Original Estimates Research Articles

Orchestrating Information Acquisition

We study how to orchestrate information acquisition in an environment where bidders endowed with original estimates (“types”) about their private values can acquire further information by incurring a cost. We consider both single-round and fully sequential short-listing rules. The optimal single-round shortlisting rule admits the set of most efficient bidders that maximizes expected virtual surplus adjusted by the second-stage signal and information acquisition cost. When shortlisting is fully sequential, at each round, the most efficient remaining bidder is admitted provided that her conditional expected contribution to the virtual surplus is positive. (JEL D44, D82, D83)

Source‐to‐sink: Regional grain size trends to reconstruct sediment budgets and catchment areas

AbstractSource‐to‐sink studies and calculating sediment budgets of ancient systems are important approaches for basin analysis. Because of the enormous scale of basins, most existing studies depend on subsurface datasets. As drilling campaigns focus on structural highs or specific trap types, well datasets cover only limited subareas of entire sedimentary basins. Outcrop studies are almost always based on even more spatially limited datasets. The ramifications for basin analysis are considerable: (1) actual sediment budgets are underestimated; (2) catchment denudation rates and sizes are miscalculated; (3) predicted net:gross ratios in sink areas bear high uncertainties. This paper outlines a new workflow‐defined approach to reconstruct regional grain size profiles to better estimate sediment budgets across an entire sedimentary basin, even when datasets have spatial limited coverage. The workflow includes compilation of grain size data, transformation to mass balance frameworks, and lateral matching of local to regional grain size profiles. The approach was tested on two representative continental‐to‐marine delta systems which are covered by four spatially limited datasets while the entire sedimentary basin (sink area) is much larger. The original estimates account for only maximum 40% of the actual total sediment volume as analysed with the new approach. The new method provides significantly improved constraints for catchment (source) models as well as input parameters (sediment budget, input locations, fractions) for process‐based depositional modelling for predictions of net:gross and detailed facies proximal to distal relationships. General benefits include lower uncertainties in clastic reservoir quality prediction (hydrocarbon exploration) and provenance analysis (fundamental research).

A Reliability Generalization Meta-Analysis of the Padua Inventory-Revised (PI-R)

Background/Objective: The Padua Inventory-Revised (PI-R) is a widely applied instrument to measure obsessive-compulsive symptoms in clinical and nonclinical samples. We conducted a reliability generalization meta-analysis on the PI-R. Method: An exhaustive literature search yielded 118 empirical studies that had applied the PI-R, from which 30 studies (33 samples) reported an original reliability estimate. Results: Assuming a random-effects model, the average internal consistency reliability (Cronbach's alpha) was .92 (95% CI [.91, .93]) for the total scores, and ranged from .74 to .89 for the subscales. Assuming mixed-effects models, moderator analyses showed a positive statistically significant association between the standard deviation of the total scores and the reliability coefficients (p = .002; R2 = .38). Conclusions: In terms of reliability, the PI-R scale was found to be adequate for both research and clinical purposes, although exhibiting large heterogeneity across studies. Future empirical studies using the PI-R should be required to provide at least one reliability estimate based on their own data.

Isotopic analysis in teeth of contemporary brazilians with known diet and geolocation and its forensic value for human identification

Dental anthropological data may provide valuable information about an individual's life, including age at death, health, signs of violence, ancestry, diet features, intentional modifications, and geographic origin. These pieces of information may be further detailed by diet and residential mobility estimates provided by isotopic analyses. The use of isotope data in the modern population is strongly dependent on the diverse origin of food supply, thus requiring an updated and location-specific database. In this study, we have analyzed the isotopic ratio of strontium, carbon, and nitrogen in enamel and dentin collagen of third molars individuals from three main cities in Brazil. Besides the isotope data, we have also surveyed their diet in adolescence habits to develop models to be applied for forensic studies in the Brazilian territory. We show that the forensic value of the place of origin estimation based 87Sr/86Sr levels is reduced in these highly urbanized samples. Among the outliers, most individuals are older than the mean age (25.1) or had water from wells in childhood. The sample's diet has a robust C4 presence and mean trophic levels consistent with the declared high frequency of chicken, meat, and dairy products, also compatible with the high consumption of sugar, rice, and beans in the local culture. Individuals with special diets, either by choice or therapeutic needs, were potential outliers among the group. Our results also contribute to the international human tissues isotopic database and can contribute for human identification of Brazilians or foreigners with distinct isotopic signatures.

