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1
Chipman, John S. "HAAVELMO’S CONTRIBUTIONS TO SIMULTANEOUS-EQUATIONS ESTIMATION." Econometric Theory 31, no. 2 (July 31, 2014): 233–48. http://dx.doi.org/10.1017/s0266466614000280.
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This paper surveys Trygve Haavelmo’s contributions to econometrics. A brief summary of his 1944 monograph is followed by an analysis of the six important papers he contributed during 1943–47. Four of them were devoted to macroeconomic models including estimation of the Keynesian marginal propensity to consume; the first two introduced the methodology of a system of structural equations; the third marked a milestone in econometric method by deriving the reduced form of such a system; and the fourth analyzed the contrast between time-series and cross-section analysis. The fifth (joint with M.A. Girshick) on the demand for food provided a definitive treatment of estimation of demand and supply functions; it carried out the execution of a five-equation structural model of the U.S. economy. The sixth was an interesting policy model of the interrelationship between the agricultural and the rural sector of the economy, which was fitted to U.S. data and addressed to questions of policy.
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Lo, Chi Ho, Wing Kam Fung, and Zhong Yi Zhu. "Structural Parameter Estimation Using Generalized Estimating Equations for Regression Credibility Models." ASTIN Bulletin 37, no. 02 (November 2007): 323–43. http://dx.doi.org/10.2143/ast.37.2.2024070.
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A generalized estimating equations (GEE) approach is developed to estimate structural parameters of a regression credibility model with independent or moving average errors. A comprehensive account is given to illustrate how GEE estimators are worked out within an extended Hachemeister (1975) framework. Evidenced by results of simulation studies, the proposed GEE estimators appear to outperform those given by Hachemeister, and have led to a remarkable improvement in accuracy of the credibility estimators so constructed.
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Lo, Chi Ho, Wing Kam Fung, and Zhong Yi Zhu. "Structural Parameter Estimation Using Generalized Estimating Equations for Regression Credibility Models." ASTIN Bulletin 37, no. 2 (November 2007): 323–43. http://dx.doi.org/10.1017/s0515036100014896.
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A generalized estimating equations (GEE) approach is developed to estimate structural parameters of a regression credibility model with independent or moving average errors. A comprehensive account is given to illustrate how GEE estimators are worked out within an extended Hachemeister (1975) framework. Evidenced by results of simulation studies, the proposed GEE estimators appear to outperform those given by Hachemeister, and have led to a remarkable improvement in accuracy of the credibility estimators so constructed.
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Bernardini Papalia, Rosa, and Enrico Ciavolino. "GME Estimation of Spatial Structural Equations Models." Journal of Classification 28, no. 1 (January 21, 2011): 126–41. http://dx.doi.org/10.1007/s00357-011-9073-0.
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Shina, Arya Fendha Ibnu. "ESTIMASI PARAMETER PADA SISTEM MODEL PERSAMAAN SIMULTAN DATA PANEL DINAMIS DENGAN METODE 2 SLS GMM-AB." MEDIA STATISTIKA 11, no. 2 (December 30, 2018): 79–91. http://dx.doi.org/10.14710/medstat.11.2.79-91.
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Single equation models ignore interdependencies or two-way relationships between response variables. The simultaneous equation model accommodates this two-way relationship form. Two Stage Least Square Generalized Methods of Moment Arellano and Bond (2 SLS GMM-AB) is used to estimate the parameters in the simultaneous system model of dynamic panel data if each structural equation is exactly identified or over identified. In the simultaneous equation system model with dynamic panel data, each structural equation and reduced form is a dynamic panel data regression equation. Estimation of structural equations and reduced form using Ordinary Least Square (OLS) resulted biased and inconsistent estimators. Arellano and Bond GMM method (GMM AB) estimator produces unbiased, consistent, and efficient estimators.The purpose of this paper is to explain the steps of 2 SLS GMM-AB method to estimate parameter in simultaneous equation model with dynamic panel data. Keywords:2 SLS GMM-AB, Arellano and Bond estimator, Dynamic Panel Data, Simultaneous Equations
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Chen, Songnian, Cheng Hsiao, and Liqun Wang. "MEASUREMENT ERRORS AND CENSORED STRUCTURAL LATENT VARIABLES MODELS." Econometric Theory 28, no. 3 (November 25, 2011): 696–703. http://dx.doi.org/10.1017/s0266466611000715.
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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.
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Suzuki, Hironori, Takashi Nakatsuji, Yordphol Tanaboriboon, and Kiyoshi Takahashi. "Dynamic Estimation of Origin-Destination Travel Time and Flow on a Long Freeway Corridor: Neural Kalman Filter." Transportation Research Record: Journal of the Transportation Research Board 1739, no. 1 (January 2000): 67–75. http://dx.doi.org/10.3141/1739-09.
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A model was formulated for estimating dynamic origin-destination (O-D) travel time and flow on a long freeway with a neural Kalman filter originally developed by the authors. The model predicts O-D travel times and flows simultaneously by using traffic detector data such as link traffic volumes, spot speeds, and off-ramp volumes. The model is based on a Kalman filter that consists of two equations: state and measurement. First, the state and measurement equations of the Kalman filter were modified to consider the influence of traffic states for some previous time steps. Then artificial neural network models were integrated with the Kalman filter to enable nonlinear formulations of the state and measurement equations. Finally, a macroscopic traffic flow simulation model was introduced to simulate traffic states on a freeway in advance and predict traffic variables such as O-D travel times, link traffic volumes, spot speeds, and off-ramp volumes. The new model was compared with a regression Kalman filter in which the state and measurement equations are defined by regression models. The numerical analysis indicated that the new model was capable of estimating nonlinearity of dynamic O-D travel time and flow and helped to improve their estimation precision under free-flow traffic states as well as congested flow states.
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Skeels, Christopher L. "Instrumental Variables Estimation in Misspecified Single Equations." Econometric Theory 11, no. 3 (June 1995): 498–529. http://dx.doi.org/10.1017/s0266466600009385.
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This paper examines the exact sampling behavior of a family of instrumental variables estimators of the coefficients in a single structural equation when the model has been misspecified by the incorrect inclusion or exclusion of variables. It is found that such specification errors can have implications for the structure of the exact results obtained. A brief numerical examination of the analytical results is also provided.
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Hamerle, Alfred, Willi Nagl, and Hermann Singer. "Problems with the estimation of stochastic differential equations using structural equations models." Journal of Mathematical Sociology 16, no. 3 (November 1991): 201–20. http://dx.doi.org/10.1080/0022250x.1991.9990088.
