Sectoral Disaggregation Research Articles

Growth volatility and size: A firm-level study

This paper provides a systematic cross-country investigation of the relation between a firm’s growth volatility and its size. For the first time the analysis is carried out using comparable and representative sets of data sourced by official business registers of an important number of countries. We show that there exists a robust negative relation between growth volatility and size with an average elasticity equal to −0.18. We check the robustness of this result against a number of potential sources of bias and in particular with respect to sectoral disaggregation and against the inclusion of firm age. Our result is consistent with the idea that independently from specific country characteristics there exists a common underlying mechanism driving the elasticity between size and growth volatility. We then propose two mechanisms able to explain our result and we conclude discussing its relevance with respect to the recent literature on granularity.

Using Emissions Trading Schemes to Reduce Heterogeneous Distortionary Taxes: the Case of Recycling Carbon Auction Revenues to Support Renewable Energy

While emissions trading schemes are developed by nations to mitigate their greenhouse gas emissions, behavioural studies have shown that the political and public acceptability of these market-based instruments depends on the way the associated revenues are used. One option the general public approves of is to use them to support renewable energy. If this consists in reducing a pre-existing electricity levy that heterogeneously applies to the various sectors of the economy, the reduction of this distortionary tax thanks to the carbon revenues results in general equilibrium effects that may have unequal sectoral impacts. This is what we examine in the case of the European Union. With a modelling approach including a detailed disaggregation of European sectors, we find that using auction revenues from the Emissions Trading Scheme (ETS) to support electricity generation from renewable sources results in a 2% rise in electricity demand in the whole economy due to the reduced electricity levy that electricity consumers have to pay to support renewable energy. This results in a 1.8% ETS carbon price increase. The carbon constraint for the non-ETS sectors is 5.9% looser as a consequence of the larger electricity use by these sectors. While the energy intensive sectors generally benefit from electricity levy exemptions, we observe that, due to the energy and ETS price increase, the combination of these exemptions and of the use 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.

On the robustness of the fat-tailed distribution of firm growth rates: a global sensitivity analysis

Firms grow and decline by relatively lumpy jumps which cannot be accounted by the cumulation of small, “atom-less”, independent shocks. Rather “big” episodes of expansion and contraction are relatively frequent. More technically, this is revealed by the fat-tailed distributions of growth rates. This applies across different levels of sectoral disaggregation, across countries, over different historical periods for which there are available data. What determines such property? In Dosi et al. (The footprint of evolutionary processes of learning and selection upon the statistical properties of industrial dynamics. Industrial and corporate change. Oxford University Press, Oxford, 2016) we implemented a simple multi-firm evolutionary simulation model, built upon the coupling of a replicator dynamic and an idiosyncratic learning process, which turns out to be able to robustly reproduce such a stylized fact. Here, we investigate, by means of a Kriging meta-model, how robust such “ubiquitousness” feature is with regard to a global exploration of the parameters space. The exercise confirms the high level of generality of the results in a statistically robust global sensitivity analysis framework.

A Historical Reconstruction of Capital and Labour in Italy, 1861-2013

In this paper we provide a detailed explanation of the methodology underlying the construction of a new labour and capital stock dataset for Italy since 1861. The existing seminal paper (Rossi, Sorgato and Toniolo 1993) only covered the period 1911-1990 for labour and 1890-1990 for capital; moreover, sectoral disaggregation was limited. The labour dataset presented here includes both headcount and full-time equivalent annual estimates and provides a ten-sector breakdown. Net capital stock annual estimates are instead disaggregated by asset type (transport equipment, machinery and equipment, and construction, in turn divided into residential and non-residential). We then analyse the key features of the structural change in the Italian economy over the more than 150 years since unification. This dataset, combined with the new historical national accounts time series published by the Bank of Italy, finally makes a sectoral analysis of Italy’s long-run development possible.

Embodied energy analysis of building materials: An improved IO-based hybrid method using sectoral disaggregation

Buildings consume approximately half of the annual energy supply of the United States in their construction and operation. To effectively decrease this extensive energy footprint, both embodied and operating energy must be quantified and optimized. Although validated standard methods are available to compute operating energy, quantifying embodied energy is still complicated and inconsistent. Among the available embodied energy calculation methods, an input-output-based hybrid (IOH) method has the potential to offer a more complete calculation. However, its calculation lacks specificity and reliability, which can be improved using suggestions provided by literature. Studies across the globe have proposed techniques such as sectoral disaggregation to enhance not only the specificity and reliability, but also the completeness, of an IOH method.This study investigated and improved an IOH method of embodied energy calculation. Using the improved method, the embodied energy of commonly used building materials was calculated and evaluated. The results demonstrate a significant difference after disaggregating the relevant industry sectors. The study concludes that using embodied energy values without industry sectors being disaggregated can cause significant errors in a building’s embodied energy calculation.

