Youth unemployment has been a persistent problem in the European Union for many years and the affected countries spend a substantial part of their budget on active labour market policies, with the aim to integrate young unemployed workers into the labour market. Employment subsidy programmes are one type of active labour market policies that have been implemented. Although important amounts of money have been spent for these programmes, little is known about the effects of participation in subsidised employment on the labour market transitions. This thesis incorporates several studies that aim to estimate the effect of a subsidised employment programme. The programme provides a reduction of the social insurance contribution for employers that hire eligible workers. All three studies provide estimates for the participation of long term unemployed school leavers. In order to evaluate whether programme participation is useful for their integration into the labour market, the effect on different duration outcomes has been investigated. A major difficulty in causal analysis with non-experimental data is that the characteristics of the group of participants may by systematically different from those of the group of non-participants. Estimates may therefore reflect both the effect of participation as well as the particular selection of participants. To control for this selection bias, multivariate mixed proportional hazard models have been applied and a large number of control variables have been incorporated. The results of this thesis show that participation in the employment subsidy programme accelerates the transitions into regular, non-subsidised employment. Moreover, the employment duration is increased, compared to a regular employment spell. Finally, the estimates show that the effect of a former participation on the duration of a subsequent unemployment spell is similar to the effect of a former regular employment spell.

This thesis is comprised of three essays relating to long term unemployment in Spain. The first chapter is methodological analysis of the main dataset that is used throughout the thesis. The second and third chapter provide two applications of the dataset for the study of long term unemployment. The methodology in these chapters can be easily adapted to study unemployment in other countries. Chapter 1. On the use of administrative data for the study of unemployment Social security administrative data are increasingly becoming available in many countries. These are very attractive data as they have a long panel structure (large N, large T) and allow to measure many different variables with higher precision. Because of their nature they can capture aspects that are usually hidden due to design or timing of survey data. However, administrative data are not ready to be used for labour market research, especially studies involving unemployment. The main reason is that administrative data only capture those registered unemployed, and in some cases only those receiving unemployment benefits. The gap between total unemployment and registered unemployment is not constant neither across workers characteristics nor time. In this paper I augment Spanish Social Security administrative data by adding missing unemployment spells using information from the institutional framework. I compare the resulting unemployment rate to that of the Labour Force Survey, showing that both are comparable and thus the administrative dataset is useful for labour market research. I also explore how the administrative data can be used to study some important aspects of the labour market that the Labour Force survey can’t capture. Administrative data can also be used to overcome some of the problems of the Labour Force survey such as changes in the structure of the survey. This paper aims to provide a comprehensive guide on how to adapt administrative datasets to make them useful for studying unemployment. Chapter 2. Unemployment Duration Variance Decomposition `a la ABS: Evidence from Spain Existing studies of unemployment duration typically use self-reported information from labour force surveys. We revisit this question using precise information on spells from administrative data. We follow the recent method proposed by Alvarez, Borovickova and Shimer (2015) for estimating the different components of the duration of unemployment using administrative data and have applied it to Austria. In this paper we apply the same method (the ABS method hereafter) to Spain using Spanish Social Security data. Administrative data have many advantages compared to Labour Force Survey data, but we note that there are some incompleteness that need to be enhanced in order to use the data for unemployment analysis (e.g., unemployed workers that run out of unemployment insurance have no labour market status in the data). The degree and nature of such incompleteness is country-specific and are particularly important in Spain. Following Chapter 1, we deal with these data issues in a systematic way by using information from the Spanish LFS data as well as institutional information. We hope that our approach will provide a useful way to apply the ABS method in other countries. Our findings are: (i) the unemployment decomposition is quite similar in Austria and Spain, specially when minimizing the effect of fixed-term contracts in Spain. (ii) the constant component is the most important one; while (total) heterogeneity and duration dependence are roughly comparable. (iii) also, we do not find big differences in the contribution of the different components along the business cycle. Chapter 3. Search Capital and Unemployment Duration I propose a novel mechanism called search capital to explain long term unemployment patters across different ages: workers who have been successful in finding jobs in the recent past become more efficient at finding jobs in the present. Search ability increases with search experience and depreciates with tenure if workers do not search often enough. This leaves young (who have not gained enough search experience) and older workers in a disadvantaged position, making them more likely to suffer long term unemployment. I focus on the case of Spain, as its dual labour market structure favours the identification of search capital. I provide empirical evidence that search capital affects unemployment duration and wages at the individual level. Then I propose a search model with search capital and calibrate it using Spanish administrative data. The addition of search capital helps the model match the dynamics of unemployment and job finding rates in the data, especially for younger workers.

