Search

Construction activities are a major driver of greenhouse gas emissions worldwide. However, the majority of construction‐driven emissions are indirect, meaning that these emissions occur during the manufacturing and transport of construction materials. This is in contrast with direct emissions, which are directly emitted from construction machinery. These indirect impacts are represented as embodied emissions and are difficult to quantify at scale, limiting the effectiveness of climate policymaking in the building sector. This paper presents results from a comprehensive account of embodied emissions within the Canadian construction sector, at a resolution far higher than existing global accounts, as well as novel analyses of flows and intensities of embodied emissions. It has the specific goal of serving as a baseline for future analyses of decarbonization scenarios and the more general goal of highlighting the importance of a consumption‐based approach to climate policymaking in the sector. The accounts are produced via an environmentally extended input–output analysis based on Canadian supply–use tables for the year 2018, and results are presented for the 13 provinces and territories as well as 19 categories of buildings and infrastructure. Results show that demand from construction drives 13% of Canada's consumption‐based emissions, residential construction is by far the largest driver of emissions, and at 0.28 kgCO2eq per Canadian dollar of GDP, the efficiency of Canadian construction is roughly in line with the OECD average. A disproportionate share of emissions is driven by construction in provinces that are growing fast in terms of their populations, feature significant extractive industries, and feature higher emissions intensities. The construction sectors of western provinces are highly interconnected and receive a disproportionate proportion of embodied emissions from Alberta, whose high level of emissions promises to complicate decarbonization efforts. This article met the requirements for a gold‐gold JIE data openness badge described at http://jie.click/badges [ABSTRACT FROM AUTHOR]

Purpose: The main goal of this paper is to examine the evolution of Latin American productive integration in terms of the regional value added incorporated in intra-regional exports of Argentina, Brazil, Chile, Colombia, Mexico and Peru. In addition, the study traces the trade and productive integration trajectories for each of these countries from 1995 to 2015. Design/methodology/approach: Based on the use of OECD's global ICIO input-output tables, this paper applies the methodological framework by Wang et al. (2018) for the analysis of trade flows at the bilateral level, which allows breaking down the value of gross exports of each sector-country, depending on the origin of the value added contained in exports, as well as their use. Findings: The estimates show very low shares of value added from regional partners in the intra-regional exports of the countries studied. Conversely, the weight of the value added incorporated in these exports by countries outside the region has increased in tandem with China's expanding involvement in Latin America. This development, along with the downward trend in domestic value added incorporated in exports, indicates a lack of a regional integration process of any depth. Originality/value: This article addresses an economic problem of conventional importance from a global value chain perspective using a novel methodology based on the use of global input-output tables. [ABSTRACT FROM AUTHOR]

Central Java Province has the potential with a high number of tourist attractions, however, it has not provided optimal contribution yet to the tourism sector. This research aims to analyze the relationship between the economic sectors, the distribution impact, and the multiplier effect of output, income and labor in tourism sector on the economy in Central Java Province. This research uses secondary data, the Input-Output Table of Central Java Province, published in 2021, which is then analyzed using the Input-Output method. The result of the research indicates that the tourism sector for forward linkage is in the third highest position, and the highest supporting sub-sector of the tourism sector is the information and communication services sub-sector. Meanwhile, for the result of the backward linkage value, the tourism sector is in the third highest position, and its supporting sub-sector with the highest value is the accommodation and food and beverage provision sub-sector. The analysis result of the distribution impact indicates that the tourism sector is a leading sector. For the multiplier effect of output, the tourism sector is in the third highest position, while for the multiplier of income and labor, it is not too high in the sixth and fifth positions. [ABSTRACT FROM AUTHOR]

