the two approaches are summarized and illustrated with a numerical example of Polish transport.Conclusions / findings: The article recognizes the main determinants of the energy efficiency improvement in transport sector in Poland in the years 2000-2014. In case of Poland ODEX shows an overall progress of energy efficiency in transport by 24.3%. Results obtained with decomposition analysis indicate large divergences in energy efficiency improvements between modes of transport and vehicle types and identify areas where there is still potential for further reduction of energy consumption. Results from decomposing structure of energy use, show activity effect to be main reason for energy use growth. The distribution of each mode in total traffic of passengers and goods changes toward less energy efficient modes. The only factor driving down the energy use is energy savings.Originality / value of the article: Using two methods of decomposition analysis and comparing obtained outcomes allows to get a broader view on energy use trends. Results presented in this article are a good starting point for further detailed analysis of changes in energy use of transport.