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This chapter provides a theory model of trade finance to explain the “great trade collapse.” The model shows that, first, the riskiness of international transactions rises relative to domestic transactions during economic downturns; and second, the exclusive use of a letter of credit in international transactions exacerbates a collapse in trade during a financial crisis. The basic model considers banks’ optimal screening decisions in the presence of counterparty default risks. In equilibrium, banks will maintain a higher precision screening test for domestic firms and a lower precision screening test for foreign firms, which constitutes the main mechanism of the model.

In this chapter, we describe how random utility maximization (RUM) discrete choice models are used to estimate the demand for commodity attributes in quality-differentiated goods. After presenting a conceptual overview, we focus specifically on the conditional logit model. We examine technical issues related to specification, interpretation, estimation, and policy use. We also discuss identification strategies for estimating the role of price and non-price attributes in preferences when product attributes are incompletely observed. We illustrate these concepts via a stylized application to new car purchases, in which our objective is to measure preferences for fuel economy.

To survey the policy-driven financial controls currently being used to drive physician change in the care of populations

This paper offers a review of current health care payment models and discusses the impact of each on the potential success of PHM initiatives. We present the benefits of a multi-part model, combining visit-based fee-for-service reimbursement with a monthly “care coordination payment” and a performance-based payment system.

A multi-part model removes volume-based incentives and promotes efficiency. However, it is predicated on a pay-for-performance framework that requires standardized measurement. Application of this model is limited due to the current lack of standardized measurement of quality goals that are linked to payment incentives.

Financial models dictated by health system payers are inextricably linked to the organization and management of health care.

There is a need for better measurements and realistic targets as part of a comprehensive system of measurement assessment that focuses on practice redesign, with the goal of standardizing measurement of the structure and process of redesign. Payment reform is a necessary component of an accurate measure of the associations between practice transformation and outcomes important to both patients and society.

In recent years professional accountancy bodies (e.g., CPA), accreditation institutions (e.g., AACSB) and employers have steadily raised, and continue to raise expectations regarding the need for accounting graduates to demonstrate skills in data analytics. One of the obstacles accounting instructors face in seeking to implement data analytics, however, is that they need access to ample teaching materials. Unfortunately, there are few such resources available for advanced programming languages such as R. While skills in commonly used applications such as Excel are no doubt needed, employers often take these for granted and incremental value is only added if graduates can demonstrate knowledge in using more advanced data analytics tools for decision-making such as coding in programming languages. This, together with the current dearth of resources available to accounting instructors to teach advanced programming languages is what drives motivation for this chapter. Specifically, we develop an intuitive, two-dimensional framework for incorporating R (a widely used open-source analytics tool with a powerful embedded programming language) into the accounting curriculum. Our model uses complexity as an integrating theme. We incorporate complexity into this framework at the dataset level (simple and complex datasets) and at the analytics task level (simple and complex tasks). We demonstrate two-dimensional framework by drawing on authentic simple and complex datasets as well as simple and complex tasks that could readily be incorporated into the accounting curriculum and ultimately add value to businesses. R script programming code are provided for all our illustrations.

This article begins by examining the recommendations of Uhl-Bien and Marion that the LAMPE theory of organizational leadership could be enhanced and improved if it were to incorporate elements of complexity and complexity leadership theory. Their advice should be reversed: complexity leadership theory should incorporate the theory, methods, and models already tested in the construct of the LAMPE theory. The reasons for this conclusion are based on a general discussion of the conditions under which a processual theory can be tested and the testing procedure be made rigorous. According to this approach, complexity leadership theory cannot be most rigorous and the LAMPE organizational leadership theory might be.