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The purpose of this paper is to develop new types of direct expansion method of moments (DEMM) by using the n/3th moments for simulating nanoparticle Brownian coagulation in the free molecule regime. The feasibilities of new proposed DEMMs with n/3th moments are investigated to describe the evolution of aerosol size distribution, and some of the models will be applied to further simulation of physical processes.

The accuracy and efficiency of some kinds of methods of moments are mainly compared including the quadrature method of moments (QMOM), Taylor-expansion method of moments (TEMOM), the log-normal preserving method of moments proposed by Lee (LMM) and the derived DEMM in this paper. QMOM with 12 quadrature approximation points is taken as a reference to evaluate other methods.

The newly derived models, namely DEMM(4/3,4) and DEMM(2,6), as well as the previous DEMM(2,4), are considered to be qualified models due to their high accuracy and efficiency. They are confirmed to be valid and alternative models to describe the evolution of aerosol size distribution for particle dynamical process involving the n/3th moments.

The n/3th moments, which have clear physical interpretations when n stands for first several integers, are first introduced in the DEMM method for simulating nanoparticle Brownian coagulation in the free molecule regime.

We investigate how career disruptions in terms of job loss may impact morbidity for individuals diagnosed with type 2 diabetes (T2D). Combining unique, high-quality longitudinal data from the Swedish National Diabetes Register (NDR) with matched employer–employee data, we focus on individuals diagnosed with T2D, who are established on the labor market and who lose their job in a mass layoff. Using a conditional difference-in-differences evaluation approach, our results give limited support for job loss having an impact on health behavior, diabetes progression, and cardiovascular risk factors.

Standard multivariate tests of mean variance efficiency (MVE) have been criticised on the grounds that they require regression residuals to have a multivariate normal distribution. Generally, the existing evidence suggests that the normality assumption is questionable, even for monthly returns. MacKinlay and Richardson (1991) developed a generalised method of moments (GMM) framework which provides tests which are valid under much weaker distributional assumptions. They examined monthly US data formed into size based portfolios, for mean‐variance efficiency relative to the Sharpe‐Lintner CAPM. They found that inferences regarding mean‐variance efficiency can be sensitive to the test considered. In this paper we further investigate their GMM tests using monthly Australian data over the period 1974 to 1994. We extend upon their analysis to consider an alternative version of their GMM test and also to examine a zero‐beta version of the CAPM. Similar to the US case, our results also indicate sensitivity of inferences to the tests used. Finally, while we find that the GMM tests generally provide rejection of mean‐variance efficiency, tests involving the zero‐beta CAPM, particularly when a value‐weighted market index is used, prove less prone to rejection.

In this chapter we approach the estimation of dynamic stochastic general equilibrium models through a moments-based estimator, the empirical likelihood. We attempt to show that this inference process can be a valid alternative to maximum likelihood, which has been one of the preferred choices of the related literature to estimate these models. The empirical likelihood estimator is characterized by a simple setup and only requires knowledge about the moments of the data generating process of the model. In this context, we exploit the fact that these economies can be formulated as a set of moment conditions to infer on their parameters through this technique. For illustrational purposes, we consider a standard real business cycle model with a constant relative risk averse utility function and indivisible labor, driven by a normal technology shock.

The study aims to evaluate the influence of capital structure decisions and asset structure on firms' performance for East African listed nonfinancial firms.

The research is descriptive and employs secondary data from the East African capital markets' websites. The generalized method of moments approach is used to estimate the relationship due to its ability to account for endogeneity problems.

The result shows that capital structure decisions and asset structure strongly influence the firms' performance. When long-term debts, short-term debts and tangible fixed assets increase, the return on total assets increases. An increase in the total debt ratio raises the return on equity (ROE). However, the increase in long-term debt lowers the ROE.

The results will help investors and potential investors decide on a financing policy that maximizes performance. Likewise, governments and other policymakers review the capital markets' frameworks to attract institutional and individual investors to the markets for financial availability and to increase profitability.

The research provides evidence on the influence of capital structure decisions and asset structure on firms' performance. Furthermore, its results contribute to firms' financing policy formulation and the corporate finance literature.

This chapter analyzes the empirical relationship between the pricesetting/consumption behavior and the sources of persistence in inflation and output. First, a small-scale New-Keynesian model (NKM) is examined using the method of moment and maximum likelihood estimators with US data from 1960 to 2007. Then a formal test is used to compare the fit of two competing specifications in the New-Keynesian Phillips Curve (NKPC) and the IS equation, that is, backward- and forward-looking behavior. Accordingly, the inclusion of a lagged term in the NKPC and the IS equation improves the fit of the model while offsetting the influence of inherited and extrinsic persistence; it is shown that intrinsic persistence plays a major role in approximating inflation and output dynamics for the Great Inflation period. However, the null hypothesis cannot be rejected at the 5% level for the Great Moderation period, that is, the NKM with purely forward-looking behavior and its hybrid variant are equivalent. Monte Carlo experiments investigate the validity of chosen moment conditions and the finite sample properties of the chosen estimation methods. Finally, the empirical performance of the formal test is discussed along the lines of the Akaike's and the Bayesian information criterion.

The purpose of this paper is to investigate the influence of macroeconomic cyclical indicators and country governance on bank non-performing loans in African countries.

Data was collected from the 53 African countries covering 2005–2021. The paper develops an empirical model to examine the impact of country governance in reducing macroeconomic cycle-induced adverse effects on bank credit risk. This research estimates Random Effects models and the General Method of Moment to examine the link between microeconomic and governance factors on bank non-performing loans. Stata version 15.1 was used to conduct panel regression analysis.

The findings of the study revealed that the generalized method of moments findings contributes valuable insights into the persistence of NPLs over time and the specific effects of variables on NPL levels. The study findings highlight that the debt-to-GDP ratio, unemployment, regulatory quality, government effectiveness and inflation have significant relationships with NPLs, shedding light on their specific contributions to credit risk dynamics.

The focus on a specific set of determinants for NPLs, which may not capture all the factors that influence NPL levels. Thus, the study did not consider the impact of macroeconomic shocks, such as natural disasters or global economic crises, which can have a significant impact on NPLs.

Policymakers should prioritize maintaining sustainable debt levels, promoting employment growth and controlling inflation rates to mitigate credit risk and reduce nonperforming loans. Also, enhancing regulatory quality and government effectiveness is crucial in ensuring financial stability and minimizing non-performing loans in Africa.

This paper provides a new possible solution to minimise bank non-performing loans risk by examining interactions of country governance regarding the macroeconomic cycle behaviour.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0729

Presents the mathematical basis and some results, concerning the application of Haar's wavelets, as an expansion function, in the method of moments to solve electrostatic problems. Two applications regarding the evaluation of linear and surface charge densities were carried out: the first one on a finite straight wire, and the second one on a thin square plate. Some optimization techniques were used, whose main computational performance aspects are emphasized. Presents comparative results related to the use of Haar's wavelets and the conventional expansion functions.

In this paper, we consider the estimation of volatility parameters in the context of a linear regression where the disturbances follow a stochastic volatility (SV) model of order one with Gaussian log-volatility. The linear regression represents the conditional mean of the process and may have a fairly general form, including for example finite-order autoregressions. We provide a computationally simple two-step estimator available in closed form. Under general regularity conditions, we show that this two-step estimator is asymptotically normal. We study its statistical properties by simulation, compare it with alternative generalized method-of-moments (GMM) estimators, and present an application to the S&P composite index.