REGIONAL WATER FOOTPRINTS OF THE YANGTZE RIVER: AN INTERREGIONAL INPUT–OUTPUT APPROACH

Recently, researchers have applied the multi-regional input–output (MRIO) approach to water footprint (WF) analysis. The concept of interregional input–output (R-MRIO) was developed to analyse regional issues. Researchers have concentrated on the development of global or international input–output (N-MRIO) tables. Using the N-MRIO and the R-MRIO approach allows the study of global and regional issues, respectively. The WF is an indicator influenced by trade among nations and regions. However, the treatment of imports in an R-MRIO approach differs in whether international imports are separated or combined. We evaluate the effects of the difference between these models and discuss policy implications for the Yangtze River, China. The WF calculated using the combined type model is 11% larger than that by the separated type model. This difference can be ascribed to international imports, mainly internal consumption and interregional trade. We find that this difference affects social equity in water-abundant areas.     

Make and Use Approaches to Regional and Interregional Accounts and Models

Institutional, or sector-by-sector input–output tables have traditionally been used in regional and interregional modelling. This paper examines the origins of this tradition and argues instead, both theoretically and empirically, for the integration of make and use submodels within models of production, demand and interregional trade, outlining the manner in which they can be integrated. Further, it is argued that structural rather than reduced-form models represent a sounder theoretical base. Finally, a Danish interregional model (LINE) based on a social accounting matrix framework that employs these principles is presented. The paper also deals with the issue of data construction at the regional and interregional levels, based on the make and use approach. It is argued that when data are constructed at a low level of sectoral and spatial aggregation under accounting consistency constraints, data quality and validity are high.     

Econometric modeling of technical change

The purpose of this paper is to present a new approach to econometric modeling of substitution and technical change. Substitution is determined by observable variables, such as prices of output and inputs and shares of inputs in the value of output. Our principal innovation is to represent the rate and biases of technical change by unobservable or latent variables. This representation is considerably more flexible than the constant time trends employed in the previous literature. An added advantage of the new representation is that the latent variables can be projected into the future, so that the rate and bias of technical change can be incorporated into econometric projections.     

An Alternative Factor-analytic Approach to Aggregation of Input–Output Tables

This paper is concerned with the question of finding sets of similar micro-level industries that can be grouped to obtain a smaller set of macro-level industries. We argue that factor analysis based on the Leontief inverse is a promising approach when multiple objectives of classification must be taken into account, provided that the cosine, rather than the correlation coefficient, is adopted as the measure of similarity. We apply this approach to the 1967 US input–output table because that table has been used by researchers experimenting with alternative classification methods.     

Some remarks on a social network approach to identifying key sectors

Ostensibly, certain adaptations of social network theory extend and improve the traditional key-sector approaches. Our analysis of the underlying algebraic properties shows that a social-network-based approach proposed by García Muñiz et al. [(2008) Key Sectors: A New Proposal from Network Theory. Regional Studies, 42, 1013–1030] does not relate final demand and output in ways comparable to key-sector measures that are based on the static Leontief input–output model. Using the most recent IO table for Poland we show that the modified approach can lead to spurious empirical results and, as a consequence, to false policy implications.     

Analysis of Hospital Production: An Output Index Approach

In this study, we develop and implement an output index approach to the estimation of hospital cost functions that reflects the differentiated nature of hospital care. The approach combines the estimation of an output index within a flexible functional form. We find, in an application to California hospitals, evidence of scope economies across specialties within primary care, and diseconomies of scope within secondary and tertiary care. Minimum efficient scale is reached at larger levels of output than would be estimated by conventional techniques. These results indicate the importance of accounting for firm output heterogeneity when estimating cost functions. Copyright © 2014 John Wiley & Sons, Ltd.     

DEA target setting using lexicographic and endogenous directional distance function approaches

Directional Distance Function (DDF) is an approach often used in data envelopment analysis (DEA) due to its clear interpretation and to the flexibility provided by the possibility of choosing the projection direction towards the efficient frontier. In this paper two new DDF approaches are considered. The first one uses an exogenous directional vector and a multi-stage methodology that at each step uses the projection along the input and output dimensions of the directional vector that can be improved. This lexicographic DDF approach also computes a directional efficiency score and a directional inefficiency indicator for each input and output variable. The second approach is a non-linear optimization model that endogenously determines the directional vector so that the smallest improvement required to reach the efficient frontier is computed.     