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Hsiao, Cheng, and Qiankun Zhou. "JIVE FOR PANEL DYNAMIC SIMULTANEOUS EQUATIONS MODELS." Econometric Theory 34, no. 6 (November 2, 2017): 1325–69. http://dx.doi.org/10.1017/s0266466617000421.
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We consider the method of moments estimation of a structural equation in a panel dynamic simultaneous equations model under different sample size combinations of cross-sectional dimension, N, and time series dimension, T. Two types of linear transformation to remove the individual-specific effects from the model, first difference and forward orthogonal demeaning, are considered. We show that the Alvarez and Arellano (2003) type GMM estimator under both transformations is consistent only if ${T \over N} \to 0$ as $\left( {N,T} \right) \to \infty $. However, it is asymptotically biased if ${{{T^3}} \over N} \to \kappa \ne 0 < \infty$ as $\left( {N,T} \right) \to \infty $. Since the validity of statistical inference depends critically on whether an estimator is asymptotically unbiased, we suggest a jackknife bias reduction method and derive its limiting distribution. Monte Carlo studies are conducted to demonstrate the importance of using an asymptotically unbiased estimator to obtain valid statistical inference.
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Xie, Junyao, and Stevan Dubljevic. "Discrete-Time Kalman Filter Design for Linear Infinite-Dimensional Systems." Processes 7, no. 7 (July 15, 2019): 451. http://dx.doi.org/10.3390/pr7070451.
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As the optimal linear filter and estimator, the Kalman filter has been extensively utilized for state estimation and prediction in the realm of lumped parameter systems. However, the dynamics of complex industrial systems often vary in both spatial and temporal domains, which take the forms of partial differential equations (PDEs) and/or delay equations. State estimation for these systems is quite challenging due to the mathematical complexity. This work addresses discrete-time Kalman filter design and realization for linear distributed parameter systems. In particular, the structural- and energy-preserving Crank–Nicolson framework is applied for model time discretization without spatial approximation or model order reduction. In order to ensure the time instance consistency in Kalman filter design, a new discrete model configuration is derived. To verify the feasibility of the proposed design, two widely-used PDEs models are considered, i.e., a pipeline hydraulic model and a 1D boundary damped wave equation.
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Yuan, Ke-Hai, and Wai Chan. "Fitting structural equation models using estimating equations: A model segregation approach." British Journal of Mathematical and Statistical Psychology 55, no. 1 (May 2002): 41–62. http://dx.doi.org/10.1348/000711002159699.
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Costa, Ana Catarina, Haitong Xu, and Carlos Guedes Soares. "Robust Parameter Estimation of an Empirical Manoeuvring Model Using Free-Running Model Tests." Journal of Marine Science and Engineering 9, no. 11 (November 20, 2021): 1302. http://dx.doi.org/10.3390/jmse9111302.
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The work presents the identification and validation of the hydrodynamic coefficients for the surge, sway, and yaw motion. This is performed in two ways: using simulated data and free-running test data. The identification and validation with the simulation data are carried out using a 25° turning test and a 20°−20° zigzag manoeuvring test. For the free-running test data, two zigzag manoeuvres are used: 30°−30° zigzag for identification and 20°−20° zigzag for validation. A nonlinear manoeuvring model is proposed based on the standard Euler equations, and the hydrodynamic coefficients are computed using empirical equations. To obtain robust results, the truncated singular value decomposition is employed to diminish the multicollinearity and the parameter uncertainties due to noise. The validation is carried out by comparing the result of the measured values with the predictions obtained using the manoeuvring models. Finally, a sensitivity analysis for the simulation data is performed to understand the influence of the parameters in the manoeuvres.
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Kosmatopoulos, E. B., A. W. Smyth, S. F. Masri, and A. G. Chassiakos. "Robust Adaptive Neural Estimation of Restoring Forces in Nonlinear Structures." Journal of Applied Mechanics 68, no. 6 (June 8, 2001): 880–93. http://dx.doi.org/10.1115/1.1408614.
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The availability of methods for on-line estimation and identification of structures is crucial for the monitoring and active control of time-varying nonlinear structural systems. Adaptive estimation approaches that have recently appeared in the literature for on-line estimation and identification of hysteretic systems under arbitrary dynamic environments are in general model based. In these approaches, it is assumed that the unknown restoring forces are modeled by nonlinear differential equations (which can represent general nonlinear characteristics, including hysteretic phenomena). The adaptive methods estimate the parameters of the nonlinear differential equations on line. Adaptation of the parameters is done by comparing the prediction of the assumed model to the response measurement, and using the prediction error to change the system parameters. In this paper, a new methodology is presented which is not model based. The new approach solves the problem of estimating/identifying the restoring forces without assuming any model of the restoring forces dynamics, and without postulating any structure on the form of the underlying nonlinear dynamics. The new approach uses the Volterra/Wiener neural networks (VWNN) which are capable of learning input/output nonlinear dynamics, in combination with adaptive filtering and estimation techniques. Simulations and experimental results from a steel structure and from a reinforced-concrete structure illustrate the power and efficiency of the proposed method.
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Frazier, David, and Eric Renault. "Indirect Inference: Which Moments to Match?" Econometrics 7, no. 1 (March 19, 2019): 14. http://dx.doi.org/10.3390/econometrics7010014.
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The standard approach to indirect inference estimation considers that the auxiliary parameters, which carry the identifying information about the structural parameters of interest, are obtained from some recently identified vector of estimating equations. In contrast to this standard interpretation, we demonstrate that the case of overidentified auxiliary parameters is both possible, and, indeed, more commonly encountered than one may initially realize. We then revisit the “moment matching” and “parameter matching” versions of indirect inference in this context and devise efficient estimation strategies in this more general framework. Perhaps surprisingly, we demonstrate that if one were to consider the naive choice of an efficient Generalized Method of Moments (GMM)-based estimator for the auxiliary parameters, the resulting indirect inference estimators would be inefficient. In this general context, we demonstrate that efficient indirect inference estimation actually requires a two-step estimation procedure, whereby the goal of the first step is to obtain an efficient version of the auxiliary model. These two-step estimators are presented both within the context of moment matching and parameter matching.
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De Bortoli, Marta, and Farzin Zareian. "Performance Prediction Equations for Linear Planar Structural Systems: Concept, Formulation, and Validation." Earthquake Spectra 34, no. 2 (May 2018): 697–718. http://dx.doi.org/10.1193/110716eqs194m.
