Random Search Model Research Articles

The role of immigration in a deep recession

This paper studies the impact of pre-Great Recession immigrant inflows on the labour market during a recession. It develops a random search model of the labour market featuring vacancy persistence, endogenous return migration, and wage rigidity. Consistent with the Spanish data, some immigrants in the model leave the country during the recession, freeing up jobs for natives. Yet, differences in match-quality draws between immigrants and natives also impact firms’ job creation decisions. The return-migration channel positively affects natives, while job creation effects are negative in the calibrated Spanish economy. I find that immigrants mitigate the impact of the recession and enhance natives’ welfare. During the recession, the native unemployment rate would have been 2 percentage points higher in the absence of the pre-crisis immigration boom. Return migration plays a key role, with short- and medium-run impacts on the native unemployment rate 6 times larger than all other channels combined.

A novel approach for prediction of groundwater quality using gradient boosting-based algorithms

ABSTRACT This study explores the potential of the GPBoost approach for groundwater quality assessment in comparison to three other gradient boosting-based algorithms. Three methods, random search, grid search, and Bayesian optimization were used to find the optimal values of various hyperparameters with all four-gradient boosting-based algorithms. One hundred and two samples of Entropy weighted water quality index with 14 input parameters are used for assessing groundwater quality. The calculated EWQI values for drinking range between 80.4 and 394.96 in pre-monsoon and 39.6 to 338.79 during the post-monsoon period. Moreover, spatial distribution maps displayed that the central portions of the study area fall under medium water quality. The performances of models were compared based on multiple statistical criteria, including Correlation Coefficient (CC), root mean square error (RMSE), and mean absolute error (MAE). The results reveal that the CC value by all modeling approaches is more than 0.93, suggesting a comparable performance by all methods. Results in terms of RMSE values in predicting the EWQI values suggest GPBoost (random search) model performed better than the other three models, thus suggesting a competitive performance by GPBoost in comparison to other gradient boosting-based approaches. Relative importance analysis provided by random and grid search methods highlights the significance of NO3 −, Mg2+, TDS, EC, and TH as important input parameters for predicting EWQI.

Certifiably employable? Occupational regulation and unemployment duration

AbstractOccupational regulation is a labor market institution that has received a growing amount of attention. However, there is a gap in the literature regarding the relationship between occupational credentials and unemployment duration in the United States. Thus, we propose a random search model to explain differences in unemployment duration resulting from heterogeneous effects from licenses and certification. Our model predicts that an occupational credential with a stronger signaling/human capital effect results in a shorter individual unemployment duration. To estimate the relationship between occupational credentials and spells of unemployment, we perform a survival analysis using panel data from the Survey of Income and Program Participation (SIPP) for the years 2013–2019. We find that both licensing and certification are associated with reductions in unemployment spells for Black males that are similar in magnitude. Our results provide some suggestive guidance to policymakers since certification is less costly and not mandatory like occupational licensing.

Contracting and search with heterogeneous principals and agents

This paper incorporates a risk-neutral principal-agent problem into a random search model to study contracting and search in general equilibrium. I introduce heterogeneity in principals' and agents' production technologies in terms of the distribution of output across states of nature. Under optimal contracting, this heterogeneity can give rise to complementarity in contracting between specific principal and agent types. In contrast to complementarity in production, complementarity in contracting affects only the division of the surplus but not its size and can induce principals to engage in overly intense search before forming a match. I show that a reduction in search frictions and contractual innovations can induce principals to engage in overly intense search.

Sufficient statistics for frictional wage dispersion and growth

This paper develops a sufficient statistics approach for estimating the role of search frictions in wage dispersion and life‐cycle wage growth. We show how the wage dynamics of displaced workers are directly informative of both for a large class of search models. Specifically, the correlation between pre‐ and post‐displacement wages is informative of frictional wage dispersion. Furthermore, the fraction of displaced workers who suffer a wage loss is informative of frictional wage growth and job‐to‐job mobility, independent of the job‐offer distribution and other labor‐market parameters. Applying our methodology to US data, we find that search frictions account for less than 20% of wage dispersion. In addition, we estimate that between 40 to 80% of workers experience no frictional wage growth during an employment spell. Our approach allows us to estimate how frictions change over time. We find that frictional wage dispersion has declined substantially since 1980 and that frictional wage growth, while low, is more important toward the end of expansionary periods. We finish by estimating two versions of a random search model to show how at least two different mechanisms—involuntary job transitions or compensating differentials—can reconcile our results with the job‐to‐job mobility seen in the data. Regardless of the mechanism, the estimated models show that frictional wage growth accounts for about 15% of life‐cycle wage growth.