On Two Existing Approaches to Statistical Analysis of Social Media Data

Using social media data for statistical analysis of general population faces commonly two basic obstacles: firstly, social media data are collected for different objects than the population units of interest; secondly, the relevant measures are typically not available directly but need to be extracted by algorithms or machine learning techniques. In this paper, we examine and summarise two existing approaches to statistical analysis based on social media data, which can be discerned in the literature. In the first approach, analysis is applied to the social media data that are organised around the objects directly observed in the data; in the second one, a different analysis is applied to a constructed pseudo survey dataset, aimed to transform the observed social media data to a set of units from the target population. We elaborate systematically the relevant data quality frameworks, exemplify their applications and highlight some typical challenges associated with social media data.     

EXPANDING EXTRACTIONS

In this paper, we generalize hypothetical extraction techniques. We suggest that the effect of certain economic phenomena can be measured by removing them from an input–output (I–O) table and by rebalancing the set of I–O accounts. The difference between the two sets of accounts yields the phenomenon's effect (or importance). We suggest that the approach can be used to measure the effect of changes in intermediate output, which are otherwise not easily rationalized within a Leontief framework. Of course, it can also be used to estimate the possible effects of the shutdown of a particular establishment or other identifiable segment of an economy. We demonstrate some properties and potential of the approach using the annual 2006 US I–O accounts.     

A dual measure of correlation between the Solow residual and output growth

In this paper, we measure U.S. technology shocks by implementing a dual approach, which is based on price data instead of aggregate quantity data. By doing so, we find the relative volatility of technology shocks and the correlation between output fluctuation and technology shocks to be much smaller than those revealed in most real-business-cycle (RBC) studies. Our results support the findings of Burside et al. (Eur Econ Rev 40:861–869, 1996), who showed that the correlation between technology shocks and output is exaggerated in the RBC literature. This suggests that one should examine other sources of fluctuations for a better understanding of the business cycle phenomena.     

ECONOMETRIC ANALYSIS OF EUROPEAN CARBON DIOXIDE EMISSIONS BASED ON RECTANGULAR SUPPLY-USE TABLES

This paper formalises the so-called Supply-Use Based Econometric (SUBE) approach that allows for the introduction of econometric analysis in the calculation of backward input–output multipliers of the Leontief-type quantity model, using rectangular supply and use tables. The SUBE approach does not require any kind of inverse matrix and incorporates the traditional approach (with square supply-use tables) as a particular case. The empirical analysis shows that the SUBE carbon dioxide multipliers for the EU27 are considerably lower than those obtained by the traditional Leontief inverse. In an application of the SUBE approach, the European economy appears to emit about 10% less carbon dioxide than in a situation in which it would not import any intermediate inputs from outside the EU27.     

R&D in a strategic delegation game

This paper studies how a separation of ownership and management affects firms' R&D and production decisions in Cournot quantity competition. It is found that when R&D spillovers are small, owners strategically direct their managers away from profit maximization towards sales. Consequently, managerial firms invest more in R&D and have higher output and lower prices compared to their entrepreneurial counterparts. On the other hand, when spillovers are large, owners ‘penalize’ managers for sales. In this case, managerial firms have lower R&D, lower output and higher prices. Nonetheless, managerial firms have lower profits than their entrepreneurial counterparts regardless of spillovers. This paper also examines the welfare effects of a separation of ownership and management. It is found that in terms of first-best social welfare, managerial firms are more (less) efficient than their entrepreneurial counterparts with low (high) spillovers. However, in terms of second-best social welfare, managerial firms are less efficient with all spillovers. © 1997 John Wiley & Sons, Ltd.     

行业联合限产模型

本文提出了行业联合限产可行性的理论基础，并尝试给出了分配生产配额的限产模型，以期能寻找一种避免价格战不利影响，减少社会资源浪费的可行途径。     

Modeling the Economy as a Whole: An Integrative Approach

This article integrates the social surplus approach with input‐output, stock‐flow consistent, social accounting, and social fabric modeling with a structure‐agency methodology to develop a historically grounded model of the economy. The first two sections develop a model of the monetary structure of the social provisioning process. The third section introduces agency into the model in the form of the acting organization. The fourth section uses the social fabric approach and historical context drawn from social structures of accumulation to develop a socially embedded, historically contextualized, structured‐agency model of the economy as a whole. The final section discusses the importance of the model.     