<p>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.</p><p>In the second essay, “A Framework for Estimating Persistence of Local Labor</p><p>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.</p><p>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.</p> / Dissertation

This dissertation applies economic theories and econometric methods to analyze the interactions between government policies and economic agents in two important and current topics: the protection of the environment and illegal migration.Following the introduction, the second chapter studies the empirical strength of bi-directional linkages between environmental standards and performance, on the one hand, and environmental innovation, on the other. Our empirical results reveal that environmental R&amp;D both spurs the tightening of government environmental standards and is spurred by the anticipation of such tightening, suggesting that U.S. environmental policy (at least in the context of the manufacturing industries that we study) has been responsive to innovation and effective in inducing innovation.The third chapter studies whether a voluntary reduction pollution programs can prompt firms to develop new environmental technologies that yield future emission reduction benefits. Conversely, a VRP may induce a participating firm to divert resources from environmental research to environmental monitoring and compliance activities that yield short-term benefits in reduced emissions. We find evidence that higher rates of program participation are associated with significant reductions in the number of successful environmental patent applications four to six years after the program ended.The fourth chapter examines the migration duration of Mexican immigrants in the U.S. using data from the Mexican Migration Project (MMP). In the past, temporary migrations were frequent, and often the rule rather than the exception in the case of Mexican immigrants. This pattern may be changing due to the tightening of the border between Mexico and the Unites States. Moreover, this paper examines whether migration experience, demographic characteristics, economic conditions or social networks drive the time Mexican immigrants to reside illegally in the United States. The empirical analysis shows that the migration duration increases as the U.S. expected real wage increases. Tighter U.S. migration policies have an ambiguous effect on the migration duration while longer distances decrease the hazard of return to their state of origin.In the final chapter of this dissertation, the general findings are concluded and some future avenues of research are discussed.