Asymmetric Lévy Flights Are More Efficient in Random Search

We study the first-arrival (first-hitting) dynamics and efficiency of a one-dimensional random search model performing asymmetric Lévy flights by leveraging the Fokker–Planck equation with a δ-sink and an asymmetric space-fractional derivative operator with stable index α and asymmetry (skewness) parameter β. We find exact analytical results for the probability density of first-arrival times and the search efficiency, and we analyse their behaviour within the limits of short and long times. We find that when the starting point of the searcher is to the right of the target, random search by Brownian motion is more efficient than Lévy flights with β≤0 (with a rightward bias) for short initial distances, while for β>0 (with a leftward bias) Lévy flights with α→1 are more efficient. When increasing the initial distance of the searcher to the target, Lévy flight search (except for α=1 with β=0) is more efficient than the Brownian search. Moreover, the asymmetry in jumps leads to essentially higher efficiency of the Lévy search compared to symmetric Lévy flights at both short and long distances, and the effect is more pronounced for stable indices α close to unity.

Unobservable investments, trade efficiency and search frictions

AbstractInformation structure can affect market efficiency by influencing participants' investment incentives. In this case, the entrants' type distribution and the market trade efficiency are both affected by the information structure, so they are jointly determined and correlated. In order to investigate the effects of asymmetric information, this paper uses a random search model of ex ante investments and trade efficiency, assuming that the amount of investment remains the investor's private information. I show that the ex ante payoffs are equivalent to the equilibrium payoffs when investments are observable. In the unique steady state equilibrium, non‐degenerate investment distribution and price distribution emerge simultaneously with ex ante identical agents. The investments motivated by unobservability fail to improve social welfare due to the mismatches caused by unobservability. Allocating positive bargaining power to investors alleviates the mismatch problem and improves social welfare.

Radioactive source search problem and optimisation model based on meta-heuristic algorithm

Abstract In the process of rational development and utilisation of nuclear energy, people often face nuclear accidents such as lost and stolen radioactive sources; so, the means of searching for these sources quickly in highly radioactive environments is an important security challenge. In the past, these jobs were limited to workers specialising in nuclear technology. They used gamma-ray detection equipment to search for radioactive sources, but the search efficiency was low. The main purpose of this article is to design a meta-heuristic algorithm based on imitating professional technicians to locate radioactive sources in a computer-aided manner. At the same time, due to the complexity that may characterise the actual search, the search strategy must be optimised. The article established an intelligent random search model with human thinking. Finally, it was proved based on the mathematical theory that the complexity of the model search algorithm is linear, and the simulation experiment results show that the optimisation algorithm has good efficiency and fault tolerance.

Grid Search for Predicting Coronary Heart Disease by Tuning Hyper-Parameters

Diagnosing the cardiovascular disease is one of the biggest medical difficulties in recent years. Coronary cardiovascular (CHD) is a kind of heart and blood vascular disease. Predicting this sort of cardiac illness leads to more precise decisions for cardiac disorders. Implementing Grid Search Optimization (GSO) machine training models is therefore a useful way to forecast the sickness as soon as possible. The state-of-the-art work is the tuning of the hyperparameter together with the selection of the feature by utilizing the model search to minimize the false-negative rate. Three models with a cross-validation approach do the required task. Feature Selection based on the use of statistical and correlation matrices for multivariate analysis. For Random Search and Grid Search models, extensive comparison findings are produced utilizing retrieval, F1 score, and precision measurements. The models are evaluated using the metrics and kappa statistics that illustrate the three models’ comparability. The study effort focuses on optimizing function selection, tweaking hyperparameters to improve model accuracy and the prediction of heart disease by examining Framingham datasets using random forestry classification. Tuning the hyperparameter in the model of grid search thus decreases the erroneous rate achieves global optimization.

Unobservable Investments, Trade Efficiency and Search Frictions

Market participants can invest to increase their gains from trade before searching for partners. The entrants' type distribution and trade efficiency are jointly determined and correlated. This paper explores a random search model of ex ante investments and trade efficiency, assuming that the investment amount remains the investor's private information. We show that the ex ante payoffs are equivalent to the equilibrium payoffs when investments are observable. In the unique steady state equilibrium, non-degenerate investment distribution and price distribution emerge simultaneously with ex-ante identical agents. In the basic model, where investing agents have no bargaining power, the extra investments fail to improve social welfare even when the search friction vanishes and the investments become efficient due to the mismatches caused by unobservability. Allocating positive bargaining power to investors alleviates the mismatch problem and improves social welfare.

Commercial Real Estate Market with Two-sided Random Search: Theory and Implications

ABSTRACT In this paper, we set up a two-sided random search model to study the trading behaviour between buyers and sellers in the commercial real estate market. Our model shows that the interaction between search and bargaining has a profound influence on the role played by the market search friction regarding the equilibrium transaction price of commercial property and the well-being of both buyers and sellers. Against the traditional view that the existence of search friction always plays a negative role in the commercial real estate market, we find that under some conditions the market search friction can increase the equilibrium transaction price of commercial property and thus benefit sellers, which is considered the most valuable especially during the downturn of a business cycle.

