A NOTE ON ADDED INFORMATION IN THE RAS PROCEDURE: REEXAMINATION OF SOME EVIDENCE

ABSTRACT.  An example in Miernyk (1977) presented a rather counterintuitive result, namely, that introducing accurate exogenous information into an RAS matrix estimating procedure could lead to an estimate that was worse than one generated by RAS using no exogenous information at all. This became an oft-cited black mark against RAS. Miller and Blair (1985) included a different (and small) illustration of the same possibility. It was recently pointed out by one of us that the Miller–Blair numerical results are wrong. For that reason, we decided to reexamine all the empirical evidence we could find on the subject. While figures in both Miernyk and Miller–Blair appear to be wrong, more recent published examples seem to have it right. In short, it is possible to identify examples in which additional (correct) information leads to poorer RAS estimates, at least under several fairly common metrics for comparing "closeness" of matrices. However, the overwhelming majority of the evidence is to the contrary. As a general rule, introduction of accurate exogenous information into RAS improves the resulting estimates, and counterexamples should probably not be taken too seriously.     

A LINEAR PROGRAMMING APPROACH TO SOLVING INFEASIBLE RAS PROBLEMS

ABSTRACT The RAS procedure is widely used to update national and regional input-output tables and international trade tables and to construct regional tables from national ones. Special problems, however, have been encountered when the procedure is used to adjust interregional trade tables. In this paper, the special properties of interregional trade tables that increase the likelihood of nonconvergence of the RAS procedure are discussed, and two linear programming methods of solving infeasible RAS problems are provided. First, a closed linear programming approach, which enables exogenous information to override the purely mechanical solution of infeasible RAS problems, is presented. Finally, the open linear programming approach is applied successfully to adjust U.S. interregional trade data that had previously failed to converge using the RAS procedure.     

Establishing Stage‐Discharge Relationships in Multiple‐Channelled,Ephemeral Rivers: a Case Study of the Diamantina River,Australia

The method for deriving a stage‐discharge relationship has a significant impact on the shape of the river's rating curve. We compare rating curves for a single gauging station on a mutiple‐channelled river in Australia compiled using three different methods – the Urban Runoff and Basin Systems (URBS) rainfall‐runoff model, an empirically‐based velocity‐area method, and the predictive Hydrologic Engineering Centre‐River Analysis System (HEC‐RAS) computer model. The rainfall‐runoff model was found to predict lower discharges for stage heights over 3.5 m than both the empirically‐based velocity‐area method and the HEC‐RAS model. The empirically‐based velocity‐area model predicts similar discharges to the rainfall‐runoff model for stage heights less than 3 m but much higher discharges for larger flood events. The HEC‐RAS model predicts higher discharges than both other rating curves at all stage heights probably due to under‐estimation of the impact of surface roughness on flow velocity. The three models are discussed with particular reference to their use on multiple‐channelled rivers.     

PRODUCT-MIX AND TECHNOLOGICAL CHANGE WITHIN THE LEONTIEF INVERSE

ABSTRACT. Intertemporal differences in input-output coefficients can be attributed to technological change and to changes in the mix of products composing the aggregate sectors of input-output models. In this work, we develop the theoretical foundation necessary to separate these changes for both the structural and Leontief inverse matrices. Using this foundation, we examine the relative empirical importance of technological and product-mix change. The product-mix effect is then combined with RAS estimates of the technological effect to form updated estimates of the inverse. Results show that the accuracy of updated input-output coefficients can be improved in this manner.     

Properties of Tests for Spatial Dependence in Linear Regression Models

Based on a large number of Monte Carlo simulation experiments on a regular lattice, we compare the properties of Moran's I and Lagrange multiplier tests for spatial dependence, that is, for both spatial error autocorrelation and for a spatially lagged dependent variable. We consider both bias and power of the tests for six sample sizes, ranging from twenty-five to 225 observations, for different structures of the spatial weights matrix, for several underlying error distributions, for misspecified weights matrices, and for the situation where boundary effects are present. The results provide an indication of the sample sizes for which the asymptotic properties of the tests can be considered to hold. They also illustrate the power of the Lagrange multiplier tests to distinguish between substantive spatial dependence (spatial lag) and spatial dependence as a nuisance (error autocorrelation).     

