Comparison of Two Methods of Identifying Input-Output Coefficients for Exogenous Estimation

Input-output (IO) updating research indicates substantial improvements in the forecasts when some of the coefficients have been exogenously estimated and included in the updating process. Several methods for identifying the appropriate subsets have been proposed. The present paper attempts to assess the relative performances of two such approaches: 'the largest coefficients' and 'the most important parameters' criteria. Utilizing these criteria, a set of coefficients from the 1966 IO table of the former Soviet Union were selected and exogenously determined. The remaining coefficients were updated to 1972 by means of naive, RAS, and Lagrangian techniques. Comparison of the results with the 1972 benchmark table provided the desired answers.     

Prices and factor demand in an endogenized input–output model

This paper combines factor demand functions (for intermediate input and labour) and price equations (derived from a Generalized Leontief cost function) with the traditional input–output price model. The cost functions determine factor demands for materials and labour as well as output prices at given input prices. At the second level of aggregation, the intermediate demand as a single input is split proportional to the elements in the column of the technical coefficients matrix. The emphasis in this endogenization of technical coefficients is on two features. First, the repercussion of output on input prices, and, second, the link between the econometric model for the supply side and the input–output demand model.     

Increasing the Timeliness of US Annual Input-Output Accounts

The timeliness of the US input-output (I-O) accounts is a major concern for policymakers and industry analysts, as well as academics. In response, the Bureau of Economic Analysis initiated research in 2001 to identify, develop and implement an estimating method for producing more timely and reliable annual I-O accounts than are currently available. The research included reviewing the frameworks and methods currently used by other statistical agencies and academic researchers, obtaining more timely industry source data, and developing enhanced methods and processes for the automated updating and balancing of annual I-O tables. The results of this research indicate that our new automated updating and balancing method can reduce the time lag for producing the annual I-O accounts from three years to one year without reducing quality. Our method is based on an adjusted RAS process that simultaneously balances the I-O table in producers' and purchasers' prices; uses more exogenous data; and processes tables at the most detailed level.     

New Nonlinear Approaches for the Adjustment and Updating of a SAM

Many structural relationships should be taken into account in any reasonable adjustment and updating process. These structural relationships are mainly represented by ratios of different types, such as technical coefficients or the proportion of the cell value in relation to its row or column total. We believe that in many cases (either because of lack of information or when the time elapsed for the estimation of a social accounting matrix is not long enough to allow for any significant structural change) the updating process should try to minimize the rela- tive deviation of the new coefficients from the initial ones in a homogeneous way. This homogeneity would mean that the magnitude of this relative deviation is similar among the elements of each row or column, therefore avoiding the concentration of the changes in particular cells of the SAM. In this work, we propose some new adjustment criteria in order to obtain a more homogeneous relative adjustment of the structural coefficients. These criteria combine the adjustment method proposed by Matuszewski et al. (1964) with other deviation functions. Each of the adjustment criteria proposed leads to a nonlinear optimization problem which is reformulated as a linear program. We test the usefulness of this proposal by comparing its results with the ones obtained by more standard approaches and we are able to show that these approaches tend to produce a less homogeneous pattern of coefficient adjustment, under certain circumstances, than the ones we put forward.     

Coefficient Change in Embedded Econometric and Input–Output Models at the Regional Level

This paper examines the nature of coefficient change in integrated econometric (EC) and input–output (IO) models that employ an embedding strategy. Existing approaches towards coefficient change in integrated models are first reviewed and several substantive processes that give rise to dynamic coefficients at the regional level are identified. The main sources of coefficient change arise from dynamic adjustment processes that affect the regional purchase coefficients, regional technological coefficients and regional integration parameters. Each of these sources of change requires a different treatment when adopting an EC perspective. A general framework is suggested that nests each treatment as a specific case. The different specifications are then implemented in an embedded EC and IO employment demand model for the San Diego region, and evaluated through a series of in-sample and out-of-sample forecasting experiments. Simulation performance is found to improve through the use of a time-varying integra tion parameter. The results also indicate that model performance is more sensitive to the use of dynamic regional purchase coefficients than to the use of dynamic technical coefficients.     