Spatial Dimensions of Sectoral Labor Productivity Convergence in Turkey: A Spatial Panel Data Approach

AbstractThe purpose of this study is to investigate spatial dimensions of interregional labor productivity convergence in Turkey between 2005 and 2011 period in three sector disaggregation. We employed spatial panel data approach to investigate the absolute and conditional beta convergence. Annual gross value added per worker data has been used as labor productivity proxy for 26 sub-regions. Analysis results show us that absolute and conditional convergence is highly significant for all agriculture, industry and services sector and also in sectors total. We also found that, while industry, services and sectors total show significant spatial dependency, there is no strong evidence of spatial interaction in agriculture sector for Turkey. Structural problems of Turkish agriculture sector are considered to be the main reasons behind this finding.

The Carbon Footprint of Australia's Construction Sector

Australia accounts for just 0.33% of the world's population yet it is one of the highest emitters of greenhouse gas (GHG) emissions per capita in the world. The construction sector is a substantial area for mitigation efforts in Australia because of its economic importance and its involvement with indirect GHG emissions, i.e. those embodied in construction supply chains, including construction materials and electricity use. While the majority of policies and regulations focus on reducing direct emissions from buildings, more attention needs to be paid to the embodied emissions of the whole sector as these can take up anywhere between 10% and 97% of the whole life-cycle carbon emissions.This study aims at unravelling the total carbon footprint of the construction sector in Australia from 2009 to 2013, identifying the key contributing supply chains, industries and products. An economy wide input-output (IO) analysis is performed using a collaborative, cloud-based data platform – the Industrial Ecology Virtual Laboratory (IELab). This allows for a detailed disaggregation of sectors and permits more refined analysis as well as benchmarking against other sectors in the economy.Results for CO2e emissions by final demand show the construction sector makes up 18.1% of Australia's carbon footprint, compared to only 1.9% of direct emissions in 2013. The largest contributors to these embodied emissions are electricity, water & waste and materials throughout the years. Results are also broken down by detailed construction activities in residential / non-residential, road & bridge, other heavy and civil engineering and construction services. Mitigation options for electricity supply and materials use in the Australian construction sector are suggested.

A methodology for analyzing the impact of the artisanal fishing fleets on regional economies: An application for the case of Asturias (Spain)

Artisanal fleets represent one of the most sustainable fishing segments. Under the current Common Fisheries Policy (CFP), a key issue consists of quantifying their contribution to employment and value added generation in local economies, but methodological tools have not been specifically developed to analyze this question and few empirical quantifications have been carried out due to lack of information (output, intermediate consumptions, primary inputs, etc.). This paper presents a methodology to measure the importance of artisanal fleets in an economy, on the basis of input-output (IO) analysis and by applying a disaggregation procedure that allows for distinguishing their activity when this information is aggregated into one of the sectors observable on an IO table. An empirical exercise has been conducted for the case of the artisanal fishing fleet of Asturias (region in Northwest Spain) by drawing together many different sources of data concerning its activity and by splitting the whole “Fisheries and aquaculture” sector in the symmetric IO table. The new IO table has allowed to estimate the impact of the artisanal fishing fleet's activity, showing that it exerted in 2010 higher multiplier effects on regional employment and income than the whole economy and the rest of the fisheries sector (basically, the industrial fleet). Findings also revealed that the potential of the artisanal fleet to generate gross value added is particularly important. Our results also suggest that sectoral disaggregation of IO tables is a highly versatile, useful and replicable methodology for socioeconomic studies of artisanal fisheries.

On the significance of labour reallocation for European unemployment: Evidence from a panel of 15 countries

Abstract We explore the macroeconomic effects of sectoral shifts for 15 European countries. An extensive panel is constructed that allows us to assess the impact of labour reallocation on unemployment in the European context. Indexes of labour market turbulence based on alternative sectoral disaggregation are constructed. The effect of labour reallocation on unemployment is found to be positive and significant in all specifications. This remains robust when we take into account volatility measures in the model.

