Qualitative Input–Output Analysis of the Indian Economic Structure

Qualitative input–output (IO) analysis can be considered mostly in terms of a graph-theoretic formulation, which involves the construction and use of an adjacency matrix, derived from a binary transformation of the IO coefficient matrix. Classical attempts at qualitative IO analysis have derived the structure from the direct IO coefficient table. In more recent attempts, greater sophistication has been achieved by incorporating a degree of quantification into the qualitative analysis. Also, the concept of important coefficients (IC) has been used for the construction of the adjacency matrix. The present study is carried out along these lines for the Indian economy.     

Updating Input–Output Tables with Benchmark Table Series

Numerous methods have been proposed to update input–output (I–O) tables. They rely on the assumption that the economic structure will not change significantly during the interpolation period. However, this assumption may not always hold, particularly for countries experiencing rapid development. This study attempts to combine forecasting with a matrix transformation technique (MTT) to provide a new perspective on updating I–O tables. Under the assumption that changes in the trend of an economic structure are statistically significant, the method extrapolates I–O tables by combining time series models with an MTT and proceeds with only the total value added during the target years. A simulation study and empirical analysis are conducted to compare the forecasting performance of the MTT to the Generalized RAS (GRAS) and Kuroda methods. The results show that the comprehensive performance of the MTT is better than the performance of the GRAS and Kuroda methods, as measured by the Standardized Total Percentage Error, Theil's U and Mean Absolute Percentage Error indices.     

Adjustment of Input–Output Tables from Two Initial Matrices

The compilation of the information required to construct survey-based input–output (I–O) tables consumes resources and time to statistical agencies. Consequently, a number of non-survey techniques have been developed in the last decades to estimate I–O tables. These techniques usually depart from observable information on the row and column margins, and then the cells of the matrix are adjusted using as a priori information a matrix from a past period (updating) or an I–O table from the same time period (regionalization). This paper proposes the use of a composite cross-entropy approach that allows for introducing both types of a priori information. The suggested methodology is suitable to be applied only to matrices with semi-positive interior cells and margins. Numerical simulations and an empirical application are carried out, where an I–O table for the Euro Area is estimated with this method and the result is compared with the traditional projection techniques.     

Using Weighted Least Squares to Deflate Input–Output Tables

This article proposes a balancing procedure for the deflation of input–output (I-O) tables from the viewpoint of users. This is a ‘subjective’ variant of the Weighted Least Squares (WLS) method, already known in the literature. It is argued that it is more flexible than other methods, and it is shown that SWLS subsumes the first-order approximation of RAS as a special case. Flexibility is due to the facts that (a) users can attach differential ‘reliability’ weights to first (unbalanced) estimates, depending on the confidence they have in the different parts of their pre-balancing work, (b) differently from RAS, one is not bound to take any row or column total as exogenously given, and (c) additional constraints can be added to it. The article describes also how SWLS was utilised to estimate a yearly (1959–2000) series of constant-price I-O tables for the Italian economy.     

Agglomeration and Trade with Input–Output Linkages and Capital Mobility

Abstract

This paper proposes a nesting ‘New Trade, New Economic Geography’ model in which agglomeration is driven by input–output linkages among firms, trade in goods and capital mobility. The New Economic Geography sub-model exhibits the same positive and dynamic properties as a wide class of models based on other agglomeration mechanisms. Its normative implications are nuanced: equity and efficiency do not necessarily conflict. When input–output linkages are strong, agglomeration might Pareto-dominate dispersion because agglomeration lowers producer prices. When vertical linkages are weak, the market is biased in favour of agglomeration if the planer has a strong aversion to inequalities.

RÉSUMÉ

Accumulation et commerce avec intégration amont-aval et mobilité du capital.

Cet article décrit un modèle, qui a donné naissance au modèle commercial de Flam et Helpman (1987), et de Martin et Rogers (1995) et à un modèle original à la Krugman « Nouvelle Géographie Economique » (1991). L'accumulation se produit par l'intégration amont-aval des sociétés entre elles et par la mobilité du capital. L'auteur étudie les conséquences positives puis normatives du modèle. Dans le domaine des conséquences positives, le modèle NGE montre les mêmes propriétés dynamiques que les autres modèles fondés sur d'autres mécanismes d'accumulation (migration du travail, accumulation de capital humain). Donc, ce modèle est bien adapté pour étudier les questions de localisation des industries, du commerce des biens et de la mobilité du capital. En ce qui concerne les conséquences normatives, lorsque l'intégration amont- aval est forte, l'accumulation peut l'emporter sur la dispersion de Pareto, parce que l'accumulation conduit à une diminution des prix du producteur: l'efficacité et la valeur n'entrent pas forcément en conflit dans ce modèle. Quand l'intégration verticale est faible, le marché est orienté en faveur de l'accumulation si le décideur montre une grande aversion aux inégalités.

