Benchmark Specifications Research Articles

Vintage by vine interactions most strongly influence Pinot noir grape composition in New Zealand

Vine genetics, fruit maturity, region and vineyard are perceived as factors that strongly influence Pinot noir grape and wine composition. Our study aims to understand the relationship between grape (and ultimately wine) composition and the physical appearance and performance characteristics of a vine (i.e. vine ideotype). Our experimental approach controlled these variables by studying within-block differences in vine performance across multiple seasons and vineyards. Grapes were sourced at commercial harvest from 20 single vines from 12 vineyard sites in three Pinot noir growing regions (Central Otago, Martinborough and Marlborough) of New Zealand.Across three vintages yields ranged from 0.1 kg to 6.3 kg per metre, but there was no general relationship between yield and berry soluble solids. On a vine by vine basis normalised yields did not correlate among seasons. Berry extract colour measures were, on average, three-fold higher in 2019 than in 2018.Principal Component Analysis has indicated that vintage dominated berry composition effects that might otherwise be associated with yield per vine, region and vineyard. The extent of the variation in performance of the same vines between seasons largely excludes factors that are stable between seasons as primary causes. Changes in management of the same vine from year to year appeared the most likely contributors to variation. We have derived highly significant negative linear relationships between vine yield class and the frequency of vines that were within a benchmark specification established for icon vines, providing evidence of the quality risk associated with higher yield. The results also indicate that a proportion of vines meet the benchmark specification at higher yields. From results to date we can further our research confident in the knowledge that factors such as vine yield, region or vineyard are, in themselves, unlikely to be the principal drivers of major differences in Pinot noir grape and wine composition.

THE AGGREGATE AND LOCAL ECONOMIC EFFECTS OF GOVERNMENT FINANCED HEALTH CARE

Government‐financed health care expenditures, through Medicare and Medicaid, have grown from roughly 0% to over 7.6% of national personal income over the past 50 years. This paper investigates the stimulative effects of Medicare spending. Using an annual, state‐level panel, we regress state income growth on own‐state spending and spending in other states, instrumented by unanticipated shocks to aggregate Medicare spending, to estimate local and spillover effects. In our benchmark specification, the own‐spending multiplier equals 1.3 and the spillover multiplier equals 0.4. The total Medicare spending multiplier (i.e., local plus spillover) is approximately 1.7. (JEL E32, E62, H51)

How and When to Use the Political Cycle to Identify Advertising Effects

A central challenge in estimating the causal effect of TV advertising on demand is isolating quasi-random variation in advertising. Political advertising, which topped $14 billion in expenditures in 2016, has been proposed as a plausible source of such variation and thus a candidate for an instrumental variable. We provide a critical evaluation of how and where this instrument is valid and useful across categories. We characterize the conditions under which political cycles theoretically identify the causal effect of TV advertising on demand, highlight threats to the exclusion restriction and monotonicity condition, and suggest a specification to address the most serious concerns. We test the strength of the first stage category-by-category for 274 product categories. For most categories, weak-instrument robust inference is recommended, as first-stage F-statistics are less than 10 for 221 of 274 product categories in our benchmark specification. The largest first-stage F-statistics occur in categories that typically advertise locally, such as automobile dealerships and restaurants. Failure to use the suggested specification leads to results that suggest violations of exclusion and monotonicity in a significant number of categories. Finally, we conduct a case study of the auto industry. Despite a very strong first stage, the IV estimate for this category is imprecise. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Realized Variance Modeling: Decoupling Forecasting from Estimation*

Abstract This article evaluates the in-sample fit and out-of-sample forecasts of various combinations of realized variance models and functions delivering estimates (estimation criteria). Our empirical findings highlight that: independently of the econometrician’s forecasting loss (FL) function, certain estimation criteria perform significantly better than others; the simple ARMA modeling of the log realized variance generates superior forecasts than the Heterogeneous Autoregressive (HAR) family, for any of the FL functions considered; the (2, 1) parameterizations with negative lag-2 coefficient emerge as the benchmark specifications generating the best forecasts and approximating long-range dependence as does the HAR family.