On the Robustness of the Fat-Tailed Distribution of Firm Growth Rates: A Global Sensitivity Analysis

Firms grow and decline by relatively lumpy jumps which cannot be accounted by the cumulation of small, atom-less, independent shocks. Rather big episodes of expansion and contraction are relatively frequent. More technically, this is revealed by fat tail distributions of growth rates. This applies across different levels of sectoral disaggregation, across countries, over different historical periods for which there are available data. What determines such property? In Dosi et al., (2015) we implemented a simple multi-firm evolutionary simulation model, built upon the coupling of a replicator dynamic and an idiosyncratic learning process, which turns out to be able to robustly reproduce such a stylized fact. Here, we investigate, by means of a Kriging meta-model, how robust such ubiquitousness feature is with regard to a global exploration of the parameters space. The exercise confirms the high level of generality of the results in a statistically robust global sensitivity analysis framework.

Analysis of the importance of structural change in non-energy intensive industry for prospective modelling: The French case

A large number of studies have been conducted on the contribution of technological progress and structural change to the evolution of aggregate energy intensity in the industrial sector. However, no analyses have been done to examine theses changes in the non-energy intensive industry in France. We analyzed their importance in French industry with respect to their energy intensity, energy costs, value added, labour and the diffusion of production sites by using data at the 3-digit level with 236 sectors. Using a new decomposition method that gives no residual, this paper attempted to examine, over 10 years from 1996 to 2005, the changes that occurred in an area that has been neglected in energy analysis. We found that structural change had an overwhelming effect on the decline of aggregate energy intensity. Furthermore, we found that the higher the level of sector disaggregation, the more significant the changes that can be attributed to structural change, due to the homogeneity of this industrial group. The results of our study show that it is important to take into account the effects of structural change in “bottom-up” modelling exercises so as to improve the accuracy of energy demand forecasting for policy-makers and scientists.

Disaggregation of sectors in social accounting matrices using a customized Wolsky method: a comment on its estimation bias

ABSTRACTBarrera–Lozano et al. (2015) suggest an approach to disaggregate SAM matrices using a customized method based on Wolsky (1984). Starting from an aggregated sector, they propose the extraction of a branch instead of its partition. This study compares these two methods based on the magnitude of their estimation bias of the disaggregated technical coefficient matrix. From simulations of the disaggregated Leontief matrix, this work calculates linkages and multipliers for common sectors derived from using either the Wolsky (1984) sectoral disaggregation or the Barrera–Lozano et al. (2015) sectoral extraction. Results show that both approaches provide biased estimators, with the last one showing a significantly higher bias, especially in cases of incomplete information. This comparison suggests the need of additional research to provide bias corrections for input–output disaggregation methodologies.

Peeling the Onion: Analyzing Aggregate, National and Sectoral Energy Intensity in the European Union

One of the most promising ways of meeting climate policy targets is improving energy efficiency, i.e. reducing the amount of scarce and polluting resources needed to produce a given quantity of output. This study undertakes an empirical exercise using the World Input-Output Database (WIOD), a harmonized dataset comprising time-series of input-output tables along with environmental satellite accounts and socioeconomic information. The paper consists of two parts. In the first part we begin with an aggregated picture of EU27 energy intensity and its evolution between 1995 and 2009. Then we dig deeper and introduce sectoral detail to identify the economic changes that occurred during the same period. Finally, we disaggregate the EU27 into countries for regional analysis and perform a sectoral disaggregation for a fine-grained picture of energy intensity in Europe. In the second part of the study we take our findings from index decomposition analysis and subject them to panel estimations. The objective is to control for factors that may have shaped the evolution of energy intensity in the European Union. In particular, we investigate the impact of technological change, structural change, trade, environmental regulation and country-specific characteristics.

Marriage Migration and Inequality in India, 1983–2008

Using National Sample Survey data from 1983 to 2007–08, we investigate rising rates of female marriage migration in India. We find little evidence to support the idea that marriage migration is a form of disguised economic migration by women. We hypothesise that it is instead a result of the changing patterns of marriage by socioeconomic status. Regression analysis indicates that poor families are increasingly more likely to have brides who in‐migrate, a finding that is robust across a sectoral disaggregation of marriage migration. We also find that urban inequality increases the likelihood of migration by intensifying class stratifications within urban India, increasing the need for poorer urban households to seek migrant brides. Marriage thus serves to reinforce rather than undermine larger patterns of class (and not just caste) inequality.

