Aggregate Loss Research Articles

Copyright Protection in the Digital Single Market: Potential Consequences for Content Platform Competition

This paper scrutinizes the effects of the European Directive on Copyright in the Digital Single Market on platform competition. Platforms that are online content-sharing service providers must have a license agreement with collective management organizations that control the content platform that users may – or must not – upload to the platform. The paper shows that the new directive may imply market concentration and an aggregate welfare loss. The reason is that only users of the large platform (in a dual platform setting) will be allowed to upload content if the content assets are sufficiently valuable and if network effects are strong.

Copula Regression for Compound Distributions with Endogenous Covariates with Applications in Insurance Deductible Pricing

This article concerns deductible pricing in nonlife insurance contracts. The primary interest of insurers is the effect of the contract deductible on a policyholder’s aggregate loss that is determined by a compound distribution where the sum of individual claim amount is stopped by the number of claims. Policyholders choose the deductible level based on their hidden risks, which makes deductible endogenous in the regressions for both claim frequency and claim severity. To address the endogeneity in the regression for the compound aggregate loss, we introduce a novel approach using pair copula constructions to jointly model the policyholder’s deductible, number of claims, and individual claim amounts, in the context of compound distributions. The proposed method provides insurers an empirical tool to uncover the underlying risk distribution of the potential customers. In the application we consider an insurance portfolio from the property insurance program that provides property coverage for building and contents of local government entities of the Wisconsin. Using the historical data on policyholder and insurance claims, we first provide empirical evidence of the endogeneity of the deductible. Interestingly, we find that the policyholder’s deductible is negatively associated with the claim frequency but positively associated with the claim severity. For the portfolio of policyholders, the endogenous deductible model provides superior prediction for 65% and 71% of policyholders for claim frequency and severity, respectively. The endogeneity of deductible shows significant managerial implications on insurance operations. In particular, the risk score suggested by the proposed method allows the insurer to identify additional profitable underwriting strategies which are quantified by the Gini indices of 0.22 and 0.13 when switching from the exogenous deductible premium and the insurer’s contract premium, respectively. Supplementary materials for this article are available online.

Does Environmental Regulation Help Mitigate Factor Misallocation?-Theoretical Simulations Based on a Dynamic General Equilibrium Model and the Perspective of TFP.

How environmental regulation affects factor allocation is becoming an emerging hot topic in academia. In this paper, we construct a dynamic general equilibrium model accommodating environmental regulatory shock based on the H-K framework to explain the impact of environmental regulation on factor misallocation from the perspective of aggregate total factor productivity loss changes, and numerical simulation results are provided for several representative scenarios. The results show that environmental regulation has a significant effect on factor market misallocation, but this effect is not simply positive or negative, and it mainly depends on the firms’ initial factor allocation status and the intensity of the shock. Reducing the intensity of environmental regulation for firms that face stronger distortion helps mitigate factor misallocation and, on the contrary, the same policy could exacerbate factor market misallocation. Under the environmental regulatory shock condition, firms’ overhead labor input has a moderating effect on the factor allocation mitigation of environmental regulation. Distorted firms’ higher overhead labor share inhibits the correction of factor misallocation by environmental regulation. And reducing firms’ overhead labor share amplifies the correcting effect of environmental regulation on factor misallocation.

A two-stage model for high-risk prediction in insurance ratemaking: Asymptotics and inference

In actuarial practice, modern statistical methodologies are one primary consideration for real actuarial problems, such as premium calculation, insurance preservation, marginal risk analysis, etc. The claim data usually possesses a complex data structure, so direct applications of statistical techniques will result in unstable prediction. For example, insurance losses are semicontinuous variables, where a positive mass on zero is often associated with an otherwise positive continuous outcome. Thus, the prediction of high-risk events of claim data needs additional treatment to avoid significant underestimation. In this article, we propose a new two-stage composite quantile regression model for the prediction of the value-at-risks of the aggregate insurance losses. As we are interested in the statistical properties of our method, the asymptotic results are established corresponding to different types of risk levels. Finally, some simulation studies and a data analysis are implemented for the illustration of our method.

Hydraulic mechanisms of the uneven enrichment of soil organic carbon in sediments during rain-induced overland flow.