RESUMEN

Aglomeración y comercio con enlaces de entrada–salida y movilidad de capital

En este artículo expongo un modelo que atrapa el modelo comercial de Flam y Helpman (1987), de Martin y Rogers (1995) y de un modelo original según la teoría la ‘Nueva Geografía Económica’ de Krugman (1991). La aglomeración está impulsada por enlaces de entrada–salida entre las sociedades y por la movilidad de capital. Aquí analizo las implicaciones positivas y normativas del modelo. En términos de implicaciones positivas, el modelo NEG expone las mismas propiedades dinámicas como una amplia clase de modelos basados en otros mecanismos de aglomeración (migración laboral, acumulación de capital humano). De este modo, el modelo encaja bien para estudiar cuestiones en cuanto a la ubicación de la industria, el comercio de mercancías y la movilidad de capital. Con respecto a las implicaciones normativas, cuando son sólidos los enlaces de entrada–salida, la aglomeración podría dominar la dispersión en el diagrama de Pareto debido a que la aglomeración hace disminuir los precios de los productores: en este modelo la eficiencia y la equidad no necesariamente están en conflicto. Cuando los enlaces verticales son débiles, el mercado es sesgado a favor de la aglomeración si el planificador tiene una fuerte aversión a las desigualdades.     

An Aggregated Regional Economic Input–Output Analysis within a Fuzzy Environment

Abstract

Imprecision within economic input–output frameworks can be a problem, particularly when investigating the characteristics of defined industry sectors. This study undertakes an aggregated regional economic input–output analysis, within a fuzzy environment. The dearth of studies encompassing a fuzzy approach within input–output analysis largely concerns the problematic representation of imprecision. Results pertaining to the fuzzy output multipliers associated with each sector group are described, including possibilistic mean and variance; also identified is a specific ranking of the sector groups. Where appropriate, results are compared with those from a Monte Carlo simulation based stochastic analysis.     

Augmenting the Input–Output Framework for ‘Common Pool’ Resources: Operationalising the Full Leontief Environmental Model

In its initial formulation, the full Leontief (1970) Leontief, W. 1970. Environmental repercussions and the economic structure: an input–output approach. Review of Economics and Statistics, 52: 262–277. [Crossref], [Web of Science ®] [Google Scholar] environmental model augments the conventional Input–Output (IO) table by introducing pollution generation and separately identified pollution elimination sectors. Essentially it extends IO analysis to incorporate the use of a ‘common pool’ resource. Subsequent literature has either been analytical in nature or has concentrated on pollution generation but not cleaning activity. In this paper we generate an empirical full Leontief environmental IO system, based on augmenting the existing Scottish IO tables through endogenising waste generation and waste disposal activity. Due to weaknesses in data, our empirical results need to be treated with some caution. However, the construction of the extended IO system and the interpretation of the output and price multiplier results raise a number of interesting practical and conceptual issues. The analysis undertaken here can be extended to other ‘common pool’ resources such as the use of highways and irrigation systems.     

Some Relationships between T-Accounts,Input–Output Tables and Social Accounting Matrices

Some relationships between the T-accounting format for presenting commodity balances; input–output (IO) tables; and social accounting matrices are discussed in this paper. The starting point is to recognize that IO tables do not contain all the information that is needed to complete a social accounting matrix (SAM), or, therefore, for the modelling of phenomena that depend on having a fully articulated SAM, such as the interdependence of the distribution of income and the structure of production. There is a need, therefore, to establish the character of the extra information that is required and this can be achieved by imposing the requirement that a SAM should be consistent with the basic cash identity that is fundamental to all social accounting. A second agendum is to develop the argument that, while T-accounts can, in principle, provide a database equivalent to that of a SAM, in practice, they are typically found to be an imperfect substitute. It is important, therefore, in designing a database, to go beyond the confines of an (extended) IO system and T-accounts. SAMs provide an appropriate framework for doing so.     

Beyond Intermediates: The Role of Consumption and Commuting in the Construction of Local Input–Output Tables

Estimating intermediate trade using conventional non-survey methods produces biased results. This problem has led to a methodological recommendation that emphasizes the accurate estimation of intermediate trade flows. This paper argues for a qualification of the consensus view: when simulating input–output (IO) tables, analysts need also to consider spillover effects driven by wage and consumption flows. In particular, for metropolitan economies, capturing wage and consumption flows is essential to obtain accurate Type II multipliers. This is demonstrated by constructing an interregional IO table that captures the interdependence between a city and its commuter belt, nested within the wider regional economy.     

Completing Input–Output Tables using Partial Information,with an Application to Canadian Data

This paper develops a three-stage extension of the standard biproportional RAS algorithm-an extension that we label TRAS-to incorporate information in addition to row and column margins. The TRAS algorithm is tested using pseudo-censored input–output tables and is shown to produce more accurate estimates than does the RAS algorithm.     

Disaggregating input–output tables in time: the temporal input–output framework

The input–output framework has evolved dramatically since its initial formulation. New analytical techniques and extensions have allowed a more comprehensive assessment of the economy and expanded its applicability. Nonetheless, the core of the framework has remained unchanged: an annually compiled input–output table, which conveys monetary flows between sectors in a region in a particular year. Hence, the technical coefficients derived from it are ‘average’ input compositions, neglecting fluctuations in production capacity, seasonality and temporal shocks within that period. This paper develops a consistent methodology to disaggregate the annual input–output table in its time dimension in order to estimate intra-year input–output matrices with distinct technical structures for a particular year. The main advantages in relation to the annual model are to allow seasonal effects to be studied within the input–output framework, to better understand the process of coefficient change and to offer a more comprehensive dynamic view of production.     

