Efficient Method Of Moments Research Articles

Lag order selection for long-run variance estimation in econometrics

. Estimating the long-run variance (LRV) is crucial for several econometric issues. Constructing reliable heteroskedasticity autocorrelation consistent (HAC) variance-covariance matrices and implementing efficient generalized method of moments (GMM) estimation procedures require a consistent LRV estimate. A good VARHAC estimator (HAC matrix with the spectral density at frequency zero constructed using a VAR spectral estimation) requires accurately estimating the sum of autoregressive (AR) coefficients; however, a criterion that minimizes the innovation variance does not necessarily yield the best spectral estimate. This article implements an optimal VARHAC estimator using an alternative information criterion, considering the bias in the sum of the parameters for the AR estimator of the spectral density at frequency zero.

On the calibration of stochastic volatility models to estimate the real-world measure used in option pricing

It is widely noted that the Heston stochastic volatility model fails to capture the fat tails often observed in daily equity returns. Adding random jumps improves the model’s ability to capture extreme events. This extension is known as the Bates stochastic volatility jump (SVJ) model. The model parameters for the Heston and Bates SVJ models are generally calibrated to option prices inducing the so-called risk-neutral measure. However, in the absence of a sufficiently liquid options market, one has to resort to calibration under the realworld measure. In this paper, we calibrate the Heston and Bates SVJ models to historical equity returns in the United States and South Africa using the efficient method of moments(EMM). We then show how a real-world stochastic volatility model can be used in practice to test a simple volatility targeting strategy. Our findings suggest that stochastic volatility and jumps are both required to characterise equity returns in South Africa. Furthermore, volatility targeting is an effective strategy that allows investors to manage the downside risk of a portfolio.

Efficient EDM-PO Method for the Scattering From Electrically Large Objects With the High-Order Impedance Boundary Condition

This work proposes an efficient hybrid method consisting of the efficient iterative method of moments–physical optics (EI-MoM-PO) and the equivalent dipole moment (EDM) with the high-order impedance boundary condition (HOIBC) to explore the electromagnetic scattering from the object with an isotropic or anisotropic surface coating. By introducing the HOIBC into the EDM method, the relationship between the equivalent electric and magnetic dipole moments is established. Therefore, the EDM method is extended to general cases. For the composite scattering from electrically large objects including MoM and PO regions, the EDM method is implemented to fill the MoM impedance matrix and to accelerate the evaluation of the coupling between the MoM and PO regions, which considerably improves the computing efficiency. The numerical results indicate that the proposed hybrid method allows for a substantial decrease in computation time. Also, they also agree well with the traditional finite element method, MoM, or MoM-PO method, which proves the validity of the proposed method.

Finite-sample corrected inference for two-step GMM in time series

This paper develops a finite-sample corrected inference for the efficient generalized method of moments (GMM) in time series. To capture a higher-order uncertainty embodied in estimating the time series GMM weight matrix, we extend the finite-sample corrected variance formula of Windmeijer (2005) to heteroskedasticity autocorrelated robust (HAR) inference. Using fixed-smoothing asymptotics, we show that our finite-sample corrected test statistics lead to standard asymptotic t or F critical values and suffer from less over-rejection of the null hypothesis than existing GMM procedures on finite-samples, including continuously updating GMM. Not only does our finite-sample corrected variance formula correct for the bias arising from the plugged-in long-run variance estimation, but it is also not exposed to a potential side effect of Windmeijer’s formula, which can introduce an additional source of over-rejection after the correction.