In the last 10 years, military expenditures of NATO EU countries (according to NATO definitions and data) have increased by almost 50 %, from €145 billion in 2014 to €215 billion in 2023. In this context, it is important to assess the economic consequences that the current increase in military spending is likely to have on Europe's economies. We focus on Germany, Italy and Spain, and we concentrate on arms acquisitions. The article investigates the economic effect of military expenditure on growth and employment and compares it to the impact that could emerge from a similar expenditure for education, health and the environment. We use an input–output methodology – already adopted by several studies – to assess the relevance of imports and of demand towards different sectors providing intermediate inputs. We assess the likely impact on output and jobs of one billion euros of extra spending in arms, and compare it to the outcomes of the same amount spent in education, health and the environment. Our findings show that for all countries non-military public expenditures have a greater impact on the economy and employment than spending for arms acquisition. [ABSTRACT FROM AUTHOR]

MESSAGE is an Integrated Assessment Model (IAM) useful for developing anthropogenic climate change scenarios and the evaluation of long-term energy policies. MESSAGE is constrained by its internal scenario generator, which project energy commodity demand inputs based only on population and GDP growth assumptions; the lack of sectoral and supply-chain details prevents modeling impacts from develpoments in non-energy sectors. Here we link MESSAGEix-Australia, a national-level MESSAGE IAM variant, to an input-output scenario builder to generate future energy commodity demands. The coupled IO_IAM framework then captures indirect energy implications of various socio-economic scenarios. Two scenarios were used to demonstrate this capability: first on the policy-based decarbonisation pathways for Australia, and second on the adoption of self-healing roads. This study showcases that a link between IO and IAM methods provides an opportunity for bringing together the strengths of the two approaches for assessing a wide range of sustainability questions. [ABSTRACT FROM AUTHOR]

We examine changes in the manufacturing sector value chains of the EU, US, China, and India between 2018 and 2023 by introducing three metrics for supply-chain vulnerability. For our first metric, the physical length of a supply chain based on the distance between the producer of the final product and input source country, we find modest evidence of near-shoring for the US, EU, and India. Second, utilizing political distances between the supply chain participants, our assessment of the geopolitical risks of supply chains reveals slight friend-shoring by the US and EU, mainly a result of Russia's reduced participation in their supply chains. Third, looking at the already extensive supply chain diversification of the studied countries, we find diversification has increased modestly since 2018. [ABSTRACT FROM AUTHOR]

Inter-provincial trade is accompanied by the transfer of embodied pollution emissions, leading to emissions leakage, thereby hindering the sustainable development of society. Therefore, it is imperative to analyze the characteristics of embodied pollutant emission and spatial transfer driven by inter-provincial trade. In this study, the quantitative and spatial characteristics of the six main embodied pollutants (i.e., SO2, NOX, CO, VOC, PM2.5, and PM10) were analyzed by a hypothetical extraction method (HEM) and complex network analysis (CNA) under an input–output analysis (IOA) framework. Then, the row arrange series (RAS) method was employed to simulate the impacts of varying levels of trade intensity, economic growth rate, and technological progress on embodied pollutants and spatial-transfer characteristics. The major findings are as follows: (i) the increase in inter-provincial trade led to a corresponding rise in embodied pollutant emissions due to the relocation of production activities towards provinces with higher emission intensity. Excessive responsibility was assumed by provinces such as Shanxi and Hebei, engaging in production outsourcing for reducing pollutants. (ii) The macro direction of pollutant transfer paths was from the resource-rich northern and central provinces towards the trade-developed southern provinces. Sectors in the transfer path, such as the industry sectors of Shanxi, Guangdong, Henan, and the transport sector of Henan, exhibited high centrality and dominated pollutant transfer activities in the network. (iii) The industry sector, characterized by substantial energy consumption, was the predominant emitter of all pollutant production-based emissions, accounting for more than 40% of total emissions. This study is conducive to analyzing the impacts of inter-provincial trade on embodied pollutant emissions and developing emissions reduction policies considering equitable allocation of emissions responsibilities from both production and consumption perspectives. [ABSTRACT FROM AUTHOR]

We develop a dynamic model of input–output networks that incorporates adjustment costs of changing inputs. Our closed-form solution for the dynamics of the economy shows that temporary shocks to upstream sectors, whose output travels through long supply chains, have disproportionately significant welfare impact compared to affected sectors' Domar weights. We conduct a spectral analysis of the U.S. production network and reveal that the welfare impact of temporary sectoral shocks can be represented by a low-dimensional, 3-factor structure. [ABSTRACT FROM AUTHOR]