Radio wave propagation from antennae at satellite altitudes into the Earth-ionosphere waveguide

The problem of the excitation of the earth-ionosphere waveguide by a short linear antenna or by a small circular one at satellite altitudes is considered. The formulation allows for a spherical regular wave guide as well as for a radially inhomogeneous anisotropic ionosphere. A method for the solution is based on the use of the reciprocity theorems for anisotropic media. Numerical techniques have been developed. Some results for VLF are given. To gain some physical interpretations, the fields of sources at low ionospheric heights were investigated.     

RAS‐ING THE TRANSACTIONS OR THE COEFFICIENTS: IT MAKES NO DIFFERENCE*

ABSTRACT The biproportional RAS technique has become one of the most important tools to update, regionalize, or balance input–output tables. In this note, we rigorously prove that the estimation of the intermediate transactions matrix yields the same results as the estimation of the input coefficients matrix or the output coefficients matrix. We also show that this does not hold for any of the other updating procedures that have been commonly proposed as an alternative to RAS.     

Adaptive separation of regular and irregular magnetic activity for K indices

A numerical data adaptive separation method is developed for the discrimination of quasi-regular magnetic variations from the irregular variations for the determination of the K indices. The method is based on a pattern comparison and discrimination technique using harmonic analyses and is more objective than the hand-scaling method. The wave characteristics of a quiet regular or reference day are compared with those of the disturbed day being examined. The harmonic components that are consistent with those of the reference day are determined by a cosine weighting function. The Fourier coefficients are calculated from these modified harmonics and are then transformed back to the time domain. This ‘regular variation’ is subtracted from the data before the ranges are determined for the semi-logarithmic K scale. The method is tested on digital data from the Canadian magnetic observatories Victoria, Meanook and Ottawa over a 4 month period. The data are at a 10 s sampling interval and encompass the full range of K values (0–9). These K values are compared and checked with hand-scaled values, which were carefully and independently determined from reconstructed magnetograms from the same data. The two methods were found to agree ∼ 97% of the time, with most errors occurring during very irregular periods. This is comparable with values carefully determined by highly skilled observers. It is proposed that the method is suitable for use on a regular basis.     

Semiparametric Maximum Likelihood Estimates of Spatial Dependence

We semiparametrically model spatial dependence via a combination of simpler weight matrices (termed spatial basis matrices) and fit this model via maximum likelihood. Estimation of the model relies on the intuition that bounds to the log‐determinant term in the log‐likelihood can provide penalties to overfitting both the level and pattern of spatial dependence. By relying on symmetric and doubly stochastic spatial basis matrices that reflect different weight specifications assigned to neighboring observations, we are able to derive a mathematical expression for bounds on the log‐determinant term that appears in the likelihood function. These bounds can be conveniently calculated allowing us to solve for maximum likelihood estimates at the bounds using a simple optimization over two quadratic forms that involve small matrices. An intuitively pleasing aspect of our approach is that the objective function for the bounded log‐likelihoods contains one quadratic form equal to the sum‐of‐squared errors measuring the quality of fit, and another quadratic form reflecting a penalty to overfitting spatial dependence. We apply our semiparametric estimation method to a housing model using 57,647 U.S. census tracts.     

Between‐group Differences in the Patterning of Musculo‐skeletal Stress Markers: Avoiding Confounding Factors by Focusing on Qualitative Aspects of Physical Activity

This paper presents a method for studying between‐group differences in physical activity patterns through the analysis of musculo‐skeletal stress markers (MSM). The specific aim was to develop a method that could overcome the problems related to confounding variables such as body size by shifting the analytical focus from the comparison of differences in intensity to the comparison of differences in kinds of activity. Instead of testing whether there are differences in the measures of central tendency of MSM scores between two groups, we proposed looking for differences in MSM covariation patterns. Formally, this is achieved through the statistical comparison of group‐specific MSM intercorrelation matrices. The null hypothesis is that the matrices are equal, and the statistical significance of the test statistic is obtained with a permutation test. In this way, the problem of confounding variables such as body size is mostly avoided because the procedure is based on the comparison of group‐specific sets of correlation coefficients which are scale‐free. The method was employed in a case study to investigate the differences in activity patterns between men and women from the Early Bronze Age population buried at the necropolis in Mokrin, Serbia. The null hypothesis of no difference between the male and female MSM correlation matrices was rejected (p = 0.0135). After the statistical significance of the difference was established, further investigation of male and female activity patterns was undertaken by means of principal component analysis (PCA) with varimax rotation. PCA results suggest that covariation between MSMs is stronger in the male sample. Success in demonstrating differences in activity patterns between sexes implies that the proposed method can be used to test for differences in physical activity between groups of individuals defined by criteria other than sex. Copyright © 2011 John Wiley & Sons, Ltd.     

