Match Quality Research Articles

Reevaluating the evidence on seasonality in housing market match quality: Replication of Ngai and Tenreyro (2014)

SummaryI revisit Ngai and Tenreyro (2014)'s empirical analysis of seasonal match quality in American Housing Survey (AHS) data. Using 1999 data only, Ngai and Tenreyro show that homes purchased in the summer season are occupied longer and have fewer and less costly renovations soon after purchase, pointing to superior match quality for households who move house during the thicker summer market. However, applying the same methods to other years of the AHS substantially weakens these results. In addition, I document heaping in a key variable, the prior move month, and implement a multiple imputation correction. Ngai and Tenreyro's use of a coarsened measure of duration seems to largely overcome the biases that heaping introduces.

InterpolationSLAM: An effective visual SLAM system based on interpolation network

Visual SLAM can be mainly divided into direct method and feature-based method, and these two methods develop relatively independently. In recent years, feature-based SLAM systems have been significantly improved by introducing more robust features, effective matching and optimization frameworks, or other sensors. The introduction of semantic information also promotes the development of direct methods. However, visual SLAM usually assumes that the system satisfies the constant velocity assumption. This assumption may lead to a poor initial pose so that the subsequent optimization falls into a local minimal. Meanwhile, large field of view changes often lead to an increase in the error of feature matching for feature-based method and large illumination changes often lead to an increase of photometric error for direct method, thus negatively influencing SLAM systems. In this paper, we mainly target at feature-based method. In detail, we focus on the number and quality of feature matches, as well as the accuracy of the initial pose, thus an interpolation mechanism for SLAM is proposed. Specifically, we introduce the interpolation network originally used to increase the number of video frames into visual SLAM. First, we point out that the traditional interpolation network evaluation metrics are not suitable for the SLAM systems, and we provide the corresponding evaluation metric. Secondly, we verify that it works both for hand-crafted and deep learning features. Thirdly, in order to verify the effectiveness and transferability of our method, we also apply our method to SLAM systems based on direct method, which proves that our method is also applicable to the direct method. Fourthly, we point out that the interpolation network effectively slows down the pose transformation of the SLAM system by inserting an intermediate frame between the previous frame and the current frame, so that the system can obtain a better initial pose based on the constant velocity assumption. This can also explain why visual-inertial systems can effectively improve the performance of visual SLAM. Finally, to ensure the efficiency of the SLAM system, we provide a turning detection module and propose a method to interpolate only at turnings. Extensive experiments and analyses verify the effectiveness and transferability of the proposed system.

Algorithmic identification of Ph.D. thesis-related publications: a proof-of-concept study

In this study we propose and evaluate a method to automatically identify the journal publications that are related to a Ph.D. thesis using bibliographical data of both items. We build a manually curated ground truth dataset from German cumulative doctoral theses that explicitly list the included publications, which we match with records in the Scopus database. We then test supervised classification methods on the task of identifying the correct associated publications among high numbers of potential candidates using features of the thesis and publication records. The results indicate that this approach results in good match quality in general and with the best results attained by the “random forest” classification algorithm.

Local labor markets and job match quality: Teachers

This paper examines how short-term variation in potential teachers’ outside options affects who chooses to teach in public schools. I use variation in state level unemployment rates as a source of plausibly exogenous variation in outside options available to first-year teachers among teachers surveyed in the NCES School and Staffing Survey. I find that those who become teachers when the local labor market is weak are both more likely to have come from highly selective colleges and more likely to express dissatisfaction with their jobs. Other observable demographic, educational, and certification characteristics of newly hired teachers are not affected. Teachers who enter during weaker labor markets are also no less likely to remain in teaching in the short run. Economic downturns provide a potential opportunity for schools to attract and retain academically talented workers, but this may come at a cost to those workers in the form of reduced job satisfaction.

Development and evaluation of a survey instrument to assess veterinary medical record suitability for multi-center research studies.

