SELECTION BIAS CORRECTIONS BASED ON THE MULTINOMIAL LOGIT MODEL: MONTE CARLO COMPARISONS

Abstract.  This survey presents the set of methods available in the literature on selection bias correction, when selection is specified as a multinomial logit model. It contrasts the underlying assumptions made by the different methods and shows results from a set of Monte Carlo experiments. We find that, in many cases, the approach initiated by Dubin and MacFadden (1984) as well as the semi-parametric alternative recently proposed by Dahl (2002) are to be preferred to the most commonly used Lee (1983) method. We also find that a restriction imposed in the original Dubin and MacFadden paper can be waived to achieve more robust estimators. Monte Carlo experiments also show that selection bias correction based on the multinomial logit model can provide fairly good correction for the outcome equation, even when the IIA hypothesis is violated.     

Conditional Cash Transfers, Schooling, and Child Labor: Micro-Simulating Brazil's Bolsa Escola Program

A growing number of developing economies are providing cashtransfers to poor people that require certain behaviors on theirpart, such as attending school or regularly visiting healthcare facilities. A simple ex ante methodology is proposed forevaluating such programs and used to assess the Bolsa Escolaprogram in Brazil. The results suggest that about 60 percentof poor 10- to 15-year-olds not in school enroll in responseto the program. The program reduces the incidence of povertyby only a little more than one percentage point, however, andthe Gini coefficient falls just half a point. Results are betterfor measures more sensitive to the bottom of the distribution,but the effect is never large.     

The Political Economy of Education and Development in an Open Economy

If the price effect of opening up a developing economy may be expected to act as a disincentive for investment in human capital, the opposite is likely to be true of the income effect, especially in the presence of credit market imperfections among the poor. It is shown in this paper that this may no longer be the case in a society initially dominated by an oligarchic capitalist elite that is afraid of losing its political control in favor of an educated middle class. Although it may sometimes be in its interest to democratize by subsidizing education when the economy is closed, incentives to do so disappear when the economy is open to trade or factor flows.     

Is sustainable growth optimal?

This paper analyzes sustainable growth in a stochastic environment, with human extinction as a possible outcome. The basic constraint of sustainability is that consumption never decreases over an infinite horizon, which requires that the probability of extinction be maintained at zero. We show that this problem can be examined in a standard optimal-growth model. Under certain conditions, the solution of this problem is a corner solution with probability of survival equal to one, at the cost of economic growth. These conditions depend on the initial development level and on the elasticity of utility with respect to consumption. In some circumstances, which depend on the social discount rate, optimal-growth paths do not exist. In these situations, the sustainable-growth concept has a clear autonomy with respect to the usual optimality criterion.     

Inequality of Opportunity in Brazil: A Corrigendum

This note acknowledges and corrects a programming error in our paper “Inequality of Opportunity in Brazil” (Review of Income and Wealth, 53(4), 585–618, 2007). Once the error is corrected, our bounds approach to the identification of individual model parameters in the presence of omitted variable biases is much less useful than indicated in the original paper. In the specific context of the measurement of inequality of opportunity, this implies that the decomposition of overall inequality of opportunity into direct and indirect effects is not reliable. However, the parametric approach introduced in our paper remains useful for obtaining a lower‐bound estimate of overall ex‐ante inequality of opportunity, as proposed by Ferreira and Gignoux (2011).     

Robust Dickey–Fuller tests based on ranks for time series with additive outliers

In this paper the unit root tests proposed by Dickey and Fuller (DF) and their rank counterpart suggested by Breitung and Gouriéroux (J Econom 81(1): 7–27, 1997) (BG) are analytically investigated under the presence of additive outlier (AO) contaminations. The results show that the limiting distribution of the former test is outlier dependent, while the latter one is outlier free. The finite sample size properties of these tests are also investigated under different scenarios of testing contaminated unit root processes. In the empirical study, the alternative DF rank test suggested in Granger and Hallman (J Time Ser Anal 12(3): 207–224, 1991) (GH) is also considered. In Fotopoulos and Ahn (J Time Ser Anal 24(6): 647–662, 2003), these unit root rank tests were analytically and empirically investigated and compared to the DF test, but with outlier-free processes. Thus, the results provided in this paper complement the studies of the previous works, but in the context of time series with additive outliers. Equivalently to DF and Granger and Hallman (J Time Ser Anal 12(3): 207–224, 1991) unit root tests, the BG test shows to be sensitive to AO contaminations, but with less severity. In practical situations where there would be a suspicion of additive outlier, the general conclusion is that the DF and Granger and Hallman (J Time Ser Anal 12(3): 207–224, 1991) unit root tests should be avoided, however, the BG approach can still be used.     

Poisson–geometric INAR(1) process for modeling count time series with overdispersion

In this paper, we propose a new first‐order non‐negative integer‐valued autoregressive [INAR(1)] process with Poisson–geometric marginals based on binomial thinning for modeling integer‐valued time series with overdispersion. Also, the new process has, as a particular case, the Poisson INAR(1) and geometric INAR(1) processes. The main properties of the model are derived, such as probability generating function, moments, conditional distribution, higher‐order moments, and jumps. Estimators for the parameters of process are proposed, and their asymptotic properties are established. Some numerical results of the estimators are presented with a discussion of the obtained results. Applications to two real data sets are given to show the potentiality of the new process.     

Reparameterized inverse gamma regression models with varying precision

In this article, we propose a mean linear regression model where the response variable is inverse gamma distributed using a new parameterization of this distribution that is indexed by mean and precision parameters. The main advantage of our new parametrization is the straightforward interpretation of the regression coefficients in terms of the expectation of the positive response variable, as usual in the context of generalized linear models. The variance function of the proposed model has a quadratic form. The inverse gamma distribution is a member of the exponential family of distributions and has some distributions commonly used for parametric models in survival analysis as special cases. We compare the proposed model to several alternatives and illustrate its advantages and usefulness. With a generalized linear model approach that takes advantage of exponential family properties, we discuss model estimation (by maximum likelihood), black further inferential quantities and diagnostic tools. A Monte Carlo experiment is conducted to evaluate the performances of these estimators in finite samples with a discussion of the obtained results. A real application using minerals data set collected by Department of Mines of the University of Atacama, Chile, is considered to demonstrate the practical potential of the proposed model.     

THE LEVEL OF WORLD INEQUALITY: HOW MUCH CAN ONE SAY?

This paper constructs estimates of income and consumption inequality for the world (124 countries), using various measures of inequality. It then goes on to examine the possible effects of various sources of error in the estimates, and attempts to set rough limits to the size of such effects. Among the sources of error examined are purchasing power parities used for currency conversion, systematic errors in estimates of per capita incomes, differences in age structure, government tax and expenditure policy, and lifetime income effects. The paper concludes that, although the level of uncertainty in the estimates is too great to permit conclusions about, for instance, trends over time, it is clear that the level of world inequality is extreme, and that it is primarily due to differences in average incomes across countries rather than to intra-country inequality.