The Use of Menthol as Temporary Consolidant in the Excavation of Qin Shihuang's Terracotta Army

Temporary consolidation is widely used to protect delicate artefacts or other fragile relics in art conservation. Although cyclododecane is extensively accepted, the safety‐related issues have become an increasing concern and its short working time is always annoying. Inspired by its low melting point, polar structure, well‐established safety profile, easy local availability and low cost, we propose menthol as a new temporary consolidant on the new excavation site of Qin Shihuang's Terracotta Army. In this paper, we offer a preliminarily exploration of the kinetics of menthol sublimation on two different matrices, its residue after volatilization, its penetrability and distribution in simulated terracotta samples, as well as other important properties in the laboratory. The results obtained from these tests reveal that the sublimation of menthol can be a zero‐ or a first‐order process, depending on the porosity of the matrices, and its best operational temperature resides in the range of 60–80°C. Finally, two field cases at the archaeological site of Qin Shihuang's Terracotta Army are presented to show that menthol is a very effective temporary consolidant.     

Early fetal maturity assessed from patterns of ossification in the hand and foot

The assessment of fetal age at death is fraught with many complications and often the determination of the maturity of the fetus is a more realistic solution to the question of fetal viability. This study examines the pattern of appearance of primary centres of ossification in the fetal hand and foot, in an attempt to construct a maturity continuum. The results show that completion of ossification in the hand precedes that in the foot and generally occurs in a more regular pattern. The method proves useful at assessing fetal maturity between the third and tenth months of intra-uterine life. In addition, the relationship to other major centres of ossification is considered.     

Representing Structural Change in U.S. Migration Patterns

This paper focuses on the identification of three sets of relationships exhibited by a time series of age-specific national migration rates and multiregional transition probability matrices: the relationship across time for the same age group, as defined by period (temporal) transformation coefficients or matrices; the relationships across age at a particular moment in time, as defined by age transformation coefficients or matrices; and the relationships across time and age, as defined by cohort transformation coefficients or matrices. Given any two of these relationships one can solve for the third. This feature of age-period-cohort relationships has a practical application in the development of improved methods for representing structural change in migration patterns over time and for indirectly estimating migration patterns using inadequate data.     

THE MULTIPLE SEALING SYSTEM of MINOAN CRETE and ITS POSSIBLE ANTECEDENTS IN ANATOLIA

Summary: The Multiple Sealing System ( MSS ) is defined as the habitual stamping of regular combinations of two or three different seal impressions on clay nodules ( bullae ). This system was thought to be peculiar to LM IB Zakro, where it is indeed most fully developed, but a Minoan MSS can now be traced back - via MM IIIB Knossos - to the earliest administrative use of sealings on Crete, at MM IIB Phaistos. This early MSS at Phaistos has close links with a similar administrative use of seals in regular combinations at Karahöyük Level I. We suggest that the MSS is a new and objective factor to be added to the known, if often disputed, glyptic relations between MBA Anatolia and Minoan Crete.     

Model Uncertainty in Matrix Exponential Spatial Growth Regression Models

This article considers the most important aspects of model uncertainty for spatial regression models, namely, the appropriate spatial weight matrix to be employed and the appropriate explanatory variables. We focus on the spatial Durbin model (SDM) specification in this study that nests most models used in the regional growth literature, and develop a simple Bayesian model‐averaging approach that provides a unified and formal treatment of these aspects of model uncertainty for SDM growth models. The approach expands on previous work by reducing the computational costs through the use of Bayesian information criterion model weights and a matrix exponential specification of the SDM model. The spatial Durbin matrix exponential model has theoretical and computational advantages over the spatial autoregressive specification due to the ease of inversion, differentiation, and integration of the matrix exponential. In particular, the matrix exponential has a simple matrix determinant that vanishes for the case of a spatial weight matrix with a trace of zero. This allows for a larger domain of spatial growth regression models to be analyzed with this approach, including models based on different classes of spatial weight matrices. The working of the approach is illustrated for the case of 32 potential determinants and three classes of spatial weight matrices (contiguity‐based, k‐nearest neighbor, and distance‐based spatial weight matrices), using a data set of income per capita growth for 273 European regions.     