Here we describe the development and evaluation of a survey instrument to assess the research suitability of veterinary electronic medical records (EMRs) through the conduct of two studies as part of the Dog Aging Project (DAP). In study 1, four reviewers used the instrument to score a total of 218 records in an overlapping matrix of pairs to assess inter-rater agreement with respect to appropriate format (qualification), identification match (verification), and record quality. Based upon the moderate inter-rater agreement with respect to verification and the relatively large number of records that were incorrectly rejected the instrument was modified and more specific instructions were provided. In study 2, a modified instrument was again completed by four reviewers to score 100 different EMRs. The survey scores were compared to a gold standard of board-certified specialist review to determine receiver operating curve statistics. The refined survey had substantial inter-rater agreement across most qualification and verification questions. The cut-off value identified had a sensitivity of 95 and 96% (by reviewer 1 and reviewer 2, respectively) and a specificity of 82% and 91% (by reviewer 1 and reviewer 2, respectively) to predict gold standard acceptance or rejection of the record. Using just qualification and verification questions within the instrument (as opposed to full scoring) minimally impacted sensitivity and specificity and resulted in substantial time savings in the review process.

The Influence of Community Social Capital on Impact Investors’ Selection of Investment Targets

How are exchange partners matched to each other in the market given a great amount of uncertainty facing these actors about the match quality? Different from prior studies that focus mostly on the actor and dyadic level factors, I argue that the process of matching is embedded in the concrete social and geographic settings, and the social contexts—especially the level of social capital—of local communities can mitigate the uncertainty facing exchange partners and therefore facilitate their resource exchanges. I test my theory in the nascent but fast-growing market of impact investing. In addition to financial returns, impact investors explicitly seek to create social and environmental impacts but often must face great uncertainties in selecting investment targets due to the difficulty of measuring the social and environmental impacts of their investments. Empirical results support my argument showing that to mitigate uncertainty, “impact-first” investors that are nonprofits and less concerned about financial returns, in contrast to “financial-first” investors that are forprofits and more concerned about financial returns, select target companies located in geographic communities rich in social capital. The findings of this study contribute to organization literature on the matching problem and growing research on impact investment and have practical implications regarding the important role of the local community in social innovations.

Information design of matching platforms when user preferences are bidimensional

Companies that provide a two‐sided platform for users to proactively seek a match face great challenges in increasing matching efficiency and ensuring match quality. This paper examines how information designs can be used to improve matching outcomes when users derive utility from a match's vertical attribute (i.e., quality) and its horizontal attribute (i.e., idiosyncratic fit). We consider a game‐theoretic model in which competing senders propose matching requests to competing receivers and users on the two sides are differentiated both horizontally and vertically. We first demonstrate that users' preference for the vertical attribute intensifies competition and hurts matching efficiency, and to avoid competition a sender may switch from a close receiver to a distant receiver even when the weight that he places on a match's horizontal closeness increases. Second, we examine four information designs in which one type of information from one side of the market is withheld. Designs that withhold either side's vertical information increase the number of matches, with the improvement from withholding receivers' information being greater. By contrast, designs that withhold either side's horizontal information can cause all requests to concentrate on one receiver and lead to the most severe match failure. Third, an increase in matching volume comes at the expense of certain users' welfare, as withholding one side's vertical information can hurt not only high‐quality users on both sides but also the low‐quality users on the opposite side. Although withholding one side's horizontal information may increase the matching volume under certain conditions, it can be Pareto dominated by a design that withholds one side's vertical information. Fourth, when strategic user pricing is involved, it not only redistributes user welfare but also corrects for matching distortion. Finally, in contrast to the result when strategic pricing is absent, when strategic pricing is present the platform withholding one side's vertical information can benefit all users on the opposite side, while withholding one side's horizontal information can benefit all users on the same side.

Labor Market Benefit of Disaggregated Disclosure*

ABSTRACTAsymmetric information is a fundamental friction that results in mismatches and efficiency losses in the labor market. In this study, we posit that more disaggregated financial disclosure by a CEO candidate's prior employer can help the hiring firm better assess the possible fit between its operational needs and the candidate's skill set. Using a mandatory segment reporting reform in the United States (SFAS 131) as an exogenous shock to disclosure disaggregation, we find a significant increase in the firm‐CEO match quality when the hiring firm has access to more disaggregated segment information about the external candidate's past employment. Furthermore, the improvement in firm‐CEO matching is greater when segment information is incrementally more useful for evaluation of candidate skills. These findings reveal a novel labor market benefit of disaggregated financial disclosure: alleviating pre‐hiring information deficiencies and facilitating efficient allocation of CEO talent across firms.

