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This paper provides a selective survey of the panel macroeconometric techniques that focus on controlling the impact of “unobserved heterogeneity” across individuals and over time to obtain valid inference for “structures” that are common across individuals and over time. We consider issues of (i) estimating vector autoregressive models; (ii) testing of unit root or cointegration; (iii) statistical inference for dynamic simultaneous equations models; (iv) policy evaluation; and (v) aggregation and prediction.

The purpose of this paper is the development and the assessment of detailed and macro-modelling methodology approaches, suitable for the analysis of composite material bolted joints.

A benchmark single-lap, single-bolt composite joint configuration is investigated, in order to demonstrate the different joint analysis approaches which are applicable in advanced riveted/bolted parts of aeronautical structures. In particular, several joint macro-models, i.e. numerical and analytical ones, as well as a detailed three-dimensional FE solid joint representation, were developed and compared in terms of stiffness prediction, while they were validated using respective experimental results. In addition, the numerical macro-model is implemented in a full scale, multi-bolt fuselage panel in order to demonstrate its capability to efficiently predict the panel’s response under compressive loads.

Good correlation was observed between the majority of the models’ predictions and the relative experimental data regarding the lap joint configuration, while the simplified numerical macro-model showed some discrepancies due to the contact instabilities, which, however, may be accepted taking into account the remarkable solution time reductions. In the same manner, the FE macro-model illustrates sufficient accuracy in the prediction of the panel’s response, while, simultaneously, it maintains a low CPU time.

The present study is part of Nikolaos Perogamvros’ doctoral thesis, an original research work. There are very limited literature papers which include the development and the assessment of different efficient and detailed composite joint analysis approaches, regarding their accuracy and efficiency in the stiffness prediction of a composite bolted joint configuration, as well as on the prediction of a multi-bolt panel’s response.

Advances in Econometrics is a series of research volumes first published in 1982 by JAI Press. The authors present an update to the history of the Advances in Econometrics series. The initial history, published in 2012 for the 30th Anniversary Volume, describes key events in the history of the series and provides information about key authors and contributors to Advances in Econometrics. The authors update the original history and discuss significant changes that have occurred since 2012. These changes include the addition of five new Senior Co-Editors, seven new AIE Fellows, an expansion of the AIE conferences throughout the United States and abroad, and the increase in the number of citations for the series from 7,473 in 2012 to over 25,000 by 2022.

The most simple equivalent frame system with reduced degrees of freedom is proposed for handling multi‐story multi‐bay infilled frames. The system is composed of homogenized continuum for the reinforced concrete members braced with unilateral diagonal struts for each bay, which are only activated in compression. Identification of the equivalent system characteristics and nonlinear material properties are accomplished from the concepts of inverse analysis approach along with statistical tests of hypotheses is employed to establish the appropriate filtering scheme and the proper accuracy tolerance. The suggested system allows for nonlinear finite element static and dynamic analysis of sophisticated infilled reinforced concrete frames. Sensitivity analysis is undertaken to check the suitability of the proposed system to manipulate various structural applications.

Separately, nonlinear finite element analysis, artificial neural networks (ANNs) and continuous damage mechanics (CDM) attracted many investigators to model masonry infilled frames. The purpose of this paper is to pursue four phases to develop a versatile model for partially and fully low-rise infilled RC frames using these tools.

The first phase included the study of the behavior of 1,620 low-rise infilled reinforced concrete frames using macro-scale nonlinear pushover finite element analysis. The approach helped to explore the effects of imposing different masonry infill distributions for one of the typical models of school buildings in Egypt. The outputs of this phase were used in the second phase for the development of an ANN model where input neurons included number of stories, continuity conditions, frame geometry, infill distribution and properties of RC sections. The third phase included the employment of the notions of CDM on the structural scale. Monitoring frames’ stiffness degradation allowed for damage variables identification. In the fourth phase, the simpler equivalent static lateral load (ESLL) for elastic analysis was employed in conjunction with ANN and CDM to obtain the capacity curves for partially and fully low-rise infilled RC frames.

The obtained capacity curves were compared with the nonlinear finite element results. The close agreement of all curves indicated how rigorous, yet simple, the suggested solution procedure is.

The study is concerned with an important type of service buildings. These are the school buildings of Egypt.

The paper presents a combination of four phases that include FE analysis, ANNs, ESLL, and CDM to obtain the capacity curves for partially and fully low-rise infilled RC frames. Such a combination of approaches in tackling a practical problem related to service buildings is innovative and deserves research interest.

Reinforced concrete structural frames with masonry infills (infill-frames) are commonly used for construction worldwide. While the behavior of such frames has been studied extensively in the context of earthquake loading, studies related to their fire performance are limited. Therefore, this study aims to characterize the behavior of infill-frames under fire exposure by presenting a state-of-the-art literature review of the same.

Both experimental and computational studies have been included with a special emphasis on numerical modeling (simplified as well as advanced). The cold behavior of the infill-frame and its design requirements in case of fire exposure are first reviewed to set the context. Subsequently, the applicability of numerical modeling strategies developed for modeling cold infill-frames to simulate their behavior under fire is critically examined.

The major hurdles in developing generic numerical models for analyzing thermo-mechanical behavior of infill-frames are identified as: lack of temperature-dependent material properties, scarcity of experimental studies for validation and idealizations in coupling between thermal and structural analysis.

This study presents one of the most popular research problems connected with practical and reliable utilization of numerical models, as a good alternative to expensive traditional furnace testing, in assessing fire resistance of infill-frames. It highlights major challenges in thermo-mechanical modeling of infill-frames and critically reviews the available approaches for modeling infill-frames subjected to fire.

Following Ang and Piazzesi’s (2003) study, the authors use an affine term structure model to study the relevance of macroeconomic (domestic and foreign) factors for Peru’s sovereign yield curve in the period from November 2005 to December 2015. The paper aims to discuss this issue.

Risk premia are modeled as time-varying and depend on both observable and unobservable factors; and the authors estimate a vector autoregressive model considering no-arbitrage assumptions.

The authors find evidence that macro factors help to improve the fit of the model and explain a substantial amount of variation in bond yields. However, their influence is very sensitive to the specification model. Variance decompositions show that macro factors explain a significant share of the movements at the short and middle segments of the yield curve (up to 50 percent), while unobservable factors are the main drivers for most of the movements at the long end of the yield curve (up to 80 percent). Furthermore, the authors find that international markets are relevant for the determination of the risk premium in the short term. Higher uncertainty in international markets increases bond yields, although this effect vanishes quickly. Finally, the authors find that no-arbitrage restrictions with the incorporation of macro factors improve forecasts.

To the authors’ knowledge this is the first application of this type of models using data from an emerging country such as Peru.