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This paper presents and validates an analytical formulation, denoted as Performance Prediction Equations (PPEs), that relates the seismic response engineering demand parameter (EDP) of buildings to earthquake parameters such as magnitude, epicentral distance, and type of faulting. PPEs are conceptually novel and can be readily included in any hazard calculation program to directly estimate EDP hazard curves. The PPEs presented herein are based on the linearization of response spectrum analysis (RSA) formulation for estimation of the seismic response of multi-degree-of-freedom (MDOF) models for planar structural systems. Equations for mean and variance are provided for floor displacement, interstory drift ratio, and normalized base shear. The input parameters needed to apply the proposed PPEs are the modal properties of the structural system and the selection of an existing ground motion model (GMM). The proposed PPEs are validated against simulated results using a set of planar building models and the Campbell-Bozorgnia 2014 GMM. The comparison confirms that the proposed PPEs provide an accurate estimate of the statistics of the said EDPs.
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Morley, Clive. "Demand Modelling Methodologies: Integration and other Issues." Tourism Economics 6, no. 1 (March 2000): 5–19. http://dx.doi.org/10.5367/000000000101297442.
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The exponential growth in tourist numbers motivates serious analysis of this phenomenon. The econometric methods commonly used do not take this central feature of demand seriously in the form and estimating of tourism demand models. Cointegration analysis has been used in recognition of the problem as a technical estimation issue. But this is unsatisfactory, due to both technical methodological concerns with the use of cointegration analysis and because it overcomes the growth issue rather than incorporating it into the model. A model form which does incorporate growth is proposed. Other, newer methods – neural networks and structural equations modelling – are sometimes applied, but these too are not unproblematic.
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Dagenais, Marcel G. "Estimation et spécification." Articles 54, no. 4 (July 6, 2009): 427–30. http://dx.doi.org/10.7202/800790ar.
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In his presidential address to the Société Canadienne de Science Economique, at the 1978 meeting, the author had chosen to talk about the organizational problems of the Société because of the pressing nature of the situation. Should the author have decided to discuss issues related to the science of economics, as is usuall done in such occasions, he would have taken this opportunity to point out that one of the major problems of econometric research is that of specifying correctly the structural models utilized. Econometric textbooks discuss thoroughly the methods of estimations under the assumption that the structure of the econometric model is given. However, it is well known that in practice, trial and error procedures are extensively used to find "acceptable" functional forms for the equations of the models. Efforts have been made to develop systematic techniques of choice between functional forms, but the results available until now are very limited in scope. Much greater research efforts should be devoted to this fundamental topic.
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Chen, Liangliang, Feng Zhang, and Changjun Zhou. "Maximum Likelihood Estimation of Parameters for Advanced Continuously Reinforced Concrete Pavement (CRCP) Punchout Calibration Model." Advances in Civil Engineering 2021 (September 3, 2021): 1–8. http://dx.doi.org/10.1155/2021/7709027.
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Pavement performance prediction is the essential part of the pavement design, which is very important for highway agencies for the purpose of budget allocating. This study introduces a model of local calibration for punchout, which is the major structural distress of continuously reinforced concrete pavement (CRCP). It is assumed that the number of equivalent single axle loads’ (ESALs) leads to punchout follows a Weibull distribution. The parameters of Weibull distribution were estimated by maximum likelihood estimation (MLE). Additionally, an approach of estimating the initial value of the parameters was also presented before applying the Newton method for solving the likelihood equations. The regression result was found to fit the performance-monitoring data from LTPP very well. The proposed calibration model is capable of describing the punchout and can be employed to predict the failure rate and reliability of CRCP in the pavement design and the arrangement of rehabilitation activities.
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Kanemoto, Yoshitsugu, and Ryohei Nakamura. "A new approach to the estimation of structural equations in hedonic models." Journal of Urban Economics 19, no. 2 (March 1986): 218–33. http://dx.doi.org/10.1016/0094-1190(86)90040-9.
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Grilli, Leonardo, and Carla Rampichini. "Alternative Specifications of Multivariate Multilevel Probit Ordinal Response Models." Journal of Educational and Behavioral Statistics 28, no. 1 (March 2003): 31–44. http://dx.doi.org/10.3102/10769986028001031.
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Multivariate multilevel models for ordinal variables are quite complex with respect to both interpretation and estimation. The specification in terms of a multivariate latent distribution and a set of thresholds helps in the interpretation of the variance-covariance parameters. However, most existing estimation algorithms for multilevel models can be used only if the model is reparameterized as a univariate model with an additional dummy bottom level. Moreover, the univariate formulation allows the model to be cast in the framework of Generalized Linear Latent and Mixed Models ( Rabe-Hesketh, Pickles, & Skrondal, 2001a ), a rather general class that includes, as special cases, structural equations and factor models. This article outlines the multivariate latent distribution specification and the corresponding interpretation issues; it then shows the univariate formulation, along with some alternative parameterizations that are useful in the estimation phase. An application to student ratings data illustrates the interpretation of the parameters and the estimation procedures, with a discussion of some computational issues.
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Maslowsky, Julie, Justin Jager, and Douglas Hemken. "Estimating and interpreting latent variable interactions." International Journal of Behavioral Development 39, no. 1 (October 13, 2014): 87–96. http://dx.doi.org/10.1177/0165025414552301.
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Latent variables are common in psychological research. Research questions involving the interaction of two variables are likewise quite common. Methods for estimating and interpreting interactions between latent variables within a structural equation modeling framework have recently become available. The latent moderated structural equations (LMS) method is one that is built into Mplus software. The potential utility of this method is limited by the fact that the models do not produce traditional model fit indices, standardized coefficients, or effect sizes for the latent interaction, which renders model fitting and interpretation of the latent variable interaction difficult. This article compiles state-of-the-science techniques for assessing LMS model fit, obtaining standardized coefficients, and determining the size of the latent interaction effect in order to create a tutorial for new users of LMS models. The recommended sequence of model estimation and interpretation is demonstrated via a substantive example and a Monte Carlo simulation. Finally, extensions of this method are discussed, such as estimating quadratic effects of latent factors and interactions between latent slope and intercept factors, which hold significant potential for testing and advancing developmental theories.
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Putman, Stephen H. "Extending DRAM Model: Theory-Practice Nexus." Transportation Research Record: Journal of the Transportation Research Board 1552, no. 1 (January 1996): 112–19. http://dx.doi.org/10.1177/0361198196155200116.