Organic carbon (OC) can be unevenly enriched in different-sized sediment particles under low-intensity, rain-induced overland flows, but its hydraulic mechanisms are not completely understood. Hence, in this study, the hydraulic transport mechanisms of unevenly enriched OC between different-sized sediment particles were investigated through simulated rainfall experiments at gradients of 5°, 10°, and 15° and typical regional rainfall intensities of 45, 90, and 120 mm h−1. Results showed that the critical flow velocity of aggregate transport through loess soil was approximately 0.08 m s−1. When the flow velocity was larger than this critical value, the aggregate loss amount increased quickly and exponentially. Flow velocities lower than 0.08 m s−1 were determined to be essential conditions for uneven OC enrichment between sediment particles. At such velocities, even when the runoff depth was greater than 0.0018 m, the enrichment ratio of soil organic carbon (SOC; ERoc) values in all size classes of sediment particles was larger than 1.0. Small runoff depths caused preferential OC enrichment in silt and clay, whereas large runoff depths promoted OC enrichment in the >0.25 mm size class of sediment particles. The critical flow velocity and transport way differ between these high-OC-concentration clay and silt and large light organic particles. The interaction between flow velocity and runoff depth on ERocs in <0.05 mm particles was larger than that of >0.05 mm particles. Under the transport limit erosion, the flow velocity and stream power positively correlated with uneven ERocs in different size sediment particles through distinct laws. Slope and rainfall intensity could not be ignored in predicting uneven OC enrichment in sediments by interacting with hydraulic factor and effecting aggregate stripping, respectively. Hydraulic factors mainly affected the uneven OC enrichment by controlling particle selective detachment and transport process. Owing to the different hydraulic mechanisms of OC enrichment in different size particles, the obtained regression functions for uneven OC enrichment could be divided into two types. One was for calculating the OC concentrations in sediment particles with sizes of <2 mm (R2 > 0.844, P < 0.005), and the other was for calculating the OC concentrations in large macroaggregates (>2 mm; R2 = 0.805, P < 0.005). The findings provide an important reference for understanding SOC transport mechanisms and its mineralization potential under the effect of water erosion and improving SOC dynamic models.

Welfare and Redistribution in Residential Electricity Markets with Solar Power

Abstract An increasing number of households installing solar panels and consuming the energy thus produced raises two challenges for regulators: network financing and vertical equity. We propose alternative tariff and subsidy designs for policymakers to incentivize solar panel adoptions and guarantee that network costs are recovered, while trading off efficiency, equity, and welfare motives. We estimate a structural model of energy demand and solar panel adoption, using a unique matched dataset on energy consumption, prices, income, wealth, solar panel installations, and building characteristics for 165,000 households in Switzerland from 2008 to 2014. Our counterfactuals recommend the optimal solar panel installation cost subsidies and two-part energy tariffs to achieve a solar energy target. We show that, relative to installation cost subsidies, relying on marginal prices to incentivize solar panel adoptions is more cost efficient and progressive across the income distribution, but generates a larger aggregate welfare loss.

Synoviolin inhibits the inflammatory cytokine secretion of Müller cells by reducing NLRP3.

The pro-inflammatory cytokines secreted by Müller cells aggregate retinal cell loss and vascularization in diabetic retinopathy (DR). The deubiquitinase BRCA1-BRCA2-containing complex subunit 3 (BRCC3)-mediated nucleotide-binding domain and leucine-rich repeat receptor containing a pyrin domain 3 (NLRP3) inflammasome activation participate in this progress. This study aims to clarify whether the E3 ubiquitin ligase synoviolin (SYVN1) relieves DR via regulating the BRCC3/NLRP3 axis. The DR model was established using streptozotocin-induced mice. Immunofluorescence staining with anti-CD31, anti-glutamine synthetase, and anti-vimentin was performed to identify DR and Müller cells. Levels of pro-inflammatory cytokines, including interleukin-1β, tumor necrosis factor-α, IL-6, and IL-18, in murine serum and Müller cell supernatants were determined. Co-immunoprecipitation (Co-IP) and ubiquitination assays were used to clarify the interactions among SYVN1, BRCC3, and NLRP3. SYVN1 was reduced and BRCC3 was increased in DR retina and high glucose (HG)-induced Müller cells. Overexpressing 1 promoted the ubiquitination and degradation of BRCC3 and reduced the secretion of proinflammatory cytokines in HG-induced Müller cells. The simultaneous overexpression of 1 and Brcc3 restored the reduction of pro-inflammatory cytokines caused by the overexpression of 1 alone. Co-IP experiments confirmed the interaction between BRCC3 and NLRP3. SYVN1-mediated BRCC3 downregulation promoted NLRP3 ubiquitination and reduced pro-inflammatory cytokine secretion. 1 overexpression reduced retinal vascularization and inflammatory cytokine secretion in DR mice. SYVN1 has a protective effect on DR, whose molecular mechanisms are partly through SYVN1-mediated ubiquitination of BRCC3 and the subsequent downregulation of NLRP3.