How Japan–US Economic Interdependence Changed from 1985 to 1990: Some Findings from Price-adjusted MITI Intercountry Input–Output Tables

This paper consists of two parts. First, constant-price Japan–US intercountry input–output (IO) tables are compiled, based on Japan–US IO tables of the Ministry of International Trade and Industry (MITI) for 1985 and 1990, and the relative producer prices of both countries, which are estimated by the ‘peeling off’ method from OECD purchasing power parity data. Second, a factor decomposition analysis is carried out to show changes in Japan–US economic interdependence between 1985 and 1990. The Leontief inverse matrices of intercountry IO tables are decomposed into three matrices, which reflect domestic repercussion effects, spillover effects to the other country and feedback effects of own final demand from the other country. Then, a traditional decomposition analysis of changes in production for both countries is applied to see how both countries' economic interdependence changed. It is found that Japan–US economic interdependence moved from a pattern of Japan's dependence on the US to an almost equally interdependent pattern, although the degree of dependence was still higher in Japan in 1990. At the same time, there are significant industrial structural changes in the relationship between both countries, as a result of the significant appreciation of the yen relative to the dollar from 1985 to 1990.     

The RAS Approach in Updating Input–Output Matrices: An Instrumental Variable Interpretation and Analysis of Structural Change

The main purposes of the paper are to reconsider the rationale of the RAS method, and to attempt to improve on its interpretation and usefulness. The substitution and fabrication factors in the RAS method are interpreted as statistical estimates obtained by the method of instrumental variables. This enables the computation of asymptotic standard errors for the factors and the relative precision of the predicted technical coefficients. Furthermore, an adjustment cost minimization model to describe how a sector determines its substitution and fabrication factors is presented. The solutions of the model provide another rationale for the RAS method, and the associated Lagrangian multipliers can be useful for assessing structural constraints and structural change.     

An efficiency measure satisfying the Dmitruk–Koshevoy criteria on DEA technologies

The purpose of this paper is to develop an efficiency measurement model by enhancing a CCR (Charnes?CCooper?CRhodes) model and then to prove that the enhanced model satisfies five desirable properties: indication, strict monotonicity, homogeneity, continuity and units unvariance. In order for our model to be empirically tractable, we also provide an algorithm aimed at estimating efficiency scores.     

On the dimensionality of bounds generated by the Shapley–Folkman theorem

The Shapley–Folkman theorem places a scalar upper bound on the distance between a sum of non-convex sets and its convex hull. We observe that some information is lost when a vector is converted to a scalar to generate this bound and propose a simple normalization of the underlying space which mitigates this loss of information. As an example, we apply this result to the Anderson (1978) core convergence theorem, and demonstrate how our normalization leads to an intuitive, unitless upper bound on the discrepancy between an arbitrary core allocation and the corresponding competitive equilibrium allocation.     

Input–output linkages and the propagation of domestic productivity shocks: assessing alternative theories with stochastic simulation

Relatively small sectoral productivity shocks could lead to sizable macroeconomic variability. Whereas most contributions in the literature analyze the issue of aggregate sensitivity using simple general equilibrium models, a novel approach is proposed in this paper, based on stochastic simulations with a global computable general equilibrium model. We find that the variability of the GDP, induced by sectoral shocks, is basically determined by the degree of industrial concentration as measured by the Herfindahl index of industrial value added. The degree of centrality in inter-industrial connectivity, measured by the standard deviation of second-order degrees, is mildly significant, but it is also correlated with the industrial concentration index. After controlling for the correlation effect, we find that connectivity turns out to be statistically significant, although less so than granularity.     

Comparative Research on the Stock Return Distributional Models

This paper compares the stock return distribution models of mixture normal distribution, mixed diffusion-jump and GARCH models based on the data of Chinese stock market. The Schwarz criterion is also used. We find all these models can capture the features of stock returns partly. EGARCH model is the best fitting to daily return and stable during different period. When the weekly and monthly returns are tested, the differences of the models＇ fitness become unobvious and unstable.     

A PCA–DEA approach to measure the quality of life in Estonian counties

This paper investigates the application of a PCA–DEA model to assess the quality of life (QOL) scores in Estonian counties and analyses the model's results. The dataset is a balanced panel of 15 Estonian counties covering the period from 2000 to 2011. We consider a PCA–DEA model as an alternative method to estimate and predict QOL scores and rankings of Estonian counties. The method consists of a two-stage analysis that begins with a principal component analysis. In the second stage, the standard DEA is used. The results from the conventional DEA model and the PCA–DEA model are compared and discussed. A comparison of the methodologies demonstrates that a PCA–DEA model provides a powerful tool for performance ranking. The rankings of Estonian counties using QOL scores for different model specifications are presented. Finally, the QOL ranking of Estonian counties is revised using PCA–DEA.