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The DRAM and EMPAL models of household and employment location and land use, respectively, have seen numerous applications by regional planning agencies and metropolitan planning organizations. One reason for this is that compared with other location and land use models, they are relatively easy to use. The theoretical structure of these models is that of aggregate multinomial logit. They are representations of choice probability means for household types and employment types, with their structures being derived from location surplus formulations. In operation the parameters of these models’ equations can most easily be estimated by use of a nonlinear programming formulation rather than by logit regression. Use of this technique allows a great simplification in the data requirements for calibration. In addition, this technique permits testing of alternative or auxiliary (to the standard model structures) variables in the model attractiveness formulations. The development of the models’ equation structures is described first. The problems and techniques of calibration-estimation of the equations’ parameters are then described. Finally, several experiments in model augmentation undertaken by agency staff as a part of ongoing model implementation efforts are described. These experiments demonstrate the flexibility of the structure for both application and experiment.
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Cavallaro, Luca, Fabio Dentale, Giovanna Donnarumma, Enrico Foti, Rosaria E. Musumeci, and Eugenio Pugliese Carratelli. "RUBBLE MOUND BREAKWATER OVERTOPPING: ESTIMATION OF THE RELIABILITY OF A 3D NUMERICAL SIMULATION." Coastal Engineering Proceedings 1, no. 33 (October 25, 2012): 8. http://dx.doi.org/10.9753/icce.v33.structures.8.
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Until recently, physical models were the only way to investigate into the details of breakwaters behavior under wave attack. From the numerical point of view, the complexity of the fluid dynamic processes involved has so far hindered the direct application of Navier-Stokes equations within the armour blocks, due to the complex geometry and the presence of strongly non stationary flows, free boundaries and turbulence. In the present work the most recent CFD technology is used to provide a new and more reliable approach to the design analysis of breakwaters, especially in connection with run-up and overtopping. The solid structure is simulated within the numerical domain by overlapping individual virtual elements to form the empty spaces delimited by the blocks. Thus, by defining a fine computational grid, an adequate number of nodes is located within the interstices and a complete solution of the full hydrodynamic equations is carried out. In the work presented here the numerical simulations are carried out by integrating the three-dimensional Reynolds Average Navier-Stokes Equations coupled with the RNG turbulence model and a Volume of Fluid Method used to handle the dynamics of the free surface. The aim of the present work is to investigate the reliability of this approach as a design tool. Two different breakwaters are considered, both located in Southern Sicily: one a typical quarry stone breakwater, another a more complex design incorporating a spill basin and an armoured layer made up by Coreloc® blocks.
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Abraham, John E., and John Douglas Hunt. "Parameter Estimation Strategies for Large-Scale Urban Models." Transportation Research Record: Journal of the Transportation Research Board 1722, no. 1 (January 2000): 9–16. http://dx.doi.org/10.3141/1722-02.
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Large-scale urban models often are subdivided into simpler submodels. The parameters of these models can be estimated using approaches that differ in regard to whether the full modeling system is run during an estimation procedure or whether that overall estimation is performed simultaneously with the estimation of the individual submodels. There are also ways in which extra data or extra models can be used to further inform parameter values. Five different techniques are presented (“limited view,” “piecewise” “simultaneous,” “sequential,” and “Bayesian sequential”), and the statistical theory necessary to justify each technique concurrently is described. The practical advantages and disadvantages are discussed, and each technique is illustrated using a simple nested logit model example. The concepts then are further illustrated by describing the sequential parameter estimation process for a land use/transport interaction model of the Sacramento, California, region. The ideas and examples should help modelers place more of an emphasis on overall calibration, allow them to follow a more rigorous approach in establishing the parameters of large-scale urban models, and help them understand the theory and assumptions that they are implicitly adopting. Two techniques in particular are noted as worthy of future research in large-scale urban modeling: ( a) establishing the likelihood function based directly on the structural equations of the model, eliminating or reducing the need to “solve” for the model outputs during parameter estimation; and ( b) using Bayesian techniques to adjust parameters in an overall estimation without discarding what is already known about those parameters.
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HU, XIAOLI, and JIBIN LI. "PERIODIC SOLUTIONS FOR A FOURTH-ORDER EQUATION AND APPLICATIONS IN A MODEL OF STRUCTURAL MECHANICS." International Journal of Bifurcation and Chaos 14, no. 04 (April 2004): 1477–88. http://dx.doi.org/10.1142/s0218127404010011.
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By developing topological shooting methods, the existence of single-humped periodic solutions and homoclinic orbit for a class of fourth-order ordinary differential equations is obtained, under some general conditions. Using these strict mathematical conclusions to a model of the deflection patterns of elastic struts resting on elastic foundations, the existence of single-humped periodic solutions which have been found by asymptotical and numerical methods is determined. An estimation of the half-period of the periodic solutions is also given.
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Balakrishna, Ramachandran, and Haris N. Koutsopoulos. "Incorporating within-Day Transitions in Simultaneous Offline Estimation of Dynamic Origin-Destination Flows without Assignment Matrices." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (January 2008): 31–38. http://dx.doi.org/10.3141/2085-04.
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An offline methodology is presented: it simultaneously estimates dynamic origin-destination (O-D) matrices, without using assignment matrices that incorporate within-day transition equations. The proposed formulation and solution approach extends a calibration method recently developed that directly uses the output of any network loading model (such as a dynamic traffic assignment or simulation model) so that the complex relationships between O-D flows and model outputs are accurately captured (as opposed to the more common method of approximate linear relationships based on the assignment matrix). The study extends the original formulation by incorporating spatial and temporal relationships among various O-D flows (transition equations). These transition equations link O-D flow variables across time intervals in such a way that known structural demand patterns can be preserved in the new estimates. Such transition equations, although common in the context of real-time O-D flows, complicate the offline simultaneous estimation of O-D flows and have not been used to their full potential in the past. The approach is demonstrated through a case study.
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Lanir, Y., O. Lichtenstein, and O. Imanuel. "Optimal Design of Biaxial Tests for Structural Material Characterization of Flat Tissues." Journal of Biomechanical Engineering 118, no. 1 (February 1, 1996): 41–47. http://dx.doi.org/10.1115/1.2795944.