Submitted by Aelson Maciera (aelsoncm@terra.com.br) on 2017-08-09T15:24:44Z No. of bitstreams: 1 DissCZO.pdf: 1359694 bytes, checksum: 90de19ac8dc5ae4c2ad7e286ab945d9b (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-08-09T17:18:02Z (GMT) No. of bitstreams: 1 DissCZO.pdf: 1359694 bytes, checksum: 90de19ac8dc5ae4c2ad7e286ab945d9b (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-08-09T17:18:08Z (GMT) No. of bitstreams: 1 DissCZO.pdf: 1359694 bytes, checksum: 90de19ac8dc5ae4c2ad7e286ab945d9b (MD5) / Made available in DSpace on 2017-08-09T17:23:14Z (GMT). No. of bitstreams: 1 DissCZO.pdf: 1359694 bytes, checksum: 90de19ac8dc5ae4c2ad7e286ab945d9b (MD5) Previous issue date: 2011-12-07 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / When a group of patients is monitored until a pre-established date for observation of the recurrence time of an event, it is possible that, at the end of the monitoring period, a parcel of such group has not yet suffered the event of interest. When that happens, even if the period is extended, there is evidence that an appropriate model for the theoretical survival function of the time until the event occurs would be one model able to bear this kind of data. This class of long duration models will be defined because the form presented by the nonparametric estimation of hazard function in this type of study indicates that the model should be flexible to allow such function to be increasing, decreasing, constant or U-shaped. In this report, we present the long duration modified Weibull model (LDMW) as a proposal to contemplate the issues in the medicine area. The LDMW model has a flexible hazard curve, which enables adjustment when the hazard is decreasing, increasing, U-shaped, unimodal, initially decreasing and posteriorly unimodal and constant. The report also particularizes models already known in the literature that contemplate long duration, such as the long duration Weibull (LDW), long duration Exponential (LDE) and short duration models, such as the modified Weibull (MW), Weibull and Exponential. The simulations showed that the odds of coverage reach the nominal probability of 95% for moderately to big sized samples, that the LDMW p model parameters estimation is costless when compared to the MW and that the selection criteria of the AIC and BIC models are not adequate to discriminate the LDMW model adjustment when compared to the LDW model adjustment for small or moderately sized samples. The LDMW model and its particular cases were adjusted into two sets of real data considering the Classic and Bayesian Inference. The first data set is about the time until the seroreversion of children born from HIV-positive mothers and the second data set is about the recurrence time of breast cancer in women. / Quando um grupo de pacientes é seguido até uma data pré-estabelecida, para a observação do tempo até a ocorrência de um evento, pode acontecer que, na data de término do acompanhamento, uma parcela do grupo não tenha sofrido o evento de interesse. Quando ocorre, ainda que se estenda o prazo, existem indícios de que um modelo adequado para a função de sobrevivência teórica do tempo até a ocorrência do evento seja um modelo que comporte esse tipo de dados. Será definida essa classe de modelos de longa duração, pois a forma apresentada pela estimativa não paramétrica da função de risco, nesse tipo de estudo, indica que o modelo deve ser flexível no sentido de permitir que a função de risco seja uma função crescente, decrescente, constante ou em forma de U. Nesta dissertação, apresenta-se o modelo Weibull modificado de longa duração (WMLD) como proposta para contemplar os problemas na área médica. O modelo WMLD possui curva de risco flexível, possibilitando o ajuste quando há o risco decrescente, crescente, forma de U, unimodal, inicialmente decrescente e, posteriormente, descrevendo forma unimodal e constante. Particulariza modelos já conhecidos na literatura que contemplam a longa duração como o Weibull de longa duração (WLD), exponencial de longa duração (ELD) e modelos de curta duração, como Weibull modificado (WM), Weibull e exponencial. As simulações feitas mostraram que as probabilidades de cobertura atingem a probabilidade nominal de 95% para amostras moderadas a grandes, que não existe custo de estimação do parâmetro p do modelo WMLD, quando comparado com o WLD, e que os critérios de seleção de modelos AIC e BIC não são adequados para discriminar o ajuste do modelo WMLD comparado com o ajuste do modelo WLD, para tamanhos de amostras pequenos ou moderados. Ajustou-se o modelo WMLD e seus casos particulares em dois conjuntos de dados reais, considerando a inferência clássica e a bayesiana. O primeiro conjunto de dados trata-se do tempo até a sororreversão de crianças que nasceram de mães portadoras do vírus HIV e o segundo trata-se do tempo até a recidiva em mulheres com câncer de mama.

