Model selection and error estimation

We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical {\sc vc} dimension, empirical {\sc vc} entropy, andmargin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

Strike outcomes and wage settlements in Spain

This paper analyzes collective bargaining using Spanish firm level data. Centralto the analysis are the joint determination of wage and strike outcomes in adynamic framework and the possibility of segregate wage equation for strike andnon-strike outcomes. Conditional to strikes taking place, we confirm a negativerelationship between strike duration and wage changes in a dynamic context.Furthermore, we find selection in wage equations induced by the strike outcome.In this sense, the possibility of wage determination processes being differentin strike and non-strike samples is not rejected by the data. In particular,wage dynamics are of opposite sing in both strike and non-strike equations.Finally, we find evidence of a 0.33 percentage points wage change strike premium.

Comparing and validating hypothesis test procedures: Graphical and numerical tools

When the behaviour of a specific hypothesis test statistic is studied by aMonte Carlo experiment, the usual way to describe its quality is by givingthe empirical level of the test. As an alternative to this procedure, we usethe empirical distribution of the obtained \emph{p-}values and exploit itsinformation both graphically and numerically.

Correspondence analysis and categorical conjoint measurement

We show the equivalence between the use of correspondence analysis (CA)of concadenated tables and the application of a particular version ofconjoint analysis called categorical conjoint measurement (CCM). Theconnection is established using canonical correlation (CC). The second part introduces the interaction e¤ects in all three variants of theanalysis and shows how to pass between the results of each analysis.

The impact of eliminating a child benefit on birth timing and infant health

We study the effects of the cancellation of a sizeable child benefit in Spainon birth timing and neonatal health. In May 2010, the government announced that a2,500-euro universal "baby bonus" would stop being paid to babies born startingJanuary 1, 2011. We use detailed micro data from birth certificates from 2000 to 2011,and find that more than 2,000 families were able to anticipate the date of birth of theirbabies from (early) January 2011 to (late) December 2010 (for a total of about 10,000births a week nationally). This shifting took place in part via an increase as well as ananticipation of pre-programmed c-sections, seemingly mostly in private clinics. We findthat this shifting of birthdates resulted in a significant increase in the number ofborderline low birth weight babies, as well as a peak in neonatal mortality. The resultssuggest that announcement effects are important, and that families and healthprofessionals may face effective trade-offs when deciding on the timing (and method) ofbirth.

The long-run and intergenerational education impacts of intergovernmental transfers

This paper provides regression discontinuity evidence on long-run and intergenerational education impacts of a temporary increase in federal transfers to local governments in Brazil. Revenues and expenditures of the communities benefiting from extra transfers temporarily increased by about 20% during the 4 year period from 1982 to the end of 1985. Schooling and literacy gains for directly exposed cohorts established in previous work that used the 1991 census are attenuated but persist in the 2000 and 2010 censuses. Children and adolescents of the next generation --born after the extra funding had disappeared-- show gains of about 0.08 standard deviation across the entire score distribution of two nationwide exams at the end of the 2000s. While we find no evidence of persistent improvements in school resources, we document discontinuities in education levels, literacy rates and incomes of test takers' parents that are consistent with intergenerational human capital spillovers.

The changing relationship between commodity prices and equity prices in commodity exporting

We explore the linkage between equity and commodity markets, focusing in particular on its evolution over time. We document that a country's equity market valuehas significant out-of-sample predictive ability for the future global commodity priceindex for several primary commodity-exporting countries. The out-of-sample predictive ability of the equity market appears around 2000s. The results are robust to usingseveral control variables as well as firm-level equity data. Finally, our results indicatethat exchange rates are a better predictor of commodity prices than equity markets,especially at very short horizons.

Univariate versus multivariate modeling of panel data

Panel data can be arranged into a matrix in two ways, called 'long' and 'wide' formats (LFand WF). The two formats suggest two alternative model approaches for analyzing paneldata: (i) univariate regression with varying intercept; and (ii) multivariate regression withlatent variables (a particular case of structural equation model, SEM). The present papercompares the two approaches showing in which circumstances they yield equivalent?insome cases, even numerically equal?results. We show that the univariate approach givesresults equivalent to the multivariate approach when restrictions of time invariance (inthe paper, the TI assumption) are imposed on the parameters of the multivariate model.It is shown that the restrictions implicit in the univariate approach can be assessed bychi-square difference testing of two nested multivariate models. In addition, commontests encountered in the econometric analysis of panel data, such as the Hausman test, areshown to have an equivalent representation as chi-square difference tests. Commonalitiesand differences between the univariate and multivariate approaches are illustrated usingan empirical panel data set of firms' profitability as well as a simulated panel data.