The Effectiveness of Jobs Reservation: Caste,Religion and Economic Status in India

This article investigates the effect of jobs reservation on improving the economic opportunities of persons belonging to India's Scheduled Castes (SC) and Scheduled Tribes (ST). Using employment data from the 55^th NSS round, the authors estimate the probabilities of different social groups in India being in one of three categories of economic status: own account workers; regular salaried or wage workers; casual wage labourers. These probabilities are then used to decompose the difference between a group X and forward caste Hindus in the proportions of their members in regular salaried or wage employment. This decomposition allows us to distinguish between two forms of difference between group X and forward caste Hindus: ‘attribute’ differences and ‘coefficient’ differences. The authors measure the effects of positive discrimination in raising the proportions of ST/SC persons in regular salaried employment, and the discriminatory bias against Muslims who do not benefit from such policies. They conclude that the boost provided by jobs reservation policies was around 5 percentage points. They also conclude that an alternative and more effective way of raising the proportion of men from the SC/ST groups in regular salaried or wage employment would be to improve their employment‐related attributes.     

Bayesian Model Averaging for Spatial Econometric Models

We extend the literature on Bayesian model comparison for ordinary least-squares regression models to include spatial autoregressive and spatial error models. Our focus is on comparing models that consist of different matrices of explanatory variables. A Markov Chain Monte Carlo model composition methodology labeled MC ³ by Madigan and York is developed for two types of spatial econometric models that are frequently used in the literature. The methodology deals with cases where the number of possible models based on different combinations of candidate explanatory variables is large enough such that calculation of posterior probabilities for all models is difficult or infeasible. Estimates and inferences are produced by averaging over models using the posterior model probabilities as weights, a procedure known as Bayesian model averaging. We illustrate the methods using a spatial econometric model of origin–destination population migration flows between the 48 U.S. states and the District of Columbia during the 1990–2000 period.     

Medieval village planning in northern England: some evidence from Yorkshire

A village plan comprising regular toft rows facing a street or green is common in lowland Yorkshire north of the river Aire and west of the river Hull, and many such plans are believed to have been established in the late eleventh and early twelfth centuries. The obvious occasion for a settlement reorganisation involving the creation of regular plans was the aftermath of a phase of devastation between 1066 and 1070. Domesday Book data are used to identify the local circumstances that favoured regular plan creation. A two-stage recolonisation is hypothesised: first, local survivors were grouped into “manorial” type communities where pre-Conquest village layouts were usually revived; second, free colonists were attracted from other districts and settled in villages of regular plan. Subsequent population growth was in some cases associated with the addition of regular toft rows to existing settlements, thereby giving rise to the more widely distributed partly-regular plans.     

Constructing the Spatial Weights Matrix Using a Local Statistic

Spatial weights matrices are necessary elements in most regression models where a representation of spatial structure is needed. We construct a spatial weights matrix, W , based on the principle that spatial structure should be considered in a two‐part framework, those units that evoke a distance effect, and those that do not. Our two‐variable local statistics model (LSM) is based on the G_i* local statistic. The local statistic concept depends on the designation of a critical distance, d_c, defined as the distance beyond which no discernible increase in clustering of high or low values exists. In a series of simulation experiments LSM is compared to well‐known spatial weights matrix specifications—two different contiguity configurations, three different inverse distance formulations, and three semi‐variance models. The simulation experiments are carried out on a random spatial pattern and two types of spatial clustering patterns. The LSM performed best according to the Akaike Information Criterion, a spatial autoregressive coefficient evaluation, and Moran's I tests on residuals. The flexibility inherent in the LSM allows for its favorable performance when compared to the rigidity of the global models.     

Analysis of a Distribution of Point Events Using the Network‐Based Quadrat Method

This study proposes a new quadrat method that can be applied to the study of point distributions in a network space. While the conventional planar quadrat method remains one of the most fundamental spatial analytical methods on a two‐dimensional plane, its quadrats are usually identified by regular, square grids. However, assuming that they are observed along a network, points in a single quadrat are not necessarily close to each other in terms of their network distance. Using planar quadrats in such cases may distort the representation of the distribution pattern of points on a network. The network‐based units used in this article, on the other hand, consist of subsets of the actual network, providing more accurate aggregation of the data points along the network. The performance of the network‐based quadrat method is compared with that of the conventional quadrat method through a case study on a point distribution on a network. The χ² statistic and Moran's I statistic of the two quadrat types indicate that (1) the conventional planar quadrat method tends to overestimate the overall degree of dispersion and (2) the network‐based quadrat method derives a more accurate estimate on the local similarity. The article also performs sensitivity analysis on network and planar quadrats across different scales and with different spatial arrangements, in which the abovementioned statistical tendencies are also confirmed.