Spousal Insurance, Outside Options and Wage Bargaining

Spousal insurance raises a worker's outside option, allowing workers to bargain a higher wage. To study this mechanism I propose a random search model with ex-ante heterogeneity in ability, endogenous marriage, endogenous labor supply of spouses and wages determined by Nash Bargaining. Using the model, I derive an empirical specification to test the mechanism and the sources of endogeneity to be addressed. I use a combination of an instrument derived from theory and one instrument based on policy variation to confirm the predictions of the model. A 1 percentage point increase in the share of married women working increases the wage of married individuals by 2.51-3.51%.

Fully Convolutional Deep Neural Networks with Optimized Hyperparameters for Detection of Shockable and Non-Shockable Rhythms.

Deep neural networks (DNN) are state-of-the-art machine learning algorithms that can be learned to self-extract significant features of the electrocardiogram (ECG) and can generally provide high-output diagnostic accuracy if subjected to robust training and optimization on large datasets at high computational cost. So far, limited research and optimization of DNNs in shock advisory systems is found on large ECG arrhythmia databases from out-of-hospital cardiac arrests (OHCA). The objective of this study is to optimize the hyperparameters (HPs) of deep convolutional neural networks (CNN) for detection of shockable (Sh) and nonshockable (NSh) rhythms, and to validate the best HP settings for short and long analysis durations (2–10 s). Large numbers of (Sh + NSh) ECG samples were used for training (720 + 3170) and validation (739 + 5921) from Holters and defibrillators in OHCA. An end-to-end deep CNN architecture was implemented with one-lead raw ECG input layer (5 s, 125 Hz, 2.5 uV/LSB), configurable number of 5 to 23 hidden layers and output layer with diagnostic probability p ∈ [0: Sh,1: NSh]. The hidden layers contain N convolutional blocks × 3 layers (Conv1D (filters = Fi, kernel size = Ki), max-pooling (pool size = 2), dropout (rate = 0.3)), one global max-pooling and one dense layer. Random search optimization of HPs = {N, Fi, Ki}, i = 1, … N in a large grid of N = [1, 2, … 7], Fi = [5;50], Ki = [5;100] was performed. During training, the model with maximal balanced accuracy BAC = (Sensitivity + Specificity)/2 over 400 epochs was stored. The optimization principle is based on finding the common HPs space of a few top-ranked models and prediction of a robust HP setting by their median value. The optimal models for 1–7 CNN layers were trained with different learning rates LR = [10−5; 10−2] and the best model was finally validated on 2–10 s analysis durations. A number of 4216 random search models were trained. The optimal models with more than three convolutional layers did not exhibit substantial differences in performance BAC = (99.31–99.5%). Among them, the best model was found with {N = 5, Fi = {20, 15, 15, 10, 5}, Ki = {10, 10, 10, 10, 10}, 7521 trainable parameters} with maximal validation performance for 5-s analysis (BAC = 99.5%, Se = 99.6%, Sp = 99.4%) and tolerable drop in performance (<2% points) for very short 2-s analysis (BAC = 98.2%, Se = 97.6%, Sp = 98.7%). DNN application in future-generation shock advisory systems can improve the detection performance of Sh and NSh rhythms and can considerably shorten the analysis duration complying with resuscitation guidelines for minimal hands-off pauses.

Sufficient Statistics for Frictional Wage Dispersion and Growth

This paper develops a sufficient statistics approach for estimating the role of search frictions in wage dispersion and lifecycle wage growth. We show how the wage dynamics of displaced workers are directly informative of both for a large class of search models. Specifically, the correlation between pre- and post-displacement wages is informative of frictional wage dispersion. Furthermore, the fraction of displaced workers who suffer a wage loss is informative of frictional wage growth and job-to-job mobility, independent of the job-offer distribution and other labor-market parameters. Applying our methodology to US data, we find that search frictions account for less than 20 percent of wage dispersion. In addition, we estimate that between 40 to 80 percent of workers experience no frictional wage growth during an employment spell. Our approach allows us to estimate how frictions change over time. We find that frictional wage dispersion has declined substantially since 1980 and that frictional wage growth, while low, is more important towards the end of expansionary periods. We finish by estimating two versions of a random search model to show how at least two different mechanisms—involuntary job transitions or compensating differentials—can reconcile our results with the job-to-job mobility seen in the data. Regardless of the mechanism, the estimated models show that frictional wage growth accounts for about 15 percent of lifecycle wage growth.