Complementarities between mathematical and computational modeling: the case of the repeated Prisoners' Dilemma

We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the mathematical model. Our main conclusion is that mathematical and computational models are good complements for research in social sciences. Indeed, while computational models are extremely useful to extend the scope of the analysis to complex scenarios hard to analyze mathematically, formal models can be useful to verify and to explain the outcomes of computational models.

The European Union in North Korea: Current Realities and Paths for Future Engagement – A Qualitative and Quantitative Study

Malgrat la rellevància estratègica i el paper desestabilitzador de Corea del Nord a la regió econòmicament més dinàmica del món, la UE no compta amb cap estratègia clara per involucrar-se amb aquest país. Combinant tècniques d’anàlisi qualitatives i quantitatives, aquest treball pretén descobrir possibles contradiccions internes que impedeixin la definició d'una política exterior europea coherent i efectiva amb respecte a Corea del Nord, així com discrepàncies entre les percepcions d’actors interns de la UE i les d’actors externs. S'han detectat importants diferències d’expectatives i mancances en termes de coherència, tant entre les visions expressades pels actors interns com entre les opinions d’aquests actors i les dels futurs líders sudcoreans enquestats – diferències que fins i tot afecten la promoció dels drets humans

The achievable region approach to the optimal control of stochastic systems

The achievable region approach seeks solutions to stochastic optimisation problems by: (i) characterising the space of all possible performances(the achievable region) of the system of interest, and (ii) optimisingthe overall system-wide performance objective over this space. This isradically different from conventional formulations based on dynamicprogramming. The approach is explained with reference to a simpletwo-class queueing system. Powerful new methodologies due to the authorsand co-workers are deployed to analyse a general multiclass queueingsystem with parallel servers and then to develop an approach to optimalload distribution across a network of interconnected stations. Finally,the approach is used for the first time to analyse a class of intensitycontrol problems.

Doctors without borders: The returns to an occupational license for Soviet immigrant physicians in Israel

Re-licensing requirements for professionals that move across borders arewidespread. In this paper, we measure the returns to an occupationallicense using novel data on Soviet trained physicians that immigrated toIsrael. An immigrant re-training assignment rule used by the IsraelMinistry of Health provides an exogenous source of variation inre-licensing outcomes. Instrumental variables and quantile treatmenteffects estimates of the returns to an occupational license indicate excesswages due to occupational entry restrictions and negative selectioninto licensing status. We develop a model of optimal license acquisitionwhich suggests that the wages of high-skilled immigrant physicians in thenonphysician sector outweigh the lower direct costs that these immigrantsface in acquiring a medical license. Licensing thus leads to lower averagequality of service. However, the positive earnings effect of entry restrictionsfar outweighs the lower practitioner quality earnings effect that licensinginduces.

Strategies for sequential prediction of stationary time series

We present simple procedures for the prediction of a real valued sequence. The algorithms are based on a combinationof several simple predictors. We show that if the sequence is a realization of a bounded stationary and ergodic random process then the average of squared errors converges, almost surely, to that of the optimum, given by the Bayes predictor. We offer an analog result for the prediction of stationary gaussian processes.

A subsampling approach to estimating the distribution of diversing statistics with application to assessing financial market risks

In this paper we propose a subsampling estimator for the distribution ofstatistics diverging at either known rates when the underlying timeseries in strictly stationary abd strong mixing. Based on our results weprovide a detailed discussion how to estimate extreme order statisticswith dependent data and present two applications to assessing financialmarket risk. Our method performs well in estimating Value at Risk andprovides a superior alternative to Hill's estimator in operationalizingSafety First portofolio selection.

Weak approximations. A Malliavin calculus approach

We introduce a variation of the proof for weak approximations that issuitable for studying the densities of stochastic processes which areevaluations of the flow generated by a stochastic differential equation on a random variable that maybe anticipating. Our main assumption is that the process and the initial random variable have to be smooth in the Malliavin sense. Furthermore if the inverse of the Malliavin covariance matrix associated with the process under consideration is sufficiently integrable then approximations fordensities and distributions can also be achieved. We apply theseideas to the case of stochastic differential equations with boundaryconditions and the composition of two diffusions.