Mobility and the Return to Education: Testing a Roy Model with Multiple Markets

Self-selected migration presents one potential explanation for why observed returns to a college education in local labor markets vary widely even though U.S. workers are highly mobile. To assess the impact of self-selection on estimated returns, this paper first develops a Roy model of mobility and earnings where workers choose in which of the 50 states (plus the District of Columbia) to live and work. Available estimation methods are either infeasible for a selection model with so many alternatives or place potentially severe restrictions on earnings and the selection process. This paper develops an alternative econometric methodology which combines Lee's (1983) parametric maximum order statistic approach to reduce the dimensionality of the error terms with more recent work on semiparametric estimation of selection models (e.g., Ahn and Powell, 1993). The resulting semiparametric correction is easy to implement and can be adapted to a variety of other polychotomous choice problems. The empirical work, which uses 1990 U.S. Census data, confirms the role of comparative advantage in mobility decisions. The results suggest that self-selection of higher educated individuals to states with higher returns to education generally leads to upward biases in OLS estimates of the returns to education in state-specific labor markets. While the estimated returns to a college education are significantly biased, correcting for the bias does not narrow the range of returns across states. Consistent with the finding that the corrected return to a college education differs across the U.S., the relative state-to-state migration flows of college- versus high school-educated individuals respond strongly to differences in the return to education and amenities across states.Selection Bias, Polychotomous Choice, Roy Model, Return to Education, Migration

RinRuby: Accessing the R Interpreter from Pure Ruby

RinRuby is a Ruby library that integrates the R interpreter in Ruby, making R's statistical routines and graphics available within Ruby. The library consists of a single Ruby script that is simple to install and does not require any special compilation or installation of R. Since the library is 100% pure Ruby, it works on a variety of operating systems, Ruby implementations, and versions of R. RinRuby's methods are simple, making for readable code. This paper describes RinRuby usage, provides comprehensive documentation, gives several examples, and discusses RinRuby's implementation. The latest version of RinRuby can be found at the project website: http://rinruby.ddahl.org/.

Family Violence and Football: The Effect of Unexpected Emotional Cues on Violent Behavior

We study the link between family violence and the emotional cues associated with wins and losses by local professional football teams. We hypothesize that the risk of violence is affected by the 'gain-loss' utility of game outcomes around a rationally expected reference point. Our empirical analysis uses police reports of violent incidents on Sundays during the professional football season. Controlling for the pre-game point spread and the size of the local viewing audience, we find that upset losses (defeats when the home team was predicted to win by 4 or more points) lead to a 10 percent increase in the rate of at-home violence by men against their wives and girlfriends. In contrast, losses when the game was expected to be close have small and insignificant effects. Upset wins (when the home team was predicted to lose) also have little impact on violence, consistent with asymmetry in the gain-loss utility function. The rise in violence after an upset loss is concentrated in a narrow time window near the end of the game, and is larger for more important games. We find no evidence for reference point updating based on the halftime score.reference dependence, gain-loss utility, intimate partner violence

The Demand for Sons: Evidence from Divorce, Fertility, and Shotgun Marriage

This paper shows how parental preferences for sons versus daughters affect divorce, child custody, marriage, shotgun marriage when the sex of the child is known before birth, and fertility stopping rules. We document that parents with girls are significantly more likely to be divorced, that divorced fathers are more likely to have custody of their sons, and that women with only girls are substantially more likely to have never been married. Perhaps the most striking evidence comes from the analysis of shotgun marriages. Among those who have an ultrasound test during their pregnancy, mothers carrying a boy are more likely to be married at delivery. When we turn to fertility, we find that in families with at least two children, the probability of having another child is higher for all-girl families than all-boy families. This preference for sons seems to be largely driven by fathers, with men reporting they would rather have a boy by more than a two to one margin. In the final part of the paper, we compare the effects for the U.S. to five developing countries.

