Structural Form Parameters Research Articles

힘의 흐름을 따르는 현수교의 초기 구조형태계획

하중에 민감한 케이블을 사용하는 현수교의 기하학적 형상은 하중을 저항할뿐만 아니라 시지각적 실루엣이 된다. 이 연구에서는 정력학적 도해법이 지니는 두 가지 가능성을 이용해서 힘의 흐름을 따르는 현수교의 초기 구조형태계획법을 제시한다. 첫째, 힘다각형을 이용해서 동일한 힘에 대해서 다양한 하중경로를 모색할 수 있다. 둘째, 구조형태와 힘다각형 사이에 존재하는 상반원리를 이용해서 새로 형성된 하중경로에 대응하는 구조형태를 생성할 수 있다. 먼저 현수교의 구조적 및 미학적 측면에 영향을 미치는 주요 구조형태변수를 선정한다. 이러한 변수에 대해서 구조형태와 힘다각형의 상호관계를 분석한다. 이를 토대로 현수교의 초기 구조형태계획에 대한 일련의 설계과정절차들을 개발한다. 이 연구에서 제시하는 구조형태계획법은 유사 형태저항 구조시스템의 설계대안을 생성하는데 수월하게 확장해서 사용할 수 있다. 또한 구조형태와 힘의 흐름과의 상호관계를 설명하는 교육용 도구로도 사용될 수 있을 것으로 기대한다. Geometric form of a suspension bridge that uses load-sensitive cables takes on not only resisting loads but also becoming a visually sensible shillouette. This study has proposed a preliminary structural form planning for a suspension bridge following force flow by adopting the two possibilities of the graphic statics. First, the force polygon allows alternative load paths for the same loading condition. Second, a new structural form for the newly developed load path can be constructed using the reciprocal principle that exits between a structure space and the corresponding force polygon. Major structural form parameters that affect both structural and aesthetic aspecs are first identified. The relationships between structural forms and the corresponding force polygons are then investigated for the identified parameters. Upon the investigation, a stepwise process is developed for a preliminary structural form planning for a suspension bridge. The proposed structural form planning method is general that can be easily expanded to generate design alternatives of similar form-active structural systems. It is also expected that this method will be used as an educational tool to explain the interrelationships between structural forms and their force flows.

MEASUREMENT ERRORS AND CENSORED STRUCTURAL LATENT VARIABLES MODELS

We consider censored structural latent variables models where some exogenous variables are subject to additive measurement errors. We demonstrate that overidentification conditions can be exploited to provide natural instruments for the variables measured with errors, and we propose a two-stage estimation procedure. The first stage involves substituting available instruments in lieu of the variables that are measured with errors and estimating the resulting reduced form parameters using consistent censored regression methods. The second stage obtains structural form parameters using the conventional linear simultaneous equations model estimators.

Method-of-moment view of linear simultaneous equation systems

In this paper, we review the modern method-of-moment-based approaches to identification and estimation of linear simultaneous equation systems. First, we present the rank condition for the structural form (SF) parameter identification. The rank condition comes naturally and is much easier to understand than that in the conventional reduced-form-based indirect approach. Then, we show how to estimate all SF parameters jointly (in a single step) with method-of-moment estimators. As it turns out, using only unconditional moments, but not any conditional moments, greatly simplifies the identification and estimation issues, and makes light work of conveying the essential ideas involved.

Simultaneous equations in ordered discrete responses with regressor‐dependent thresholds

Summary The parameters of ordered discrete response (ODR) models are identified only up to a positive scale. In this paper, we examine the identification issue for simultaneous equations with ODR, where the well-known identification problem in simultaneous equations of recovering structural-form parameters from reduced-form parameters is compounded with the ODR identification problem. We allow the thresholds in ODR to be regressor dependent as well as constant; the former is particularly challenging because threshold parameters get mixed with regression parameters, adding one more dimension to the identification problem. We also explore a cross-equation restriction on threshold differences, under which the structural form parameters are fully identified as if the dependent variables are continuously distributed. An empirical example with farm–household joint labour supply is provided to illustrate the identification issues, to show how our proposals work and to apply tests devised for the threshold constancy and cross-equation restrictions.

Modeling Nonlinear Autoregressive Distributed Lag Models: A New Approach

It is a common practice in econometrics that estimation is carried out in terms of the reduced form parameters and the structural form parameters are retrieved using the functional relationship between structural form parameters and the reduced form parameters. The reduced form of many useful economic models is a nonlinear distributed lag model (NLADL) with error structure which may have autocorrelation. In addition, the relationship between the reduced form and the structural parameters is often nonlinear and in a ratio form. In such situations existing sampling theory estimation procedures result in estimators for the structural parameters which do not have finite moments and do not possess optimal sampling properties. As an alternative, we propose a two step Bayesian estimation method. The Bayesian method has great potential and allows us to obtain the posterior probability density functions of all parameters of interest. In particular, its application for the analysis of adaptive expectation partial adjustment models for which the reduced form is a NLADL model, has been found extremely useful. An application to Nerlove’s supply response function supports the proposed methodology.

