Inequality, Productivity, and Child Labor: Theory and Evidence

A recent theoretical literature has linked reductions in income inequality to reductions in child labor in countries that are relatively well-off, but has not explored how income distribution affects child labor in very poor countries. We show that while in higher-productivity countries with child labor, a more equal income distribution will reduce or eliminate child labor, in low productivity countries, a more equal distribution of income will exacerbate child labor. Econometric specifications studying child labor among 10- to-14 year olds yield results generally consistent with these predictions. Policy actions that aim to bring about more equality so as to reduce child labor will likely not have the desired effect unless a country in which they are taken is sufficiently wealthy.

Does Child Labor Decrease When Parental Incomes Rises

In the presence of two-sided altruism, i.e., when parents and children care about each other's utility, increases in parental income need not always lead to increases in schooling and to decreases in child labor. This surprising result derives from the systematic way capital market constraints bind as parental income rises: child labor increases as soon as parental income rises by enough to eliminate transfers from children to parents.

A Theory of Exploitative Child Labor

We develop a model of exploitative child labor with two key features: first, parents have imperfect information about whether employment opportunities available to their children are exploitative or not. Second, firms choose whether or not to exploit their child workers. In our model, a ban on exploitative child labor is desirable, because it resolves the problem of imperfect information faced by parents, and therefore leads to Pareto efficiency. We also find that a ban leads to an increase in the wages of child workers, and that firm profits, even for firms that do not exploit child workers, fall. Finally, a ban has ambiguous effects at the macroeconomic level: aggregate child employment and aggregate output can rise or fall.

A Theory of Exploitative Child Labor

We develop a model of exploitative child labor with two key features: first, parents have imperfect information about whether employment opportunities available to their children are exploitative or not. Second, firms choose whether or not to exploit their child workers. In our model, a ban on exploitative child labor is desirable, because it resolves the problem of imperfect information faced by parents, and therefore leads to Pareto efficiency. We also find that a ban leads to an increase in the wages of child workers, and that firm profits, even for firms that do not exploit child workers, fall. Finally, a ban has ambiguous effects at the macroeconomic level: aggregate child employment and aggregate output can rise or fall.child labor, economic exploitation

A Theory of Exploitative Child Labor

Child labor laws should aim to protect children who work, instead of trying to remove children from work. In this paper, we identify an instance when the risk of exploitation lowers the expected bene…t of child labor to the child,and therefore suppresses child labor force participation. Targeted legal intervention that lowers or removes the risk of exploitation raises child participation in the labor market, child welfare, and overall societal welfare. Targeting on child labor more broadly may reduce child labor force participation, child welfare, and overall societal welfare. Our key assumptions for generating these results are that parents decide for each child based on their child's best interest, that parents face imperfect information about the risks their children confront upon entering the labor market, and that firms may choose to exploit this information imperfection by employing children under forced-labor-type conditions.child labor, exploitation

Slave Redemption When it Takes Time to Redeem Slaves

We analyze slave redemption programs—the buying of slaves to give them their freedom--in a simple matching model, i.e., under the assumption that it takes time to find slaves to buy or sell. Unlike in a supply and demand framework, where sufficiently large and effective redemption programs must lead to an increase in the price at which slaves are exchanged, we find that such programs do not necessarily raise the price of slaves. We also use the model to explain why a slave redemption program can slow the flow of people into the actual state of slavery, but at the same time can increase the number of people captured to be slaves. We present contemporary examples to suggest that the weight that should be assigned to costs inflicted on the extra captured people, versus the benefits enjoyed by those redeemed, depends critically on the nature of the experience at, and just after, capture.slavery, matching models

Lesbian, Gay, and Bisexual Voters in the 2000 US Presidential Election

Lesbians, gay men, and bisexuals (LGBs) in the United States are strikingly more likely to vote for Democratic presidential candidates than are heterosexuals. LGBs are one of the Democratic Party’s most loyal voting blocs, despite the absence of one of the most important mechanisms for creating party identification: inter-generational transmission. We use the 2000 Presidential election to examine whether LGB voters overwhelmingly chose Al Gore because they viewed him as superior to George W. Bush on LGB-related policy issues or because of their greater overall liberalism and Democratic Party identification. We also examine the impact of socialization within the LGB community for generating political liberalism, Democratic Party identification, and interest in LGB policies. Using logit analysis on a 2000 Harris Interactive poll of 13,000 Americans, including 1,000 LGBs, we find that concern for LGB rights, policy liberalism, and party identification all played a role in the LGB vote. Analysis of the LGB sub-sample supports a model of political socialization within the LGB community leading to stronger interest in LGB rights, liberalism, Democratic party identification, and support for Gore

Summary Report of Mission Acceleration Measurements for STS-79. Launched 16 Sep. 1996

The Space Acceleration Measurement System (SAMS) collected acceleration data in support of the Mechanics of Granular Materials experiment during the STS-79 Mir docking mission, September 1996. STS-79 was the first opportunity to record SAMS data on an Orbiter while it was docked to Mir. Crew exercise activities in the Atlantis middeck and the Mir base module are apparent in the data. The acceleration signals related to the Enhanced Orbiter Refrigerator Freezer had different characteristics when comparing the data recorded on Atlantis on STS-79 with the data recorded on Mir during STS-74. This is probably due, at least in part, to different transmission paths and SAMS sensor head mounting mechanisms. Data collected on Atlantis during the STS-79 docking indicate that accelerations due to vehicle and solar array structural modes from Mir transfer to Atlantis and that the structural modes of the Atlantis-Mir complex are different from those of either vehicle independently. A 0.18 Hz component of the SAMS data, present while the two vehicles were docked, was probably caused by the Mir solar arrays. Compared to Atlantis structural modes of about 3.9 and 4.9 Hz, the Atlantis-Mir complex has structural components of about 4.5 and 5.1 Hz. After docking, apparent structural modes appeared in the data at about 0.8 and 1.8 Hz. The appearance, disappearance, and change in the structural modes during the docking and undocking phases of the joint Atlantis-Mir operations indicates that the structural modes of the two spacecraft have an effect on the microgravity environment of each other. The transfer of structural and equipment related accelerations between vehicles is something that should be considered in the International Space Station era

Malware Type Recognition and Cyber Situational Awareness

Current technologies for computer network and host defense do not provide suitable information to support strategic and tactical decision making processes. Although pattern-based malware detection is an active research area, the additional context of the type of malware can improve cyber situational awareness. This additional context is an indicator of threat capability thus allowing organizations to assess information losses and focus response actions appropriately. Malware Type Recognition (MaTR) is a research initiative extending detection technologies to provide the additional context of malware types using only static heuristics. Test results with MaTR demonstrate over a 99% accurate detection rate and 59% test accuracy in malware typing