Arabidopsis Glutathione-S-Transferases GSTF11 and GSTU20 Function in Aliphatic Glucosinolate Biosynthesis.

Glutathione (GSH) conjugation with intermediates is required for the biosynthesis of glucosinolate (GSL) by serving as a sulfur supply. Glutathione-S-transferases (GSTs) primarily work on GSH conjugation, suggesting their involvement in GSL metabolism. Although several GSTs, including GSTF11 and GSTU20, have been recently postulated to act in GSL biosynthesis, molecular evidence is lacking. Here, we demonstrated that GSTF11 and GSTU20 play non-redundant, although partially overlapping, roles in aliphatic GSL biosynthesis. In addition, GSTU20 plays a more important role than GSTF11, which is manifested by the greater loss of aliphatic GSLs associated with GSTU20 mutant and a greater number of differentially expressed genes in GSTU20 mutant compared to GSTF11 mutant. Moreover, a double mutation leads to a greater aggregate loss of aliphatic GSLs, suggesting that GSTU20 and GSTF11 may function in GSL biosynthesis in a dosage-dependent manner. Together, our results provide direct evidence that GSTU20 and GSTF11 are critically involved in aliphatic GSL biosynthesis, filling the knowledge gap that has been speculated in recent decades.

Evaluating the thermal aging-induced raveling potential of thin friction course (TFC)

Thin friction course (TFC) mixed with open-graded aggregate ranging from 3 to 5 mm, styrene-butadiene rubber (SBR)-modified asphalt emulsion, and cement is constructed to improve the skid resistance of underlying pavements and reduce traffic noise. Considering the small thickness (approximately 5 mm) and open gradation of TFC, the mixture is exposed to environmental conditions over its entire thickness. Therefore, the TFC is vulnerable to aging-induced damage, such as aging-induced late raveling distress. This paper aims to determine the aging-induced raveling performance of TFCs, chemical composition transformation, and raveling-related rheological properties of asphalt emulsion residue via a wet track abrasion test (WTAT), transform infrared spectroscopy (FTIR), and a linear amplitude sweep (LAS) test, respectively. Finally, a correlation analysis was conducted. The results indicate that at the initial aging period, prolonging the aging duration could decrease the raveling potential of TFC. However, late raveling may occur when the TFC specimens are aged for 14d, and the aggregate loss increase with the aging duration. Similarly, the enhanced emulsion and SBR dosages are favorable to improve the raveling resistance of TFC and delay the late raveling of TFC. Regarding the chemical transformation, the existence of SBR latex decreases the aging degree. Furthermore, according to the LAS test, the increased SBR latex contents may improve the fatigue resistance of asphalt emulsion residue owing to the spot-welding effects. Finally, the aging degree index SI correlates well with the raveling potential of TFC with a correlation coefficient of 0.71. Typically, the higher the aging degree of asphalt emulsion, the lower the raveling potential of TFC; the greater the fatigue resistance of asphalt emulsion, the lower the raveling potential of TFC.

Phase Type Zero Truncated Poisson Lindley Distributions and their application in modeling Secondary Cancer Cases