Estimating the Number of Illnesses Caused by Agents Transmitted Commonly Through Food: A Scoping Review.

Estimates of the overall human health impact of agents transmitted commonly through food complement surveillance and help guide food safety interventions and regulatory initiatives. The purpose of this scoping review was to summarize the methods and reporting practices used in studies that estimate the total number of illnesses caused by these agents. We identified and included 43 studies published from January 1, 1995, to December 31, 2019, by searching PubMed and screening selected articles for other relevant publications. Selected articles presented original estimates of the number of illnesses caused by ≥1 agent transmitted commonly through food. The number of agents (species or subspecies for pathogens) included in each study ranged from 1 to 31 (median: 4.5; mean: 9.2). Of the 40 agents assessed across the 43 studies, the most common agent was Salmonella (36; 84% of studies), followed by Campylobacter (33; 77%), Shiga toxin-producing Escherichia coli (25; 58%), and norovirus (20; 47%). Investigators used a variety of data sources and methods that could be grouped into four distinct estimation approaches-direct, surveillance data scaled-up, syndrome or population scaled-down, and inferred. Based on our review, we propose four recommendations to improve the interpretability, comparability, and reproducibility of studies that estimate the number of illnesses caused by agents transmitted commonly through food. These include providing an assessment of statistical and nonstatistical uncertainty, providing a ranking of estimates by agent, including uncertainties; describing the rationale used to select agents and data sources; and publishing raw data and models, along with clear, detailed methods. These recommendations could lead to better decision-making about food safety policies. Although these recommendations have been made in the context of illness estimation for agents transmitted commonly through food, they also apply to estimates of other health outcomes and conditions.

Randomised, double-blind comparison of a fixed co-formulation of intra-articular polynucleotides and hyaluronic acid versus hyaluronic acid alone in the treatment of knee osteoarthritis: two-year follow-up

BackgroundA first-year interim analysis of this two-year study suggested that intra-articular injections of highly purified, natural-origin polynucleotides and hyaluronic acid (HA) as a fixed combination (PNHA) might improve knee function and joint pain more effectively than HA alone in patients with knee osteoarthritis (OA). The purpose of the second-year analysis herein described was to verify whether the first-year interim outcomes persist over the whole two-year period.MethodsRandomised, double-blind, HA-controlled clinical trial in 100 knee OA patients (98 randomised, 79 completing the study) in a high-specialisation tertiary care setting. The hypothesised difference of efficacy between PNHA and HA for the original sample size estimate is 20%. Treatment cycle: three intra-articular knee injections of either PNHA or HA, at baseline and weekly for two weeks. Evaluations: Western Ontario and McMaster Universities (WOMAC) score and Knee Society Score (KSS) as, respectively, primary and secondary endpoints, evaluated at baseline and after 2, 6, 12, and 24 months; synovial fluid levels of mediators (at baseline and the end of the treatment cycle). Adverse effects investigated at each control visit. Statistical analysis: Kruskal-Wallis test for independent samples (nonparametric one-way analysis of variance) after correction of means for age, Body Mass Index and Kellgren-Lawrence grade. If significant, pairwise post-hoc Sidak multiple comparisons.ResultsKSS total score and KSS pain item: significant improvement in both groups, with significantly more pain improvement in patients treated with PNHA (2-point reduction) than HA (1-point reduction). Both groups experienced significant long-term reductions in WOMAC total scores: significantly stronger in PNHA-treated patients after 24 months with a steady difference of 16% favouring PNHA in WOMAC pain subscore. No clinically significant adverse events in either group.ConclusionsThe outcomes of the 2-year study confirmed that a short cycle of intra-articular treatment (3 weekly double-blind injections) with polynucleotides (long-acting viscosupplementation properties, chondrocyte activation, pain-relieving properties) in fixed combination with high molecular weight hyaluronic acid is more effective in improving knee function and pain in knee OA patients than HA alone. PNHA may be elective for viscosupplementation in knee OA patients with fastidious and resistant pain and worsening disease.Trial registrationNCT02417610.Registration, 15/04/2015.ClinicalTrials.gov database link:

Test scores’ robustness to scaling: The scale_transformation command

Social scientists frequently rely on the cardinal comparability of test scores to assess achievement gaps between population subgroups and their evolution over time. This approach has been criticized because of the ordinal nature of test scores and the sensitivity of results to order-preserving transformations that are theoretically plausible. Bond and Lang (2013, Review of Economics and Statistics 95: 1468–1479) document the sensitivity of measured ability to scaling choices and develop a method to assess the robustness of changes in ability over time to scaling choices. In this article, I present the scale_transformation command, which expands the Bond and Lang (2013) method to more general cases and optimizes their algorithm to work with large datasets. The command assesses the robustness of an achievement gap between two subgroups to any arbitrary choice of scale by finding bounds for the original gap estimation. Additionally, it finds scale transformations that are very likely and unlikely to benchmark against the results obtained. Finally, it also allows the user to measure how much gap growth coefficients change when including controls in their specifications.

Efficient parallelization of tensor network contraction for simulating quantum computation

We develop an algorithmic framework for contracting tensor networks and demonstrate its power by classically simulating quantum computation of sizes previously deemed out of reach. Our main contribution, index slicing, is a method that efficiently parallelizes the contraction by breaking it down into much smaller and identically structured subtasks, which can then be executed in parallel without dependencies. We benchmark our algorithm on a class of random quantum circuits, achieving greater than 105 times acceleration over the original estimate of the simulation cost. We then demonstrate applications of the simulation framework for aiding the development of quantum algorithms and quantum error correction. As tensor networks are widely used in computational science, our simulation framework may find further applications.

The role of unpaid domestic work in explaining the gender gap in the (monetary) value of leisure

The value of travel time savings (VTTS) representing the willingness to pay to reduce travel time, consists of two components: the value of liberating time [equal to the value of leisure (VoL)] and the value of time assigned to travel (VTAT), representing the travel conditions of a trip. Their relative values indicate which dimension to emphasize when investing in transport: speed or comfort. In this paper, we formulate and estimate a framework aimed at the improvement in the estimation of the VoL. By introducing a novel treatment of time assigned to domestic work, we consider that unpaid labor should be assigned a wage rate as a measure of the expenses avoided when assigning time to those chores. We use state-of-the-art data on time use and expenses as well as online data on gig workers collected in Austria, and apply the time-use and expenditure model of Jara-Diaz et al. (Transp Res Part B 42(10):946–957, 2008). The wage rates for paid and unpaid work were combined to re-formulate the budget constraint, which affected women more than men due to the higher involvement of the former in domestic activities. Compared against the original estimation, the VoL changed from €10/h for men and €6/h for women to €9/h for both genders, which in turn yields a larger average VTAT, which becomes positive for public transport. As a conclusion, the novel treatment of domestic labor contributes to closing the gap in the VoL between genders and highlights the power of unveiling the components behind the VTTS. The empirical findings imply that investments in travel time reductions rather than in comfort should be prioritized, given the very good conditions of public transport in Austria.

Estimation of water origins within an explosive cyclone over the Sea of Japan using an isotopic regional spectral model

AbstractMoisture sources and their corresponding temperature and humidity are important for explosive extratropical cyclones’ development regarding latent heating. To clarify the water origins and moisture-transport processes within an explosive cyclone, we simulated an explosive cyclone migrating poleward across the Sea of Japan on November 30, 2014, by using an isotopic regional spectral model. In the cyclone’s center area, a replacement of water origins occurred during the cyclone’s development. During the early stage, the warm conveyor belt (WCB) transported large amounts of moisture from the East China Sea and Kuroshio into the cyclone’s inner region. While in the deepening stage, the cold conveyor belt (CCB) and dry intrusion (DI) conveyed more moisture from the Northwest Pacific Ocean and the Sea of Japan, respectively. Compared with the contribution of local moisture, that of remote moisture was dominant in the cyclone’s center area. Regarding the water origins of condensation within the frontal system in the deepening stage, the Northwest Pacific Ocean vapors, principally transported by the CCB, contributed 35.5% of the condensation in the western warm front. The East China Sea and Kuroshio moisture, conveyed by the WCB, accounted for 32.4% of the condensation in the cold and eastern warm fronts. In addition, condensation from the Sea of Japan, which was mainly triggered by the DI and induced by the topography, occurred on the west coast of the mainland of Japan and near the cyclone center. The spatial distribution of the isotopic composition in condensation and water vapor also supports the water-origin results.