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A rational methodology is developed for optimal design of biaxial stretch tests intended for estimating material parameters of flat tissues. It is applied to a structural model with a variety of constitutive equations and test protocols, and for a wide range of parameter levels. The results show nearly identical optimal designs under all circumstances. Optimality is obtained with two uniaxial stretch tests at mutually normal directions inclined by 22.5 deg to the axes of material symmetry. Protocols which include additional equibiaxial tests provide superior estimation with lower variance of estimates. Tests performed at angles 0, 45, and 90 deg to the axes of material symmetry provide unreliable estimates. The optimal sampling is variable and depends on the protocols and model parameters. In conclusion, the results indicate that biaxial tests can be improved over presently common procedures and show that this conclusion applies for a variety of circumstances.
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Blecker, Robert A., Michael Cauvel, and Y. K. Kim. "Systems estimation of a structural model of distribution and demand in the US economy." Cambridge Journal of Economics 46, no. 2 (January 11, 2022): 391–420. http://dx.doi.org/10.1093/cje/beab052.
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Abstract This paper investigates non-cyclical, short-run relationships between income distribution and the components of aggregate demand in the US from 1963–2016. Previous studies using this ‘structural’ methodology have typically found that demand is wage-led in most large, advanced economies. However, these studies have been criticised for treating total output and the wage share as exogenous, potentially leading to simultaneity bias. This paper corrects for such possible bias as well as common shocks to the equations by using systems GMM. Surprisingly, these estimates imply that private-sector aggregate demand is more, rather than less, wage-led (or in some cases, less profit-led) compared with OLS estimates of identically specified models. This paper is also the first to provide separate estimates of non-residential and residential investment functions and to distinguish the effects of shocks to different underlying determinants of the wage share (unit labour costs and firms’ monopoly power), finding that these differ qualitatively.
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Yang, S. M., and C. A. Jeng. "Structural Control of Distributed Parameter Systems by Output Feedback." Journal of Dynamic Systems, Measurement, and Control 120, no. 3 (September 1, 1998): 322–27. http://dx.doi.org/10.1115/1.2805404.
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Most of the controller design in distributed parameter systems requires not only the measurement and/or estimation of distributed states, but also the feedback gain in a function of time and spatial coordinates. These requirements are difficult, if not impossible, to meet in engineering implementation. An output feedback algorithm for the structural control of distributed parameter systems is presented in this paper. The algorithm employs a solution technique to simplify the functional Riccati equation into a set of algebraic equations such that sensor and actuator can be applied at discrete, instead of distributed, locations in the structure systems. The control law does not require any model discretization thereby preventing the spillover associated with discrete parameter models. An example of a slewing beam system in distributed parameter model is employed to demonstrate that the bending vibration can be effectively suppressed by a control input at the hub together with a minimal set of output measurements. The performance of the controller is shown superior to that of discrete systems using modal truncation techniques.
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Guseva-Lozinski, Elena. "Mathematical modeling of temporal changes in snow-firn properties in the cold season." Annals of Glaciology 24 (1997): 309–13. http://dx.doi.org/10.1017/s0260305500012362.
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The paper describes a non-linear dynamic thermomechanical model of the snow–firn development in the high mountain environment during the cold season. The model allows the estimation of the thermal and mechanical development of snow in an inhomogeneous stratified snowpack and in the upper part of the firn layer, the development of the snow–firn structure and transformation of snow into firn. The non-linear mathematical model consists of a heat problem, water-vapor diffusion problem, densification of the snow–firn layer, structural equations and strength conditions of the metamorphosed snow–firn depending on its temperature, structural parameters, density and rate of sublimation. The model includes conditions of snow transformation into firn and its structural changes. These equations are non-linear and coupled. The iterative finite-difference numerical method was used for the calculations and involved a full mathematical model. Numerical experiments were implemented using the complete model as well as real. The numerical computations were made for various meteorological data, temperature gradients and in the wide range of structural parameters. The calculation results were found to be in good agreement with the results of observations.
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Guseva-Lozinski, Elena. "Mathematical modeling of temporal changes in snow-firn properties in the cold season." Annals of Glaciology 24 (1997): 309–13. http://dx.doi.org/10.3189/s0260305500012362.
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The paper describes a non-linear dynamic thermomechanical model of the snow–firn development in the high mountain environment during the cold season. The model allows the estimation of the thermal and mechanical development of snow in an inhomogeneous stratified snowpack and in the upper part of the firn layer, the development of the snow–firn structure and transformation of snow into firn. The non-linear mathematical model consists of a heat problem, water-vapor diffusion problem, densification of the snow–firn layer, structural equations and strength conditions of the metamorphosed snow–firn depending on its temperature, structural parameters, density and rate of sublimation. The model includes conditions of snow transformation into firn and its structural changes. These equations are non-linear and coupled. The iterative finite-difference numerical method was used for the calculations and involved a full mathematical model. Numerical experiments were implemented using the complete model as well as real. The numerical computations were made for various meteorological data, temperature gradients and in the wide range of structural parameters. The calculation results were found to be in good agreement with the results of observations.
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Muñoz-Márquez, Clara Edith, Raquel Morales Barrera, and Alejandra del Carmen Domínguez Espinosa. "Model of Psychological Empowerment Based on Structural Equations for Predicting Autonomy." Revista Colombiana de Psicología 30, no. 2 (August 2, 2021): 55–69. http://dx.doi.org/10.15446/rcp.v30n2.82149.
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The study relies on the assumption that one of the main effects of phycological empowerment composed by attributes like self-esteem, locus of control, and assertiveness, is increased autonomy. The theoretical arguments are tested based on a structural equation model that allows estimating hypothetical relationships simultaneously. Additionally, differences in means between women and men are estimated for each phycological variable and the hypothetical model is tested separately to both sexes. 1,569 people (56% women) from five Mexican States compose the sample. The average age is 29 years and 59% of the sample has college degrees. The results suggest that psychological empowerment is strongly related to autonomy. How to cite this article: Muñoz-Márquez, C. E., Morales Barrera, R., & Domínguez Espinosa, A. del C. (2021). Model of Psychological Empowerment Based on Structural Equations for Predicting Autonomy. Revista Colombiana de Psicología, 30(2), 55-69. Retrieved from https://revistas.unal.edu.co/index.php/psicologia/article/view/82149
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Robichaud, Karen, Frank Wilson, and James Christie. "Development of speed curves and traffic flow measures for the Highway User Benefit Assessment model." Canadian Journal of Civil Engineering 19, no. 3 (June 1, 1992): 375–82. http://dx.doi.org/10.1139/l92-045.