Richard Cantillon’s stabilizing market dynamics

ABSTRACT1 We consider a dynamic input output model that represents important aspects of Richard Cantillon’s discussion of economic structure and market dynamics. Merchants and inventories determine prices that diverge from (longer run) equilibrium. We contrast this stable formulation of price determination with an unstable benchmark specification in which variations in mercantile inventories play no role. Appreciated the stabilising properties of classical dynamics but did not isolate the influence of inventory behaviour. We briefly consider the role of inventories in macroeconomics, and note that balance sheet effects have rendered credit dislocations considerably more persistent than they were in Cantillon’s day.

On the macro-drivers of realized volatility: the destabilizing impact of UK policy uncertainty across Europe

ABSTRACTThis paper studies the bivariate HEAVY system of daily and intra-daily volatility equations and its macro-augmented asymmetric power extension. We focus on economic drivers that exacerbate stock market volatility and can be proved to be major threats for financial stability. Our study proves the inflammatory effects of UK Policy Uncertainty alongside global credit and commodity factors that spread across European financial markets. This UK-led spillover phenomenon should be considered by world market participants and recognized, monitored and mitigated by policymakers amid the Brexit fears and the associated highly probable harm for Europe. Other findings are as follows. First, once we allow for power transformations, asymmetries, and macro-effects in the benchmark specification, it is found that both powered conditional variances are significantly affected by the powers of squared negative returns and realized measure, further improving the HEAVY framework's forecasting accuracy. Second, the structural breaks applied to the bivariate system capture the time-varying behavior of the parameters, in particular during the global financial crisis of 2007/08. Third, higher UK uncertainty levels increase the leverage and global macro-effects from credit and commodity markets on all European stock markets' realized volatilities.

Contributions to integral nuclear data in ICSBEP and IRPhEP since ND2016

The contributions to the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and the International Reactor Physics Experiment Evaluation Project (IRPhEP) was last presented to the international nuclear data community at ND2016. Since ND2016, integral benchmark data that are available for nuclear data testing has continued to increase. The 2018 edition of the International Handbook of Evaluated Criti-cality Safety Benchmark Experiments (ICSBEP Handbook) now contains 574 evaluations with benchmark specifications for 4,916 critical, near-critical, or subcritical configurations, 45 criticality alarm placement/shielding configuration with multiple dose points apiece, and 215 configurations that have been categorized as fundamental physics measurements that are relevant to criticality safety applications. The 2018 edition of the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP Handbook) contains data from 159 different experimental series that were performed at 54 different nuclear facilities. Currently 156 of the 159 evaluations are published as approved benchmarks with the remaining three evaluations published as drafts. Measurements found in the IRPhEP Handbook include criticality, buckling and extrapolation length, spectral characteristics, reactivity effects, reactivity coefficients, kinetics, reaction-rate distributions, power distributions, isotopic compositions, and/or other miscellaneous types of measurements for various types of reactor systems. Additional benchmark evaluations will be included in the 2019 editions of these handbooks. These handbooks continue to represent the standard for neutronics benchmark experiment evaluation.

Adapting TPC-C benchmark to measure performance of multi-document transactions in MongoDB

MongoDB is a popular distributed database that supports replication, horizontal partitioning (sharding), a flexible document schema and ACID guarantees on the document level. While it is generally grouped with "NoSQL" databases, MongoDB provides many features similar to those of traditional RDBMS such as secondary indexes, an ad hoc query language, support for complex aggregations, and new as of version 4.0 multi-statement, multi-document ACID transactions. We looked for a well understood OLTP workload benchmark to use in our own system performance test suite to establish a baseline of transaction performance to enable flagging performance regressions, as well as improvements as we continue to add new functionality. While there exist many published and widely used benchmarks for RDBMS OLTP workloads, there are none specifically for document databases. This paper describes the process of adapting an existing traditional RDBMS benchmark to MongoDB query language and transaction semantics to allow measuring transaction performance. We chose to adapt the TPC-C benchmark even though it assumes a relational database schema and SQL, hence extensive changes had to be made to stay consistent with MongoDB best practices. Our goal did not include creating official TPC-C certifiable results, however, every attempt was made to stay consistent with the spirit of the original benchmark specification as well as to be compliant to all specification requirements where possible. We discovered that following best practices for document schema design achieves better performance than using required normalized schema. All the source code used and validation scripts are published in github to allow the reader to recreate and verify our results.

