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We analyze the sizes of standard cointegration tests applied to data subject to linear interpolation, discovering evidence of substantial size distortions induced by the interpolation. We propose modifications to these tests to effectively eliminate size distortions from such tests conducted on data interpolated from end-of-period sampled low-frequency series. Our results generally do not support linear interpolation when alternatives such as aggregation or mixed-frequency-modified tests are possible.

To contribute for a reliable estimation of the compressive strength of unreinforced masonry from the properties of the constituents (units and mortar).

Sophisticated non‐linear continuum models, based on damage, plasticity, cracking or other formulation, are today standard in several finite element programs. The adequacy of such models to provide reliable estimates of masonry compressive strength, from the properties of the constituents, remains unresolved. The authors have shown recently that continuum models might significantly overestimate the prediction of the compressive strength. Hence, an alternative phenomenological approach developed in a discrete framework is proposed, based on attributing to masonry components a fictitious micro‐structure composed of linear elastic particles separated by non‐linear interface elements. The model is discussed in detail and a comparison with experimental results and numerical results using a standard continuum model is provided.

Clear advantages in terms of compressive strength and peak strain prediction were found using the particle model when compared with standard continuum models. Moreover, compressive and tensile strength values provided by the model were found to be particle size‐ and particle distortion‐independent for practical purposes. It is also noted that size‐dependent responses were obtained and that shear parameters rather than tensile parameters were found to play a major role at the meso‐level of the phenomenological model.

This paper provides further insight into the compressive behaviour of quasi‐brittle materials, with an emphasis on the strength prediction of masonry composites. Reliable prediction of masonry strength is of great use in the civil engineering field, allowing one to reduce experimental testing in expensive wallets and to avoid the usage of conservative empirical formulae.

Measurement of diminishing or divergent cross section dispersion in a panel plays an important role in the assessment of convergence or divergence over time in key economic indicators. Econometric methods, known as weak σ-convergence tests, have recently been developed (Kong, Phillips, & Sul, 2019) to evaluate such trends in dispersion in panel data using simple linear trend regressions. To achieve generality in applications, these tests rely on heteroskedastic and autocorrelation consistent (HAC) variance estimates. The present chapter examines the behavior of these convergence tests when heteroskedastic and autocorrelation robust (HAR) variance estimates using fixed-b methods are employed instead of HAC estimates. Asymptotic theory for both HAC and HAR convergence tests is derived and numerical simulations are used to assess performance in null (no convergence) and alternative (convergence) cases. While the use of HAR statistics tends to reduce size distortion, as has been found in earlier analytic and numerical research, use of HAR estimates in nonparametric standardization leads to significant power differences asymptotically, which are reflected in finite sample performance in numerical exercises. The explanation is that weak σ-convergence tests rely on intentionally misspecified linear trend regression formulations of unknown trend decay functions that model convergence behavior rather than regressions with correctly specified trend decay functions. Some new results on the use of HAR inference with trending regressors are derived and an empirical application to assess diminishing variation in US State unemployment rates is included.

The purpose of this paper is to prepare Ti(C,N) coatings on TA15 treated and not treated by shot peening using double glow plasma alloying technique. The effect of shot peening on the wear behavior of Ti(C,N) coatings is discussed.

The Ti(C,N) coatings were prepared by double glow plasma alloying technique on two different TA15 substrate; one is shot peened and the other is not.

Ti(C,N) coating on SP-treated TA15 was thicker and denser, and the grain size was smaller compared with that on original TA15. Compared with the Ti(C,N) coating on original TA15, the wear resistance of that on SP-treated TA15 is improved. Ti(C,N) coating on SP-treated TA15 showed higher nanohardness and bearing capacity than that on original TA15.

