4 resultados para Job creation

em Duke University


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This dissertation consists of three separate essays on job search and labor market dynamics. In the first essay, “The Impact of Labor Market Conditions on Job Creation: Evidence from Firm Level Data”, I study how much changes in labor market conditions reduce employment fluctuations over the business cycle. Changes in labor market conditions make hiring more expensive during expansions and cheaper during recessions, creating counter-cyclical incentives for job creation. I estimate firm level elasticities of labor demand with respect to changes in labor market conditions, considering two margins: changes in labor market tightness and changes in wages. Using employer-employee matched data from Brazil, I find that all firms are more sensitive to changes in wages rather than labor market tightness, and there is substantial heterogeneity in labor demand elasticity across regions. Based on these results, I demonstrate that changes in labor market conditions reduce the variance of employment growth over the business cycle by 20% in a median region, and this effect is equally driven by changes along each margin. Moreover, I show that the magnitude of the effect of labor market conditions on employment growth can be significantly affected by economic policy. In particular, I document that the rapid growth of the national minimum wages in Brazil in 1997-2010 amplified the impact of the change in labor market conditions during local expansions and diminished this impact during local recessions.

In the second essay, “A Framework for Estimating Persistence of Local Labor

Demand Shocks”, I propose a decomposition which allows me to study the persistence of local labor demand shocks. Persistence of labor demand shocks varies across industries, and the incidence of shocks in a region depends on the regional industrial composition. As a result, less diverse regions are more likely to experience deeper shocks, but not necessarily more long lasting shocks. Building on this idea, I propose a decomposition of local labor demand shocks into idiosyncratic location shocks and nationwide industry shocks and estimate the variance and the persistence of these shocks using the Quarterly Census of Employment and Wages (QCEW) in 1990-2013.

In the third essay, “Conditional Choice Probability Estimation of Continuous- Time Job Search Models”, co-authored with Peter Arcidiacono and Arnaud Maurel, we propose a novel, computationally feasible method of estimating non-stationary job search models. Non-stationary job search models arise in many applications, where policy change can be anticipated by the workers. The most prominent example of such policy is the expiration of unemployment benefits. However, estimating these models still poses a considerable computational challenge, because of the need to solve a differential equation numerically at each step of the optimization routine. We overcome this challenge by adopting conditional choice probability methods, widely used in dynamic discrete choice literature, to job search models and show how the hazard rate out of unemployment and the distribution of the accepted wages, which can be estimated in many datasets, can be used to infer the value of unemployment. We demonstrate how to apply our method by analyzing the effect of the unemployment benefit expiration on duration of unemployment using the data from the Survey of Income and Program Participation (SIPP) in 1996-2007.

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AIMS: To assess the impact of involuntary job loss due to plant closure or layoff on relapse to smoking and smoking intensity among older workers. DESIGN, PARTICIPANTS, SAMPLE: Data come from the Health and Retirement Study, a nationally representative survey of older Americans aged 51-61 in 1991 followed every 2 years beginning in 1992. The 3052 participants who were working at the initial wave and had any history of smoking comprise the main sample. METHODS: Primary outcomes are smoking relapse at wave 2 (1994) among baseline former smokers, and smoking quantity at wave 2 among baseline current smokers. As reported at the wave 2 follow-up, 6.8% of the sample experienced an involuntary job loss between waves 1 and 2. FINDINGS: Older workers have over two times greater odds of relapse subsequent to involuntary job loss than those who did not. Further, those who were current smokers prior to displacement that did not obtain new employment were found to be smoking more cigarettes, on average, post-job loss. CONCLUSIONS: The stress of job loss, along with other significant changes associated with leaving one's job, which would tend to increase cigarette consumption, must outweigh the financial hardship which would tend to reduce consumption. This highlights job loss as an important health risk factor for older smokers.

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Transgenic overexpression (40- to 100-fold) of the wild-type human beta2-adrenergic receptor in the hearts of mice leads to a marked increase in cardiac contractility, which is apparently due to the low level of spontaneous (i.e., agonist-independent) activity inherent in the receptor. Here we report that transgenic mice expressing a mutated constitutively active form of the receptor (CAM) show no such phenotype, owing to its modest expression (3-fold above endogenous cardiac beta-adrenergic receptor levels). Surprisingly, treatment of the animals with a variety of beta-adrenergic receptor ligands leads to a 50-fold increase in CAM beta2-adrenergic receptor expression, by stabilizing the CAM beta2-adrenergic receptor protein. Receptor up-regulation leads in turn to marked increases in adenylate cyclase activity, atrial tension determined in vitro, and indices of cardiac contractility determined in vivo. These results illustrate a novel mechanism for regulating physiological responses, i.e., ligand-induced stabilization of a constitutively active but inherently unstable protein.

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To investigate the neural systems that contribute to the formation of complex, self-relevant emotional memories, dedicated fans of rival college basketball teams watched a competitive game while undergoing functional magnetic resonance imaging (fMRI). During a subsequent recognition memory task, participants were shown video clips depicting plays of the game, stemming either from previously-viewed game segments (targets) or from non-viewed portions of the same game (foils). After an old-new judgment, participants provided emotional valence and intensity ratings of the clips. A data driven approach was first used to decompose the fMRI signal acquired during free viewing of the game into spatially independent components. Correlations were then calculated between the identified components and post-scanning emotion ratings for successfully encoded targets. Two components were correlated with intensity ratings, including temporal lobe regions implicated in memory and emotional functions, such as the hippocampus and amygdala, as well as a midline fronto-cingulo-parietal network implicated in social cognition and self-relevant processing. These data were supported by a general linear model analysis, which revealed additional valence effects in fronto-striatal-insular regions when plays were divided into positive and negative events according to the fan's perspective. Overall, these findings contribute to our understanding of how emotional factors impact distributed neural systems to successfully encode dynamic, personally-relevant event sequences.