The Impact of Family Income on Child Achievement

Understanding the consequences of growing up poor for a child's well-being is an important research question, but one that is difficult to answer due to the potential endogeneity of family income. Past estimates of the effect of family income on child development have often been plagued by omitted variable bias and measurement error. In this paper, we use a fixed effect instrumental variables strategy to estimate the causal effect of income on children's math and reading achievement. Our primary source of identification comes from the large, non-linear changes in the Earned Income Tax Credit (EITC) over the last two decades. The largest of these changes increased family income by as much as 20%, or approximately $2,100. Using a panel of over 6,000 children matched to their mothers from National Longitudinal Survey of Youth datasets allows us to address problems associated with unobserved heterogeneity and endogenous transitory income shocks as well as measurement error in income. Our baseline estimates imply that a$1,000 increase in income raises math test scores by 2.1% and reading test scores by 3.6% of a standard deviation. The results are even stronger when looking at children from disadvantaged families who are affected most by the large changes in the EITC, and are robust to a variety of alternative specifications.

Some Observations on Transitory Stall in Conical Diffusers

Results from an experimental investigation on the flow through conical diffusers are presented. The mean and fluctuating velocity fields are compared for three diffusers with total diffusion angles of 16, 20 and 24 degrees, in the throat Mach number (M sub t) range of 0.05 to 0.95. Each of the diffusers were 14 cm long and had a 5.08 cm inlet diameter, and the flow exited into the ambient. The boundary layer at the throat was thin with the throat diameter (D sub t) to momentum thickness (O) ratio being as high as 800 at M(sub t) = 0.4. While the 16 deg diffuser flow exited with a top-hat mean velocity profile, increasing losses due to increasing separation resulted in fuller profiles for the 20 and 24 degree cases. A detailed flow field study was conducted for the 16 deg. diffuser. The u'-spectrum, measured at the exit plane, exhibited a peak apparently due to the ensuing jet column instability throughout the M(sub t) range covered. In addition, a much lower frequency spectral peak also occurred in the M(sub t) range of 0.3 to 0.7. Both of the spectral peaks were due to axisymmetric flow fluctuations. A self-sustaining flow oscillation occurred in the M(sub t) range of 0.6 to 0.85, emitting a loud tone, when the jet column instability frequency matched the resonance frequency of the diffuser. Limited data showed that artificial acoustic excitation was effective in reducing the flow fluctuations, with a resultant increase in the pressure recovery, at low M(sub t)

Teaching Reading To Slow Learning Children In The Wilmer Hutchins High School Hutchins, Texas

Teachers find many books and articles written on teaching reading to slow learning children. No other educational skill has received so much emphasis or has been the subject of such a great variety of investigations. There is, however, a volume of books dealing with the reading of children but a scarcity of books dealing directly with the reading of children who are slow learners. Yet, in every classroom, there is a little group of slow learners , that is, children who do not have the capacity to keep up with their classmates and whose problems must be met in some way by their teachers. Slow reading may then have one or more of three main causes. It may be due to inefficient eye movements, excessive vocalizations, or word-for-word reading. These three causes are, of course, interrelated. A child who reads every word as a unit must have many fixations and has time to vocalize if he wishes. Excess vocalization leads to many fixations, and the pupil tends to read syllable by syllable which is even worse than the word-for-word. The child with too many fixations usually vocalizes, and the largest unit he sees at once is a word. In general, the three habits go together, and it is often impossible to tell for any given child which habit comes first, or if all three developed together. The typical slow reader at Wilmer Hutchins High School is not the victim of a single bad habit but the possessor of an unfortunate system of habits, each of which reinforces the other. The whole performance is inefficient because it is clumsy and time-consuming. Even if a child becomes familiar with the techniques, he never gets the degree of comprehension for which his efforts should be rewarded because his technique breaks up reading matter into tiny and meaningless units. Regardless of the method used in teaching slow learners, there are certain matters in which special care must be taken by teachers of slow learning children

Integration of R and Scala Using rscala

The rscala software is a simple, two-way bridge between R and Scala that allows users to leverage the unique strengths of both languages in a single project. Scala classes can be instantiated from R and Scala methods can be called. Arbitrary Scala code can be executed on-the-fly from within R and callbacks to R are supported. R packages can be developed based on Scala. Conversely, rscala also enables R code to be embedded within a Scala application. The rscala package is available from the Comprehensive R Archive Network (CRAN) and has no dependencies beyond base R and the Scala standard library

Using Land Values to Predict Future Farm Income

land values, almon lag, farm profitability, Agribusiness, Agricultural Finance, Farm Management, Financial Economics, Production Economics,