Efficient Analysis of Planar, Arbitrarily Shaped, and (Bi)-Anisotropic Metasurface Antennas

An efficient method of moments (MoM) scheme is presented for the analysis of planar, possibly cascaded metasurfaces (MTSs) implementing high-impedance surfaces. The MTS can be designed on an arbitrarily shaped domain and is accounted for as a set of cascaded electric sheet impedances. In the proposed method, the shaped MTS is included in a larger rectangular domain meshed with rooftop basis functions, resulting in a Toeplitz–block Toeplitz structure for the substrate impedance matrix, which enables fast Fourier transform (FFT)-based acceleration of matrix–vector products. The basis functions lying in the rectangular domain but outside the MTS are disabled by including zeros in the impedance matrix. The obtained linear system of equations is well conditioned, does not require any specific near-field treatment, and can be solved iteratively using the generalized minimal residual (GMRES) method. It has been demonstrated that the algorithm is able to handle efficiently any MTS antenna shape in single-layer or multilayer configuration with almost linear complexity. It is shown that the high-impedance sheets improve the convergence rate. MTSs with more than 40 wavelengths size, meshed with more than 1 million basis functions, can be analyzed on a conventional computer in less than 15 min. A very good agreement is shown through comparison with results from other software packages.

Measuring preferences for energy efficiency in ACI and EU nations and uncovering their impacts on energy conservation

Energy efficiency, commonly interpreted as the ratio of output of performance, service, goods or energy, to input of energy, is of critical importance for reducing dependence on oil, controlling greenhouse gas emissions from fossil-fuel combustion and mitigating environmental damages in order to achieve a sustainable global energy system. In this paper, for the first time to the best of our understanding, we measure the (hidden) preferences for energy efficiency and capture their impacts on energy conservation in a panel of ASEAN countries, China and India (in short, the ACI nations) from 1985 to 2020. We apply the state-space models to estimate country-specific preferences for energy efficiency as a latent variable and then explore their impacts on the demand for renewable energy using an efficient generalised method of moments (GMM) estimator for the panel of chosen countries. We find strong evidence that intensities of preferences for energy efficiency increase the demand for renewable energy in ACI nations. In an extension of our study, we replicate our analysis for leading European Union (EU) nations using clean energy to arrive at interesting comparative insights. We gain further insights into the understanding of how structural breaks can influence the impacts of preferences for energy efficiency on the demand for renewables for ACI nations.

Approximate maximum likelihood for complex structural models

Indirect Inference (I-I) is a popular technique for estimating complex parametric models whose likelihood function is intractable, however, the statistical efficiency of I-I estimation is questionable. While the efficient method of moments, Gallant and Tauchen (1996), promises efficiency, the price to pay for this efficiency is a loss of parsimony and thereby a potential lack of robustness to model misspecification. This stands in contrast to simpler I-I estimation strategies, which are known to display less sensitivity to model misspecification due in large part to their focus on specific elements of the underlying structural model. In this research, we propose a new simulation-based approach that maintains the parsimony of I-I estimation, which is often critical in empirical applications, but can also deliver estimators that are nearly as efficient as maximum likelihood. This new approach is based on using a constrained approximation to the structural model, which ensures identification and can deliver estimators that are consistent and nearly efficient. We demonstrate this approach through several examples, and show that this approach can deliver estimators that are nearly as efficient as maximum likelihood, when feasible, but can be employed in many situations where maximum likelihood is infeasible.

Firm‐level aggregate corruption and competition: The role of telecommunications infrastructure

AbstractThis study examines the relationship between competition and corruption in the presence of enhanced telecommunications infrastructure. We use firm‐level aggregate data provided by the World Bank Enterprise Surveys and collected between 2006 and 2018. Our fixed‐effects results are two‐fold. First, the number of competing firms increases corruption in developing countries. This result is consistent with the previous literature on the competition‐corruption nexus. Second, corruption decreases as the number of competing firms increases in countries with better information and communication technology endowment. Our results are robust to controlling for endogeneity via the two‐step, feasible efficient generalized method of moments and suggest that e‐governance may help to reduce firm‐level corruption in a competitive environment. Given the negative impact of corruption on investment and growth, developing countries should aim at adopting and using more telecommunications infrastructure, along with the traditional approaches of combatting corruption that are based on enforcing rules of law or building stronger institutions, just to name a few, to boost investment and economic growth.