Bikes versus lease cars: the adoption,design and use of cafeteria systems in the Netherlands

In the 1990s, Dutch employers started adopting individualized pay systems, commonly called ‘cafeteria systems’. Reports on their use by employers and employees suggest a bewildering variety in their adoption, design and use (by employees). This paper presents an analytical framework to analyse this variety. We distinguish as the main explanatory factor whether there has been voluntary or coerced adoption. The latter refers to introduction as part of sectoral collective labour agreements. Different adoption drivers are argued to have consequences for the design and employee use of cafeteria systems.     

基于BP神经网络的商品房销售量预测研究

商品房销售量受多个因素的作用，而且这些作用多是非线性的。商品房销售量预测实质上是实现一个非线性的映射。本文选择了恰当的经济指标作为BP网络的输入输出变量，探讨将神经网络技术应用于商品房销售量的预测领域，并与回归模型、Logistic模型的预测结果进行比较，结果表明人工神经网络方法在商品房销售量预测中的应用是可行的，预测效果更好。     

Comparisons of Economic Inefficiency Between Output and Input Measures of Technical Inefficiency Using the Fourier Flexible Cost Function

The current paper constructs a Fourier flexible cost function, which is commonly known to be a more general function form than the typical translog form, and can globally approximate a true (but unknown) cost function. Both allocative and technical inefficiencies are considered using the Fourier function in the context of the parametric approach. The former is modeled using shadow input prices and the latter is formulated either by adding an extra term of scale parameter (when the Farrell's (1957) input technical inefficiency is assumed), or by correcting all the terms involving output quantities by a scale parameter (when the Farrell's output technical inefficiency is assumed). It is found that sample banks could save up to 23% of total costs, within the range of 3 and 69% uncovered by the previous works, in which allocative inefficiency plays a more important role than technical inefficiency. Furthermore, the cost of misallocated labor input alone constitutes more than 80% of total allocative inefficiency. Financial deregulation starting from 1991 in Taiwan appears to have improved economic efficiency of the banking industry.     

An envelopment-based approach to measuring regional social progress

Today, more than ever, it is becoming evident that Gross Domestic Product (GDP) alone is not sufficient in guiding national development strategies. In this sense, measuring the social progress of a country can provide an additional lens on national performance, which would eventually help policymakers to not only gain an advanced understanding of the ways that would unleash greater long-term economic success, but also be able to propose strategies that would create the conditions for all individuals in a society to reach their full potential, enhancing and sustaining the quality of their lives. In this paper, we propose a method to measure social progress at the sub-national level, with an application to the Peruvian regions. As such, this paper builds a unified envelopment-based model for integrating a two-stage process of the index generation. We compare and contrast the radial and non-radial envelopment approaches; it is evident from the model that the non-radial approach provides better insights when compared to the radial approach.     

Reconciling Domestication Techniques,the Notion of Re-exports and Some Comments on Regional Accounting

Recent work by Jackson (1998) subtly pointed out a means of forming direct input coefficient matrices from national technology that is different from that published elsewhere. In this paper, I rationalize his approach and also point out that prior approaches may still be useful in certain applications where the phenomenon of re-exports (imports that satisfy exports) are explicit in exports accounts. In the second half of this paper, I show some means of developing regional accounts, currently being used in the US, that are more elaborate than those Jackson discussed. For example, I substitute regional shares of employment with earnings shares to obtain productivity adjusted regional output. I also suggest using available regional value added and regional labour income when producing regional Use matrices.     

Testing the Stability of a Production Function with Urbanization as a Shift Factor

Urban economists have long sought to explain the relationship between urbanization levels and output. In this paper we revisit this question and test the long-run stability of a production function including urbanization using non-stationary panel data techniques. Our results show that a long-run relationship between urbanization, output per worker and capital per worker cannot be rejected for either our sample of 30 developing countries or our sample of 22 developed countries. We do find, however, that the sign and magnitude of the impact of urbanization varies considerably across the countries. In addition, we estimate the long-run average effects on GDPW of urbanization and capital. These results offer new insights and potential for dynamic urban models rather than the simple cross-section approach.