Insurance of chronic illness is slowly gaining ground in Kenya which has lead to insurance firms introducing insurance products of chronic illness among them being cancer insurance policies. However, unlike other chronic illnesses, cancer can move from the organ of origin to another which will consequently lead to increased cost of treatment. This can not be modeled using ordinary distributions hence it has become an area of interest for many researchers. Zero-truncated phase type distributions are used to solve this drawback of ordinary distributions as it can in-cooperate these transitions while modeling claim count data. They further improve modeling of claim count data as they only consider positive values of claim count excluding zeros. This is the nature of real claim count data as zero claim frequency can not attract any claim severity amount. In this paper aggregate claim losses of secondary cancers in Kenya are estimated using Zero-truncated Poisson Lindley distributions. Zero-truncated one parameter as well as Zero-truncated two parameter Poisson Lindley distributions are derived. Their compound probability generating functions are also constructed. The transitions states of secondary cancer states are estimated using continuous Chapman Kolmogorov equation and used as the matrix parameters for the claim count distributions. Pareto, Generalized Pareto, Weibull, OPPL and TPPL distributions are the distributions considered in this research in modeling claim numbers. This study concludes that aggregate losses of secondary cancer cases using Kenyan data are best modeled by PH-ZTOPPL Generalized Pareto model for PH-ZTOPPL distribution models while for PH-ZTTPPL distribution models the best model was PH-ZTTPPL-Generalized Pareto model. The two best models were compared and PH-ZTTPPL-Generalized Pareto model was proven to be the best model. Comparing this model with PH-TPPL Generalized Pareto model from earlier research PH-TPPL Generalized Pareto model proved to be a better model implying that zero claim count data should be considered in estimation of aggregate losses

Exact Insurance Premiums for Cyber Risk of Small and Medium-Sized Enterprises

As cyber attacks have become more frequent, cyber insurance premiums have increased, resulting in the need for better modeling of cyber risk. Toward this direction, Jevtić and Lanchier [Insur. Math. Econ. 91 (2020) 209–223] proposed a dynamic structural model of aggregate loss distribution for cyber risk of small and medium-sized enterprises under the assumption of a tree-based local-area-network topology that consists of the combination of a Poisson process, homogeneous random trees, bond percolation processes, and cost topology. Their model assumes that the contagion spreads through the edges of the network with the same fixed probability in both directions, thus overlooking a dynamic cyber security environment implemented in most networks, and their results give an exact expression for the mean of the aggregate loss but only a rough upper bound for the variance. In this paper, we consider a bidirectional version of their percolation model in which the contagion spreads through the edges of the network with a certain probability of moving toward the lower level assets of the network but with another probability of moving toward the higher level assets of the network, which results in a more realistic cyber security environment. In addition, our mathematical approach is quite different and leads to exact expressions for both the mean and the variance of the aggregate loss, and therefore an exact expression for the insurance premiums.

Impact of COVID-19 on the US and Texas Economy: A General Equilibrium Approach

This paper examines the impact of COVID-19 on the US and Texas economy using a computable general equilibrium model, REMI PI+. We consider three scenarios based on economic forecasts from various sources, including the University of Michigan’s RSQE (Research Seminar in Quantitative Economics), IMF, and the Wi orld Bank. We report a GDP loss of $106 million (a 6% decline) with 1.2 million jobs lost (6.6%) in Texas in 2020. At the national level, GDP loss is $996 billion (a 5% decline) with 11.5 million jobs lost (5.5%) in the same year. By 2026, the aggregate total GDP loss in Texas ranges from $378 to $629 million. The estimated unemployment rate in Texas in 2021 ranges from 5% to 7.7%, depending on modeling assumptions. The granularity of the CGE results allow examination of the most and least impacted industries. Health Care and Social Assistance, Construction, and Accommodation and Food Services incur the most job loss while State and Local Government and Farm will likely see an increase in jobs for 2020. These insights separate our work from most current impact studies.

Suitability Assessment of Construction and Demolition Waste as a Highway Material

For Being a developing country urbanization is growing rapidly in Bangladesh and there has been a significant increase in the construction of roads. But due to lack of financial aid many of the roads are still unsealed. However, not only the utilization of Construction and Demolition Waste (CDW) in flexible pavement will be helpful for the reduction of road construction costs but also it will help to reduce environmental pollution which may be caused by disposing CDW in open area. The objective of this research is to utilize the CDW in base and sub base layers in the flexible pavement design to reduce the cost of road construction and environmental pollution. Proceeding by collecting CDW like brick from demolished building and conventional brick from kiln, a no of standard test conducted in laboratory namely Aggregate Impact Value, Crushing Value, Specific Gravity, Water Absorption and Loss Angeles Abrasion Test for three times. After analyzing the test results, we found that the average Aggregate Impact Value for CDW and Conventional Aggregate (CA) are respectively 29.52% and 23.87%, Aggregate Crushing value for CDW and CA are respectively 28.10% and 22.88%, Los Angeles Abrasion value for CDW and CA are respectively 31.47% and 28.52%, specific gravity value for CDW and CA both is 1.75, water absorption for CDW and CA are respectively 7.62% and 12.23%. After analyzing the test results and comparing with the standard value, we figure out that the CDW are useful for using base and sub base layers in the flexible pavement.