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Transport Canada has developed a model, called the Highway User Benefit Assessment Model (HUBAM), as part of their assessment procedure for selecting projects for federal funding. A key step in this model is the estimation of average speed. These speed equations are the focus of the research on which this paper is based.The University of New Brunswick (UNB) recently completed a research project funded by Transport Canada and the New Brunswick Department of Transportation on the factors that influence highway speed. The purpose of the study was to develop speed equations for the Province of New Brunswick which could be incorporated into HUBAM. As part of the research, this paper evaluated the accuracy of the default equations in HUBAM relating speed and flow rate.An analysis of the speed and traffic flow data indicated that HUBAM underestimates speed for New Brunswick conditions. The low estimates appear to result from the curves of speed versus volume to capacity. It was concluded that regression equations developed by UNB should provide more realistic results, since the UNB equations provide a superior estimate of the observed field data. Key words: speed, traffic flow, highway access, highway user costs.
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Attoh-Okine, Nii O. "Modeling incremental pavement roughness using functional network." Canadian Journal of Civil Engineering 32, no. 5 (October 1, 2005): 899–905. http://dx.doi.org/10.1139/l05-050.
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Incremental roughness prediction is a critical component of decision making of any pavement management systems, therefore, proper estimation is of paramount importance. This paper presents the application of functional equations and networks to incremental roughness prediction of flexible pavement. In the functional networks, neuron functions are multivariate and multiargumentative. Functional equations form the basis of functional networks, therefore, established theorem in functional equations are easily applicable in the analysis. The model is developed from validated set of incremental and interactive pavement distress functions in the highway design and maintenance standard models (HDM). The models proposed and developed are intended for use in infrastructure management (pavement) applications and as a performance model for pavement design. The paper presents a computational procedure of the functional network using the serial associative functional network. The functional equation and networks approach use the domain knowledge and data for developing the roughness models.Key words: pavement roughness, functional equation, functional networks, neural networks, pavement management.
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Kaur, Katrin, Anatoli Vassiljev, Ivar Annus, Nils Kändler, and Janet Roosimägi. "Numerical investigation of the impact of irregular pipe wall build-up on velocity in the water distribution system." Journal of Water Supply: Research and Technology-Aqua 69, no. 7 (August 28, 2020): 647–55. http://dx.doi.org/10.2166/aqua.2020.035.
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Abstract This paper presents novel equations for different wall build-up types in old pipes developed for the estimation of real flow velocities in a water distribution system (WDS). This is important when estimating the contamination propagation rate in an operational WDS. Because the inner surface geometry of old rough pipes is complex, real velocities cannot be estimated by conventional WDS models. Therefore, a computational fluid dynamics (CFD) model was used to analyse the flow dynamics in old rough pipes with even and uneven roughness build-up. The developed equations for the velocity correction coefficients derive from the results of numerical simulations. Numerically obtained velocity fields show that in some cases, pipe wall build-up can affect the effective flow section significantly and the flow velocity can be underestimated by more than two times. Therefore, different velocity correction equations have to be used for different types of pipe wall build-up.
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Vijay, Rohit, Abhijit P. Deshpande, and Susy Varughese. "Nonlinear Rheological Modeling of Asphalt Using White-Metzner Model with Structural Parameter Variation Based Asphaltene Structural Build-up and Breakage." Applied Rheology 18, no. 2 (April 1, 2008): 23214–1. http://dx.doi.org/10.1515/arh-2008-0006.
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Abstract Rheological behavior of asphalt is strongly affected by loading conditions, temperature and environment. One of the main challenges in understanding the rheology of asphalt is to relate the chemical constituents and the micro-structure of asphalt on one hand to its rheological behavior on the other hand. In this work, nonlinear rheological behaviour of asphalt was investigated using a structural rheological model. A first order kinetic equation to describe structural changes in asphalt has been incorporated with the nonlinear rheological model of White- Metzner. The resulting set of governing equations was solved numerically to describe the rheology of asphalts. Different modes of rheological testing and asphalts with different compositions were considered. An analysis and comparison of model behaviour with experimental data from the literature is carried out in both stress growth at constant shear rate and oscillatory shear modes. A strategy is proposed for the estimation and tuning of the model parameters based on available experimental data and literature. Qualitatively, the model can capture the rheological behaviour of non-Newtonian fluids such as asphalt under different modes of rheological testing. Quantitative analysis from this work shows that the model describes the rheological behaviour of asphalt for the temperature range of 20 – 60ºC. It is demonstrated that a single set of equations tuned with the steady shear experimental data can be used to predict the nonlinear rheological behaviour of asphalts. In addition, it is shown that the model parameters can be related to the chemical composition of asphalts.
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Hong, Hoon, Alexey Ovchinnikov, Gleb Pogudin, and Chee Yap. "SIAN: software for structural identifiability analysis of ODE models." Bioinformatics 35, no. 16 (January 2, 2019): 2873–74. http://dx.doi.org/10.1093/bioinformatics/bty1069.
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Abstract Summary Biological processes are often modeled by ordinary differential equations with unknown parameters. The unknown parameters are usually estimated from experimental data. In some cases, due to the structure of the model, this estimation problem does not have a unique solution even in the case of continuous noise-free data. It is therefore desirable to check the uniqueness a priori before carrying out actual experiments. We present a new software SIAN (Structural Identifiability ANalyser) that does this. Our software can tackle problems that could not be tackled by previously developed packages. Availability and implementation SIAN is open-source software written in Maple and is available at https://github.com/pogudingleb/SIAN. Supplementary information Supplementary data are available at Bioinformatics online.
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Jin, Shaobo, Fan Yang-Wallentin, and Kenneth A. Bollen. "A unified model-implied instrumental variable approach for structural equation modeling with mixed variables." Psychometrika 86, no. 2 (June 2021): 564–94. http://dx.doi.org/10.1007/s11336-021-09771-4.
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AbstractThe model-implied instrumental variable (MIIV) estimator is an equation-by-equation estimator of structural equation models that is more robust to structural misspecifications than full information estimators. Previous studies have concentrated on endogenous variables that are all continuous (MIIV-2SLS) or all ordinal . We develop a unified MIIV approach that applies to a mixture of binary, ordinal, censored, or continuous endogenous observed variables. We include estimates of factor loadings, regression coefficients, variances, and covariances along with their asymptotic standard errors. In addition, we create new goodness of fit tests of the model and overidentification tests of single equations. Our simulation study shows that the proposed MIIV approach is more robust to structural misspecifications than diagonally weighted least squares (DWLS) and that both the goodness of fit model tests and the overidentification equations tests can detect structural misspecifications. We also find that the bias in asymptotic standard errors for the MIIV estimators of factor loadings and regression coefficients are often lower than the DWLS ones, though the differences are small in large samples. Our analysis shows that scaling indicators with low reliability can adversely affect the MIIV estimators. Also, using a small subset of MIIVs reduces small sample bias of coefficient estimates, but can lower the power of overidentification tests of equations.