Disertacijoje nagrinėjamos dvi iki šiol netyrinėtos problemos: 1. Lietuvių kalbos garsų trukmių prognozavimo modelių kūrimas Iki šiol visi darbai, kuriuose yra nagrinėjamos lietuvių kalbos garsų trukmės, yra atlikti kalbininkų, tačiau šie tyrimai yra daugiau aprašomosios statistikos pobūdžio ir apsiriboja pavienių požymių įtakos garso trukmei analize. Šiame darbe, mašininio mokymo algoritmo pagalba, požymių įtaka garsų trukmei yra išmokstama iš duomenų ir užrašoma sprendimo medžio pavidalu. 2. Nuo kalbos nepriklausomų garsų trukmių prognozavimo modelių kūrimo metodas, naudojant didelės apimties daugelio, kalbėtojų automatiškai, anotuotą garsyną. Dėl skirtingų kalbėtojų tarties specifikos ir dėl automatinio anotavimo netikslumų, kuriant garsų trukmės modelius visame pasaulyje yra apsiribojama vieno kalbėtojo ekspertų anotuotais nedidelės apimties garsynais. Darbe pasiūlyti skirtingų kalbėtojų tarties ypatybių normalizavimo ir garsyno duomenų triukšmo atmetimo algoritmai leidžia garsų trukmių modelių kūrimui naudoti didelės apimties, daugelio kalbėtojų automatiškai anotuotus garsynus. Darbo metu atliktas audicinis tyrimas, kurio pagalba parodoma, kad šnekos signalą sudarančių garsų trukmės turi įtakos klausytojų/respondentų suvokiamam šnekos signalo natūralumui; kontekstinės informacijos panaudojimas garsų trukmių prognozavimo uždavinio sprendime yra svarbus faktorius įtakojantis sintezuotos šnekos natūralumą; natūralaus šnekos signalo atžvilgiu, geriausiai vertinamas yra... [toliau žr. visą tekstą] / Two heretofore unanalyzed aspects are addressed in this dissertation: 1. Building a model capable of predicting phone duration of Lithuanian. All existing investigations of phone durations of Lithuanian were performed by linguists. Usually these investigations are the kind of exploratory statistics and are limited to a single factor, affecting phone duration, analysis. Phone duration dependencies on contextual factors were estimated and written in explicit form (decision tree) in this work by means of machine learning method. 2. Construction of language independent method for creating phone duration models using very large, multi-speaker, automatically annotated speech corpus. Most of the researchers worldwide use speech corpus that are: relatively small scale, single speaker, manually annotated or at least validated by experts. Usually the referred reasons are: using multi-speaker speech corpora is inappropriate because different speakers have different pronunciation manners and speak in different speech rate; automatically annotated corpuses lack accuracy. The created method for phone duration modeling enables the use of such corpus. The main components of the created method are: the reduction of noisy data in speech corpus; normalization of speaker specific phone durations by using phone type clustering. The performed listening tests of synthesized speech, showed that: the perceived naturalness is affected by the underlying phones durations; The use of contextual... [to full text]

Este trabalho apresenta as principais causas para a mortalidade das empresas paulistas criadas entre 2003 e 2007 a partir de base de dados cedida pelo SEBRAE-SP para o desenvolvimento dessa pesquisa. A amostra final, construída a partir de dados disponibilizados pela primeira vez para estudos desta natureza, contou com 662 empresas e 33 variáveis coletadas por meio de questionário aplicado diretamente às próprias empresas. A análise consistiu no teste de modelos econométricos, baseados na literatura dos modelos de duração, de forma a traduzir quais fatores são mais críticos para a sobrevivência das empresas a ponto de distingui-las em dois grupos: o das empresas vencedoras, cuja longevidade está pautada em ações que promovem ganhos de produtividade e eficiência, e aquelas desprovidas dessas ações e que muito provavelmente deixarão o mercado. Os três tipos de modelos abordados neste trabalho - não paramétrico, semi-paramétrico (riscos proporcionais) e paramétrico - apresentaram resultados similares, sendo que na abordagem de riscos proporcionais os resultados foram segmentados por tamanho e setor de atuação das empresas. Para as micro empresas, a idade do empreendedor e a iniciativa em investir na qualificação da mão de obra dos funcionários mostraram-se importantes mitigadores do risco de falha desse grupo de empresa, enquanto que para as pequenas empresas, a inovação em processos e a elaboração de um plano de negócios se destacaram dentre o conjunto de variáveis. Entre empresas dos setores de comércio e serviços, as empresas do primeiro grupo que faziam o acompanhamento das finanças (fluxo de caixa) apresentaram menor risco de falhar. Para aquelas do setor de serviços, a idade do empreendedor, o investimento em qualificação dos funcionários e o tamanho da empresa ao nascer foram importantes para reduzir o risco de falha no tempo. Outro resultado encontrado, por meio do modelo paramétrico utilizando distribuição Weibull, foi que o risco de a empresa deixar o mercado mostrou-se crescente, pelo menos nos cinco primeiros anos de existência da empresa. Entretanto, esse resultado não deve ser generalizado para períodos de tempo maiores que cinco anos. / This thesis presents the main results that determined the bankruptcy of enterprises located in the São Paulo State from 2003 to 2007. The models used in this work were possible due to the partnership with SEBRAE, Small Business Service Supporting, located in the State of São Paulo. This institution provided the data basis for this research and its final version was compound by 662 enterprises and 33 variables, which were collected from a survey done by SEBRAE and the related enterprise. For first time available for research like this The research was supported by econometrics models, more precisely duration models, which identified the most important factors regarding enterprises survival. Two enterprise groups were distinguished: that one that will survive and grow and another will fail. In this work, three models were used: parametric, non-parametric and proportional risk with all of them presenting similar results. The proportional risk approach was applied for economic sectors and enterprises size. For the micro size business, the entrepreneurship\'s age and the resources applied on the employee\'s qualification were important to reduce the risk to fail in the time, whereas for small enterprises, variables like innovation and business plan building were the most important variables. For the commerce and service sectors, the enterprises related to the first one, the enterprises which kept attention on financial results (cash flow) presented lower risk to fail. For service sector, variables such as: entrepreneur\'s age, investment on the employee\'s qualification and enterprise\'s size were the most important variables to explain the difference the risk to fail between the enterprises. Another result presented was the risk to fail, which indicates the likelihood of an enterprise to leave its business activity. In this case, the parametric model using Weibull distribution concluded that the risk grows in the first five years. However, this result must be carefully evaluated since it would be necessary a longer term data to ensure this result.

