A Heteroskedasticity Robust Breusch-Pagan Test for Contemporaneous Correlation in Dynamic Panel Data Models

This paper proposes a heteroskedasticity-robust Breusch–Pagan test of the null hypothesis of zero cross-section (or contemporaneous) correlation in linear panel data models, without necessarily assuming independence of the cross-sections. The procedure allows for either fixed, strictly exogenous and/or lagged dependent regressor variables, as well as quite general forms of both non-normality and heteroskedasticity in the error distribution. The asymptotic validity of the test procedure is predicated on the number of time series observations, T, being large relative to the number of cross-section units, N, in that: either (i) N is fixed as T→∞; or, (ii) N 2/T→0 as both T and N diverge, jointly, to infinity. Given this, it is not expected that asymptotic theory would necessarily provide an adequate guide to finite sample performance when T/N is “small”. Because of this we also propose, and establish asymptotic validity of, a number of wild bootstrap schemes designed to provide improved inference when T/N is small. Across a variety of experimental designs, a Monte Carlo study suggests that the predictions from asymptotic theory do, in fact, provide a good guide to the finite sample behaviour of the test when T is large relative to N. However, when T and N are of similar orders of magnitude, discrepancies between the nominal and empirical significance levels occur as predicted by the first-order asymptotic analysis. On the other hand, for all the experimental designs, the proposed wild bootstrap approximations do improve agreement between nominal and empirical significance levels, when T/N is small, with a recursive-design wild bootstrap scheme performing best, in general, and providing quite close agreement between the nominal and empirical significance levels of the test even when T and N are of similar size. Moreover, in comparison with the wild bootstrap “version” of the original Breusch–Pagan test (Godfrey and Yamagata, 2011) our experiments indicate that the corresponding version of the heteroskedasticity-robust Breusch–Pagan test appears reliable. As an illustration, the proposed tests are applied to a dynamic growth model for a panel of 20 OECD countries

The Human Blockage Impact on ARIS Assisted D2D Communication Systems

Aerial reconfigurable intelligent surface (ARIS), is an intelligent reflecting surface (IRS) mounted by unmanned aerial vehicle (UAV), represent a promising candidate for assisting device to device (D2D) millimeter wave (mmWave) communication in temporal and urgent situations, e.g., open-air events. IRS can efficiently mitigate the high blockage impact on mmWave propagation signal in base station to device use case. But, the scenario of D2D communication is different as both the transmitter (TX) to ARIS and the ARIS to receiver (RX) links are highly susceptible to be blocked due to the low height of the TX and RX. Consequently, in this paper, the impact of human bodies blockage on ARIS aided D2D mmWave communication is studied. Firstly, we assure the effectiveness of using ARIS in this network to significantly enhance its performance, then, the effect of ARIS height on the blockage occurrence and system performance is investigated to find out the optimum height. Our results proves that ARIS highly mitigates the blockage, reduces it by 85%, comparable to the case without it. Moreover, a high increase in system spectral efficiency, 1.2 bps/Hz, can be guaranteed, if ARIS is configured at optimum height

A heteroskedasticity robust Breusch-Pagan test for contemporaneous correlation in dynamic panel data models

Working paper dated August 16, 2011This paper proposes a heteroskedasticity-robust Breusch-Pagan test of the null hypothesis of zero cross-section (or contemporaneous) correlation in linear panel data models. The procedure allows for either xed, strictly exogenous and/or lagged de- pendent regressor variables, as well as quite general forms of both non-normality and heteroskedasticity in the error distribution. Whilst the asymptotic validity of the test procedure, under the null, is predicated on the number of time series observations, T, being large relative to the number of cross-section units, N, independence of the cross-sections is not assumed. Across a variety of experimental designs, a Monte Carlo study suggests that, in general (but not always), the predictions from asymptotic the- ory provide a good guide to the finite sample behaviour of the test. In particular, with skewed errors and/or when N=T is not small, discrepancies can occur. However, for all the experimental designs, any one of three asymptotically valid wild bootstrap approximations (that are considered in this paper) gives very close agreement between the nominal and empirical signi cance levels of the test. Moreover, in comparison with wild bootstrap version of the original Breusch-Pagan test (Godfrey and Yamagata, 2011) the corresponding version of the heteroskedasticity-robust Breusch-Pagan test is more reliable. As an illustration, the proposed tests are applied to a dynamic growth model for a panel of 20 OECD countries

Cloud Computing as Evolution of Distributed Computing – A Case Study for SlapOS Distributed Cloud Computing Platform

The cloud computing paradigm has been defined from several points of view, the main two directions being either as an evolution of the grid and distributed computing paradigm, or, on the contrary, as a disruptive revolution in the classical paradigms of operating systems, network layers and web applications. This paper presents a distributed cloud computing platform called SlapOS, which unifies technologies and communication protocols into a new technology model for offering any application as a service. Both cloud and distributed computing can be efficient methods for optimizing resources that are aggregated from a grid of standard PCs hosted in homes, offices and small data centers. The paper fills a gap in the existing distributed computing literature by providing a distributed cloud computing model which can be applied for deploying various applications