"Ensure access to affordable, reliable, sustainable, and modern energy for all" is one of the United Nations' 17 Sustainable Development Goals. A key target for achieving this goal is increasing the share of renewable energy. In the United States, many states are evaluating the environmental and economic impacts of the renewable energy transition. This study provides an in-depth evaluation of the economic impact of Ohio's proposed Community Solar Pilot Program, which plans to install 1750 MW of new solar capacity, including 250 MW on distressed Appalachian sites. We combine two input–output models to estimate the economic impact of community solar projects: the Jobs and Economic Development Impact (JEDI) model from the National Renewable Energy Laboratory (NREL) for the construction phase, and IMPLAN for the projects' 25-year lifespan. Data for this study were gathered through surveys of local solar developers, who are familiar with the regional costs of installing and operating solar projects. Our findings indicate that the community solar program could support 32,430 full-time job years and contribute USD 4.37 billion to Ohio's Gross State Product (GSP). Additionally, the program could generate USD 409.5 million in local tax revenue over its lifetime. The study highlights the potential of renewable energy initiatives to foster economic growth, particularly in economically distressed regions like Appalachian Ohio. [ABSTRACT FROM AUTHOR]

Purpose – The main goal of this paper is to examine the evolution of Latin American productive integration in terms of the regional value added incorporated in intra-regional exports of Argentina, Brazil, Chile, Colombia, Mexico and Peru. In addition, the study traces the trade and productive integration trajectories for each of these countries from 1995 to 2015. Design/methodology/approach – Based on the use of OECD’s global ICIO input-output tables, this paper applies the methodological framework by Wang et al. (2018) for the analysis of trade flows at the bilateral level, which allows breaking down the value of gross exports of each sector-country, depending on the origin of the value added contained in exports, as well as their use. Findings – The estimates show very low shares of value added from regional partners in the intra-regional exports of the countries studied. Conversely, the weight of the value added incorporated in these exports by countries outside the region has increased in tandem with China’s expanding involvement in Latin America. This development, along with the downward trend in domestic value added incorporated in exports, indicates a lack of a regional integration process of any depth. Originality/value – This article addresses an economic problem of conventional importance from a global value chain perspective using a novel methodology based on the use of global input–output tables.

The internalization of the social cost of carbon (SCC) is the most efficient alternative to reduce the emissions that cause global warming. However, the carbon pricing initiatives implemented in many countries differ significantly from the empirical estimates of the SCC. Therefore, this study simulates the economic and environmental effects of internalizing the SCC in all the world’s nations through the environmental extension of a multi-regional input–output (MRIO) price model. The results show that the most affected countries economically are characterized by having an energy matrix with high participation of fossil fuels. In addition, there are relevant increases in the prices of energy and food, which are likely to raise poverty rates in low- and middle-income countries. It is concluded that the global emission reduction can vary between 5.1% and 50.3% depending on the SCC used, and only ten countries explain 77% of this reduction. In addition, global emissions reduction falls if data from a more recent base year is used, demonstrating that the structural transformations of the economy also strongly affect the impacts of carbon pricing. Finally, it is recommended that energy efficiency measures be incentivized to address partially this cost shock. [ABSTRACT FROM AUTHOR]

Global Value Chains (GVCs) significantly influence international trade and environmental outcomes. Despite the economic benefits of GVCs, their impact on the environment remains under-examined. This study analyzes the effects of GVC participation (considering forward and backward positions) on total carbon emissions embodied in exports (TEEE) and imports (TEEI). Utilizing panel data from 65 economies spanning 1995 to 2018, we apply input-output matrices and the system generalized method of moments (GMM-SYS) approach. Our results indicate that GVC participation generally is associated with reductions in TEEI and increases in TEEE, with backward participation exerting a more substantial impact. Furthermore, we observed asymmetrical impacts of GVC participation between developed and developing countries. Developed nations tend to reap greater benefits from GVC in terms of diminished CO2 emissions associated with imports, as well as notable CO2 reductions in both exports and imports, particularly when forward participation is the focal point. Conversely, developing countries grapple with heightened environmental burdens stemming from their engagement in backward linkages. [ABSTRACT FROM AUTHOR]