A repeated shuttle sprint test with female and male international field hockey players is reliable and associated with single sprint but not intermittent endurance performance.

Field hockey is a high-intensity intermittent team sport that has recently undergone a series of rule changes that have resulted in a greater demand for repeated high-intensity movements. Coaches and practitioners now require a reliable assessment of repeated accelerations, decelerations and changes of direction to assess these important match qualities. This investigation assessed the test-retest reliability of a novel 6x40m repeated shuttle sprint test (20m + 20m with a 180° turn) and its association with 40m straight line sprint and YoYo Intermittent Recovery Test performance in 28 International field hockey players (n = 14 females and n = 14 males). The sum of 6 sprint times (SUM) demonstrated ‘excellent’ (ICC = 0.94 and CV = 0.59%) and ‘good’ (ICC = 0.84 and CV = 0.75%) reliability in females and males, respectively. Best sprint time during the repeated shuttle sprint test also demonstrated suitable reliability to evaluate field hockey physical performance (ICC = 0.92 & 0.76, CV = 0.76% & 1.00% in females and males, respectively). SUM was significantly associated with 40 m straight line sprint performance in females (r = 0.90; p<0.001) and males (r = 0.92; p<0.001), but only a weak association was found with YoYo Intermittent Recovery Test performance for either group (r = 0.20; p = 0.495 & r = -0.19; p = 0.525 in females and males, respectively). In summary, field hockey testing batteries that include a repeated shuttle sprint test should consider including a test of intermittent endurance. Further, changes in SUM greater than 1.0% can be confidently interpreted by coaches and practitioners as a real change for both female and male elite field hockey players.

Application Costs and Congestion in Matching Markets

Abstract A matching market often requires recruiting agents, or ‘programmes’, to costly screen ‘applicants’, and congestion increases with the number of applicants to be screened. We investigate the role of application costs: higher costs reduce congestion by discouraging applicants from applying to certain programmes; however, they may harm match quality. In a multiple-elicitation experiment conducted in a real-life matching market, we implement variants of the Gale-Shapley deferred-acceptance mechanism with different application costs. Our experimental and structural estimates show that a (low) application cost effectively reduces congestion without harming match quality.

Occupational Matching and Cities

In this paper, I document that workers in larger cities have significantly more occupational options than workers in smaller ones. They are able to form better occupational matches and earn higher wages. I also note differences in occupation reallocation patterns across cities. I develop a dynamic model of occupation choice that microfounds agglomeration economies and captures the empirical patterns. The calibration of the model suggests that better occupational match quality accounts for approximately 35 percent of the observed wage premium and one-third of the greater inequality in larger cities. (JEL J24, J31, J41, J63, R23)

Research on Chinese Women’s Super-League’s Promotion

Chinese Women’s Super League (CWSL for short) has a comparatively short history. Initiated in 1997, it represented the highest level of Chinese Football. Because of Covid-19, the Chinese Women’s Super League changed into a tournament system and audiences were only allowed to watch online games. The purpose of the study was to help CWSL promote its notability under the circumstance of Covid-19 by using Neil Borden’s marketing mix theory of 4Ps developed in 1950. SWOT analysis was used throughout the study. The result showed that the Chinese Women’s Super League had difficulties improving its match quality and fan engagement online due to Covid-19 and its internal operation. Specific advice to improve the league’s notability was listed below, including but not limited to opening clubs’ official websites and players’ official accounts, making sports videos, collaborating with well-known anchors, implanting a lottery system into the live broadcast, affiliating all women teams to men football clubs, increase the number of women teams and matches, and sell season tickets. Future studies will focus on specific online promotion strategies. In addition, after Covid-19 ends, future studies will generate new market strategies for all Chinese Women’ Football leagues.