Efficient Method of Moments for Simulating Atmospheric Aerosol Growth: Model Description, Verification, and Application

AbstractThe atmospheric aerosol dynamics model (AADM) has been widely used in both comprehensive air quality model systems and chemical transport modeling globally. The AADM consists of Smoluchowski's coagulation equation (SCE), whose solution undergoing Brownian coagulation in the free molecular regime is a challenge because it is inconsistent with aerosols whose size distribution cannot exactly follow the lognormal size distribution. Thus, a new method for solving the SCE without assuming lognormal size distribution is proposed and developed. The underlying principle of this method is that the hybridization of the well‐established method of moments with the assumed lognormal size distribution (log MOM) and Taylor‐series expansion method of moments (TEMOM) is implemented. This method shows excellent agreement with the sectional method (SM) which is used as reference. The accuracy of these two specific models closely approaches that of the TEMOM, but overcomes the limitation of the classical log MOM. The computational time of this scheme is considerably lower than that of the SM. The new method was successfully implemented to reveal the formation and growth of secondary particles emitted from a vehicle exhaust tailpipe. It was found that the formation of new particles only occurs in the interface region of the turbulent exhaust jet (which is very close to the tailpipe exit), whereas no new particles are formed in the mixture of the exhaust jet plume and the surrounding cold air downstream. The new method is verified as an efficient and reliable numerical scheme for studying atmospheric aerosol dynamics.

Impact of Frequency-Dependent Soil Models on Grounding System Performance for Direct and Indirect Lightning Strikes

The goal of this article is to investigate the effect of frequency-dependent soil models on the performance of grounding electrodes subjected to lightning strikes. Several soil models are examined while accounting for the variation of soil resistivity and permittivity as a function of the lightning current frequency spectrum. The analysis is performed for a homogeneous soil and a two-layer horizontally stratified soil. The impact of the frequency-dependent soil parameters on the ground potential rise (GPR) of simple grounding electrodes subjected to lightning is analyzed and discussed. The analysis is performed in the frequency domain and in the time domain. A wind turbine and its grounding system are also considered in this article. Special attention is given to the case of indirect lightning, rarely mentioned in the literature. The GPR of the grounding electrodes is examined when the frequency dependence of the soil is taken into account and the lightning channel is located at close distances to the electrodes. Indeed, the level of induced electromagnetic fields caused by a nearby lightning channel can still be too high and potentially dangerous. The computations are performed using an efficient Method of Moments (MoM) numerical tool based on surface-wire integral equations for a stratified medium in the frequency range from dc to several MHz. Numerical results demonstrate that the frequency dependency of the soil parameters results in a decrease of the potential rise of the grounding electrodes, with respect to the case where the parameters are assumed constant.

A Latent Factor Model for Forecasting Realized Variances

Abstract This article proposes a parsimonious model to forecast large vectors of realized variances (RVar) by exploiting their common dynamics within a latent factor structure. Their long persistence is captured by aggregating latent factors with AR(1) dynamics. The model has obvious advantages over standard autoregressive models not only in terms of parametrization, but also in terms of efficiency, when increasing the dimension of the vector, as it provides more information on the commonality of the series’ dynamics. The model easily accommodates further empirical features of RVars, such as conditional heteroskedasticity. For estimation purposes, we use the maximum likelihood method based on Kalman filter and the efficient method of moments, both being easy to implement and providing accurate estimates. Our empirical illustration on real data shows that the model we propose often outperforms standard models, most of which are, for vectors of RVar series, only implementable under heavy parametric restrictions.

A Hybrid-Analytical-Model for the Paraboloidal Reflector Antenna

In this paper, a computationally efficient method of moments (MoM)-physical optics (PO) formulation of the general paraboloidal reflector antenna problem is developed. The formulation hybridizes the integral equation approach characteristic of the conventional ‘low-frequency’ methods and the asymptotic solution of the wave-object interaction problem of PO. This formulation is based on an adaptation of an approach prescribed by Kerdemilidis - for a parametric description of the antenna’s geometry - leading to a generalization in a relatively simplified format of an ordinarily analytically involved process. The obtained results show a good agreement with the reported results due to other approaches and, consequently, prove the validity of the proposed model.