This dissertation consists of four papers, each with an application of a discrete dependent variable model, censored regression or duration model to a credit market phenomenon or monetary policy question. The first three essays deal with bank lending policy, while the last one studies interest rate policy by Central Banks. In the first essay, a bivariate probit model is estimated to contrast the factors that influence banks’ loan granting decision and individuals’ risk of default. This model is used as a tool to construct a Value at Risk measure of the credit risk involved in a portfolio of consumer loans and to investigate the efficiency of bank lending policy. The second essay takes the conclusions from the first paper as a starting point. It investigates if the fact that banks do not minimize default risk can be explained by the existence of return maximization policy. For this purpose, a Tobit model with sample selection effects and variable censoring limits is developed and estimated on the survival times of consumer loans. The third paper focuses on dormancy, instead of default risk or survival time, as the most important factor affecting risk and return in bank lending. By means of a duration model the factors determining the transition from an active status to dormancy are studied. The estimated model is used to predict the expected durations to dormancy and to analyze the expected profitability for a sample loan applicants. In the fourth paper, the discrete nature of Central Bank interest rate policy is studied. A grouped data model, that can take the long periods of time without changes in the repo rate by the Central Bank into account, is estimated on weekly Swedish data. The model is found to be reasonably good at predicting interest rate changes. / Diss. (sammanfattning) Stockholm : Handelshögsk.

The duration of construction of a project depends on many factors, such as: cost, location, site characteristics, procurement methods, area of construction, footprint of the building and its height, etc. It is very important to be able to predict these durations accurately in order to successfully complete a project on time. Various construction duration estimation tools have been developed to make accurate predictions, as &ldquo / time is money.&rdquo / The main objective of this study was to develop a model that can be used to predict the construction duration of a project in a reliable and practical way. Contractors can thus use a project&#039 / s characteristics, as given in the tender documents, to estimate the actual amount time it would take them to complete the construction works. In this study, factors affecting the duration of a construction project and models for estimating construction durations were investigated. Within this framework, duration estimation models such as / Bromilow&rsquo / s Time-Cost (BTC) Model and Building Cost Information Service (BCIS) Model were used while Simple Linear Regression (SLR) and Multiple Linear Regression (MLR) analyses were conducted on data related to seven case study buildings that are situated at the Middle East Technical University (METU) campus in Ankara. This data was obtained from the Department of Construction and Technical Works (DCTW) at METU. The closeness in estimation of the regression analyses was investigated and finally an MLR model was obtained which was based on two parameters / the area of the building and the area of its fa&ccedil / ade. On the other hand, as opposed to studies reported in literature, the effect of cost on duration was not seen to be significant.

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