Essays on labour market search

This thesis contains three studies on the topic of labour market search. Chapter 1 provides an overview of the studies. Chapter 2 reports an experimental study which examines how social comparisons affect behavior in a sequential search task. In a control treatment subjects search in isolation, while in two other treatments subjects get feedback on the search decisions and outcomes of a partner subject. The average level and rate of decline of reservation wages are similar across treatments. Nevertheless, subjects who are able to make social comparisons search differently from those who search in isolation. Within a search task we observe a reference wage effect: when a partner exits, the subject chooses a new reservation wage which is increasing in partner income. We also observe a social learning effect: between search tasks, subjects who have been paired with a more patient and successful partner increase their reservation wages in the next task. Chapter 3 reports a study in which we provide the first microeconometric estimates of the hazards to matching on both sides of a labour market, decomposed into two constituent parts. Namely, (i) the rate at which job-seekers and vacancies contact each other (i.e. having interviews), and (ii) the probability that a contact results in a match. To do this, we use unique data which contains information on job-seekers, vacancies, interviews and interview outcomes. We use a specification which addresses the problems of the temporal aggregation bias and spatial spillovers highlighted by the two-sided estimates. Our estimates suggest that market tightness affects the matching rates mainly through affecting the meeting rates. In both the raw data and the estimates, we find the decline in the matching hazard is driven by the decline in the contact hazard, and not by a fall in the matching probability. And we also report the effects of various characteristics on matching decomposed into the effects on meeting and matching probability. Using the same data as Chapter 3, Chapter 4 provides further evidence on the mechanism by which job-seekers and vacancies decide whom to contact during their search. Since the data features an environment where both sides of the market have access to a database (or marketplace) of potential partners, a natural model of search is one of stock-flow matching, and we show that the predictions of this model outperform those of a simple random matching model. Our descriptive and econometric evidence shows that it is the inflow rate of new agents, rather than the total stock of agents, which determines the contact rates of existing agents, consistent with the predictions of the stock-flow model. Chapter 5 summarizes the findings of this dissertation and concludes

Social comparisons in job search

© 2019 Elsevier B.V. Using a laboratory experiment we examine how social comparisons affect behavior in a sequential search task. In a control treatment subjects search in isolation, while in two other treatments subjects get feedback on the search decisions and outcomes of a partner subject. The average level and rate of decline of reservation wages are similar across treatments. Nevertheless, subjects who are able to make social comparisons search differently from those who search in isolation. Within a search task we observe a reference wage effect: when a partner exits, the subject chooses a new reservation wage which is increasing in partner income. We also observe a social comparison effect between search tasks: subjects whose partners in a previous task searched for longer choose a higher reservation wage in the next task. Our findings imply that the provision of social information can change job-seekers search behavior

A generic mission-level flight control surface EMA power consumption simulation tool

The use of electromechanical actuators (EMAs) for aeronautical applications promises substantial benefits regarding efficiency and operability. To advance the design of power electronics and secondary power supply, there is a need for the ability to swiftly study the effects of aircraft mission and operational aspects on the actuator energy consumption. Pursuant to this, the aim of the work presented in this paper is twofold: (i) to build a generic mission-level flight control surface EMA power consumption simulation framework and (ii) to apply this framework to a case study involving a small all-electric aircraft, in which selected factors that impact energy consumption are investigated. The core of the framework comprises physics-based EMA power estimators, linked with a six-degree-of-freedom flight dynamics and control simulation module. The case study results show that the actuator power consumption correlates positively with the proportional gains in the flight control system but is inversely proportional to the trajectory radius and linearly dependent on turbulence intensity. The developed framework could aid in the selection of the actuator, as well as in the optimisation of airborne electronics and secondary power supply

Essays on labour market search

This thesis contains three studies on the topic of labour market search. Chapter 1 provides an overview of the studies. Chapter 2 reports an experimental study which examines how social comparisons affect behavior in a sequential search task. In a control treatment subjects search in isolation, while in two other treatments subjects get feedback on the search decisions and outcomes of a partner subject. The average level and rate of decline of reservation wages are similar across treatments. Nevertheless, subjects who are able to make social comparisons search differently from those who search in isolation. Within a search task we observe a reference wage effect: when a partner exits, the subject chooses a new reservation wage which is increasing in partner income. We also observe a social learning effect: between search tasks, subjects who have been paired with a more patient and successful partner increase their reservation wages in the next task. Chapter 3 reports a study in which we provide the first microeconometric estimates of the hazards to matching on both sides of a labour market, decomposed into two constituent parts. Namely, (i) the rate at which job-seekers and vacancies contact each other (i.e. having interviews), and (ii) the probability that a contact results in a match. To do this, we use unique data which contains information on job-seekers, vacancies, interviews and interview outcomes. We use a specification which addresses the problems of the temporal aggregation bias and spatial spillovers highlighted by the two-sided estimates. Our estimates suggest that market tightness affects the matching rates mainly through affecting the meeting rates. In both the raw data and the estimates, we find the decline in the matching hazard is driven by the decline in the contact hazard, and not by a fall in the matching probability. And we also report the effects of various characteristics on matching decomposed into the effects on meeting and matching probability. Using the same data as Chapter 3, Chapter 4 provides further evidence on the mechanism by which job-seekers and vacancies decide whom to contact during their search. Since the data features an environment where both sides of the market have access to a database (or marketplace) of potential partners, a natural model of search is one of stock-flow matching, and we show that the predictions of this model outperform those of a simple random matching model. Our descriptive and econometric evidence shows that it is the inflow rate of new agents, rather than the total stock of agents, which determines the contact rates of existing agents, consistent with the predictions of the stock-flow model. Chapter 5 summarizes the findings of this dissertation and concludes