Theory and Experiment of UWB Archimedean Conformal Spiral Antennas

A conformal UWB Archimedean spiral antenna on a dielectric hemisphere is theoretically and experimentally investigated. The analysis method, design, and optimization of this type of spherical antennas is performed using an efficient spatial domain method of moments in conjunction with triangular basis functions and asymptotic Green’s functions. A special conformal mapping is used to enhance the impedance bandwidth and axial ratio (AR) bandwidth for a circularly polarized spherical spiral antenna. Emphasis is given to the efficient asymptotic approach in spherical multilayered media. To validate the theory, a UWB leaky-wave conformal spiral antenna was designed, manufactured, and tested. The measured results indicate a pretty wideband behavior for this antenna starting from 1.7 to 6 GHz (1.8 octaves) in its input impedance responses. The circular polarization is maintained over 1.26 octave with less than 3 dB AR.

Extraordinary Transmission and Radiation From Finite by Infinite Arrays of Slots

In this communication an efficient method of moments (MoM) code is used for the analysis of the extraordinary transmission (EOT) through a periodic array of rectangular slots in a conducting screen, in the case where the number of slots is finite in one direction and infinite in the orthogonal direction. The slots can be arbitrarily rotated within the periodic unit cell. Once the magnetic current density on the slots is obtained by means of MoM, both the transmission coefficient and the far-field radiated by the array of slots are computed. The onset of EOT turns out to be strongly dependent on the orientation of the slots with respect to the direction in which the array is infinite. If the slots are perpendicular to this direction, EOT appears for a single infinite chain of slots. However, tens of parallel chains of slots are required to reproduce the EOT response when the slots are aligned along the parallel chains direction. The obtained radiation patterns show the excitation of grating lobes as the number of slots grow in the direction where the arrays are finite.

Implementation of an efficient method of moments for treatment of soot formation and oxidation processes in three-dimensional engine simulations

In this work, an efficient numerical approach for detailed soot particle dynamics modeling in three-dimensional engine simulation is proposed. The recently developed moment projection method is incorporated into engine computational fluid dynamics codes to handle the detailed soot particle dynamics. The main advantage of moment projection method over other methods of moments is its ability to handle the soot oxidation problem which plays a significant role in determining the evolution of soot particles in engines. The new approach has been applied to study the soot formation and oxidation processes in a dual-fueled compression ignition engine operated under different conditions. Results suggest that the new approach is highly efficient with little CPU cost induced by the treatment of the detailed soot model. The integrated engine-soot model is able to correctly capture the emission trend for soot particles under different fuel injection timings. With this new approach, a detailed physical and chemical insight into the soot formation and oxidation processes inside the engines can be achieved. The findings indicate that the proposed numerical approach is a promising framework for soot modeling in three dimensional engine simulations.

An Improved Antenna Theory Model of Lightning Return Stroke Using a Distributed Current Source–Part II: Applications

A full-wave method of Maxwell's equations is adopted for the analysis of lightning electromagnetic fields. The method is based on a numerical solution of the electric field integral equation by the method of moments (MoM). A new electromagnetic model of the lightning channel based on a thin-wire antenna with distributed current sources allows the use of Sommerfeld integrals for the evaluation of electromagnetic fields due to lightning, in stratified media. In order to extend the study to more complex systems including the lightning channel and its nearby structures, an array of conducting wires and metallic surfaces is used to represent the entire system. An efficient and cost-effective MoM method capable to compute the variation of spatial one-dimensional linear currents and two-dimensional surface currents is implemented. It permits the evaluation of the electromagnetic interference effects of lightning in a complex environment, without the use of approximate formulas. The proposed method is capable of analyzing the electromagnetic interference effects of lightning for a wide range of applications. Several case studies, including the analysis of lightning-induced disturbances on overhead lines, underground cables, and shielding enclosures, are also presented.