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Gandomi, Amir H., Ali Faramarzifar, Peyman Ghanad Rezaee, Abazar Asghari, and Siamak Talatahari. "NEW DESIGN EQUATIONS FOR ELASTIC MODULUS OF CONCRETE USING MULTI EXPRESSION PROGRAMMING." Journal of Civil Engineering and Management 21, no. 6 (June 9, 2015): 761–74. http://dx.doi.org/10.3846/13923730.2014.893910.
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An innovative multi expression programming (MEP) approach is used to derive new predictive equations for tangent elastic modulus of normal strength concrete (NSC) and high strength concrete (HSC). Similar to several building codes, the modulus of elasticity of NSC and HSC is formulated in terms of concrete compressive strength. Furthermore, a generic model is developed for the estimation of the elastic modulus of both NSC and HSC. Comprehensive databases are gathered from the literature to develop the models. For more verification, a parametric analysis is carried out and discussed. The proposed formulas are found to be accurate for the prediction of the elastic modulus of NSC and HSC. The predictions made by the MEP-based models are more accurate than those obtained by the existing models.
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Xue, Huili, Kun Lin, Yin Luo, and Hongjun Liu. "Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation." Shock and Vibration 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/9301876.
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A minimum-variance unbiased estimation method is developed to identify the time-varying wind load from measured responses. The formula derivation of recursive identification equations is obtained in state space. The new approach can simultaneously estimate the entire wind load and the unknown structural responses only with limited measurement of structural acceleration response. The fluctuating wind speed process is investigated by the autoregressive (AR) model method in time series analysis. The accuracy and feasibility of the inverse approach are numerically investigated by identifying the wind load on a twenty-story shear building structure. The influences of the number and location of accelerometers are examined and discussed. In order to study the stability of the proposed method, the effects of the errors in crucial factors such as natural frequency and damping ratio are discussed through detailed parametric analysis. It can be found from the identification results that the proposed method can identify the wind load from limited measurement of acceleration responses with good accuracy and stability, indicating that it is an effective approach for estimating wind load on building structures.
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Keay, Myoung-Jin. "An Exponential Endogenous Switching Regression with Correlated Random Coefficients." Econometrics 10, no. 1 (December 21, 2021): 1. http://dx.doi.org/10.3390/econometrics10010001.
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This paper presents a method for estimating the average treatment effects (ATE) of an exponential endogenous switching model where the coefficients of covariates in the structural equation are random and correlated with the binary treatment variable. The estimating equations are derived under some mild identifying assumptions. We find that the ATE is identified, although each coefficient in the structural model may not be. Tests assessing the endogeneity of treatment and for model selection are provided. Monte Carlo simulations show that, in large samples, the proposed estimator has a smaller bias and a larger variance than the methods that do not take the random coefficients into account. This is applied to health insurance data of Oregon.
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Gong, Mao Sheng, Xiao Hua Li, Yan Bin Gao, and Qi Fang Liu. "Study on Probabilistic Identification Method of Structural Physical Parameter Based on Bayesian Estimation." Applied Mechanics and Materials 578-579 (July 2014): 1113–17. http://dx.doi.org/10.4028/www.scientific.net/amm.578-579.1113.
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Base on the structural modal parameters, the linear regression models of physical parameters are derived from the dynamic equations. The posterior joint Probability Density Function (PDF) of physical parameters is obtained by using Bayesian statistics theory. Then the Markov Chain Monte Carlo (MCMC) sample method is adopted to get the marginal PDF and optimal estimation of structural physical parameters. A numerical simulation of a 5-stroy structure under the excitation of white noise with different noise level is used to identify the physical parameters by the presented method. It is shown that the method can not only determine the optimal estimate but also get the probability distribution of the structural physical parameters from the known modal parameters of the primary modes. The method is with higher validity, robustness and efficiency, and can be applied to the structural health monitoring, damage evaluation, and so on.
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Yan, Banfu, Wenbing Chen, You Dong, and Xiaomo Jiang. "Tension Force Estimation of Cables with Two Intermediate Supports." International Journal of Structural Stability and Dynamics 20, no. 03 (February 19, 2020): 2050032. http://dx.doi.org/10.1142/s0219455420500327.
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The presence of intermediate supports usually imposes difficulties in identifying the tension force of stayed cables in cable-stayed bridges or hanger cables in arch bridges. This paper establishes the partial differential equations of motion of the cable and derives two numerical models with (Model 1) and without (Model 2) considering the flexural rigidity. The effects of two intermediate supports on the identification accuracy of the cable tension force are further studied analytically and experimentally. The effects of several non-dimensional parameters (e.g. damper location, support stiffness, flexural rigidity, and mode order of the cable) on the identification accuracy of the models are also investigated. It is theoretically concluded that the simplified Model 2 provides acceptable accuracy on tension force identification when the non-dimensional parameter [Formula: see text] is greater than 90 (slender cables), whereas the accurate Model 1 can be applied for tension force identification at any scenarios. The feasibility of two models is further verified by three numerical examples and field tests on two real-world arch bridges.
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Smith, Blair J., and Donald R. Scott. "Level of Structural Aggregation and Predictive Accuracy of Milk Supply Response Estimates." Northeastern Journal of Agricultural and Resource Economics 15, no. 1 (April 1986): 32–36. http://dx.doi.org/10.1017/s0899367x00001306.
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Milk supply response was estimated for Pennsylvania using three different levels of structural aggregation. The base level involved the estimation of milk production in a single equation. Under the second method, production was the product of two equations: milk per cow and number of milk cows. The third method factored production into three equations: milk per cow, number of dairy farms, and number of cows per farm. As expected, the greater the degree of disaggregation the more was learned about the structural aspects of milk production. At the same time, predictive accuracy generally decreased, but the differences among models was slight.
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Pieterse-Quirijns, E. J., E. J. M. Blokker, E. van der Blom, and J. H. G. Vreeburg. "Non-residential water demand model validated with extensive measurements and surveys." Drinking Water Engineering and Science 6, no. 2 (October 31, 2013): 99–114. http://dx.doi.org/10.5194/dwes-6-99-2013.