The hydrology of Vertosols used for cotton production: I. Hydraulic, structural and fundamental soil properties

This paper describes the hydraulic, structural and fundamental soil properties for 23 Vertosol horizons from 18 sampling sites in New South Wales and southern Queensland. At each site a combination of infiltration measurements and soil sampling was conducted. Samples were collected for determination of the soil water characteristic, shrink–swell relationships, and fundamental soil properties such as particle size distributions, pH, electrical conductivity (EC), exchangeable cations (Ca2+, Mg2+, K+, Na+), extractable P contents, extractable sulfate and Fe contents, and CaCO3 and total C contents. Large cores were sampled, impregnated with resin, and sectioned for image analysis. The program SOLICON v2.1 was used to calculate structural form parameters from the images. Measured hydraulic conductivities of the surface soils were large compared with earlier reported research for Vertosols. However, a sharp decrease in hydraulic conductivity occurred with depth in the profiles, which is assumed to be due to increased bulk densities and exchangeable sodium percentages (ESP). The data also indicated a general north–south trend in the structural development of these Vertosols. Surface soils from the northern areas, such as the Gwydir and Namoi valleys, exhibited more porous structural forms, and as a result, greater average hydraulic conductivities. This appears to be due to differences in ESP, clay content and the mineralogical suite of the clay; surface samples with smaller ESPs and larger proportions of smectitic clay tended to have the greatest values of hydraulic conductivity. Other fundamental soil properties such as extractable Fe and P contents, and CaCO3 content, were found to have little or no correlation to the hydraulic or structural properties of these Vertosols, while differences in measured shrink-swell and water retention properties were largely a function of soil depth. The database developed has given an overview of the hydraulic properties of Vertosols used for cotton production in south-eastern Australia.

Linking hydraulic conductivity and tortuosity parameters to pore space geometry and pore-size distribution

To enable a link between the pore size distribution of the soil measured in two dimensions and the hydraulic conductivity, a factor, which includes the connectivity and tortuosity of the pore network in three dimensions, is needed. In order to increase confidence in the models which predict hydraulic conductivity, this paper aims to gain insight into relationship between tortuosity and connectivity parameters used in statistical models of hydraulic conductivity and soil structural form measurements derived with image analysis. The analysis was based on a dataset of the hydraulic and soil structural properties of 19 Vertisol samples from Eastern Australia. The soil structural data were measured on large (200 mm height and 150 mm diameter) cores at 5–7 depth slices. Several soil structural form parameters, including a pore size distribution, were calculated using an image analysis program ( Solicon v2.1). The hydraulic conductivity model developed by Kosugi [Soil Sci. Soc. Am. J. 63 (1999) 270] based on the lognormal pore size distribution was fitted to measured hydraulic conductivities. Hydraulic conductivity was strongly related to porosity and a measure of connectivity in the horizontal direction (pore genus). The tortuosity parameters α and β from the Kosugi [Soil Sci. Soc. Am. J. 63 (1999) 270] model were related to the mean pore size, with increasing mean pore size indicating decreasing tortuosity of the sample.

Cotton root growth in a compacted Vertisol (Grey Vertosol). II. Correlation with image analysis parameters

A differential staining procedure was developed to study the degree of association between soil structural form parameters, derived using the SOLICON image analysis system, and the root growth of cotton plants. Under the climatic conditions that prevailed during the experimental period, severe impedance of taproots was associated with a clod width in the range 28 mm to ≥30 mm and a macroporosity value in the range 0.00–0.04 m3/m3. The new root assessment procedure detected soil structural features, for example, well-aerated zones adjacent to near-surface roots in degraded soil not shown by other methods and allowed direct measurement of the proportion of a root’s surface in contact with the soil atmosphere. However, the assessment method should be complemented by direct measurement of the morphology of nearby cotton taproots that have been pulled from the soil. Features that can be assessed include root flatness, the number of lateral roots, root obliquity, and the degree of tapering. In this experiment the lack of flattening in roots pulled from the compacted soil suggested that poor aeration was a bigger problem for the cotton plants than mechanical impedance. Root deformation was not associated with a large decline in lint yield at this site because the crop was irrigated frequently and did not suffer any nutritional stress, and the relatively steep field slope permitted rapid surface drainage.