Calculation and analysis of pollutants during takeoff and landing based on airborne data

AbstractThis study adopts the calculation method of reducing pollutant emission during flight based on the flight record data from Nantong to Chengdu. More accurate flight record data can be obtained by interpolating, filtering, and weighting QAR (airborne quick access recorder) data in order to recover specific flight conditions. BMMF2 and P3‐T3 flow correction method are used to correct the fuel flow value in the QAR data and analyze the exact consumption time of each phase of the LTO (landing take‐off cycle) based on the key parameter. The actual pollutant emission results calculated using QAR data are compared with the reference data of International Civil Aviation Organization under the same conditions, and then changes of pollutant emission in each flight stage are analyzed. The results show that in the four modes of approach, taxi, take‐off, and climb of standard landing and take‐off (LTO) cycle, the pollutants emitted in the taxi section account for about 60% of the whole cycle, the taxi time is reduced by 6.78 min, the total emission is reduced by 11.4%, and the fuel consumption is reduced by 11.96%. The estimated nitrogen oxide emissions of LTO in stages using the QAR measured data after accurately dividing the flight phase, which is over 28% different from the original estimation method. The QAR data can analyze the pollutant emissions of aircraft in different stages. Methods for calculating the engine emissions of the LTO phase can provide a more accurate reference for assessing pollution of near‐ground aircraft and airports in different regions.

Bias correction of radar and satellite rainfall estimates and increasing its accuracy using modified merging

Bias correction in the weather radar and the tropical rainfall measuring mission (TRMM) rainfall estimates are used to improve its accuracy. This correction is usually done separately for both radar and TRMM. Even though the corrections are done separately, the results of these corrections can be further improved using the merging. Among the methods of merging, modified local bias, mean field bias and conditional merging may be suitable methods used to correct rainfall estimates from remote sensing surrounding in the Makassar Strait. The aim of this research corrects radar and TRMM rainfall estimates, then combining them to obtain more accurate rainfall estimates. The performance will be validated using correlation, root mean square error (RMSE) and mean absolute error (MAE). The result shows that modified mean field bias (Mod_MFB) and local bias (LB) can increase accuracy, mainly RMSE and MAE but not in correlation. However, conditional merging (CM) and modified LB can improve accuracy by increasing correlation and decrease RMSE and MAE. The modification of CM, LB modification and original estimation of remote sensing successively are the order of the best methods. Moreover, merging three data types is not automatically better than merging the two types of data. However, combination 3 types of data offer the stability of accuracy.

"Estimation of Geographical Origin of Amfissis Cultivar Olive Oil Based on GC-FID/MS and Chemometrics"

Virgin olive oil (VOO) is a basic component of the Mediterranean diet due to the presence of various compounds with distinct health benefits...

Optimally-Weighted Image-Pose Approach (OWIPA) for Distracted Driver Detection and Classification

Distracted driving is the prime factor of motor vehicle accidents. Current studies on distraction detection focus on improving distraction detection performance through various techniques, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). However, the research on detection of distracted drivers through pose estimation is scarce. This work introduces an ensemble of ResNets, which is named Optimally-weighted Image-Pose Approach (OWIPA), to classify the distraction through original and pose estimation images. The pose estimation images are generated from HRNet and ResNet. We use ResNet101 and ResNet50 to classify the original images and the pose estimation images, respectively. An optimum weight is determined through grid search method, and the predictions from both models are weighted through this parameter. The experimental results show that our proposed approach achieves 94.28% accuracy on AUC Distracted Driver Dataset.

Is the Value Premium Smaller Than We Thought?

The construction of the original HML portfolio (Fama and French, 1993) includes six seemingly innocuous decisions that could easily have been replaced with alternatives that are just as reasonable. I propose such alternatives and construct HML portfolios. In sample, the average estimate of the value premium is dramatically smaller than the original estimate of the value premium. The difference is 0.09% per month and statistically significant. Out of sample, however, this difference is statistically indistinguishable from zero. The results suggest that the original value premium estimate is upward biased because of a chance result in the original research decisions.

