On the quantitative importance of wage bargaining models

Four general equilibrium search models are compared quantitatively. Thebaseline framework is a calibrated macroeconomic model of the US economydesigned for a welfare analysis of unemployment insurance policy. Theother models make three simple and natural specification changes,regarding tax incidence, monopsony power in wage determination, and therelevant threat point. These specification changes have a major impacton the equilibrium and on the welfare implications of unemploymentinsurance, partly because search externalities magnify the effects ofwage changes. The optimal level of unemployment insurance dependsstrongly on whether raising benefits has a larger impact on searcheffort or on hiring expenditure.

MOOGLE: a metamodel-based model search engine

Models are becoming increasingly important in the software development process. As a consequence, the number of models being used is increasing, and so is the need for efficient mechanisms to search them. Various existing search engines could be used for this purpose, but they lack features to properly search models, mainly because they are strongly focused on text-based search. This paper presents Moogle, a model search engine that uses metamodeling information to create richer search indexes and to allow more complex queries to be performed. The paper also presents the results of an evaluation of Moogle, which showed that the metamodel information improves the accuracy of the search.

Essays on Job Search and Labor Market Dynamics

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.

Transiting exoplanets from the CoRoT space mission XIII. CoRoT-13b: a dense hot Jupiter in transit around a star with solar metallicity and super-solar lithium content

We announce the discovery of the transiting planet CoRoT-13b. Ground-based follow-up in CFHT and IAC80 confirmed CoRoT's observations. The mass of the planet was measured with the HARPS spectrograph and the properties of the host star were obtained analyzing HIRES spectra from the Keck telescope. It is a hot Jupiter-like planet with an orbital period of 4.04 days, 1.3 Jupiter masses, 0.9 Jupiter radii, and a density of 2.34 g cm(-3). It orbits a G0V star with T(eff) = 5 945 K, M(*) = 1.09 M(circle dot), R(*) = 1.01 R(circle dot), solar metallicity, a lithium content of +1.45 dex, and an estimated age of between 0.12 and 3.15 Gyr. The lithium abundance of the star is consistent with its effective temperature, activity level, and age range derived from the stellar analysis. The density of the planet is extreme for its mass, implies that heavy elements are present with a mass of between about 140 and 300 M(circle plus).

Transiting exoplanets from the CoRoT space mission XVII. The hot Jupiter CoRoT-17b: a very old planet

We report on the discovery of a hot Jupiter-type exoplanet, CoRoT-17b, detected by the CoRoT satellite. It has a mass of 2.43 +/- 0.30 M(Jup) and a radius of 1.02 +/- 0.07 R(Jup), while its mean density is 2.82 +/- 0.38 g/cm(3). CoRoT-17b is in a circular orbit with a period of 3.7681 +/- 0.0003 days. The host star is an old (10.7 +/- 1.0 Gyr) main-sequence star, which makes it an intriguing object for planetary evolution studies. The planet's internal composition is not well constrained and can range from pure H/He to one that can contain similar to 380 earth masses of heavier elements.

Testing for large extra dimensions with neutrino oscillations

We consider a model where sterile neutrinos can propagate in a large compactified extra dimension giving rise to Kaluza-Klein (KK) modes and the standard model left-handed neutrinos are confined to a 4-dimensional spacetime brane. The KK modes mix with the standard neutrinos modifying their oscillation pattern. We examine former and current experiments such as CHOOZ, KamLAND, and MINOS to estimate the impact of the possible presence of such KK modes on the determination of the neutrino oscillation parameters and simultaneously obtain limits on the size of the largest extra dimension. We found that the presence of the KK modes does not essentially improve the quality of the fit compared to the case of the standard oscillation. By combining the results from CHOOZ, KamLAND, and MINOS, in the limit of a vanishing lightest neutrino mass, we obtain the stronger bound on the size of the extra dimension as similar to 1.0(0.6) mu m at 99% C.L. for normal (inverted) mass hierarchy. If the lightest neutrino mass turns out to be larger, 0.2 eV, for example, we obtain the bound similar to 0.1 mu m. We also discuss the expected sensitivities on the size of the extra dimension for future experiments such as Double CHOOZ, T2K, and NO nu A.

The Ins and Outs of Unemployment: A Conditional Analysis

We analyze how unemployment, job finding and job separation rates react to neutral and investment-specific technology shocks. Neutral shocks increase unemployment and explain a substantial portion of unemployment volatility; investment-specific shocks expand employment and hours worked and mostly contribute to hours worked volatility. Movements in the job separation rates are responsible for the impact response of unemployment while job finding rates for movements along its adjustment path. Our evidence qualifies the conclusions by Hall (2005) and Shimer (2007) and warns against using search models with exogenous separation rates to analyze the effects of technology shocks.

Aplicações de modelos de procura para bens duráveis de baixa liquidez

I use Search models to study decentralized markets of durable goods. I explore the concept of market liquidity of Lippman and McCall (1986) and show that the theory of optimal search is useful to address the following issues: What governs the time required to make a transaction on these markets? What is the relationship between the price of goods and the time required to make transactions? Why is optimal to wait to make a transaction in markets where individuals discount future utility? What is the socially optima search level? Two specifications are used, the traditional model of job search and a version of Krainer and LeRoy (2001) model.

Representação das necessidades de informação na organização da informação: uma análise de modelos teóricos de busca

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelos de comportamento de busca de informação: contribuições para a organização da informação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Polarimetry of the binary PDS 144

Aims. Our goal is to study the circumstellar environment associated with each component of the wide intermediate-mass pre-main sequence binary system PDS 144 using broadband polarimetry. Methods. We present near-infrared (NIR) linear polarimetric observations of PDS 144 gathered with the IAGPOL imaging polarimeter along with the CamIV infrared camera at the Observatorio do Pico dos Dias (OPD). In addition, we re-analyzed OPD archive optical polarization to separate the binary and estimate the interstellar polarization using foreground stars. Results. After discounting the interstellar component, we found that both stars of the binary system are intrinsically polarized. The polarization vectors at optical and NIR bands of both components are aligned with the local magnetic field and the jet axis. These findings indicate an interplay between the interstellar magnetic field and the formation of the binary system. We also found that the PDS 144N is less polarized than its southern companion in the optical. However, in the NIR PDS 144N is more polarized. Our polarization data can only be explained by high inclinations (i greater than or similar to 80 degrees) for the disks of both members. In particular, comparisons of our NIR data with young stellar objects disk models suggest predominantly small grains in the circumstellar environment of PDS 144N. In spite of the different grain types in each component, the infrared spectral indexes indicate a coeval system. We also found evidence of coplanarity between the disks.

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

Evolutionary synthesis of stochastic gene network models using feature-based search spaces

A feature-based fitness function is applied in a genetic programming system to synthesize stochastic gene regulatory network models whose behaviour is defined by a time course of protein expression levels. Typically, when targeting time series data, the fitness function is based on a sum-of-errors involving the values of the fluctuating signal. While this approach is successful in many instances, its performance can deteriorate in the presence of noise. This thesis explores a fitness measure determined from a set of statistical features characterizing the time series' sequence of values, rather than the actual values themselves. Through a series of experiments involving symbolic regression with added noise and gene regulatory network models based on the stochastic 'if-calculus, it is shown to successfully target oscillating and non-oscillating signals. This practical and versatile fitness function offers an alternate approach, worthy of consideration for use in algorithms that evaluate noisy or stochastic behaviour.