Decomposition Analysis of Aggregate Energy Intensity Changes in Tunisia over the Period 1980–2007

The aim of this paper is to investigate the main factors that have contributed to the decline in aggregate energy intensity of the Tunisian economy, during the period 1980–2007. Using the Logarithmic Mean Division Index (LMDI) decomposition method, we decompose the total changes in energy intensity into inter-fuel substitution effects, technological effects, and structural effects. The decomposition analysis is carried out at two levels of sectoral disaggregation (3 sectors and 13 sub-sectors) and uses three energy sources: petroleum, natural gas, and electricity. Our results show that the main contributor to the decline in energy intensity of the Tunisian economy throughout the period studied is the technological effect. This result was confirmed when we decomposed the energy intensity changes in the industrial and service sectors. On the other hand, the inter-fuel substitution effect contributed to increasing energy intensity, but without affecting its general downward trend. Finally, for the structural effects, we observed a significant mutual effect of cancellation at sector and sub-sector levels.

Trading Land: A Review of Approaches to Accounting for Upstream Land Requirements of Traded Products.

SummaryLand use is recognized as a pervasive driver of environmental impacts, including climate change and biodiversity loss. Global trade leads to “telecoupling” between the land use of production and the consumption of biomass‐based goods and services. Telecoupling is captured by accounts of the upstream land requirements associated with traded products, also commonly referred to as land footprints. These accounts face challenges in two main areas: (1) the allocation of land to products traded and consumed and (2) the metrics to account for differences in land quality and land‐use intensity. For two main families of accounting approaches (biophysical, factor‐based and environmentally extended input‐output analysis), this review discusses conceptual differences and compares results for land footprints. Biophysical approaches are able to capture a large number of products and different land uses, but suffer from a truncation problem. Economic approaches solve the truncation problem, but are hampered by the limited disaggregation of sectors and products. In light of the conceptual differences, the overall similarity of results generated by both types of approaches is remarkable. Diametrically opposed results for some of the world's largest producers and consumers of biomass‐based products, however, make interpretation difficult. This review aims to provide clarity on some of the underlying conceptual issues of accounting for land footprints.

Disaggregation of sectors in social accounting matrices using a customized Wolsky method

The aim of this work is to enable the implementation of disaggregation processes for specific and homogeneous sectors in Social Accounting Matrices (SAMs), while taking into account the difficulties in data collection from these types of sectors. The method proposed is based on the Wolsky technique, customized for the disaggregation of SAMs, within the current-facilities framework. The Spanish SAM for 2008 is used as a benchmark for the analysis, and the specific sector chosen for disaggregation is that of the Spanish Optical Sector.

Financial Constraints, Innovation Performance and Sectoral Disaggregation

How do the effects of financial constraints on innovation performance vary by sector and firm characteristics? This paper uses innovation survey data from 11 European countries to examine the heterogeneity of these effects. Our results suggest that the impact of direct measures of financial barriers differs in production and service sectors, and also by the firm's export orientation. In particular, financial constraints appear to have more pronounced negative effects in the production sector than in the service sector. Among different types of firms, the response to financial constraints seems to be stronger for non‐exporters.

Exploring the impacts of a carbon tax on the Chinese economy using a CGE model with a detailed disaggregation of energy sectors

This paper applies a computable general equilibrium model to investigate the impacts of a carbon tax on China's economy and carbon emissions based on China's 2010 Input–Output Table. To obtain robust simulation results, we further disaggregate the energy sectors into eight departments according to energy use characteristics. The empirical results indicate that a moderate carbon tax would significantly reduce carbon emissions and fossil fuel energy consumption and slightly reduce the pace of economic growth. However, a large carbon tax has a significantly negative impact on China's economy and social welfare. Moreover, a large carbon tax would entail marked price changes in China. Of the fossil fuels in use, reducing coal consumption would have the greatest impact on reducing carbon emissions, and the ad valorem duty rate for coal would be the highest after levying a carbon tax because it has the highest carbon emission coefficient. Therefore, China should strive to promote clean coal technology, which may be crucial to reducing carbon emissions. Moreover, levying a carbon tax would improve the use of clean energy, which would be an effective means of reducing carbon emissions. Therefore, the Chinese government should formulate the regulations for and pass a carbon tax as early as possible to achieve its carbon emission abatement target and further contribute to mitigating climate change.

Climate policy. Political implications of data presentation.

Climate policy. Political implications of data presentation.