Lying and social norms: A lab-in-the-field experiment with children

We conduct a lab-in-the-field experiment with 567 children, aged four to eleven, in which we investigate the effect of social norms on lying and test whether norm sensitivity changes with age. Children think about a number between 1 and 6 in private, then roll a die, and report whether the number that came up is the same as the one they thought of. Just before making their report, we expose children to different empirical and normative information prescribing lying or honesty. We show that a normative intervention suggesting other children approve of honesty effectively reduces lying. We find limited evidence of the influence of our empirical interventions: information suggesting other children report honestly is effective only for younger children, while information suggesting other children report dishonestly does not influence lying patterns. We further observe that, although lying is omnipresent across all age groups, honesty significantly increases with age

Social comparisons in job search: Experimental evidence

Using a laboratory experiment we examine how social comparisons affect behavior in a sequential search task. In a control treatment, subjects search in isolation while in two other treatments subjects get feedback on the search decisions and outcomes of a partner subject. The average level and rate of decline in reservation wages are similar across treatments. Nevertheless, subjects who are able to make social comparisons search differently from those who search in isolation. Within a search task we observe a reference wage effect: when a partner exits, the subject chooses a new reservation wage which is increasing in partner income. We also observe a social learning effect: between search tasks, subjects who have been paired with a more patient and successful partner increase their reservation wages in the next task

Experimental Study of Aircraft Achieving Dutch Roll Mode Stability without Weathercock Stability

Weathercock stability is usually considered essential to achieve normal flight, while the Dutch roll mode stability can still be achieved without weathercock stability which has been algebraically proved. This paper proposed a flight experiment to investigate the characteristics of an airplane with Dutch roll mode stability but no weathercock stability. Firstly, the algebraic analysis based on a standard lateral-directional mode approximation was made to demonstrate the effect of yawing stability derivative Cnβ on the Dutch roll mode characteristics. The flight experiment was organized after that using a model glider which was modified to have zero Cnβ but with marginal change on Cyβ. The convergence of Dutch roll mode in flight meets the algebraic and numerical analysis as expected. However, the difference of handling characteristics between the original and modified configurations indicates some other roles the weathercock stability plays in flight as well as some limitations of utilizing mode criterion in flight quality analysis

Driving Forces for Oppositely Charged Polyion Association in Aqueous Solutions: Enthalpic, Entropic, but Not Electrostatic

Driving forces for association between oppositely charged biological or synthetic polymers in aqueous solution have long been identified as electrostatic in origin. This attraction is broken down into an entropic component, due to loss of counterions, and an enthalpic component, stemming from Coulombic attraction between opposite charges. While the balance between entropic and enthalpic contributions shifts according to the conditions, the presence of exotherms or endotherms on mixing, though small, are viewed as signatures of Coulombic interactions which support theories of polyelectrolyte association rooted in continuum electrostatics. Here, a head-to-head comparison is made between mechanisms based on electrostatics and those based on specific ion pairing, or ion exchange. Using a Hofmeister series of counterions for a common polycation, poly­(diallyldimethylammonium), enthalpy changes on association with poly­(styrenesulfonate) are shown to derive from changes in water perturbation, revealed by Raman scattering studies of water O–H vibrations. The free energy for complexation is almost completely entropic over all salt concentrations

Evaluation of the comprehensive efficiency of the interception pipeline in the urban rainwater pipe network for the initial rainwater collection and storage

Urban runoff pollution has become one of the important limiting factors hindering the continuous improvement of water environment. In the process of drainage system reconstruction, the evaluation of interception pipeline for the collection and storage efficiency of initial rainwater is an important work. Therefore, this study uses the analytic hierarchy process to establish an evaluation system and method containing 4 first-level indicators and 10 second-level indicators to evaluate the comprehensive efficiency of the interception pipeline for initial rainwater collection and storage. Taking the interception pipeline in a drainage system in Shanghai as a case study, the established evaluation method was adopted to evaluate it, and the comprehensive indexes under the rainfall return periods of 0.5 year, 1 year, 3 years and 5 years were calculated. The results indicated that the evaluation method could be well applied to the effectiveness evaluation of intercepting pipelines in drainage systems, and could provide technical support for the planning and design of urban runoff pollution control projects in the future

Seismic Impedance Inversion Using a Joint Deep Learning Model Based on Convolutional Neural Network and Transformer

Seismic impedance is an important factor in characterizing reservoirs, so accurate seismic impedance inversion is significant in seismic exploration. However, achieving high-resolution impedance inversion has remained a complex problem due to challenges related to the unknown seismic wavelet and the frequency band limitations of the observed data. In recent years, deep learning methods such as convolutional neural network (CNN) have been successfully applied to the field of seismic impedance inversion, which can obtain higher resolution results compared with traditional inversion methods. However, limited by the size of the local receptive field, CNN is not conducive to extracting global information. In contrast, a transformer can efficiently extract long-range dependencies but relies entirely on the self-attention mechanism to compute correlations between data, which requires a lot of training data. Therefore, this article proposes a joint deep learning model based on CNN and a transformer for impedance inversion. Among them, CNN and transformer are used to learn local and global information in the data, respectively, and feature fusion through residual connection, which can improve the feature representation capability of neural networks. In addition, we train a CNN-based forward operator that can introduce information from unlabeled data into the network training to enhance the network's generalization ability and improve the stability of the inversion. Experimental results in the SEAM model and field data show that the method can predict impedance effectively and with better accuracy than classical constrained sparse spike inversion and conventional deep learning methods