Introduction: The development of the digital economy has a profound impact on industrial economics. The article starts from the perspective of industrial organization theory. The thesis aims to analyze the industrial development of the digital economy and its three structural variables: digital manufacturing industry, digital service industry, and the development of industrial digitization on carbon emission intensity. Method: Based on the data of Input-output Tables with extended tables of 30 provinces, this paper analyzes the industrial development of digital economy and its three structural variables: digital manufacturing industry, digital service industry, and the development of industrial digitization on carbon emission intensity. Results and discussion: The empirical results show that: 1) at the national level, the development of China's digital economy industries has a suppressive effect on carbon emission intensity; 2) in terms of spatial effects, the development of digital economy has significant carbon spillover effects, but digital industrialization and industrial digitization present different spatial effect results; 3) from the analysis of regional heterogeneity, in the northeast, central and western regions, the direction of influence of digital industrialization and industrial digitalization on carbon emission intensity is consistent; in the eastern region, the development of digital industrial service sector and industrial digitalization has a suppressive effect on carbon emission intensity, while digital industrial manufacturing sector presents a pro-increasing effect; 4) Non-linear relationship analysis shows that the development of the digital industrial manufacturing sector has a "promoting and then inhibiting" effect on carbon emission intensity. Overall, the impact of digital industry development on carbon intensity exhibits a "promoting increase, then suppressing, then promoting increase" trend. In conclusion, the findings suggest that China's digital economy industry has entered the low-carbon development stage. [ABSTRACT FROM AUTHOR]

The World Trade Organization (WTO) and European Union (EU) have both put forward tax reforms that impact fisheries' fuel costs, which are similar in the object of taxation but quite different in the externalities addressed, goals, scope, exemptions or tax rates, creating an opportunity to compare the effects and discuss the alternatives. These proposals are the result of long and intense debates in political, social and academic spheres. However, certain aspects remain unclear. First of all, the number of empirical studies is still limited, particularly considering that fisheries governance is subject to heterogeneous management systems and institutional contexts creating room for different potential outputs. Second, coastal states have no fiscal competence beyond 12 miles, which limits the scope of the reforms to small scale fleets (SSF). All in all, the economic consequences for the fleets remain unclear. To this end, we will build on the Galician fishing sector (NW Spain) input–output tables to discuss the direct impacts, effects and side effects of these reforms on a representative European fleet. Flaws identified in both initiatives mean that targeted externalities will not be corrected and, moreover, additional ones, such as distributional effects penalising SSF or fuel spillovers, could be boosted. Alternative policy approaches are discussed. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Economia e Sociologia Rural is the property of Sociedade Brasileira de Economia e Sociologia Rural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to the scarcity of subnational interregional input–output (IRIO), various approaches to their estimation are actively under investigation in the literature. This paper focuses on the application of spatial econometric method. It determines intra- and interregional coefficients through a joint procedure which successfully avoids the direct recycling of estimates for other geographies and granularities. Instead, the use of Bayesian methods is proposed, which formally integrate limited evidence from existing regional tables (Finland) with a set of sectoral data on value added for 73 NUTS-3 regions in Poland, the latter being dominant. An empirical test of replicating the Korean survey-based IRIO table demonstrates that the accuracy of this approach slightly outperforms an alternative IRIOLQ procedure. The incorporation of time-based distance measurement has only modest effects on empirical fit, and the use of big geolocation dataset to account for commuting relocates 18.9% of the induced effect from a city to its periphery. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Tourism is an important and almost certainly increasing driver of anthropogenic climate change. However, intelligence on the total greenhouse gas emissions related to tourism trips – including travel to and from the destination – is limited, especially at sub-national destination scale. This paper uses an environmentally extended input-output approach to estimate the total greenhouse gas emissions consequent on inbound and domestic tourism trips in Wales, a region of the UK. We use the UN World Tourism Organisation (TSA) concept of visitors and trips to estimate the overall carbon footprint of tourism at around 3.4 megatons in 2019, 8.7% of total territorial emissions. We further compare these results with estimates for 2007 which suggests that there has been a modest reduction of under 2% per annum since 2007, but with significant data issues affecting comparability. Apparently slow progress in decarbonisation, including an increase in intercontinental visits to Wales over the period, suggest tourism here has not yet embarked upon a climate-responsible transformation. [ABSTRACT FROM AUTHOR]