On the Estimation and Comparison of Lifetime Morbid Risks

Lifetime morbid risks are usually determined either by the Kaplan- Meier product limit estimator or by simpler estimators such as the lifetime prevalence, the Weinberg method or the Schulz method, which can be con- sidered an elaboration of the Weinberg method. We show that the Kaplan-Meier product limit estimator of lifetime mor- bid risk may yield unreliable estimates. Although the simplicity of the Schulz method and the Weinberg method is appealing, we suggest that under a proper model, those methods can be replaced by the original Stromgren estimator which is almost equally simple, and more accurate. Increased ac- curacy is achieved when the investigators have prior indication regarding the distribution of the ages at onset for those affected by the disorder, and even when that indication is vague and only limited knowledge of the distribution is available.

The potential benefits of employee equity funds in the United States

PurposeThe mainstream framework for corporate governance is that all corporate activity should be directed towards shareholder wealth maximization. This article posits that public policy should move away from shareholder primacy and instead recognize employees as key contributors to corporate value-creation. One way to implement this approach is to require the creation of Employee Equity Funds (EEFs) at large corporations, which would pay employees dividends alongside external shareholders and establish a collective employee voice in corporate governance. EEFs may reduce economic inequality while improving firm performance and macroeconomic stability. This article provides an original estimate of average employee dividends, illustrating the potential of employee equity funds.Design/methodology/approachAnalysis of employee dividends for Employee Equity Funds at large U.S. corporations, using publicly available corporate finance data.FindingsBased on historic dividend payments and employee counts in public 10-K filings, I find that, if EEFs held 20% of outstanding equity, the average employee dividend across this sample would be $2,622 per year, while the median is $1,760. This indicates that employee dividends can be a small but meaningful form of redressing wealth inequality for the low-wage workforce, though it should emphatically not be seen as a replacement for fair wages.Originality/valueOriginal data analysis of a proposed policy reform to increase the benefits of employee equity in the United States.

Why the pandemic scars won't run so deep

▪ We now expect the scarring effect from the pandemic on the supply‐side of the UK's economy to be much more limited – a 1% permanent cut to GDP compared to our original estimate of 2.6%. But we still forecast UK GDP growth will average a relatively modest 1.4% a year through the 2020s. ▪ The resilience of the labour market is key to our estimate of more limited scarring. We think unemployment may have peaked already at a little more than 1ppt above its pre‐pandemic level, limiting hysteresis effects, while recent ONS data suggests there has not been a mass exodus of foreign‐born workers. ▪ We think the UK's large negative output gap will persist for some time, so the risk of a rapid recovery triggering a sustained rise in inflation is low. We also think the repair job for the public finances is smaller than the OBR estimates.

Revisiting the external financial dependence index in light of the rise of corporate net lending: What do we really measure?

This paper revisits the External Financial Dependence (EFD) index originally formulated employing data for American firms in the 1980s by Rajan and Zingales (1998). This index is meant to reflect technological characteristics of the industries and it is commonly assumed that its values are stable in time and across countries. Despite its popularity, there have been reduced attempts to extend the original estimations. This paper fills this gap, providing new estimations of the EFD index for G7 countries between 1980 and 2015. First, we argue that, theoretically, there are different factors (mostly related to technical change) that can alter the values of the EFD index. Second, we show that the assumptions of stability in time and space find little empirical support. Third, it is maintained that the EFD index can be considered a proxy of corporate net lending as there are significant theoretical and empirical similarities between the two concepts.

Self-Supervised Monocular Depth Estimation of Untextured Indoor Rotated Scenes

Self-supervised deep learning methods have leveraged stereo images for training monocular depth estimation. Although these methods show strong results on outdoor datasets such as KITTI, they do not match performance of supervised methods on indoor environments with camera rotation. Indoor, rotated scenes are common for less constrained applications and pose problems for two reasons: abundance of low texture regions and increased complexity of depth cues for images under rotation. In an effort to extend self-supervised learning to more generalised environments we propose two additions. First, we propose a novel Filled Disparity Loss term that corrects for ambiguity of image reconstruction error loss in textureless regions. Specifically, we interpolate disparity in untextured regions, using the estimated disparity from surrounding textured areas, and use L1 loss to correct the original estimation. Our experiments show that depth estimation is substantially improved on low-texture scenes, without any loss on textured scenes, when compared to Monodepth by Godard et al. Secondly, we show that training with an application's representative rotations, in both pitch and roll, is sufficient to significantly improve performance over the entire range of expected rotation. We demonstrate that depth estimation is successfully generalised as performance is not lost when evaluated on test sets with no camera rotation. Together these developments enable a broader use of self-supervised learning of monocular depth estimation for complex environments.