LANDSAT image differencing as an automated land cover change detection technique

Image differencing was investigated as a technique for use with LANDSAT digital data to delineate areas of land cover change in an urban environment. LANDSAT data collected in April 1973 and April 1975 for Austin, Texas, were geometrically corrected and precisely registered to United States Geological Survey 7.5-minute quadrangle maps. At each pixel location reflectance values for the corresponding bands were subtracted to produce four difference images. Areas of major reflectance differences are isolated by thresholding each of the difference images. The resulting images are combined to obtain an image data set to total change. These areas of reflectance differences were found, in general, to correspond to areas of land cover change. Information on areas of land cover change was incorporated into a procedure to mask out all nonchange areas and perform an unsupervised classification only for data in the change areas. This procedure identified three broad categories: (1) areas of high reflectance (construction or extractive), (2) changes in agricultural areas, and (3) areas of confusion between agricultural and other areas

Noise Infusion as a Confidentiality Protection Measure for Graph-Based Statistics

We use the bipartite graph representation of longitudinally linked employer-employee data, and the associated projections onto the employer and employee nodes, respectively, to characterize the set of potential statistical summaries that the trusted custodian might produce. We consider noise infusion as the primary confidentiality protection method. We show that a relatively straightforward extension of the dynamic noise-infusion method used in the U.S. Census Bureau’s Quarterly Workforce Indicators can be adapted to provide the same confidentiality guarantees for the graph-based statistics: all inputs have been modified by a minimum percentage deviation (i.e., no actual respondent data are used) and, as the number of entities contributing to a particular statistic increases, the accuracy of that statistic approaches the unprotected value. Our method also ensures that the protected statistics will be identical in all releases based on the same inputs

Modeling Endogenous Mobility in Earnings Determination

We evaluate the bias from endogenous job mobility in fixed-effects estimates of worker- and firm-specific earnings heterogeneity using longitudinally linked employer-employee data from the LEHD infrastructure file system of the U.S. Census Bureau. First, we propose two new residual diagnostic tests of the assumption that mobility is exogenous to unmodeled determinants of earnings. Both tests reject exogenous mobility. We relax the exogenous mobility assumptions by modeling the evolution of the matched data as an evolving bipartite graph using a Bayesian latent class framework. Our results suggest that endogenous mobility biases estimated firm effects toward zero. To assess validity, we match our estimates of the wage components to out-of-sample estimates of revenue per worker. The corrected estimates attribute much more of the variation in revenue per worker to variation in match quality and worker quality than the uncorrected estimates

Modeling Endogenous Mobility in Wage Determination

We evaluate the bias from endogenous job mobility in fixed-effects estimates of worker- and firm-specific earnings heterogeneity using longitudinally linked employer-employee data from the LEHD infrastructure file system of the U.S. Census Bureau. First, we propose two new residual diagnostic tests of the assumption that mobility is exogenous to unmodeled determinants of earnings. Both tests reject exogenous mobility. We relax the exogenous mobility assumptions by modeling the evolution of the matched data as an evolving bipartite graph using a Bayesian latent class framework. Our results suggest that endogenous mobility biases estimated firm effects toward zero. To assess validity, we match our estimates of the wage components to out-of-sample estimates of revenue per worker. The corrected estimates attribute much more of the variation in revenue per worker to variation in match quality and worker quality than the uncorrected estimates

Earnings Inequality and Mobility Trends in the United States: Nationally Representative Estimates from Longitudinally Linked Employer-Employee Data

Using earnings data from the U.S. Census Bureau, this paper analyzes the role of the employer in explaining the rise in earnings inequality in the United States. We first establish a consistent frame of analysis appropriate for administrative data used to study earnings inequality. We show that the trends in earnings inequality in the administrative data from the Longitudinal Employer-Household Dynamics Program are inconsistent with other data sources when we do not correct for the presence of misused SSNs. After this correction to the worker frame, we analyze how the earnings distribution has changed in the last decade. We present a decomposition of the year-to-year changes in the earnings distribution from 2004-2013. Even when simplifying these flows to movements between the bottom 20%, the middle 60% and the top 20% of the earnings distribution, about 20.5 million workers undergo a transition each year. Another 19.9 million move between employment and nonemployment. To understand the role of the firm in these transitions, we estimate a model for log earnings with additive fixed worker and firm effects using all jobs held by eligible workers from 2004-2013. We construct a composite log earnings firm component across all jobs for a worker in a given year and a non-firm component. We also construct a skill-type index. We show that, while the difference between working at a low- or middle-paying firm are relatively small, the gains from working at a top-paying firm are large. Specifically, the benefits of working for a high-paying firm are not only realized today, through higher earnings paid to the worker, but also persist through an increase in the probability of upward mobility. High-paying firms facilitate moving workers to the top of the earnings distribution and keeping them there

Technology and the Demand for Skill:An Analysis of Within and Between Firm Differences

We estimate the effects of technology investments on the demand for skilled workers using longitudinally integrated employer-employee data from the U.S. Census Bureau's Longitudinal Employer-Household Dynamics Program infrastructure files spanning two Economic Censuses (1992 and 1997). We estimate the distribution of human capital and its observable and unobservable components within each business for each year from 1992 to 1997. We measure technology using variables from the Annual Survey of Manufactures and the Business Expenditures Survey (services, wholesale and retail trade), both administered during the 1992 Economic Census. Static and partial adjustment models are fit. There is a strong positive empirical relationship between advanced technology and skill in a cross-sectional analysis of businesses in both sectors. The more comprehensive measures of skill reveal that advanced technology interacts with each component of skill quite differently: firms that use advanced technology are more likely to use high-ability workers, but less likely to use high-experience workers. These results hold even when we control for unobservable heterogeneity by means of a selection correction and by using a partial adjustment specification.

Self-handicapping mediates between impulsiveness and self-discipline

Self-handicapping, while not a very acknowledged tendency, is very prevalent today. Especially among students of any grade level, the behavior prevents many from reaching their full potential. The purpose of this experiment was to see how Selfhandicapping mediated between Impulsiveness and Self-discipline which can later be used by teachers to help students with this phenomenon. A short survey was given to psychology undergraduate students at the University of Tennessee-Chattanooga whose age ranged from 18-44 and were predominantly Caucasian. Self-handicapping was found to mediate between Impulsiveness and Self-discipline (r = .512) compared to Impulsiveness and Self-discipline (r= .288) without using self-handicapping as a mediator. The implications that can be taken from this study include using the results in an educational setting to pinpoint selfhandicapping tendencies. Despite limitations in the study, it was conducted in an environment that was cohesive to the environment in which it would be applied