Analysis of the BEAVRS PWR benchmark using SCALE and PARCS

Abstract This paper presents an analysis of the Benchmark for Evaluation And Validation of Reactor Simulations (BEAVRS) performed using SCALE 6.1.2 and PARCS 3.2 computer codes. The benchmark specification contains a detailed design, operational data and measurements for a real 4-loop Westinghouse pressurized water reactor (PWR). The lattice physics simulations were prepared using TRITON depletion sequence and NEWT neutron transport solver (SCALE package). The 238-neutron group library based on evaluated nuclear data file – ENDF/B-VII nuclear data libraries was applied. A set of branch and burnup calculations was prepared, and group constants in the form of PMAXS files were generated with GenPMAXS. The full-core models were prepared using the PARCS nodal-diffusion core simulator. The PMAXS libraries were used with PARCS to investigate the core operation. The hot zero power measurement data, including control rod worths and critical boron concentrations, were compared using simulations, and satisfactory results were achieved. The first fuel cycle was simulated, and acceptable agreement with boron letdown curve and measurements were obtained. Finally, conclusions and recommendations for future research were presented.

An Online Testing Scheme for Detection of Gate Faults in ESOP-Based Reversible Circuit

In the present era of computation, reversible computing has emerged as promising computing paradigm before the research community. Consequently, efficient design of reversible circuit has received immense attention in design industry. But not only the cost efficient designs get the priority but developing methodologies for testing of such circuit bear high value. Emphasizing on this need, in this work, we have introduced an online testing scheme for indentifying two major gate faults—missing-gate fault and appearance fault in ESOP-based reversible designs. In the testing process, initially, the selected input function is transformed to its corresponding testable circuit in which additional gates and lines (ancillary lines) are appended in the primary design. Next, we generate fault-specific test vectors which later are executed over the circuit for identifying the possible faults present in the design. This approach has been successfully tested on a wide spectrum of benchmark specifications to ascertain its functional correctness, and the computed results are tabulated at the end of the article. Comparison with existing testing algorithms is given in the result tables, and a substantial improvement over reported work’s results is projected in those result sets.

Robust optimization of forecast combinations

We develop a methodology for constructing robust combinations of time series forecast models which improve upon a given benchmark specification for all symmetric and convex loss functions. Under standard regularity conditions, the optimal forecast combination asymptotically almost surely dominates the benchmark, and also optimizes the chosen goal function. The optimum in a given sample can be found by solving a convex optimization problem. An application to the forecasting of changes in the S&P 500 volatility index shows that robust optimized combinations improve significantly upon the out-of-sample forecasting accuracy of both simple averaging and unrestricted optimization.

Domestic value chains as stepping stones to global value chain integration

AbstractIdentifying the determinants of global value chain (GVC) integration is essential to understand the past expansion and current slowdown in GVCs. In this paper, we study the role of domestic value chains (DVCs) for GVC integration. In the presence of industry‐specific fixed costs of fragmenting production and of switching across input suppliers, DVCs can either be stepping stones or stumbling blocks for subsequent GVC entry. Focusing on backward linkages, that is, the sourcing of intermediates, we provide robust empirical evidence in favour of the stepping‐stone hypothesis. In our benchmark specification, a one standard deviation increase in DVC integration raises subsequent GVC integration by about 0.4%. To identify the mechanisms at work, we exploit two dimensions of industry‐level heterogeneity: product differentiation (a proxy of fragmentation costs) and relationship specificity (a proxy of the costs of switching between suppliers). We find that DVC integration is less conducive to GVC integration in industries that are characterised by relatively high switching costs and relatively low fragmentation costs.

