Measuring Employment and Income for Low-Income Populations with Administrative and Survey Data

We discuss the strengths and weaknesses of income and employment data in national surveys, in unemployment insurance (UI) wage records, and in tax returns. The CPS, SIPP, NLS, and PSID surveys provide valuable information on the behavior of the low-income population. They have broad and fairly accurate measures of income for national samples, and their focus on families as the unit of analysis and their ease of access greatly enhance their value. The value of these data sets for evaluating welfare reform is severely limited, however. With the devolution of responsibility for TANF, the CPS and SIPP sampling frames and sample sizes mean that, at best, they can be only supplementary data sources for understanding the effects of welfare reform at the state and local levels. The apparent decline in program coverage in the CPS is also worrisome. UI data are available at the state level and can be matched to individuals in existing samples at relatively low cost. It is straightforward to do follow-up analyses on income and employment for workers who remain in the state, and UI data are timely. However, earnings are available only for individuals, while changes in family composition upon exit from welfare have been shown to have a large bearing on economic well-being. UI data do not allow us to track these changes. There also appears to be a substantial problem with some workers being classified as independent contractors and hence not entering the UI system. Overall gaps in coverage appear to be at least 13 percent and may be significantly higher. Even when wages are reported, there is some evidence that they are understated by a significant amount. We also present evidence on the degree to which tax data can be used to understand the incomes and employment of low-skilled workers. The paper concludes with brief recommendations for future research that might help fill some of the gaps we have identified.

Representation by Integrating Reproducing Kernels

Based on direct integrals, a framework allowing to integrate a parametrised family of reproducing kernels with respect to some measure on the parameter space is developed. By pointwise integration, one obtains again a reproducing kernel whose corresponding Hilbert space is given as the image of the direct integral of the individual Hilbert spaces under the summation operator. This generalises the well-known results for finite sums of reproducing kernels; however, many more special cases are subsumed under this approach: so-called Mercer kernels obtained through series expansions; kernels generated by integral transforms; mixtures of positive definite functions; and in particular scale-mixtures of radial basis functions. This opens new vistas into known results, e.g. generalising the Kramer sampling theorem; it also offers interesting connections between measurements and integral transforms, e.g. allowing to apply the representer theorem in certain inverse problems, or bounding the pointwise error in the image domain when observing the pre-image under an integral transform

The High Speed Water Tunnel three-component balance

An experimental program was initiated in the High Speed Water Tunnel to measure force coefficients for hydrofoils under cavitating conditions. This program necessitated either a new force balance or a major modification of the existing one. Various balance configurations and pressure seal designs which were considered are described. A balance modification design was selected which consists of an appendage bolted between the existing balance and the water tunnel working section. This appendage alters the basic geometry of the force balance so that the model is now mounted on a parallelogram linkage instead of on a simple pivoted lever. The addition of the parallelogram force table suspension to the old balance renders the modified balance unresponsive to moments which in the old balance, interacted with forces and resulted in errors in the force readings. This modification which is described in detail was accomplished and resulted in a successful force balance capable of accurate measurement of forces on cavitating and noncavitating hydrofoils; and, in fact, it is expected to replace the old force balance for all force measurement work in the High Speed Water Tunnel. The cost and construction time for the balance modification were considerably less than would have been required for an entirely new force balance of comparable accuracy and sensitivity

Research turbine for high temperature core engine application. 1: Cold-airoverall performance of solid scaled turbine

A solid, half-scale model of a 50.8-cm (20-in) research turbine designed for a high temperature core engine application was investigated over a range of speeds and pressure ratios. The results of this test are presented. The effect of rotor blade twist was also investigated. At the design equivalent speed and specific work output, the total efficiency of the turbine with untwisted rotor blades was 87.1 percent; at the same pressure ratio the efficiency of the turbine with twisted rotor blades was 88.0 percent

Cold-air performance of a tip turbine designed to drive a lift fan

Performance was obtained over a range of speeds and pressure ratios for a 0.4 linear scale version of the LF460 lift fan turbine with the rotor radial tip clearance reduced to about 2.5 percent of the rotor blade height. These tests covered a range of speeds from 60 to 140 percent of design equivalent speed and a range of scroll inlet total to diffuser exit static pressure ratios from 2.6 to 4.2. Results are presented in terms of equivalent mass flow, equivalent torque, equivalent specific work, and efficiency

Mean-Field Theory of Meta-Learning

We discuss here the mean-field theory for a cellular automata model of meta-learning. The meta-learning is the process of combining outcomes of individual learning procedures in order to determine the final decision with higher accuracy than any single learning method. Our method is constructed from an ensemble of interacting, learning agents, that acquire and process incoming information using various types, or different versions of machine learning algorithms. The abstract learning space, where all agents are located, is constructed here using a fully connected model that couples all agents with random strength values. The cellular automata network simulates the higher level integration of information acquired from the independent learning trials. The final classification of incoming input data is therefore defined as the stationary state of the meta-learning system using simple majority rule, yet the minority clusters that share opposite classification outcome can be observed in the system. Therefore, the probability of selecting proper class for a given input data, can be estimated even without the prior knowledge of its affiliation. The fuzzy logic can be easily introduced into the system, even if learning agents are build from simple binary classification machine learning algorithms by calculating the percentage of agreeing agents.Comment: 23 page

Cold-air investigation of a 4 1/2 stage turbine with stage-loading factor of 4.66 and high specific work output. 2: Stage group performance

The stage group performance of a 4 1/2 stage turbine with an average stage loading factor of 4.66 and high specific work output was determined in cold air at design equivalent speed. The four stage turbine configuration produced design equivalent work output with an efficiency of 0.856; a barely discernible difference from the 0.855 obtained for the complete 4 1/2 stage turbine in a previous investigation. The turbine was designed and the procedure embodied the following design features: (1) controlled vortex flow, (2) tailored radial work distribution, and (3) control of the location of the boundary-layer transition point on the airfoil suction surface. The efficiency forecast for the 4 1/2 stage turbine was 0.886, and the value predicted using a reference method was 0.862. The stage group performance results were used to determine the individual stage efficiencies for the condition at which design 4 1/2 stage work output was obtained. The efficiencies of stages one and four were about 0.020 lower than the predicted value, that of stage two was 0.014 lower, and that of stage three was about equal to the predicted value. Thus all the stages operated reasonably close to their expected performance levels, and the overall (4 1/2 stage) performance was not degraded by any particularly inefficient component

Cold air investigation of 4 1/2-stage turbine with stage loading factor of 4.66 and high specific work output. 1: Overall performance

The turbine developed design specific work output at design speed at a total pressure ratio of 6.745 with a corresponding efficiency of 0.855. The efficiency (0.855)was 3.1 points lower than the estimated efficiency quoted by the contractor in the design report and 0.7 of a point lower than that determined by a reference prediction method. The performance of the turbine, which was a forced vortex design, agreed with the performance determined by the prediction method to about the same extent as did the performance of three reference high stage loading factor turbines, which were free vortex designs