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Abstract. Existing Dutch guidelines for the design of the drinking water and hot water system of non-residential buildings are based on outdated assumptions on peak water demand or on unfounded assumptions on hot water demand. They generally overestimate peak demand values required for the design of an efficient and reliable water system. Recently, a procedure was developed based on the end-use model SIMDEUM to derive design-demand-equations for peak demand values of both cold and hot water during various time steps for several types and sizes of non-residential buildings, viz. offices, hotels and nursing homes. In this paper, the design-demand-equations are validated with measurements of cold and hot water patterns on a per second base and with surveys. The good correlation between the simulated water demand patterns and the measured patterns indicates that the basis of the design-demand-equations, the SIMDEUM simulated standardised buildings, is solid. Surveys were held to investigate whether the construction of the standardised buildings based on the dominant variable corresponds with practice. Surveys show that it is difficult to find relationships to equip the standardised buildings with users and appliances. However, the validation proves that with a proper estimation of the number of users and appliances in only the dominant functional room of the standardised buildings, SIMDEUM renders a realistic cold and hot water diurnal demand pattern. Furthermore, the new design-demand-equations based on these standardised buildings give a better prediction of the measured peak values for cold water flow than the existing guidelines. Moreover, the new design-demand-equations can predict hot water use well. In this paper it is illustrated that the new design-demand-equations lead to reliable and improved designs of building installations and water heater capacity, resulting in more hygienic and economical installations.
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Zhang, Junhui, Junhui Peng, Yejuan Chen, Jue Li, and Feng Li. "Estimation of Soil-Water Characteristic Curve for Cohesive Soils with Methylene Blue Value." Advances in Civil Engineering 2018 (July 5, 2018): 1–7. http://dx.doi.org/10.1155/2018/9213674.
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This study described a new methylene blue test to measure the methylene blue value (MBV) for 15 cohesive soils and established the relationship between MBV and plasticity index (PI) and between MBV and percent passing No. 200 sieve (P200), respectively. Thereafter, the soil-water characteristic curves (SWCCs) for 15 cohesive soils based on Fredlund and Xing’s model were generated by the pressure plate test. Then, regression equations for determining the four fitting parameters in a previously developed SWCC equation by using the measured MBV were utilized to generate the SWCC for the cohesive soils. At the same time, the slope parameter, bf, in the SWCC equations was found to be associated with the moisture susceptibility of cohesive soils. A higher bf value indicates that the material is more moisture susceptible. In addition, a lower MBV/PI/P200 shows a lower suction at the same degree of saturation; on the other hand, a higher MBV/PI/P200 presents a higher suction. Therefore, the moisture-holding capacity of cohesive soils increases with increasing MBV, PI, and P200. Finally, the proposed estimation method was validated by a comparison between the four determined fitting parameters from MBV and the pressure plate test.
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Barszcz, Tomasz, and Piotr Czop. "Estimation of feedwater heater parameters based on a grey-box approach." International Journal of Applied Mathematics and Computer Science 21, no. 4 (December 1, 2011): 703–15. http://dx.doi.org/10.2478/v10006-011-0056-4.
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Estimation of feedwater heater parameters based on a grey-box approachThe first-principle modeling of a feedwater heater operating in a coal-fired power unit is presented, along with a theoretical discussion concerning its structural simplifications, parameter estimation, and dynamical validation. The model is a part of the component library of modeling environments, called the Virtual Power Plant (VPP). The main purpose of the VPP is simulation of power generation installations intended for early warning diagnostic applications. The model was developed in the Matlab/Simulink package. There are two common problems associated with the modeling of dynamic systems. If an analytical model is chosen, it is very costly to determine all model parameters and that often prevents this approach from being used. If a data model is chosen, one does not have a clear interpretation of the model parameters. The paper uses the so-called grey-box approach, which combines first-principle and data-driven models. The model is represented by nonlinear state-space equations with geometrical and physical parameters deduced from the available documentation of a feedwater heater, as well as adjustable phenomenological parameters (i.e., heat transfer coefficients) that are estimated from measurement data. The paper presents the background of the method, its implementation in the Matlab/Simulink environment, the results of parameter estimation, and a discussion concerning the accuracy of the method.
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Yang, Hongzhi, Xuliang Guo, Zhenfeng Wang, and Shanshan Hu. "Feasibility-Based Design Model For Road Vertical Alignment." Baltic Journal of Road and Bridge Engineering 16, no. 4 (December 28, 2021): 270–96. http://dx.doi.org/10.7250/bjrbe.2021-16.548.
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Road vertical alignment design is a multi-objective design problem that needs to consider multiple constraints. Intelligent design based on optimization algorithms cannot wholly solve problems, such as multi-objective, uncertainty, and constraint dynamics. The article proposes a model of dynamically transforming design constraints into feasible regions as the design develops, to provide decision information before design actions rather than performing constraint evaluation after the design that reduces the empirical estimation. The design actions are divided into new design actions and modifying design actions, and corresponding feasible regions derived from constraints of design specifications and control elevations are established, respectively. Geometrical equations and program algorithms of feasible regions are described in the graphic environment, which is applied to the vertical alignment design to improve the design efficiency and decision-making level.
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Sulistyowati, Niken, Bonar Marulitua Sinaga, and Novindra Novindra. "Impacts of Government and Household Expenditure on Human Development Index." JEJAK 10, no. 2 (September 10, 2017): 412–28. http://dx.doi.org/10.15294/jejak.v10i2.11305.
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The objective of this reseach are to: (1) analyze the factors affecting human development index and household expenditures for health, education and others, (2) predict the impacts of government expenditure policy in the field of education, health, and infrastructure on human development index in Central Java. The model was built using econometric approach in the form of a system of simultaneous equations, including five blocks i.e. government's revenue, expenditures, input, output, and performance. The system of simultaneous equations consisted of 26 equations (19 structural equations and 7 identity equations). The estimation method used Two Stage Least Squares with SYSLIN procedure. Prediction simulation used the stepwise Autoregressive method. The model simulation used Newton's method and SIMNLIN procedure. The results of policy simulation concludes that the combination of the increase in government expenditure for education and infrastructure lead to better performance in increasing income per capita, disposable income and HDI compared to the combination of the policy of the increase in government expenditure for education and in both municipalities and district, but municipalities receive greatest impact compared to the district.