ECONOMETRIC MODELS OF ASYMMETRIC PRICE TRANSMISSION

Abstract In this paper, we review the existing empirical literature on price asymmetries in commodities, providing a way to classify and compare different studies that are highly heterogeneous in terms of econometric models, type of asymmetries and empirical findings. Relative to the previous literature, this paper is novel in several respects. First, it presents a detailed and updated survey of the existing empirical contributions on price asymmetries in the transmission mechanism linking input prices to output prices. Second, this paper presents an extension of the traditional distinction between long‐run and short‐run asymmetries to new categories of asymmetries, such as: contemporaneous impact, distributed lag effect, cumulated impact, reaction time, equilibrium and momentum equilibrium adjustment path, regime effect, regime equilibrium adjustment path. Each empirical study is then critically discussed in the light of this new classification of asymmetries. Third, this paper evaluates the relative merits of the most popular econometric models for price asymmetries, namely autoregressive distributed lags, partial adjustments, error correction models, regime switching and vector autoregressive models. Finally, we use the meta‐regression analysis to investigate whether the results of asymmetry tests are not model‐invariant and find which additional factors systematically influence the rejection of the null hypothesis of symmetric price adjustment. The main results of our survey can be summarized as follows: (i) each econometric model is specialized to capture a subset of asymmetries; (ii) each asymmetry is better investigated by a subset of econometric models; (iii) the general significance of the F test for asymmetric price transmission depends mainly on characteristics of the data, dynamic specification of the econometric model, and market characteristics. Overall, our empirical findings confirm that asymmetry, in all its forms, is very likely to occur in a wide range of markets and econometric models.     

ON THE PARAMETERIZATION OF TECHNIQUES FOR REPRESENTING REGIONAL ECONOMIC STRUCTURES

This paper is concerned with two parameterized methods of regionalising input–output coefficients: the Flegg et al. Location Quotient (FLQ) and its augmented version (AFLQ). For applying the two techniques, a parameter δ has to be estimated. In this regard, the paper faces two matters that are still open in the literature: the existence of a range of δ that can be used in different regions and the estimation of the most appropriate value of δ. For this aim, a Monte Carlo simulation has been carried out in order to generate ‘true’ multiregional I-O tables randomly. From the simulation, analyses based on probability distributions and regression were also carried out. Finally, these simulation results have been compared with those of an empirical case. Results confirm that there is actually a range of values of δ within which the best δ is more likely to fall. For the FLQ, this range is centred on 0.3 with an associated probability of 33% (if the width of the range is set at 0.1), whereas, for the AFLQ, the relevant range is between 0.3 and 0.4 with a probability by 38%. Finally, this paper provided a way to estimate the best δ for a given region, without knowing the relevant and detailed economic structure at sectoral level.     

Alternative Input-Output Matrix Updating Formulations

There has been a recent resurgence of interest in biproportional adjustment methods for updating and interpreting change in matrix representations of regional structures, most commonly input-output accounts. Although the biproportional method, commonly called the RAS technique in the input-output literature, has been shown to have a number of theoretically appealing properties, various alternatives do exist. In this paper, we develop and empirically assess a number of alternatives, comparing performance and examining the attributes of these adjustment methods. Two of these are sign-preserving updating methods for use when tables contain both positive and negative entries. One of these is shown to generate less information gain than does a generalized RAS method that Junius & Oosterhaven (2003) formulated to deal with matrices with both positive and negative values. Overall, while the RAS method continues to be commonly used and its choice is often rational, alternative methods can perform as well or better along certain dimensions and in certain contexts.     

Multivariate partial adjustment of financial ratios: a Bayesian hierarchical approach

In this paper we propose a multivariate extension of the partial adjustment model of financial ratios. To that end, we use a dynamic factor model which assumes that financial ratios measuring, essentially, the same economic–financial dimension of the firm evolve in a similar way, reflecting the evolution of the common factor. The proposed model is hierarchical with three levels. The first describes the relationship between each ratio and its common factor; the second describes the evolution of the common factors over time by means of Lev's ( 1969 ) partial adjustment model; and the third analyzes the similarity of firms' adjustment coefficients, taking into account their characteristics. The methodology is applied to the analysis of a set of financial ratios related to the business and financial structure of the firm. Copyright © 2008 John Wiley & Sons, Ltd.     