First-order asymptotic theory for parametric misspecification tests of Garch models

publication-status: Publishedtypes: ArticleFinal version of the article as published in Econometric Theory, vol. 35, issue 2, pp. 364-410. Copyright © Cambridge University Press 2009. Available online at http://journals.cambridge.org/This paper develops a framework for the construction and analysis of parametric misspecification tests for generalized autoregressive conditional heteroskedastic (GARCH) models, based on first-order asymptotic theory. The principal finding is that estimation effects from the correct specification of the conditional mean (regression) function can be asymptotically nonnegligible. This implies that certain procedures, such as the asymmetry tests of Engle and No. (1993, Journal of Finance 48. 1749-1777) and the nonlinearity test of Lundbergh and Terasvirta (2002, Journal of Econometrics 110, 417-435), are asymptotically invalid. A second contribution is the proposed use of alternative tests for asymmetry and/or nonlinearity that, it is conjectured, should enjoy improved power properties. A Monte Carlo study supports the principal theoretical findings and also suggests that the new tests have fairly good size and very good power properties when compared with the Engle and Ng (1993) and Lundbergh and Terasvirta (2002) procedures

Explaining UK Food Price Inflation. (Transparency of Food Pricing (TRANSFOP) Working Paper 1)

Retail food price inflation in the UK peaked at nearly 14% in the summer of 2008, a level much higher than had been seen in the previous 10 years and, since then, food price inflation has continued to lead general inflation. An obvious factor driving domestic retail food prices is world commodity prices, but other factors matter too. In this paper, we model UK food price inflation and explore a range of potential drivers including world food prices, exchange rates, manufacturing costs, oil prices and wages. Over the period 1990-2010, we show that the major drivers of UK food price inflation are world raw food prices and the exchange rate; less important are manufacturing costs, unemployment and earnings. Oil prices matter too but indirectly via their effect on world agricultural commodity prices. We also show that the effect on domestic retail food price inflation depends on the duration of the shocks arising on world commodity markets

Neglecting Structural Breaks when Estimating and Valuing Dynamic Correlations for Asset Allocation

This paper assesses the econometric and economic value consequences of neglecting structural breaks in dynamic correlation models and in the context of asset allocation framework. It is shown that changes in the parameters of the conditional correlation process can lead to biased estimates of persistence. Monte Carlo simulations reveal that short-run persistence is downward biased while long-run persistence is severely upward biased, leading to spurious high persistence of shocks to conditional correlation. An application to stock returns supports these results and concludes that neglecting such structural shifts could lead to misleading decisions on portfolio diversification, hedging, and risk management

RXs Directions based Codebook Solution for Passive RIS Beamforming

Recently, reconfigurable intelligent surface (RIS) has immensely been deployed to overcome blockage issue and widen coverage for enabling superior performance 6G networks. Mainly, systems use RIS as an assistant to redirect the transmitter (TX) incident signal towards the receiver (RX) by configuring RIS elements amplitudes and phase shifts in a passive beamforming (PBF) process. Channel estimation (CE) based PBF schemes achieve optimal performance, but they need high overhead and time consumption, especially with high number of RIS elements. Codebook (CB) based PBF solutions can be alternatives to overcome these issues by only searching through a limited reflection patterns (RPs) and determining the optimal one based on a predefined metric. However, they consume high power and time relevant to the used CB size. In this work, we propose a direction based PBF (D-PBF) scheme, where we aim to map between the RXs directions and the codebook RPs and store this information in an updated database (DB). Hence, if the matching between a coming RX and a particular RP exists, the proposed scheme will directly select this RP to configure the RIS elements, otherwise, it memorizes this codeword for future searching. Finally, if the matching failed, searching through the memorized RPs will be done to find the optimal one, then updating the DB accordingly. After a time period, which depends on the CB size, the DB will converge, and the D-PBF scheme will need no searching to select the optimal RP. Hence, the proposed scheme needs extremely lower overhead, power, and time comparable to the CE and conventional CB based solutions, while obtaining acceptable performance in terms of effective rate

Network slice allocation for 5G V2X networks: A case study from framework to implementation and performance assessment

Empowered by the capabilities provided by fifth generation (5G) mobile communication systems, vehicle-to-everything (V2X) communication is heading from concept to reality. Given the nature of high-mobility and high-density for vehicle transportation, how to satisfy the stringent and divergent requirements for V2X communications such as ultra-low latency and ultra-high reliable connectivity appears as an unprecedented challenging task for network operators. As an enabler to tackle this problem, network slicing provides a power tool for supporting V2X communications over 5G networks. In this paper, we propose a network resource allocation framework which deals with slice allocation considering the coexistence of V2X communications with multiple other types of services. The framework is implemented in Python and we evaluate the performance of our framework based on real-life network deployment datasets from a 5G operator. Through extensive simulations, we explore the benefits brought by network slicing in terms of achieved data rates for V2X, blocking probability, and handover ratio through different combinations of traffic types. We also reveal the importance of proper resource splitting for slicing among V2X and other types of services when network traffic load in an area of interest and quality of service of end users are taken into account.publishedVersionPaid open acces