Corrigendum to: Cotton root growth in compacted Vertisol (Grey Vertosol). II. Correlation with image analysis parameters

A differential staining procedure was developed to study the degree of association between soil structural form parameters, derived using the SOLICON image analysis system, and the root growth of cotton plants. Under the climatic conditions that prevailed during the experimental period, severe impedance of taproots was associated with a clod width in the range 28 mm to ≥30 mm and a macroporosity value in the range 0.00–0.04 m3/m3. The new root assessment procedure detected soil structural features, for example, well-aerated zones adjacent to near-surface roots in degraded soil not shown by other methods and allowed direct measurement of the proportion of a root’s surface in contact with the soil atmosphere. However, the assessment method should be complemented by direct measurement of the morphology of nearby cotton taproots that have been pulled from the soil. Features that can be assessed include root flatness, the number of lateral roots, root obliquity, and the degree of tapering. In this experiment the lack of flattening in roots pulled from the compacted soil suggested that poor aeration was a bigger problem for the cotton plants than mechanical impedance. Root deformation was not associated with a large decline in lint yield at this site because the crop was irrigated frequently and did not suffer any nutritional stress, and the relatively steep field slope permitted rapid surface drainage.

A double-hurdle rational addiction model with heterogeneity: Estimating the demand for tobacco

In this paper, we estimate a tobacco consumption rational addiction model with panel data. We apply Becker and Murphy's (1988, Journal of Political Economy 96, 675–700) proposal to individual rather than aggregate data. Given the censoring nature of the dependent variable, we use a double-hurdle specification after testing that the factors governing the consumption equation are not the same as those that govern the participation equation. We use non-linear panel data methods to consistently retrieve the structural form parameters, as usual linear panel data methods applied to the consumption equation conditional on participation do not provide consistent estimates. The empirical results reject the myopic model and give support to the rational addiction one. Finally, although long-run elasticities are bigger than short-run elasticities, the individual's response to prices is very small.

Semi‐parametric estimation of simultaneous equations with limited dependent variables: A case study of female labour supply

AbstractWe propose a general strategy to estimate semi‐parametrically simultaneous equations with limited dependent variables. First, each reduced form (RF) is estimated with various semi‐parametric methods. Second, the specification of each RF is tested to select an appropriate method. Third, the structural form (SF) equations are estimated using minimum distance methods and the restrictions among the SF and RF parameters. A case study of female labour supply is presented.

Alternative specifications of the error process in the stochastic simulation of econometric models

SUMMARY This paper analyses the stochastic simulation of econometric models using three different methods for specifying the probability distribution of the structural error terms. The impact of these different assumptions on the simulation bias and model variance is explored empirically. Monte Carlo variance reduction techniques are used to distinguish the effects of the different specifications. A macroeconometric model is a set of behavioural equations which represent endogenous variables as a function of predetermined variables and error terms. The model may be written in the form f(yt, xt) = ut, where yt is a vector of endogenous variables, xt is a vector of predetermined variables, and ut is a vector of stochastic error terms. The parameters of the structural functions f are estimated using econometric methods. When econometric models are used to predict the future, a point prediction is usually obtained with deterministic solution. The deterministic solution is calculated by solving f(yt, xt) = 0 for yt. This is equivalent to assuming that the stochastic terms ut are equal to zero in the future period. It is well known that, if the model is nonlinear, then E(yt I xt) is not equal to the deterministic solution. For example, see, Fisher and Salmon (1986), where large discrepancies between E(yt I xt) arid the deterministic solution are shown in some cases. Alternatively, predictions may be made using stochastic simulation. In stochastic simulation a distribution is assumed for the error vector ut. Then a pseudo-random vector st is drawn from the specified distribution. The model is then solved; the value of Yt which solves f(yt, xt) = st is found. This process is repeated n times and the resulting vectors are averaged. Since this is a Monte Carlo technique, the economist can increase accuracy by performing more replications (increasing n). The results will depend upon the distribution assumed for the error terms ut, and adopted for generating the pseudo-random error terms St. 1 Estimation errors of the structural form parameters could also be considered in simulation studies. However, it was shown in Bianchi and Calzolari (1980) that the impact of errors in estimated coefficients can be treated with analytical or analytical-numerical methods even for nonlinear models, without need of stochastic simulation. Therefore, in this study we shall not deal with errors in coefficients; coefficients will be treated as given.

The partial least squares-fix point method of estimating interdependent systems with latent variables

This paper describes a method for estimating the unknown parameters of an interdependent simultaneous equations model with latent variables. For each latent variable there may be single or multiple indicators. Estimation proceeds in three stages: first, estimates of the latent variables are constructed from the associated manifest indicators; second, treating the estimates as directly observed, fix-point estimates of the structural form parameters are obtained; third, the location parameters are estimated. The method involves only repeated application of ordinary least squares and no distributional assumptions are needed. The paper concludes with an empirical application of the method.