Growth in transition: Reexamining the roles of factor inputs and geography

In this paper we re-consider the role of factor inputs in determination of long-run growth for transition countries. For this purpose, we estimate cross-sectional growth equations using spatial econometric models. Investments in physical and human capital are found to be significant growth factors for the period after 1994. The estimated coefficients are very similar to those obtained in the literature for developed market economies. We also find evidence for spatial autocorrelation of growth, due mostly to the wars and financial crises in the region. Correction for such correlation increases the significance of the explanatory variables.     

Technological change and input-output analysis: An appraisal

There is an extensive literature on technological change (TC) pertaining to input-output (I-O) analysis, that offers the potential to significantly extend the range of applications of this valuable tool. This paper classifies and analyzes the major types of TC. It summarizes some established methods for estimating TC, expands on methods not well developed, and shows how some methods not typically identified with I-O are useful. In addition, the methods are critically evaluated and their appropriateness to various subcategories of TC assessed.Two major conclusions are drawn. First, that input-output does not deserve much of the criticism it receives for being a rigid tool of analysis, insensitive to price changes, policy regulations and innovation. Second, given the availability of numerous approaches to incorporating TC into I-O models, researchers no longer have a legitimate excuse for assuming away TC or using crude modification methods.     

Raising the bar (11)

This editorial summarizes the papers published in issue 14(2) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper deals with past and current challenges for regional science research. The second paper investigates whether people living in deprived neighbourhoods have less chance of succeeding in a job application. The third paper finds evidence that real estate firms can avoid price competition when market shares of their allies increase in the vicinity. The fourth paper is methodological: it considers a spatial autoregressive (SAR) model with heterogeneous coefficients and extensively analyzes the impact of this extension on the direct and indirect effects estimates. The fifth paper proposes an innovative method to estimate the elements of the spatial weight matrix in a spatial econometric model. The final paper is econometric–theoretical: it proposes a new generalized method of moments (GMM) estimator of the coefficients of a SAR model if the error terms are heteroskedastic of an unknown form.     

Raising the bar (10)

This editorial summarizes the papers published in issue 14(1) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper applies the Shapley-based decomposition approach to determine the impact of firm-, linkage- and location-specific factors to the survival probability of enterprises. The second paper applies Bayesian comparison methods to identify simultaneously the most likely spatial econometric model and spatial weight matrix explaining new business creation. The third paper compares the performance of continuous and discrete approaches to explain subjective well-being across space. The fourth paper applies a multiple imputation approach to determine regional purchasing power parities at the NUTS-3 level using data available at the NUTS-2 level. Finally, the last paper constructs a regional input–output table for Japan from its national counterpart using and comparing the performance of four non-survey techniques.     

Important Intermediate Transactions and Multi-sectoral Modelling

For the maintenance and development of a disaggregated econometric model, the present paper deals with some aspects related to the identification of important intermediate transactions. First, some methodological aspects related to earlier works are discussed. By comparing the properties of different selection methods based on the recent West German input–output table, the calculations confirm the common finding that the necessary level of endogenization can be bounded meaningfully by an a priori investiga tion of the intersectoral transactions. This is also valid if the selection method considers restrictions that deal with the consistence of input–output tables and if some broader error criteria are applied. The main result of the empirical applications seems to be that some attention should be paid to temporal changes of important coefficients.     

INCOME DISTRIBUTIONS IN INPUT-OUTPUT MODELS

The analysis of income distribution (ID) has traditionally been of prime importance for economists and policy-makers. However, the standard input–output (I–O) model is not particularly well equipped for studying current issues such as the consequences of decreasing access to primary inputs or the effects of specific redistributive policies. This paper addresses this gap in the existing literature. We propose that IDs can excellently be studied by restructuring the I–O relations. A new coefficients matrix is defined, the so-called augmented input coefficients matrix. This matrix is the sum of the intermediate input coefficients matrix and newly constructed matrices of sector-specific input coefficients that represent the existing distribution of income. We show that shifts in the distribution can be modelled by attributing weights to these matrices and vary these according to system-specific rules. Numerical illustrations based on the existing literature are given throughout the paper.     

