The Deterrence Effect of Prison: Dynamic Theory and Evidence

Using administrative, longitudinal data on felony arrests in Florida, we exploit the discontinuous increase in the punitiveness of criminal sanctions at 18 to estimate the deterrence effect of incarceration. Our analysis suggests a 2 percent decline in the log-odds of offending at 18, with standard errors ruling out declines of 11 percent or more. We interpret these magnitudes using a stochastic dynamic extension of Becker’s (1968) model of criminal behavior. Calibrating the model to match key empirical moments, we conclude that deterrence elasticities with respect to sentence lengths are no more negative than -0.13 for young offenders.Prison, crime, deterrence, incarceration

Crime, Punishment, and Myopia

Economic theory predicts that increasing the severity of punishments will deter criminal behavior by raising the expected price of committing crime. This implicit price can be substantially raised by making prison sentences longer, but only if offenders' discount rates are relatively low. We use a large sample of felony arrests to measure the deterrence effect of criminal sanctions. We exploit the fact that young offenders are legally treated as adults--and face longer lengths of incarceration--the day they turn 18. Sufficiently patient individuals should therefore significantly lower their offending rates immediately upon turning 18. The small behavioral responses that we estimate suggest that potential offenders are extremely impatient, myopic, or both.

Spatially Separable Blind Deconvolution of Long Exposure Astronomical Imagery

In this thesis, a spatially separable blind deconvolution algorithm is demonstrated that achieves a significantly faster processing time and superior sensitivity when processing long-exposure image data of unresolvable objects from a ground-based telescope. The proposed approach takes advantage of the structure of the long exposure point spread functions radial symmetric characteristics to approximate it as a product of one dimensional horizontal and vertical intensity distributions. Objects at geosynchronous or geostationary orbit also can be well approximated as being spatially separable as they are, in general non-resolvable. The algorithms performance is measured by computing the mean-squared error compared with the true object as well as the processing time required to perform the blind deconvolution. It will be shown that images processed by the proposed technique will possess, on average, a lower mean-squared error than images that are processed through the traditional two-dimensional blind deconvolution approach. In addition, the one dimensional will be shown to perform the deconvolution significantly faster. In both cases the seeing parameter, and thus the point spread function, is treated as an unknown variable in the image reconstruction problem

Three dimensional echocardiography in valvular heart disease

Although cardiac structures exist in three dimensions, two dimensional (2-D) echocardiography only provides information in a single tomographic plane, the orientation of which is determined by the ultrasound window. Accordingly the use of geometric assumptions and/or mental integration of information from multiple 2-D images are needed to assess cardiac function and structure. Advances in ultrasound technology and image reconstruction have opened up the possibility of using three dimensional (3-D) techniques in both quantitative applications such as measurement of ventricular volumes and qualitative applications such as the assessment of valve stenosis or regurgitation. Further technical improvements in terms of real-time 3-D imaging and development of 3-D transoesophageal echo (TOE ) probes; have opened up further applications including intra-operative guidance of percutaneous valve interventions

The Effect of Interactions on the Conductance of Graphene Nanoribbons

We study the effects of the interaction between electrons and holes on the conductance G of quasi-one-dimensional graphene systems. We first consider as a benchmark the limit in which all interactions are negligible, recovering the predictions of the tight-binding approximation for the spectrum of the system, and the well-known result G=4 e^2/h for the lowest conductance quantum. Then we consider an exactly solvable field theoretical model in which the electro-magnetic interactions are effectively local. Finally, we use the effective field theory formalism to develop an exactly solvable model in which we also include the effect of non-local interactions. We find that such interactions turn the nominally metallic armchair graphene nanoribbon into a semi-conductor, while the short-range interactions lead to a correction to the G=4 e^2/h formula.Comment: 9 pages, 1 figur