Two-stage least squares as minimum distance

SummaryThe two-stage least-squares (2SLS) instrumental-variables (IV) estimator for the parameters in linear models with a single endogenous variable is shown to be identical to an optimal minimum-distance (MD) estimator based on the individual instrument-specific IV estimators. The 2SLS estimator is a linear combination of the individual estimators, with the weights determined by their variances and covariances under conditional homoskedasticity. It is further shown that the Sargan test statistic for overidentifying restrictions is the same as the MD criterion test statistic. This provides an intuitive interpretation of the Sargan test. The equivalence results also apply to the efficient two-step generalized method of moments and robust optimal MD estimators and criterion functions, allowing for general forms of heteroskedasticity. It is further shown how these results extend to the linear overidentified IV model with multiple endogenous variables.

Efficient volumetric method of moments for modeling plasmonic thin-film solar cells with periodic structures.

Metallic nanoparticles (NPs) support localized surface plasmon resonances (LSPRs), which enable to concentrate sunlight at the active layer of solar cells. However, full-wave modeling of the plasmonic solar cells faces great challenges in terms of huge computational workload and bad matrix condition. It is tremendously difficult to accurately and efficiently simulate near-field multiple scattering effects from plasmonic NPs embedded into solar cells. In this work, a preconditioned volume integral equation (VIE) is proposed to model plasmonic organic solar cells (OSCs). The diagonal block preconditioner is applied to different material domains of the device structure. As a result, better convergence and higher computing efficiency are achieved. Moreover, the calculation is further accelerated by two-dimensional periodic Green's functions. Using the proposed method, the dependences of optical absorption on the wavelengths and incident angles are investigated. Angular responses of the plasmonic OSCs show the super-Lambertian absorption on the plasmon resonance but near-Lambertian absorption off the plasmon resonance. The volumetric method of moments and explored physical understanding are of great help to investigate the optical responses of OSCs.

Exact Bayesian moment based inference for the distribution of the small-time movements of an Itô semimartingale

We modify the Gallant and Tauchen (1996) efficient method of moments (EMM) method to perform exact Bayesian inference, where exact means no reliance on asymptotic approximations. We use this modification to evaluate the empirical plausibility of recent predictions from high frequency financial theory regarding the small-time movements of an Itô semimartingale. The theory indicates that the probability distribution of the small moves should be locally stable around the origin. It makes no predictions regarding large rare jumps, which get filtered out. Our exact Bayesian procedure imposes support conditions on parameters as implied by this theory. The empirical application uses S&P Index options extending over a wide range of moneyness, including deep out of the money puts. The evidence is consistent with a locally stable distribution valid over most of the support of the observed data while mildly failing in the extreme tails, about which the theory makes no prediction. We undertake diagnostic checks on all aspects of the procedure. In particular, we evaluate the distributional assumptions regarding a semi-pivotal statistic, and we test by Monte Carlo that the posterior distribution is properly centered with short credibility intervals. Taken together, our results suggest a more important role than previously thought for pure jump-like models with diminished, if not absent, diffusive component.

The nexus between microcredit nominal interest rates and inflation in sub-Saharan Africa: evidence from panel vector autoregression analysis

This paper investigates the dynamic effect of microcredit nominal interest rates and inflation, using a panel data of 315 microfinance institutions from 34 sub-Saharan African (SSA) countries over the period 2003 to 2011. To do so, we employ a panel vector autoregression (PVAR) model using efficient generalized method of moments (GMM) estimation as proposed by Blundell and Bond (1998). Apart from the full sample estimation, we further group our countries into three different income groups. Overall, the full sample estimation suggests that there is a negative relationship between inflation and microcredit nominal interest rates. The causality runs from inflation to microcredit nominal interest rates, whereas the reverse does not hold. Furthermore, the forecast error variances after 10 years have very low explanatory power for both microcredit nominal interest rates and inflation. Far more importantly, the significance of our study findings supports the Fisher effect (Fisher, 1930) and that microfinance len...