Determination of Farming Business Insurance Premium Prices with the Variance Premium Principle and Standard Deviation Premium Principle Methods

The agricultural sector is one of the most important economic sectors in Indonesia, however, agricultural business can also pose a risk of loss resulting in a decrease in agricultural production. This is caused by several factors such as plant pests, weeds, and rainfall. Therefore it is necessary to make an effort to reduce the risk of losses that occur, one of which is by implementing an insurance policy. The risk experienced by farmers is assumed to be a random variable that has a certain distribution. So that the calculation of this risk is related to the probability model, one of which is the aggregate loss model. Then applied the principle of variance premium, and standard deviation premium to calculate the amount of insurance premiums. The amount of premium generated for each of these principles is 2,396,277 and 2,012,839. So it can be said that with the same risk, the standard deviation premium principle produces a premium price that is more economical than the variance premium principle. So that if this principle is applied, farmers will benefit more if they insure their agricultural businesses.

ANALYSIS OF EXPERIENCE IN THE APPLICATION OF MISSILE LAUNCH DETECTION SYSTEMS

Analysis of combat losses of aircraft in local armed conflicts in recent decades shows that most cases of aircraft hits are related to the impact of guided surface-to-air and air-to-air missiles equipped with homing warheads.&#x0D; The use of modern guided missiles equipped with homing warheads is one of the main threats to aircraft of various types. This is due to the fact that modern guided missiles are characterized by high speed, maneuverability, accuracy of aiming and difficulty of detection.&#x0D; Solving the problem of protecting aircraft from guided missiles consists of several stages: detection of missile launch; confirmation that the detected missile is heading directly toward the protected object; missile identification and decision-making on the most effective countermeasure system employment.&#x0D; At present, there are no missile launch detection systems that guarantee a 100% probability of threat detection, but an analysis of aviation combat losses in local armed conflicts in recent decades convincingly shows that the number of combat losses of aircraft equipped with such systems is much lower than those in which missile launch detection is carried out visually. For example, most of the Soviet Union's losses during the war in Afghanistan and the United States‟ losses during Operation “Desert Storm” in Iraq were related to the use of portable anti-aircraft missile systems, which missiles were equipped with infrared homing warheads. Realizing the scale of the threat posed by such missiles, most of the world's leading countries have significantly increased the expenses on development new or improvement existing countermeasures. As a result, the aggregate losses of coalition forces in Iraq, Afghanistan and Syria since 2001 clearly suggest that these costs have paid off, with losses from the use of portable anti-aircraft missile systems significantly reduced, while the total number of combat sorties increased.&#x0D; Therefore, in the face of all the challenges and threats posed to Ukraine due to the aggressive actions of the Russian Federation, conducting research in the interests of aviation of the Armed Forces of Ukraine to improve the effectiveness of missile detection systems for ensuring timely detection of threats, warning of aircraft crew and activation in the automatic mode the means of countermeasures is as relevant as ever.

PROBABILISTIC FRAMEWORK FOR LOSS DISTRIBUTION OF SMART CONTRACT RISK

Smart contract risk can be defined as a financial risk of loss due to cyber attacks on or contagious failures of smart contracts. Its quantification is of paramount importance to technology platform providers as well as companies and individuals when considering the deployment of this new technology. That is why, as our primary contribution, we propose a structural framework of aggregate loss distribution for smart contract risk under the assumption of a tree-stars graph topology representing the network of interactions among smart contracts and their users. To our knowledge, there exist no theoretical frameworks or models of an aggregate loss distribution for smart contracts in this setting. To achieve our goal, we contextualize the problem in the probabilistic graph-theoretical framework using bond percolation models. We assume that the smart contract network topology is represented by a random tree graph of finite size, and that each smart contract is the center of a random star graph whose leaves represent the users of the smart contract. We allow for heterogeneous loss topology superimposed on this smart contract and user topology and provide analytical results and instructive numerical examples.