The Diffusion of Fixed Broadband: An Empirical Analysis

Broadband infrastructure is a key component of the knowledge economy. Broadband connections on both fixed and mobile networks are becoming an indicator of the knowledge economy. Employing the largest secondary data set, this study examines adoption factors of fixed broadband. The result of nonlinear and linear regression analysis of fixed broadband deployment suggests local loop unbundling (LLU) policy, platform completion between different broadband technologies and other diverse industry, ICT (Information and Communication Technology) and demographic factors influence fixed broadband diffusion. Specifically, the regression analysis of fixed broadband penetration found different types of LLU policies and previous fixed broadband penetration are significant factors of fixed broadband deployment. Some of the significant factors of fixed broadband deployment are different in developed countries than developing countries. This finding suggests, countries fostering broadband deployment need to adopt LLU policy for broadband, but the costs and benefits of the different LLU policy types should be carefully considered. Interestingly, the result of nonlinear regressions of fixed-broadband penetration suggest high levels of platform competition are related to high levels of fixedbroadband penetration, but the effects of platform competition are not statistically significant in OECD countries. This outcome is consistent with the result of linear regression analysis of developed countries (high income ITU membership countries). Considering OECD countries are composed of 30 developed countries with comparatively high GDP per capita, this result is robust. Taking into account this study's results as well as previous empirical studies on fixed broadband deployment, the effects of platform competition are strong in the initial deployment of fixed-broadband, but the effects of platform competition are decreasing when the broadband market size is sufficiently large or the broadband market is mature. Also, as expected, previous fixed- broadband penetration was found to be an influential factor of current fixed-broadband deployment in all ITU membership countries, whether characterized as developed or developing countries. Considering impacts of platform competition in ITU membership countries, currently it appears in many countries that network effects and the effects of platform competition co-exist

Valid \u3cem\u3et\u3c/em\u3e-Ratio Inference for IV

In the single-IV model, researchers commonly rely on t-ratio-based inference, even though the literature has quantified its potentially severe large-sample distortions. Building on Stock and Yogo (2005), we introduce the tF critical value function, leading to a standard error adjustment that is a smooth function of the first-stage F-statistic. For one-quarter of specifications in 61 AER papers, corrected standard errors are at least 49 and 136 percent larger than conventional 2SLS standard errors at the 5 percent and 1 percent significance levels, respectively. tF confidence intervals have shorter expected length than those of Anderson and Rubin (1949), whenever both are bounded

Robust Conditional Wald Inference for Over-Identified IV

For the over-identified linear instrumental variables model, researchers commonly report the 2SLS estimate along with the robust standard error and seek to conduct inference with these quantities. If errors are homoskedastic, one can control the degree of inferential distortion using the first-stage F critical values from Stock and Yogo (2005), or use the robust-to-weak instruments Conditional Wald critical values of Moreira (2003). If errors are non-homoskedastic, these methods do not apply. We derive the generalization of Conditional Wald critical values that is robust to non-homoskedastic errors (e.g., heteroskedasticity or clustered variance structures), which can also be applied to nonlinear weakly-identified models (e.g. weakly-identified GMM)

Gender and ethnic differences in chronic myelogenous leukemia prognosis and treatment response: a single-institution retrospective study

<p>Abstract</p> <p>Background</p> <p>In the last decade the importance of ethnicity, socio-economic and gender differences in relation to disease incidence, diagnosis, and prognosis has been realized. Differences in these areas have become a major health policy focus in the United States. Our study was undertaken to examine the demographic and clinical features of chronic myelogenous leukemia (CML) patients presenting initially at the LAC+USC Medical Center, which serves an ethnically diverse population.</p> <p>Results</p> <p>Patients were evenly split by gender, overwhelmingly Hispanic (60.9%), and quite young (median age 39, range 17–65) compared with previously reported CML patient populations. Previous CML studies identified significant anemia (Hgb <12 g/dl), significant thrombocytosis (platelets >450 × 10⁹/l), and significant leukocytosis (WBC >50 × 10⁹/l) as significant adverse pretreatment prognostic factors. Using these indicators, in addition to the validated Hasford and Sokal scores, patients were stratified and analyzed via gender and ethnicity. A significantly greater proportion of women presented with significant anemia (p = 0.019, Fisher's exact test) and significant thrombocytosis (p = 0.041, Fisher's exact test) compared to men, although no differences were found in risk stratification or treatment response. MCV values for women were significantly (p = 0.02, 2-sample t-test) lower than those for men, suggesting iron deficiency anemia. Focusing on ethnicity, Hispanics as a whole had significantly lower Hasford risk stratification (p = 0.046, Fisher's exact test), and significantly greater likelihood (p = 0.016, Fisher's exact test) of achieving 3-month complete haematological remission (CHR) compared with non-Hispanics at LAC+USC Medical Center, though differences in treatment outcome were no longer significant with analysis limited to patients treated with first-line imatinib.</p> <p>Conclusion</p> <p>Female CML patients at LAC+USC Medical Center present with more significant adverse pre-treatment prognostic factors compared to men, but achieve comparable outcomes. Hispanic patients present with lower risk profile CML and achieve better treatment responses compared to non-Hispanic patients as a whole; these ethnic differences are no longer significant when statistical analysis is limited to patients given imatinib as first-line therapy. Our patients achieve response rates inferior to those of large-scale national studies. This constellation of findings has not been reported in previous studies, and is likely reflective of a unique patient population.</p