A Laplace stochastic frontier model

We propose a Laplace stochastic frontier model as an alternative to the traditional model with normal errors. An interesting feature of the Laplace model is that the distribution of inefficiency conditional on the composed error is constant for positive values of the composed error, but varies for negative values. A simulation study suggests that the model performs well relative to the normal-exponential model when the two-sided error is misspecified. An application to U.S. Airlines is provided.     

Socioenvironmental Threats to Pastoral Livelihoods: Risk Perceptions in the Altay and Tianshan Mountains of Xinjiang,China

Subjective risk perceptions give rise to unique policy implications as they reflect both the expectation of risk exposure and the ability to mitigate or cope with the adverse impacts. Based on data collected from semistructured interviews and iterative ranking exercises with 159 households in the Altay and Tianshan Mountains of Xinjiang, China, this study investigates and explains the risks with respect to a seriously understudied population and location. Using both geostatistical and econometric methods, we show that although fear of environmental crisis is prevalent among our respondents, recently implemented pastoral conservation, sedentarization, and development projects are more likely to be ranked as the top concerns among affected households. In order to reduce these concerns, future pastoral policy must be built on the livestock economy, and intervention priority should be given to the geographic areas identified as risk hot spots. In cases where pastoralists have to give up their pastures, the transition to other comparable livelihood strategies must be enabled by creating new opportunities and training pastoralists to acquire the needed skills.     

Race,Substance Abuse,and Mental Health Disorders as Predictors of Juvenile Court Outcomes: Do They Vary By Gender?

Predicting juvenile court outcomes based on youthful offenders’ delinquency risk factors is important for the adolescent social work field as well as the juvenile justice system. Using a random sample of 341 delinquent youth from one Midwestern urban county, this study extends previous research by examining if race, substance abuse, and mental health disorders influence important delinquency outcomes (number of court offenses, felony conviction(s), probation supervision length, detention length, and number of probation services) differently for male and female juvenile offenders. Multivariate analysis findings revealed that race was significant only for males, and having a substance use disorder was a stronger predictor of delinquency outcomes for males; whereas, having a mental health disorder was a stronger predictor of delinquency outcomes for females. Implications for this research include the importance of early disorder identification and subsequent availability of gender-focused treatment.     

STOP‐GO MONETARY POLICY

We propose and estimate several discrete choice models of monetary policy decision‐making that feature time‐varying inertia. The models permit us to account for three stylized facts characterizing monetary policymaking in the United States: (1) target interest rates are gradually adjusted in small discrete movements, (2) there are some long stretches of time in which rates are repeatedly moved, and (3) there are other long stretches in which the policy rate does not change. The models are used to account for delayed monetary policy responses to the recession of 2001 and to the housing‐driven expansion of 2003–2006. (JEL E52, E58, E65)     

Are Generation X’ers Different than Late Boomers? Family and Earnings Trends among Recent Cohorts of Women at Young Adulthood

This article examines emerging trends in childbearing, marital status, and earnings for U.S. women over young adulthood across recent birth cohorts spanning the late baby boom and Generation X. We use a unique dataset that matches the 1990, 1996, and 2004 fertility and marital history modules of the Survey of Income and Program Participation with Social Security Administration longitudinal earnings records derived from survey respondents’ own tax records. While there have been some cohort-level changes, we find little empirical evidence of large-scale shifts in the family and earnings histories of young adult women born toward the end of Generation X, particularly college graduates, relative to their late baby-boom counterparts at the same stage of the life course. The broader implications of our findings and directions for further research are discussed.     

The role of ostensive and performative routine aspects in dynamic capability deployment at different organizational levels

This study clarifies how dynamic capabilities work in modifying operational capabilities at different organizational levels. While there is good understanding that routines that make up operational capabilities possess ostensive and performative aspects, whether the same applies to dynamic capabilities is unclear. In addition, there is only a limited understanding of how dynamic capabilities link to operational capabilities in terms of these two routine aspects, in general, and at different organizational levels, in particular. Our findings suggest that ostensive and performative routine aspects explain the way in which dynamic capabilities work in modifying operational capabilities. They also reveal that the pattern of the ostensive or performative routine aspects in dynamic capability deployment at a selected organizational level correspond with that associated with operational capabilities at the same level.     

Anticipating acceptance of emerging technologies using twitter: the case of self-driving cars

In an early stage of developing emerging technologies, there is often great uncertainty regarding their future success. Companies can reduce this uncertainty by listening to the voice of customers as the customer eventually decides to accept an emerging technology or not. We show that risk and benefit perceptions are central determinants of acceptance of emerging technologies. We present an analysis of risk and benefit perception of self-driving cars from March 2015 until October 2016. In this period, we analyzed 1,963,905 tweets using supervised machine learning for text classification. Furthermore, we developed two new metrics, risk rate (RR) and benefit rate (BR), which allow analyzing risk and benefit perceptions on social media quantitatively. With our results, we provide impetus for further research on acceptance of self-driving cars and a methodological contribution to acceptance of emerging technologies research. Furthermore, we identify crucial issues in the public perception of self-driving cars and provide guidance for the management of emerging technologies to increase the likelihood of their acceptance.     

Evaluating the effectiveness of urban trees to mitigate storm water runoff via transpiration and stemflow

Urban Ecosystems - Many cities in the Eastern United States are working to increase urban tree cover due to the hydrological services that trees provide, including the interception, storage and...