Wassily Leontief met with decades of success for the development of input-output analysis, and yet he remained a staunch critic of the economics profession throughout his life. To understand his success, its limits, and the origins of his discontent, this article separates the scientific activities of input-output from the system of belief built around it, and from the institutions set up to advance Leontief's research program. This leads to considering the interaction of input-output with other research programs through three poles: the scientific debate, the collision of belief systems about the world, and an institutional fight for funds and researchers. The end result is a picture of how Leontief managed to build a successful research program in which scientific inquiry led to beliefs about the world that were able to justify building institutions promoting input-output, in an environment of competition and cooperation. [ABSTRACT FROM AUTHOR]

Abstract Objectives The Social Accounting Matrix (SAM) is an extension of Input-Output tables that records macro and meso-economic accounts of a socio-economic system. Its main objective is to provide a comprehensive understanding of the interrelationships among different economic sectors and agents. The SAM can be used for various purposes, including economic analysis, policy evaluation, and economic modelling. It allows policymakers to make more informed decisions, understand potential consequences of different policy options and serve as the foundation for constructing Computable General Equilibrium (CGE) models. Data description The SAM for Germany is a comprehensive source of data that reveals the incomes and expenditures of 163 different production sectors, along with data on factors of production, households, corporations, government, and external accounts with the rest of the world. Additionally, it provides information on gross fixed capital formation, changes in inventories, and natural capital accounts. This SAM was compiled by extending the EXIOBASE Input-Output (IO) accounts with data from the Federal Statistical Office of Germany. Balancing items were also used to ensure that the Total Income and Total Expenditure of the main transactors are in balance.

Economic effects are just one of the many effects of the massive infrastructure investment in Indonesia made over the past ten years. The aim of connecting Indonesia between regions is the basis for massive infrastructure growth, especially toll road infrastructure. Several funding schemes have been implemented to build toll road infrastructure, including the Public-Private Partnership (PPP) financing scheme. This PPP financing scheme was also implemented in the Balikpapan-Samarinda toll road construction. Therefore, this research attempts to capture the impact of the construction of the Balikpapan-Samarinda toll road with a PPP scheme on the formation of the economic structure in East Kalimantan province using the Input-Output (I-O) table. The investment value for the Balikpapan-Samarinda toll road is IDR 9.97 trillion was injected (shock) into gross fixed capital formation in the construction sector. The calculation results in this research show that the construction of the Balikpapan-Samarinda toll road contributed 9.8% of total demand. Apart from that, there is a significant impact on the economic structure of East Kalimantan Province, as seen from the expenditure multiplier figure with an output total of IDR 15,111 billion, a total income of IDR 2,471 billion, and a total workforce of 25,095 workers due to investment in the construction of the Balikpapan-Samarinda toll road.

This study aims to determine the sectors that need to be developed in the non-golden triangle area of the SULAMPUA region as a result of the Nusantara Capital City (NCC) development. Descriptive research is being conducted utilizing secondary data from Statistics Indonesia’s 2016 IRIO (Inter-Regional Input-Output) table. The IRIO model is used in data analysis for 20 secondary sub-sectors. The SULAMPUA region comprises 10 provinces, with the Golden Triangle region comprising South Sulawesi, Central Sulawesi, and West Sulawesi. The study results show that to take advantage of opportunities for the development of NCC, several key industries need to be developed for non-golden triangle areas, namely the food industry (I-13), non-metallic mineral goods industry (I-21); other processing industries, machinery and equipment repair and installation services (I-27); and the wood industry, goods from wood and cork, and woven goods from bamboo, rattan, and the like (I-17). Maluku, Papua, and West Papua provinces have relatively little opportunity to develop the industrial sector and benefit from moving NCC. Because the sectors connected directly or indirectly and the key sectors of these three provinces are capital-intensive industries, MSMEs have more significant barriers to entry. This research can be a reference for local governments in exploring potential industrial sectors to be developed to achieve NCC development opportunities.