Match quality and divorce among naturalized U.S. citizens

AbstractThis research investigates the relationship between immigrants' current citizenship status, an observed measure of permanent legal status in the United States, and their likelihood of divorce. Using American Community Survey data, the research examines relatively young immigrants entering their first marriages in the United States as noncitizens. The study finds those who become naturalized U.S. citizens are at least 25% more likely to be divorced than comparable immigrants who remain noncitizens. The work explores whether immigrants with temporary visas value finding naturalized spouses in the marriage market. If so, the small resulting pool of potential spouses may increase the marginal cost of finding new partners at increasing compatibility levels. The immigrants' reservation match quality would then decrease, potentially resulting in suboptimal sorting along other partner compatibility dimensions. If the immigrants establish permanent residency after marriage, their unions might become less stable as the other compatibility characteristics become more important.

Estimating an Equilibrium Model of Horizontal Competition in Education.

The quality of the match between students and schools affects learning, but little is known about the magnitude of these effects or how they respond to changes in market structure. I develop a quantitative equilibrium model of school competition with horizontal competition in match quality. I estimate the model using data from Pakistan, a country with high private enrollment, and (1) quantify the importance of good matches, (2) show that profit-maximizing private schools' choices of quality advantage wealthier students, increasing inequality and reducing welfare and learning, and (3) provide intuition for when interventions in the market are valuable.

Autonomous Navigation Performance Using Natural Feature Tracking during the OSIRIS-REx Touch-and-Go Sample Collection Event

When the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) spacecraft collected a sample of surface material from asteroid Bennu in 2020 October, it was the first time that an autonomous optical navigation system relying on natural terrain features had been used to guide a spacecraft to a planetary surface. This system, called Natural Feature Tracking (NFT), works by rendering features from digital terrain models and then correlating them with the terrain in real-time navigation images to estimate the spacecraft's position and velocity with respect to the asteroid. Here we describe how the OSIRIS-REx mission built the catalog of features for NFT and how those features performed during rehearsals for and execution of the Touch-and-Go (TAG) sample collection event. Feature performance (quality and accuracy of match) in the rendering and correlation process is the basis of the NFT measurement. All features scored well above the minimum correlation threshold thanks to the effort invested in selecting and modeling them. Residuals across the TAG trajectory were small, indicating that features in the catalog were defined consistently relative to each other. NFT delivered the spacecraft to within 1 m of the targeted location, with a difference of only 3.5 cm and 1.4 s from the predicted location and time of touch. This exceptional performance was crucial for spacecraft safety given Bennu's rough and hazardous terrain.

TIDD: tool-independent and data-dependent machine learning for peptide identification

BackgroundIn shotgun proteomics, database search engines have been developed to assign peptides to tandem mass (MS/MS) spectra and at the same time post-processing (or rescoring) approaches over the search results have been proposed to increase the number of confident peptide identifications. The most popular post-processing approaches such as Percolator and PeptideProphet have improved rates of peptide identifications by combining multiple scores from database search engines while applying machine learning techniques. Existing post-processing approaches, however, are limited when dealing with results from new search engines because their features for machine learning must be optimized specifically for each search engine.ResultsWe propose a universal post-processing tool, called TIDD, which supports confident peptide identifications regardless of the search engine adopted. TIDD can work for any (including newly developed) search engines because it calculates universal features that assess peptide-spectrum match quality while it allows additional features provided by search engines (or users) as well. Even though it relies on universal features independent of search tools, TIDD showed similar or better performance than Percolator in terms of peptide identification. TIDD identified 10.23–38.95% more PSMs than target-decoy estimation for MSFragger, which is not supported by Percolator. TIDD offers an easy-to-use simple graphical user interface for user convenience.ConclusionsTIDD successfully eliminated the requirement for an optimal feature engineering per database search tool, and thus, can be applied directly to any database search results including newly developed ones.

Is There a Sex Difference in Technical Skills among Youth Soccer Players in Norway?

Female soccer has recently experienced an impressive increase in the number of players, and an impressive improvement in the quality of elite matches. Still, studies show sex differences in match statistics on passing accuracy and the ability to control the ball in international matches, which is explained by a lower skill of level in female soccer players as compared to male players. Therefore, the aim of this study was to evaluate if female youth soccer players had bridged the gap in technical skills to reach the level that boys have traditionally attained. Sixteen male and 17 female youth soccer players of the same age and experience level took part in technical skill tests of reception of the ball on the ground and long passes. The results show a significant difference between the sexes in reception performance in favour of the male players (p < 0.05, ES = 1.09), but no significant difference in the long pass test (p = 0.11, ES = 0.43). This leads to the conclusion that the lower score on ball reception is probably the result of experience in small-sided self-organised soccer games during childhood among the male players, which influences reception skills but not the ability to make accurate long passes.

