A sequential model for cracking down on street markets for illicit drugs

This paper develops a sequential decision-making model for assisting law enforcement officials in allocating resources during a crackdown operation on illicit drug markets. The sequential crackdown model (SCM) considers a probabilistic framework, where the probability of incarceration of a dealer and the probability of dealing are modeled as a function of the size of a drug market, crackdown enforcement level, drug dealer's financial hardship, and other market characteristics.The model was developed and tested in consultation with enforcement officials from Philadelphia, PA and Camden, NJ. We present a detailed, step-by-step implementation scheme for updating parameters on each day of the crackdown. Parameter estimation along with examples of model usage is provided. Through these examples, we illustrate how the SCM could be helpful in understanding the response of illicit drug markets to various enforcement strategies. We further show conditions under which an alternating crackdown policy (referred to as a crackdown-backoff) or a consistent use of maximum possible enforcement would be optimal strategies for managing a drug crackdown operation. Within the context of the model and parameter estimates, we show that a much quicker and less costly collapse could be implemented if the available enforcement resources are increased. Finally, the model provides possible conditions under which a crackdown operation would be unsuccessful in eliminating a drug market.     

Remittances and incumbency: Theory and evidence

By raising household income, remittances lower the marginal utility of targeted electoral transfers, thus weakening the efficacy of vote buying. Yet, remittances make individuals wealthier and believe the national economy is performing well, which is positively attributed to the incumbent. Building on these insights, I show that the confluence of these divergent channels generate a surprising result that at increasingly higher levels of dissatisfaction with the incumbent, a remittance recipient is more likely to vote for the incumbent than a non‐remittance recipient. These predictions and their underlying mechanisms are substantiated across 18 Latin American countries.     

Leaving studies because of lack of interest: an analysis of the risk factors of school dropouts in Pakistan

Quality & Quantity - Among all the students dropping out of school for different reasons in Pakistan in 2017, nearly 23% of the students dropped out because they were not...     

The pre-acquisition evaluation of target firms and cross border acquisition performance

The paper investigates the impact of the pre-acquisition evaluation of target firms on the performance of cross border acquisitions using data from a sample of acquisitions made by UK firms. The findings provide reasonable support for organizational learning theory, suggesting that the more the acquiring firm learns about the target firm then the better will be the acquisition performance. Specifically, we find support for the hypothesis that thorough evaluation of the strategic and cultural fit positively influences cross border acquisition success. Further, the analysis reveals that detailed evaluation of the target firm's employee and business capability improves acquisition performance. The managerial implications of the findings and directions for future research are also discussed.     

Proportional Odds Models with High‐Dimensional Data Structure

The proportional odds model is the most widely used model when the response has ordered categories. In the case of high‐dimensional predictor structure, the common maximum likelihood approach typically fails when all predictors are included. A boosting technique pomBoost is proposed to fit the model by implicitly selecting the influential predictors. The approach distinguishes between metric and categorical predictors. In the case of categorical predictors, where each predictor relates to a set of parameters, the objective is to select simultaneously all the associated parameters. In addition, the approach distinguishes between nominal and ordinal predictors. In the case of ordinal predictors, the proposed technique uses the ordering of the ordinal predictors by penalizing the difference between the parameters of adjacent categories. The technique has also a provision to consider some mandatory predictors (if any) that must be part of the final sparse model. The performance of the proposed boosting algorithm is evaluated in a simulation study and applications with respect to mean squared error and prediction error. Hit rates and false alarm rates are used to judge the performance of pomBoost for selection of the relevant predictors.     

Does ethics improve stock market resilience in times of instability?

This paper compares the resilience of ethical (Islamic and socially responsible) indexes among five developed (US, UK, Japan, Canada, Australia) and three emerging markets (Brazil, India, South Africa) during the period following the 2008 subprime crisis. It relies on a multivariate CAPM-EGARCH model that accounts for sudden changes in volatility through the application of an iterated cumulative sums of squares (ICSS) algorithm on daily data over the sample period 2008–2014 to model time-varying volatility and ensure reliable estimates. The study confirms the lower systemic risk associated with Islamic indexes during the bearish period and reports that SRI, despite being more subject to systemic risk, offered higher alphas in highly integrated markets, while Islamic indexes performed better in less integrated ones. The evidence also reveals a very limited increase in the models’ predictability power from the integration of sudden changes in volatility into the EGARCH models during the full sample period. This limit is more marked during the bearish sub-period. Our findings have important implications for international investment and portfolio diversification perspectives in times of financial downturn.     

中国财政刺激将经济拉出低谷？

【英国《金融时报》4月17日】即便中国第一季度国内生产总值（GDP）数据是近20年来最糟糕的,但16日发布的一批新数据显示,政府的大笔支出,使中国经济脱离了最严重的低迷阶段。     

Does it really pay to do better? Exploring the financial effects of changes in CSR ratings

Previous literature on the link between corporate social responsibility (CSR) and financial performance has focused mainly on the financial implications of a firm’s level of CSR without considering the potential effects on financial performance of variations in CSR rating. We try to fill this gap by studying whether variations in a firm’s CSR rating affect systematic risk, firm value, and portfolio performance. First, our results show that an increase in firms’ CSR efforts, as reflected by an increase in their CSR ratings, significantly reduces systematic risk. Second, a positive variation in CSR ratings significantly improves firm value. Finally, from a portfolio perspective, a strategy that consists of buying stocks that have experienced a CSR ratings increase and selling stocks that have experienced a CSR ratings decrease (or remain stable) leads to lower financial performance. Taken together, our findings provide new evidence and financial implications for firms and portfolio managers.     

Burden of illness for super-refractory status epilepticus patients

Objective: To provide an estimate of the annual number of super-refractory status epilepticus (SRSE) cases in the US and to evaluate utilization of hospital resources by these patients.

Methods: The Premier Hospital Database was utilized to estimate the number of SRSE cases based on hospital discharges during 2012. Discharges were classified as SRSE cases based on an algorithm using seizure-related International Classification of Diseases-9 (ICD-9) codes, Intensive Care Unit (ICU) length of stay (LOS), and treatment protocols (e.g. benzodiazepines, anti-epileptic drugs (AEDs), and ventilator use). Secondary analyses were conducted using more restrictive algorithms for SRSE.

Results: A total of 6,325 hospital discharges were classified as SRSE cases from a total of 5,300,000 hospital discharges. Applying a weighting based on hospital characteristics and 2012?US demographics, this projected to an estimated 41,156 cases of SRSE in the US during 2012, an estimated incidence rate of ～13/100,000 annually for SRSE in the US. Secondary analyses using stricter SRSE algorithms resulted in estimated incidence rates of ～11/100,000 and 8/100,000 annually. The mean LOS for SRSE hospitalizations was 16.5 days (median =11; interquartile range [IQR]?=?6–20), and the mean ICU LOS was 9.3 days (median =6; IQR =3–12). The mean cost of an SRSE hospitalization was $51,247 (median = $33,294; 95% CI = $49,634–$52,861).

Limitations: The analysis uses ICD-9 diagnostic codes and claims information, and there are inherent limitations in any methodology based on treatment protocol, which created challenges in distinguishing with complete accuracy between SRSE, RSE, and SE on the basis of care patterns in the database.

Conclusion: SRSE is associated with high mortality and morbidity, which place a high burden on healthcare resources. Projections based upon the findings of this study suggest an estimated 25,821–41,959 cases of SRSE may occur in the US each year, but more in-depth studies are required.