Sufficient Statistics for Frictional Wage Dispersion and Growth

This paper develops a sufficient statistics approach for estimating the role of search frictions in wage dispersion and lifecycle wage growth. We show how the wage dynamics of displaced workers are directly informative of both for a large class of search models. Specifically, the correlation between pre- and post-displacement wages is informative of frictional wage dispersion. Furthermore, the fraction of displaced workers who suffer a wage loss is informative of frictional wage growth and job-to-job mobility, independent of the job-offer distribution and other labor-market parameters. Applying our methodology to US data, we find that search frictions account for less than 20 percent of wage dispersion. In addition, we estimate that between 40 to 80 percent of workers experience no frictional wage growth during an employment spell. Our approach allows us to estimate how frictions change over time. We find that frictional wage dispersion has declined substantially since 1980 and that frictional wage growth, while low, is more important towards the end of expansionary periods. We finish by estimating two versions of a random search model to show how at least two different mechanisms—involuntary job transitions or compensating differentials—can reconcile our results with the job-to-job mobility seen in the data. Regardless of the mechanism, the estimated models show that frictional wage growth accounts for about 15 percent of lifecycle wage growth.

Efficiency improvement by navigated safety inspection involving visual clutter based on the random search model

Navigated inspection seeks to improve hazard identification (HI) accuracy. With a tight inspection schedule, HI also requires efficiency. However, lacking quantification of HI efficiency, navigated inspection strategies cannot be comprehensively assessed. This work aims to determine inspection efficiency in navigated safety inspection, controlling for HI accuracy. Based on a cognitive method of the random search model (RSM), an experiment was conducted to observe the HI efficiency in navigation, for a variety of visual clutter (VC) scenarios, while using eye-tracking devices to record the search process and analyze the search performance. The results show that the RSM is an appropriate instrument, and VC serves as a hazard classifier for navigation inspection in improving inspection efficiency. This suggests a new and effective solution for addressing the low accuracy and efficiency of manual inspection through navigated inspection involving VC and the RSM. It also provides insights into the inspectors’ safety inspection ability.

Competitive versus random search with bargaining: An empirical comparison

In this paper, we estimate and nest the canonical competitive search model of Moen (1997) inside a random search model with bargaining. The nesting allows us to compare the two models predictions, or comparative statics, using the same empirical estimation. Furthermore, nesting provides likelihood ratio tests that demonstrate the empirical differences between competitive search and random search with bargaining. The differences between the two models include whether workers search in different “sub-markets” with different levels of productivity, they direct the search to each firm/sub-market, and the wage they receive is split efficiently via Hosios (1990).

Idiothetic Path Integration in the Fruit Fly Drosophila melanogaster

After discovering a small drop of food, hungry flies exhibit a peculiar behavior in which they repeatedly stray from, but then return to, the newly discovered resource. To study this behavior in more detail, we tracked hungry Drosophila as they explored a large arena, focusing on the question of how flies remain near the food. To determine whether flies use external stimuli, we individually eliminated visual, olfactory, and pheromonal cues. In all cases, flies still exhibited a centralized search behavior, suggesting that none of these cues are absolutely required for navigation back to the food. To simultaneously eliminate visual and olfactory cues associated with the position of the food, we constructed an apparatus in which the food could be rapidly translated from the center of the arena. Flies continued to search around the original location, even after the food was moved to a new position. A random search model based on measured locomotor statistics could not reproduce the centered nature of the animal's trajectory. We conclude that this behavior is best explained by a form of path integration in which the flies use idiothetic cues to search near the location of the food. We argue that the use of path integration to perform a centered local search is not a specialization of Drosophila but rather represents an ancient behavioral mode that is homologous to the more elaborate foraging strategies of central place foragers such as ants.

The Role of Firms in Gender Earnings Inequality: Evidence from the United States

This paper documents that in the US, men are more likely than women to work in both high-wage firms and high-wage industries. I then ask why this sorting occurs. I consider two main explanations: men and women have different preferences, and men and women have different opportunities. Through the lens of a simple random search model, I find that the dominant explanation for sorting is differences in opportunities. One implication of this result is that women are at firms that offer better nonpay characteristics, and this plays an important role in explaining the gender earnings gap.

Contract and Rent Dispersion in a Frictional Labor Market

This paper incorporates a risk-neutral principal-agent model with contractual constraints into a random search model to study the interaction between contracting and search in partial and general equilibrium. I introduce heterogeneity in principals' and agents' production technologies in terms of the distribution of output across states of nature and characterize equilibrium in this context. Principals tailor contracts to agents' production technologies to incentivize agents' effort, generating dispersion in optimal contracts. The resulting endogenous dispersion in agency rents introduces an option value of search, which can generate inefficient equilibria with lengthy search and a persistent fraction of unmatched principals and agents. I show that a reduction in search costs and contractual innovations can reduce welfare. The results have implications for labor and financial economics and imply a novel theory of specialization in decentralized markets.