ALLEGRO Gas-cooled Fast Reactor (GFR) demonstrator thermal hydraulic benchmark

The European gas cooled fast reactor (GFR) demonstrator, ALLEGRO, is currently being developed by Czech Republic, France, Hungary, Slovakia and Poland. The primary aim of ALLEGRO is to demonstrate the helium-cooled fast reactor technology and to test the new ceramic refractory fuel of the industrial version of the gas-cooled fast reactor, which has an envisaged thermal power of 2400 MW. The development of ALLEGRO highly relies on Thermal Hydraulic (TH) codes which were primarily developed for two-phase flow modelling of pressurized and boiling water reactors, and which are currently being adapted for new generation reactors using gas or liquid metal coolant. In this paper we present CATHARE2, RELAP5-3D and MELCOR code to code benchmark carried out for the 75 MWth ALLEGRO reactor. During our work, first an ALLEGRO database for TH analyses was elaborated based on previous European projects. In the second step a detailed TH benchmark specification was prepared in order to help the TH model development as a third step. Fourthly, each participant calculated their own steady states and subsequently we identified several model distortions. In the final step we carried out transient calculations for 3-inch Loss Of Coolant Accident (LOCA) and total Station Blackout (SBO) initiating events. In general, the results show that there is a good agreement in the simulation results of the different codes, but further experimental code validations are proposed using helium-cooled experimental facilities, namely the S-ALLEGRO being built in Czech Republic and the STU (Slovak University of Technology) loop operated in Slovakia.

Equilibrium Asset Pricing with Transaction Costs

We study risk-sharing economies where heterogenous agents trade subject to quadratic transaction costs. The corresponding equilibrium asset prices and trading strategies are characterised by a system of nonlinear, fully-coupled forward-backward stochastic differential equations. We show that a unique solution generally exists provided that the agents' preferences are sufficiently similar. In a benchmark specification with linear state dynamics, the illiquidity discounts and liquidity premia observed empirically correspond to a positive relationship between transaction costs and volatility.

Stator Design and Performance of Superconducting Motors for Aerospace Electric Propulsion Systems

Hybrid electric propulsion has been identified as a potential solution to the ambitious environmental emissions and noise targets of the aerospace industry. Superconducting machines may be the key component of that topology enabling the high power densities and efficiencies needed in aerospace. Fully superconducting machines, however, are not a mature technology. This paper looks at the different machine design configurations focusing on the stator magnetic circuit of a fully superconducting motor. The motor has been designed for an aerospace distributed fan propulsion motor with an aerospace benchmark specification of 1 MW. The AC fully superconducting machine includes superconducting bulk magnets mounted on a conventional rotor core and an MgB2 superconducting wire wound stator. The AC losses in the stator winding are particularly sensitive to exposure to the main rotor field so different screening solutions were used to shield the superconducting windings from the rotor field. The effectiveness of the screening techniques for the stator coils and the impact on the machine performance and weight were evaluated for different stator designs, such as full stator core and air core with and without flux diverters. Various combinations of pole numbers, diverter geometries, and magnetic materials have been checked. Results show that there is a tradeoff between stator iron losses and superconducting losses.

Exploration of language specifications by compilation to first-order logic

Exploration of language specifications helps to discover errors and inconsistencies early during the development of a programming language. We propose exploration of language specifications via application of existing automated first-order theorem provers (ATPs). To this end, we translate language specifications and exploration tasks to first-order logic, which many ATPs accept as input. However, there are several different strategies for compiling a language specification to first-order logic, and even small variations in the translation may have a large impact on the time it takes ATPs to find proofs. In this paper, we first present a systematic empirical study on how to best compile language specifications to first-order logic such that existing ATPs can solve typical exploration tasks efficiently. We have developed a compiler product line that implements 36 different compilation strategies and used it to feed language specifications to 4 existing first-order theorem provers. As benchmarks, we developed language specifications for typed SQL and for a Questionnaire Language (QL), with 50 exploration goals each. Our study empirically confirms that the choice of a compilation strategy greatly influences prover performance in general and shows which strategies are advantageous for prover performance. Second, we extend our empirical study with 4 domain-specific strategies for axiom selection and find that axiom selection does not influence prover performance in our benchmark specifications.