PATH ANALYTIC APPROACH TOWARDS DEMYSTIFYING THE KEY TRIGGERS BEHIND LIKING DIFFERENT CRICKET FORMATS – A KOLKATA BASED STUDY

Cricket has multiple international formats. This study aims to find out if gender and age have any influences on liking any formats. It delves deep into the outcome quality of a cricket match to build a construct for understanding fans’ psyche behind fondness for any formats. The same construct is used to model overall liking for each format. The study uses Chi-square test for independence to investigate the influence of gender and age group on overall liking of a format. It uses Confirmatory Factor Analysis (CFA) to establish the dimensional construct and applies Structural Equation Model (SEM) to model overall liking based on the construct. The study finds no link between gender and liking of a format even though age group appears to influence. It establishes the construct REST comprising of Result, Excitement, Skill, Time and Money to measure overall liking for a format. Result and Skill are found to be insignificant for predicting the liking of Tests and T20 respectively whereas ODI appears to be more balanced. The findings give a clear indication to the regulators that test matches need to be made more unpredictable and result-oriented and T20 matches less restricted and more skilful. The regulators need to strategize making the younger generation interested in test and the older generation in T20. REST can be treated as a pioneering construct that can explain fan’s expectation from a game of cricket leading to liking a format.

Substituting petro-elastic model with a new proxy to assimilate time-lapse seismic data considering model errors

Dynamic data from oil and gas reservoirs (such as well-production or 4D seismic data) have been used often to reduce uncertainty in reservoir simulation models. These data are assimilated in the simulation models separately or jointly. Assimilation of 4D seismic data conventionally involves with a petro-elastic model (PEM) to transform outputs from the simulation models to elastic properties. The PEM is a set of different equations with uncertain parameters and its inclusion in assimilation algorithms calls on multidisciplinary teams of geoscientists and engineers. Moreover, PEM requires extraction of different outputs from the simulation models for the seismic forward model calculations. The extraction process can be costly for large-scale simulation models of giant reservoirs. This research presents a new petro-elastic proxy model (named DAI-Proxy) with a novel formulation to substitute the PEM and integrate 4D seismic data. DAI-Proxy relates time-lapse acoustic impedance to a summation of saturation and pressure changes with two coefficients which are functions of porosity. As the proxy is an approximation of the PEM, its application is affected by model error. We introduce two approaches to account for the proxy model error: (1) considering uncertain coefficients for the DAI-Proxy and (2) using fixed coefficients in the proxy while estimating model errors statistics from the prior ensemble of models. We incorporate these two approaches with a data assimilation algorithm to assimilate simultaneously 4D seismic and well-production data. A benchmark case is used with different cases of data assimilation to compare the DAI-Proxy and the PEM applications. Results show that data match quality for 4D seismic and well-production have similar responses for the PEM and DAI-Proxy implementations. In terms of production forecast, using fixed coefficients in the proxy with its model error treatment create a data assimilation framework comparable to the PEM case. Our results indicate that the traditional PEM application to integrate jointly 4D seismic and well-production data can be replaced with our new DAI-Proxy application. Given the degree of uncertainty in the PEM, related to the rock and fluid models, our proxy provides similar results with fewer uncertain inputs. The proxy offers further advantage as it needs less outputs from the simulation models for seismic forward model calculations. In addition, it helps petroleum engineers to use a computationally less expensive model (light model) as a substitute for the PEM to assimilate 4D seismic data.

Learning in Relational Contracts

We study relational contracts between a firm and a worker with mutual uncertainty about match quality. The worker’s actions are publicly observed and generate both output and information about the match quality. We show that the relational contracts may be inefficient. We characterize the inefficiency through a holdup problem on the contemporaneous output. In the frequent action limit, these inefficiencies persist if and only if information degrades at least at the same rate at which impatience vanishes. We characterize optimal relational contracts and show that they involve actions that yield both a lower payoff and less information than another action. (JEL D83, D86, J22, J31, J41, J63)