Technical Change in the Private Consumption Converter

The analysis of technological change is centered on the study of the evolution of technical coefficients in the input–output table. Complementary to this analysis, the household consumption expenditure matrix, relating consumption by commodities to consumption by purpose or by function, also incorporates some other aspects of technological change. Thus, the evolution in time of the coefficients of this consumption expenditure matrix will portray technological processes, implying substitutions between commodities to satisfy the different functions The substitution between consumption expenditure by functions is also to be taken into consideration, because it can influence, together with technological change, the use of commodities in the final demand. For Switzerland, a 1980–89 time series of household consumption expenditure matrices with 37 commodities and 58 functional consumption categories has been estimated using data from consumer expenditure surveys. In this paper, instruments generally applied to the analysis of changes in input–output technical coefficients are extended to these matrices, including methods that deal with biproportional processes of substitution.     

Pitfalls in estimating equilibrium exchange rates for transition economies

The literature on equilibrium exchange rates for the central and eastern European countries has mushroomed in recent years. In this paper, we discuss the econometric pitfalls involved in such estimations and endow the reader with the methodological ingredients to avoid such biases. We review the commonly used approaches and identify problems related to the most straightforward econometric procedures as they often do not take the transition process properly into account. As an alternative, we propose a two-stage “out-of-sample” strategy that consists of estimating the relationship between the exchange rates and fundamentals and the extrapolation of these relationships to transition economies.     

Growth and convergence in a multi-country empirical stochastic Solow model

The paper considers international per capita output and its growth using a panel of data for 102 countries between 1960 and 1989. It sets out an explicitly stochastic Solow growth model and shows that this has quite different properties from the standard approach where the output equation is obtained by adding an error term to the linearized solution of a deterministic Solow model. It examines the econometric properties of estimates of beta convergence as traditionally defined in the literature and shows that all these estimates are subject to substantial biases. Our empirical estimates clearly reflect the nature and the magnitude of these biases as predicted by econometric theory. Steady state growth rates differ significantly across countries and once this heterogeneity is allowed for the estimates of beta are substantially higher than the consensus in the literature. But they are very imprecisely estimated and difficult to interpret. The paper also discusses the economic implications of these results for sigma convergence. © 1997 John Wiley & Sons, Ltd.     

Bayesian VARs: Specification Choices and Forecast Accuracy

In this paper we discuss how the point and density forecasting performance of Bayesian vector autoregressions (BVARs) is affected by a number of specification choices. We adopt as a benchmark a common specification in the literature, a BVAR with variables entering in levels and a prior modeled along the lines of Sims and Zha (International Economic Review 1998; 39 : 949–968). We then consider optimal choice of the tightness, of the lag length and of both; evaluate the relative merits of modeling in levels or growth rates; compare alternative approaches to h‐step‐ahead forecasting (direct, iterated and pseudo‐iterated); discuss the treatment of the error variance and of cross‐variable shrinkage; and assess rolling versus recursive estimation. Finally, we analyze the robustness of the results to the VAR size and composition (using also data for France, Canada and the UK, while the main analysis is for the USA). We obtain a large set of empirical results, but the overall message is that we find very small losses (and sometimes even gains) from the adoption of specification choices that make BVAR modeling quick and easy, in particular for point forecasting. This finding could therefore further enhance the diffusion of the BVAR as an econometric tool for a vast range of applications. Copyright © 2013 John Wiley & Sons, Ltd.     

Reframing fundraising research: The challenges and opportunities of interpretivist research practices and practitioner researchers in fundraising studies

This paper examines interpretivism as an approach for researching fundraising practice as context and practice specific. In doing so, it highlights the agency of fundraisers and extends critical analysis of fundraising practice and its broader implications in ways that the dominant positivistic, functionalist literature does not. Building on previous comparisons of positivist and interpretivist approaches, we consider two fundraising studies, and benefits and challenges of using an interpretivist approach. These observations highlight both the complexity and messiness of interpretivist studies, and of the fundraising process. The paper concludes by discussing how these challenges can be managed through analytical iteration, adjustment, and pragmatism throughout the research process; while advocating for including more critical and dialectic approaches to research fundraising and fundraisers' broader practice.