The determination of the aggregate loss distribution through the numerical inverse of the characteristic function using the trapezoidal quadrature rule

Aggregate loss is the total loss suffered by an insured in a certain period. The aggregate loss depends on the claim frequency and the amount of the claim each time the insured makes a claim. The distribution of aggregate losses must be known to calculate motor vehicle insurance premiums. In general, there are two methods that can be used in determining the distribution of aggregate losses, namely exact and numerical. When an exact solution is difficult to find, numerical methods such as Monte Carlo, Panjer Recursion, and Fast Fourier Transform can be used. This research will discuss the determination of the distribution of aggregate losses through the numerical inverse of the characteristic function using the trapezoidal quadrature rule, on the data of motor vehicle insurance category 7 in Indonesia. The estimated cumulative distribution function for the largest aggregate loss is 0.999993. When x=0, it means that if someone does not file a claim, the estimated value of the cumulative distribution function is 0.9293. This value is close to the percentage of the number of insured, which is 0.9241.

Penerapan Metode Limited-Fluctuation Credibility dalam Menentukan Premi Murni pada Asuransi Kendaraan Bermotor di PT XYZ

&lt;p&gt;&lt;strong&gt;Abstract. &lt;/strong&gt;This paper discusses the method of limited-fluctuation credibility, also known as classic credibility. Credibility theory is a technique for predicting future premium rates based on past experience data. Limited fluctuation credibility consists of two credibility, namely full credibility if Z = 1 and partial credibility if Z &amp;lt;1. Full credibility is achieved if the amount of recent data is sufficient for prediction, whereas if the latest data is insufficient then the partial credibility approach is used. Calculations for full and partial credibility standards are used for loss measures such as frequency of claims, size of claims, aggregate losses and net premiums. The data used in this paper is secondary data recorded by the company PT. XYZ in 2014. This data contains data on the frequency of claims and the size of the policyholder's partial loss claims for motor vehicle insurance products category 4 areas 1. Based on the results of the application, the prediction of pure premiums for 2015 cannot be fully based on insurance data for 2014 because the credibility factor value is less than 1. So based on the limited-fluctuation credibility method, the prediction of pure premiums for 2015 must be based on manual values for pure premiums as well as insurance data for 2014. If manual values for pure premium is 2,000,000 rupiah, then the prediction of pure premium for 2015 is 1,849,342 rupiah.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords&lt;/strong&gt;&lt;strong&gt;: &lt;/strong&gt;limited fluctuation credibility, full credibility, partial credibility and partial loss&lt;/p&gt;

The Impact of COVID-19 on the Household Economy of India.

COVID-19 has disrupted the Indian economy. Government-enforced lockdown to restrict the spread of infection has impacted the household economy in particular. We combine aggregates from national income accounts and estimates from the microdata of a labour force survey covering more than 0.1 million households and 0.4 million individuals. The aggregate daily loss to households is USD 2.42 billion. While loss to earnings accounts for 72% of the total, the rest 28% is wage loss. Service-based activities account for two thirds of wage loss, and natural resource-based activities are responsible for most of the earning loss. The dominance of informal job contracts and job switching in labour markets intensifies this, with the most vulnerable group consisting of 57.8 million in casual engagement, who have a high degree of transition from one stream of employment to another on a daily basis. Supplementary InformationThe online version contains supplementary material available at 10.1007/s41027-021-00352-8.

Determination of Friction Performance of High Friction Surface Treatment Based on Alternative Macrotexture Metric.

Surface friction is currently the most common metric for evaluating the performance of high friction surface treatment (HFST). However, friction test methods such as the locked wheel skid tester (LWST) commonly provide a spot measurement. Large variations may arise in the LWST testing on curves. Based on 21 actual HFST projects, a study was performed to use a macrotexture metric, i.e., the mean profile depth (MPD) to evaluate HFST’s performance and improve its quality control (QC)/quality assurance (QA) procedures. The material properties were presented to understand the aspects of HFST. The method for calculating MPD was modified to account for the variations of macrotexture measurements. A vehicle-based test system was utilized to measure MPD periodically over an 18-month period since HFST installation. Statistical analysis was performed on the MPD measurements to identify the effects of influencing factors. Compared with the friction from LWST, MPD was equally effective in evaluating HFST performance. However, the use of MPD eliminated the errors as arisen in LWST testing and made it possible to detect surface distresses, including aggregate loss, delamination, and cracking. The expected overall MPD may be calculated by combining the MPD measurements made three months after installation at different HFST sites and used as a metric for evaluating HFST performance and QC/QA.