Convergence analysis of sampling-based decomposition methods for risk-averse multistage stochastic convex programs

We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.

Discriminação salarial por cor e gênero revisitada: uma abordagem de decomposição contrafactual utilizando regressões quantílicas

A desigualdade salarial, especialmente a resultante da discriminação contra negros e mulheres no mercado de trabalho, é um componente importante da elevada concentração de renda da economia brasileira. Ao contrário da grande maioria dos trabalhos já desenvolvidos nesta área, este trabalho não adota a hipótese de que os efeitos de atributos determinantes do salário são constantes e idênticos para os indivíduos ao longo da distribuição de renda. São estimadas as estruturas salariais para cada percentil da distribuição salarial para homens brancos, homens negros, mulheres brancas e mulheres negras utilizando a técnica de decomposição contrafactual por regressões quantílicas, proposta por Koenker e Bassett (1978) e desenvolvida por Machado e Mata (2004). Isto proporciona uma compreensão mais detalhada e abrangente dos fatores que determinam a remuneração do trabalho para diferentes níveis de renda e fornece uma medida mais completa do grau de discriminação contra os negros e mulheres no mercado de trabalho ao longo da distribuição salarial. Para os três grupos, a discriminação é crescente em relação à posição na distribuição salarial, indicando a dificuldade de se atingir posições melhor remuneradas no mercado de trabalho por parte de mulheres e negros. A discriminação afeta principalmente as mulheres negras, seguidas das mulheres brancas e dos homens negros. Para os homens negros, a discriminação é baixa entre os mais pobres e cresce nos níveis mais altos da distribuição. As mulheres brancas sofrem ao longo de toda a distribuição com maior efeito entre os 15% mais ricos. As mulheres negras sofrem com a discriminação por cor e gênero, estando assim na pior situação entre os grupos. A remuneração da educação estimada para os quatro grupos indica ganhos crescentes conforme a posição na distribuição salarial ampliando a desigualdade salarial intra-grupo, adicionalmente, observa-se uma desvalorização da educação dos negros de ambos os sexos na determinação salarial e que as mulheres sofrem algum tipo de discriminação no que diz respeito à educação apenas nos níveis salariais mais elevados. Os ganhos salariais obtidos com a equalização da escolaridade e formalização entre os grupos discriminados e os homens brancos indicam que, no caso da educação, homens e mulheres negros teriam ganhos ao longo de toda a distribuição, com ênfase entre os mais ricos. Para a formalização, a população nos decis inferiores da distribuição salarial seria a principal beneficiada.

Assessing global economic activity linkages: an empirical exercise based on global autoregressive regression

Economic performance increasingly relies on global economic environment due to the growing importance of trade and nancial links among countries. Literature on growth spillovers shows various gains obtained by this interaction. This work aims at analyzing the possible e ects of a potential economic growth downturn in China, Germany and United States on the growth of other economies. We use global autoregressive regression approach to assess interdependence among countries. Two types of phenomena are simulated. The rst one is a one time shock that hit these economies. Our simulations use a large shock of -2.5 standard deviations, a gure very similar to what we saw back in the 2008 crises. The second experiment simulate the e ect of a hypothetical downturn of the aforementioned economies. Our results suggest that the United States play the role of a global economy a ecting countries across the globe whereas Germany and China play a regional role.

Wald tests for IV regression with weak instruments

This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).

Does absorptive capacity affect project performance? A study based on project management practices, organization learning, and knowledge

The literature has emphasized that absorptive capacity (AC) leads to performance, but in projects its influences still unclear. Additionally, the project success is not well understood by the literature, and AC can be an important mechanism to explain it. Therefore, the purpose of this study is to investigate the effect of absorptive capacity on project performance in the construction industry of São Paulo State. We study this influence through potential and realized absorptive capacity proposed by Zahra and George (2002). For achieving this goal, we use a combination of qualitative and quantitative research. The qualitative research is based on 15 interviews with project managers in different sectors to understand the main constructs and support the next quantitative phase. The content analysis was the technique used to analyze those interviews. In quantitative phase through a survey questionnaire, we collected 157 responses in the construction sector with project managers. The confirmatory factor analysis and hierarchical linear regression were the techniques used to assess the data. Our findings suggest that the realized absorptive capacity has a positive influence on performance, but potential absorptive capacity and the interactions effect have no influence on performance. Moreover, the planning and monitoring have a positive impact on budget and schedule, and customer satisfaction while risk coping capacity has a positive impact on business success. In academics terms, this research enables a better understanding of the importance of absorptive capacity in the construction industry and it confirms that knowledge application in processes and routines enhances performance. For management, the absorptive capacity enables the improvements of internal capabilities reflected in the increased project management efficiency. Indeed, when a company manages project practices efficiently it enhances business and project performance; however, it needs initially to improve its internal abilities to enrich processes and routines through relevant knowledge.

Optimal two-sided tests for instrumental variables regression with heteroskedastic and autocorrelated errors

This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the nite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We introduce two weights which are invariant to orthogonal transformations of the instruments; e.g., changing the order in which the instruments appear. While tests using the MM1 weight can be severely biased, optimal tests based on the MM2 weight are naturally two-sided when errors are homoskedastic. We propose two boundary conditions that yield two-sided tests whether errors are homoskedastic or not. The locally unbiased (LU) condition is related to the power around the null hypothesis and is a weaker requirement than unbiasedness. The strongly unbiased (SU) condition is more restrictive than LU, but the associated WAP tests are easier to implement. Several tests are SU in nite samples or asymptotically, including tests robust to weak IV (such as the Anderson-Rubin, score, conditional quasi-likelihood ratio, and I. Andrews' (2015) PI-CLC tests) and two-sided tests which are optimal when the sample size is large and instruments are strong. We refer to the WAP-SU tests based on our weights as MM1-SU and MM2-SU tests. Dropping the restrictive assumptions of normality and known variance, the theory is shown to remain valid at the cost of asymptotic approximations. The MM2-SU test is optimal under the strong IV asymptotics, and outperforms other existing tests under the weak IV asymptotics.