Do extended school day programs affect performance in college admission tests?

We assess the effects of a Brazilian extended high school day program on college admission test scores. The program entails an increase in Math/Science and Language class time, and the introduction of extra-class activity time. We exploit variation in program implementation timing to apply a difference-in-differences strategy and an event-study approach. Results show positive large effects on test scores and suggest that these effects are likely driven by increased class and extra-class activity hours. Moreover, the program affects not only scores in subjects for which it contemplates increased class time, but also in Humanities. Finally, we are able to show that increased time dedicated to academic-related extra-class activities works as a multiplier of program effects. In fact, these additional hours spent in complementary activities make the magnitude of program effects double from 0.092-0.150 to 0.180-0.317 standard deviation.

Decomposing public-private teachers’ wage gap: evidence from Brazil

A two-stage wage gap decomposition permits measuring the contribution of observableand unobservable characteristics of the wage gap formation and evolution comparingteachers’ earnings in the public and private sectors from 2006 to 2017. Teachers fromthe public sector earn more than the ones from the private sector at mean, median, andquantile 10 due to the composition effect. The analysis across levels of education showsthat the composition effect is important in explaining the wage gap in early childhoodeducation while the structure effect is more relevant to the wage gap decomposition inprimary and high school education.

What Drives the Nominal Yield Curve in Brazil?

This paper describes the dynamics of the level, slope and curvature of the Brazilian nominal yield curve using only observable macroeconomic indicators. The model is able to explain 94.5% of the variation in the yield curve. We find that the main drivers of the level factor is the Brazil risk premium (5-year CDS spread) and the unemployment rate. In turn, the slope steepens with increases either in the SELIC rate or in the spot exchange rate, and flattens with increases in unemployment rate and commodity returns. Lastly, the curvature increases with the unemployment, inflation and SELIC rates, but decreases with changes in the exchange rate.

Monte Carlo Test for Stochastic Trend in Space State Models for the Location-Scale Family

In space state models for time series, a key point is the decision between modeling the trend of non-stationary processes through a deterministic or a stochastic term. The present paper introduces a Monte Carlo hypothesis test procedure to guide in such a decision. The method works for any time series distribution belonging to the location-scale family. The proposed method provides an alpha-level test for any time series of length greater than 3 and it does not demand assumptions on the distribution of the trend term when it is actually stochastic.

Evaluating the performance of degrees of freedom estimation in asymmetric GARCH models with t-student innovations

This work investigates the effects of using the independent Jeffreys prior for the degrees of freedom parameter of a t-student model in the asymmetric generalised autoregressive conditional heteroskedasticity (GARCH) model. To capture asymmetry in the reaction to past shocks, smooth transition models are assumed for the variance. We adopt the fully Bayesian approach for inference, prediction and model selection We discuss problems related to the estimation of degrees of freedom in the Student-t model and propose a solution based on independent Jeffreys priors which correct problems in the likelihood function. A simulated study is presented to investigate how the estimation of model parameters in the t-student GARCH model are affected by small sample sizes, prior distributions and misspecification regarding the sampling distribution. An application to the Dow Jones stock market data illustrates the usefulness of the asymmetric GARCH model with t-student errors.

Country risk for emerging economies: a dynamical index proposal with a case study.

We introduce a dynamical country risk index for emerging economies. The proposal is based on the intensity approach of credit risk, i.e. the default is the first jump of a point process with stochastic intensity. Two different models are used to estimate the yield spread. They differ in the relationship between the default-free instantaneous interest rate process and the intensity process. The dynamics of the interest rates is modeled through a multidimensional affine model, and the Kalman filter with an Expectation-Maximization algorithm is used to calibrate it. The USD interest rates constitute part of the input of the model, while prices of relevant domestic bonds in the emerging market complete the input. For an application, we select the Uruguayan bond market as the emerging economy.

Effects of asset frequency components on value-at-risk in emerging and developed markets

<p>Value-at-Risk was estimated using the technique of wavelet decomposition with goal to analyze the frequency components' impacts on variances of daily stock returns, and on forecasts. Daily returns of twenty-one shares of the Ibovespa and daily returns of twenty-two shares of the DJIA were used. The model was applied to the reconstructed returns to model and establish the prediction of conditional variance, applying the rolling window technique. The Value-at-Risk was then estimated, and the results showed that the DJIA shares showed more efficient market behavior than those of Ibovespa. The differences in behavior induces to affirm that VaRs, used in the analysis of financial assets from different markets with different governance premises, should be estimated by series of returns reconstructed by aggregations of components of different frequencies. A set of back-testing was applied to confront the estimated , which demonstrated that the estimation of models are consistent.</p>

Evidence on search costs under hyperinflation in Brazil: The effect of Plano Real

<p>Plano Real put an end to hyperinflation in 1994 and significantly altered price-setting behavior in Brazil. This paper investigates the impact of Plano Real on search frictions. We estimate a nonsequential search model for homogeneous goods to structurally retrieve consumers' search costs. The dataset comprises 11,673 store-level price quotes collected from 1993 to 1995 by FIPE to calculate the Consumer Price Index (CPI) in the city of São Paulo. The strategy consists of using Plano Real as a structural breakpoint in the data. We estimate the model splitting the data into before (Jan-93 to Jun-94) and after (Aug-94 to Dec-95) the plan, and we find evidence on first-order stochastic dominance of the search-cost distribution of the former into the latter; that is, search costs are higher during hyperinflation. The majority of consumers search only once or twice before buying an item, but this share is marginally higher during hyperinflation (84% vs 79%). In addition, after Plano Real, a larger share of consumers are willing to quote prices in all stores before committing to a purchase. We also document evidence of the effect of the plan on shrinking price-cost margins. When searching is less costly, stores lose market power.</p>

Incentives in Brazilian Bolsa Família CCT Program: Adverse selection, moral hazard, improving mechanisms and simulations

The <em>Bolsa Família</em> CCT Program (BFP) has successfully reduced poverty in Brazil. However, the theoretical literature on associated economic incentives is scarce. A mechanism-design analysis identifies problems of adverse selection and moral hazard in the BFP. The paper proposes simple improving incentive-mechanisms. The Citizens’ Contribution Mechanism (CCM) requires beneficiaries to devote time to the PBF encouraging recipients with higher income to leave. The Graduation Mechanism (GM) offers financial incentives to ensure sustainable emancipation of qualified beneficiaries. The Human Capital Incentive Mechanism (HCM) increases transfers to efficient municipalities. We show that the CCM solves the adverse selection problem, the GM solves the moral hazard problem of beneficiaries and the HCM solves a moral hazard problem of local managers. A simulation based on 2010 census data shows that the mechanisms allow, within 6 years, significant increases in the reach and precision of the PBF and yields cost reductions of over R$4.6 billion.