Re‐Examining the Role of Structural Change and Nonlinearities in a Phillips Curve Model for South Africa

AbstractAlthough studies generally find evidence of a Phillips curve‐type relationship in South Africa, uncertainty remains about the relevance of the model over a relatively long sample period, and whether conventional output gap measures are suitable proxies for demand pressure. This paper reviews research which shows that the Phillips curve model prevails over an extended sample, provided that the benchmark specifications include major structural changes in the balance‐of‐payments and labour market, and account for shifts in the root causes of inflation. When this is done, a linear specification with an output gap in levels correctly predicts the non‐trended inflation pattern over the period 1971(Q1)–1984(Q4), whereas a piecewise concave curve with an output gap in growth rates accurately forecasts the decelerating inflation pattern during 1986(Q1)–2001(Q2). A novel feature of the concave model is that it remains statistically robust and structurally stable when it is estimated until 2015(Q4). The concave model imparts a disinflationary bias, which suggests that monetary policy should be more expansionary during downswing phases of the business cycle and neutral during upswing phases. The analysis also considers how the shape of the Phillips curve might change if the balance‐of‐payments constraint on demand is relaxed in a significant way.

Robust Optimization of Forecast Combinations

A methodology is developed for constructing robust forecast combinations which improve upon a given benchmark specification for all symmetric and convex loss functions. The optimal forecast combination asymptotically almost surely dominates the benchmark and, in addition, minimizes the expected loss function, under standard regularity conditions. The optimum in a given sample can be found by solving a large Convex Optimization problem. An application to forecasting of changes of the S&P 500 Volatility Index shows that robust optimized combinations improve significantly upon the out-of-sample forecasting accuracy of simple averaging and unrestricted optimization.

Index-tunable anti-reflection coatings: Maximizing solar modulation ability for vanadium dioxide-based smart thermochromic glazing

Vanadium dioxide (VO2) nanoparticles with reversible semiconductor-metal phase transition holds the tremendous potential as a thermochromic material for the energy-saving smart glazing. However, the trade-off between improving the luminous transmittance (Tlum) while sacrificing the solar modulation ability (ΔTsol) hampers its bench-to-market translation. Previous studies of anti-reflection coatings (ARCs) focused primarily on increasing Tlum while neglecting ΔTsol, which is a key energy-saving determinant. The intrinsically low ΔTsol (<16%) is due to the fact that VO2 has a higher refractive index (RI) from 500 nm to 2200 nm wavelength (λ) below its critical transition temperature (τc), which causes excessive reflection at a lower temperature. This study aims to investigate ARCs with tunable RI (1.47–1.92 at λ = 550 nm) to improve the antireflection effect at a lower temperature, thereby maximizing ΔTsol for various VO2 nanosubstrates, e.g. continuous thin films, nanocomposites, and periodic micro-patterning films. We showed that the best performing coatings could maximize ΔTsol (from 15.7% to 18.9%) and increase Tlum(avg) (from 39% to 44%) simultaneously, which surpasses the current bench-mark specifications ever reported for ARC-coated VO2 smart glazing. In addition, the cytotoxicity analyses evidence that ARCs are feasible to improve the cyto-compatibility of VO2 nanoparticles-based nanocomposites. The presented RI-tunable ARC, which circumvents the complex materials selection and optical design, not only paves the way for practical applications of VO2-based smart windows but also has extensive applications in the field of solar cells, optical lenses, smart display, etc.

Monte Carlo chord length sampling for d-dimensional Markov binary mixtures

The Chord Length Sampling (CLS) algorithm is a powerful Monte Carlo method that models the effects of stochastic media on particle transport by generating on-the-fly the material interfaces seen by the random walkers during their trajectories. This annealed disorder approach, which formally consists of solving the approximate Levermore–Pomraning equations for linear particle transport, enables a considerable speed-up with respect to transport in quenched disorder, where ensemble-averaging of the Boltzmann equation with respect to all possible realizations is needed. However, CLS intrinsically neglects the correlations induced by the spatial disorder, so that the accuracy of the solutions obtained by using this algorithm must be carefully verified with respect to reference solutions based on quenched disorder realizations. When the disorder is described by Markov mixing statistics, such comparisons have been attempted so far only for one-dimensional geometries, of the rod or slab type. In this work we extend these results to Markov media in two-dimensional (extruded) and three-dimensional geometries, by revisiting the classical set of benchmark configurations originally proposed by Adams, Larsen and Pomraning [1] and extended by Brantley [2]. In particular, we examine the discrepancies between CLS and reference solutions for scalar particle flux and transmission/reflection coefficients as a function of the material properties of the benchmark specifications and of the system dimensionality.