Copyright of Jurnal Ekonomi dan Kebijakan Pembangunan is the property of IPB University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In Older to explCMe the cunwit development status and inwact of China's textile and clothing industry, the latest input-output tables of Qlina for the years 2012, 2015, 2017, 2018 and 2020 published by the National Bureau of Jftetjetics were used for empirical analysis through input-output models. The results show that China's textile and clothing industry has the nature of producing raw materials, belongs to the high to medWtf input rate, low value-added industry, intermediate product industry sector, and has a significant impact on other industrial sectors, with a more obvious driving effect on the national economy. When afianges occur in the textile and clothing industry sector, the driving effecBpn the closely related industry sectors is relatively high, but the promoting effect of changes in other sectors on China's textile and clothing industry is relatively small. In this regard, it is recommended that China's textile and clothing industry seize the opportunity to upgrade its industry, enhance industrial connections, increase product added value, build its own brand, and promote industrial development. [ABSTRACT FROM AUTHOR]

There is a significant time lag in the process of sectoral interactions, thus, it is necessary to identify the sectoral carbon emissions in time series. This paper calculates the time lag of sectoral carbon emissions of China's industrial sectors and constructs the monthly consumption data of sectors of 24 months, then simulates the monthly carbon emissions in the year 2022, the results are as follows: The terminal manufacturing industries receive carbon emissions from many sectors, and the energy supply industry generates carbon inflows to all sectors. Due to the time lag effect, some of the carbon emissions generated in the current period come from carbon accumulation in the previous periods. There are great differences in the time lag of sectoral carbon emissions, the carbon emissions of the energy supply industry are concentrated in the early stage while the time lag of the communication equipment manufacturing industry is long. Sectors show differences of carbon emissions in time series due to their different final consumption. In the whole year, the degree of carbon emissions in January and February is low and that in December is high. [ABSTRACT FROM AUTHOR]

Copyright of Jurnal Ilmu Ekonomi Terapan is the property of Universitas Airlangga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In input-output analysis, the Leontief and Ghosh models can be used to determine the price indexes of goods, which is convenient for analyzing inter-industry inflation. Their respective merits are debated, but both provide the same solution. We demonstrate that, contrary to common belief, it is superfluous to use the Leontief or Ghosh model to calculate price indexes: the price index vector alone satisfies the accounting identities without assuming constant coefficients. So, in contrast to the Leontief and Ghosh models, price indexes can be derived 'instantly', without a round-by-round process. Conducting research on price indexes deduce from the Leontief or Ghosh model becomes pointless: it suffices to study price indexes deduced from the data. We illustrate these findings with an application for France 2018. The same is demonstrated for prices with the data given in physical quantities. [ABSTRACT FROM AUTHOR]

Balancing input–output tables using iterative proportional fitting techniques can be prevented due to conflicting information. What is to be done in such cases? Literature suggests a wide variety of alternative methods. Within iterative proportional fitting techniques, modifying the constraint set to circumvent conflicting information problems has been suggested as a promising avenue. Following this approach, we identify some opportunities for improvement not yet been addressed. As a result of this research, we present an iterative proportional fitting variant. Our algorithm uses information contained in the matrix to be balanced for dynamically modifying our constraint set. We ensure economically meaningful solutions, avoiding unsought sign flips. We also respect all macroeconomic aggregates. To illustrate our findings, we provide an empirical example based on the supply-use tables for the region of Galicia (Northwest Spain). Results suggest that our methodological proposal can yield estimates almost as accurate as other alternatives while avoiding undesired outcomes. [ABSTRACT FROM AUTHOR]

Copyright of Nova Economia is the property of Nova Economia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)