Child support enforcement for teenage fathers: Problems and prospects

The NLSY data indicate that about 7.3 percent of teenage males become fathers and that very few of these fathers live with their children. Father absence and the concurrent increase in female-headed households are closely associated with the impoverishment of children. Most absent teen fathers never come into contact with the child support enforcement program, and the extent to which they financially support their children informally is not well understood. While the income of absent teen fathers is low in the teen years, it increases over time, as does the potential for collecting child support. Nevertheless, men who were absent teen fathers earn less in early adulthood than men who deferred parenting until age twenty or later and teen fathers who lived with their children. Early establishment of paternity and greater standardization in the treatment of adolescent fathers by the child support enforcement program are recommended. Further, the substantial and persistent income deficit experienced by adolescent fathers who live apart from their children raises an interesting dilemma. While children may benefit financially and psychosocially from living with two parents, the lower income of men who were absent teenage fathers may make them poor marital prospects. This raises doubts about the recent recommendations of some scholars that we should bring back the shotgun wedding.

Understanding USDA Corn and Soybean Production Forecasts: Methods, Performance and Market Impacts over 1970 - 2005

The purpose of this report is to improve understanding of USDA crop forecasting methods, performance and market impact. A review of USDA’s forecasting procedures and methodology confirmed the objectivity and consistency of the forecasting process over time. Month-to-month changes in corn and soybean production forecasts from 1970 through 2005 indicated little difference in magnitude and direction of monthly changes over time. USDA production forecast errors were largest in August and smaller in subsequent forecasts. There appeared to be no trend in the size or direction of forecast errors over time. On average, USDA corn production forecasts were more accurate than private market forecasts over 1970-2005, with the exception of August forecasts since the mid-1980s. The forecasting comparisons for soybeans were somewhat sensitive to the measure of forecast accuracy considered. One measure showed that private market forecasts were more accurate than USDA forecasts for August regardless of the time period considered. Another measure showed just the opposite. As the growing season progresses the difference in the results across the two measures of forecast accuracy diminished, with USDA forecast errors in soybeans about equal to or smaller than private market errors. USDA corn production forecasts had the largest impact on corn futures prices in August and recent price reactions have been somewhat larger than historical reactions. Similar to corn, USDA soybean production forecasts had the largest impact on soybean futures prices in August with recent price reactions appearing somewhat larger than in the past. Overall, the analysis suggests that over the long-run the USDA performs reasonably well in generating crop production forecasts for corn and soybeans.Agricultural Finance,

2007 U.S CORN PRODUCTION RISKS: WHAT DOES HISTORY TEACH US?

Financial Economics, Production Economics, Risk and Uncertainty,

Understanding USDA Corn and Soybean Production Forecasts: An Overview of Methods, Performance and Market Impacts

Agricultural Finance,

Market Instability in a New Era of Corn, Soybean, and Wheat Prices

grain, price, increase, trend, Demand and Price Analysis, Marketing, Q11, Q13,

The performance of modularity maximization in practical contexts

Although widely used in practice, the behavior and accuracy of the popular module identification technique called modularity maximization is not well understood in practical contexts. Here, we present a broad characterization of its performance in such situations. First, we revisit and clarify the resolution limit phenomenon for modularity maximization. Second, we show that the modularity function Q exhibits extreme degeneracies: it typically admits an exponential number of distinct high-scoring solutions and typically lacks a clear global maximum. Third, we derive the limiting behavior of the maximum modularity Q_max for one model of infinitely modular networks, showing that it depends strongly both on the size of the network and on the number of modules it contains. Finally, using three real-world metabolic networks as examples, we show that the degenerate solutions can fundamentally disagree on many, but not all, partition properties such as the composition of the largest modules and the distribution of module sizes. These results imply that the output of any modularity maximization procedure should be interpreted cautiously in scientific contexts. They also explain why many heuristics are often successful at finding high-scoring partitions in practice and why different heuristics can disagree on the modular structure of the same network. We conclude by discussing avenues for mitigating some of these behaviors, such as combining information from many degenerate solutions or using generative models.Comment: 20 pages, 14 figures, 6 appendices; code available at http://www.santafe.edu/~aaronc/modularity