For double glow plasma alloying technique, surface quality, surface activity and other factors will have influence on the thickness and density of the coating. The wear mechanisms of Ti(C,N) coating on original TA15 are serious abrasive wear and oxidation wear. However, the wear mechanism of Ti(C,N) coating on SP-treated TA15 is slightly oxidation wear.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2020-0283/

A misplaced reliance on value at risk (VaR) has been focused on in the media as one of the main reasons for the current financial crisis, and the recently published Turner Review by the UK Financial Services Authority concurs. The purpose of this paper is to present an introductory overview of VaR and its weaknesses which will be easily understood by non‐technical readers.

Simple numerical examples utilising real and simulated data are employed to reinforce the main arguments.

This paper explains that some of the main approaches employed by banks for computing VaR have serious weaknesses. These weaknesses have contributed to the current financial crisis.

Consistent with the introductory nature of this paper, the empirical research is limited to simple examples.

The evidence here suggest that if VaR is to play a major role under future financial regulation then research is required to develop improved estimation techniques and backtesting procedures.

This paper differs from many academic papers on VaR by assuming only a very basic knowledge of mathematics and statistics.

The purpose of this paper is to analyze the time‐inconsistency problem between inflation and unemployment rate series for Turkey.

The validity of the Barro‐Gordon model's implications is tested by using state‐space form and a Kalman filter. In order to investigate the long‐run effects of the time‐inconsistency problem, unit root and co‐integration tests are applied. First, a Hodrick‐Prescott filter is used to test the short‐run effects. Then the modified Barro‐Gordon model's constraint is applied to the detrended inflation and unemployment rate.

The results of this study suggest that both inflation and unemployment series are not stationary and they include the unit root, but that first differences of the two series are stationary. The co‐integration test results also do not support the Barro‐Gordon model's implications for the long‐run behavior of inflation and unemployment: the two variables are not cointegrated.

The results of this study suggest that the time‐inconsistency problem for Turkey can be valid in the short‐run, but sufficient proof cannot be found to support the Barro‐ Gordon model's implications for the long‐run.

Classical unit root tests are known to suffer from potentially crippling size distortions, and a range of procedures have been proposed to attenuate this problem, including the use of bootstrap procedures. It is also known that the estimating equation’s functional form can affect the outcome of the test, and various model selection procedures have been proposed to overcome this limitation. In this chapter, the authors adopt a model averaging procedure to deal with model uncertainty at the testing stage. In addition, the authors leverage an automatic model-free dependent bootstrap procedure where the null is imposed by simple differencing (the block length is automatically determined using recent developments for bootstrapping dependent processes). Monte Carlo simulations indicate that this approach exhibits the lowest size distortions among its peers in settings that confound existing approaches, while it has superior power relative to those peers whose size distortions do not preclude their general use. The proposed approach is fully automatic, and there are no nuisance parameters that have to be set by the user, which ought to appeal to practitioners.

In what seems as an infinitely ongoing debate regarding the purchasing power parity (PPP) theory, this paper seeks to question the strength of the scientific “evidence” put forward by the PPP revisionists

In this paper, the validity of the PPP revisionists' scientific evidence supporting long‐run PPP is questioned based on the replication of an influential review study that is considered by PPP revisionists to exhibit “some of the strongest evidence” in favour of the PPP theory.

By simulation experiments it is demonstrated that the traditional PPP unit root tests are non‐robust to the empirically identified (G)ARCH distortions. Due to (G)ARCH distortions, over‐rejections for the traditional unit root tests are shown to be a problem that potentially misleads researchers to believe that long‐run PPP holds under circumstances when it is in fact not valid. As a potential remedy to this problem, a new unit root test is introduced which is robust to conditional heteroscedasticity disturbances, and in contrast to traditional unit root tests, it exhibits no significant empirical support for the PPP theory.

The study illustrates that the PPP revisionists' unit root tests cannot reliably test the PPP hypothesis in the presence of (G)ARCH distortions, due to bad power and size properties. Perhaps it is time to conclude that, based on the currently existing research, it is virtually impossible to empirically come to a credible conclusion regarding whether long‐run PPP holds or not.