The Dwarf Mongoose Optimization (DMO) algorithm, inspired by the behaviors and foraging patterns of dwarf mongooses, is a recently formulated swarm-based metaheuristic method emulating the cooperative behavior of mongooses during food searches. The DMO algorithm effectively addresses various...

We present an experimental study of decentralized two‐sided matching markets with no transfers. Experimental participants are informed of everyone's preferences and can make arbitrary nonbinding match offers that get finalized when a period of market inactivity has elapsed. Several insights...

The effects on criminal behaviour of raising the minimum wage for those aged 25 and over in the United Kingdom are analysed, using data on police stop and search activities. A 1% increase in the minimum wage raises the fraction of people stopped by the police by 2.96%, the fraction of people...

We develop a model where heterogeneous agents choose whether to engage in onthe-job search (OJS) to improve labor income. The model accounts for untargeted microdata patterns: fiscal incentives affect job-to-job mobility and wage growth of stayers-but not leavers-across the income distribution,...

In the United States, workers whose past earnings were below a threshold are generally ineligible for unemployment insurance (UI), creating a discontinuous jump in the value of being unemployed. Using a regression discontinuity design with administrative panel data, we estimate a sizable local...

This report replicates the study by Belot et al. (2022), which investigates how posted wages affect labor supply through a field experiment using a job platform with varying wage postings. The paper's main finding is that a higher wage increases job seekers' interest in a vacancy, a result at...

15% of Danish workers account for 60% of unemployment. Are these workers unemployed more frequently because of their lower productivity or higher opportunity costs of employment? Using administrative data linking workers to their earnings, wealth, debt, health records, parental backgrounds,...

We develop a model where heterogeneous agents choose whether to engage in onthe-job search (OJS) to improve labor income. The model accounts for untargeted microdata patterns: fiscal incentives affect job-to-job mobility and wage growth of stayers - but not leavers - across the income...

This paper examines how caseworkers influence job finding rates and job quality. To rule out selection effects, I exploit that caseworkers are assigned based on the jobseekers’ month of birth in some offices of the Austrian public employment service. Combining administrative data on...

We examine the evolution of spatial house price dispersion during Germany's recent housing boom. Using a dataset of sales listings, we find that house price dispersion has significantly increased, which is driven entirely by rising price variation across postal codes. We show that both price...

This paper presents a competitive search model focusing on the impact of asymmetric information on credit markets. We show that limited entry by lenders results in endogenous credit rationing, which, in turn, plays a key role in managing adverse selection and prevents the credit market from...

This paper examines how caseworkers influence job finding rates and job quality. To rule out selection effects, I exploit that caseworkers are assigned based on the jobseekers' month of birth in some offices of the Austrian public employment service. Combining administrative data on caseworkers...

This theoretical study rigorously investigates how generative artificial intelligence reshapes decision-making in social entrepreneurship by modeling the opportunity search process through the lens of optimal stopping theory. Social entrepreneurs often face high uncertainty and resource...

This paper studies how dynamic changes in the search environment affect consumer search and purchase behavior. We develop a dynamic model that incorporates a non-stationary search environment and propose a feasible estimation procedure to estimate its parameters. We apply our model and...

We leverage rich data from a prominent online job board in Uruguay to assess directed search patterns in job applications, focusing on posted wages and advertised non-wage amenities. We find robust evidence of directed search based on posted wages in the cross-section, with stark heterogeneity...

We propose a standard search and bargaining model with divisible money, in which only the random matching market opens and the generalized Nash bargaining settles each trade. Assuming fixed production costs, we analytically characterize a tractable equilibrium, called a pay‐all equilibrium ,...

The job finding rate declines with the duration of unemployment, but the relative importance of workers' search behavior and employers' recruitment behavior remains unclear. We use monthly search diaries from Swiss public employment offices to shed new light on this issue. Search diaries record...

We introduce a collective experimentation problem where a continuum of agents choose the timing of irreversible actions under uncertainty and where public feedback from the actions arrives gradually over time. The leading application is the adoption of new technologies. The socially optimal...

This paper studies a dynamic quantile model for intertemporal decisions under uncertainty, in which the decision maker maximizes the τ-quantile of the stream of future utilities, for τ ∈ (0,1). We present two sets of contributions. First, we generalize existing results in directions that are...

In this study we evaluate the effects of low-skilled immigration on small businesses, wages and employment in Germany. We develop a search and matching model with heterogeneous workers, cross-skill matching, and endogenous entry into entrepreneurship. The model is calibrated using German...

We study a mean-field game of optimal stopping and investigate the existence of strong solutions via a connection with the Bank-El Karoui's representation problem. Under certain continuity assumptions, where the common noise is generated by a countable partition, we show that a strong randomized...

Electric Network Frequencys (ENF) analysis has emerged as a powerful tool for forensic investigations, providing timestamp and geolocation information of audio or video recordings based on the unique frequency pattern of the power grid. However, the forensic usability of ENF signals extracted...