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This key chapter opens with background assumptions (full employment is not assumed, the financial sector is key, and unemployment is an unnecessary evil) and then starts building a basic macro model based on the injection-leakages approach. It identifies physical investment spending as the key injection and then spends considerable time explaining the determinants of investment and the environment in which relevant decisions are made. This is perhaps the most complex part of the volume, but real-world data are referenced frequently in the hope that this makes the argument easier to follow. About halfway through the chapter, there is a shift in focus toward the financing of investment. This requires a discussion of banking and credit/money creation. The chapter ends with miscellanea regarding investment spending (including some specific observations from Kalecki and Mitchell).
The United Network for Organ Sharing (UNOS) began as the network administrative organization (NAO) overseeing the voluntary sharing of organs among transplant centers. It subsequently became the administrator of the Organ Procurement and Transplantation Network (OPTN), which Congress created to allocate deceased-donor organs when it nationalized them in 1984. The OPTN continuously makes incremental changes to organ allocation rules, raising concerns that the path dependence of allocation rules would hinder more radical change. Under pressure from the federal government, the OPTN gradually reduced the role of geographic boundaries in its allocation rules. However, it also introduced other categories so that allocation rules became increasingly complex. It initially considered continuous distribution (CD), a radical change, as an alternative for eliminating historical geographic boundaries. The OPTN subsequently committed to implementing CD for all solid organs because it offered improvements in efficiency, equity, and transparency, and because its relative simplicity would allow more expeditious incremental changes to allocation rules.
Organ transplantation offers patients greater longevity and quality of life. The allocation of scarce deceased-donor organs involves high stakes for patients, transplant centers, and Medicare. The US Congress delegated authority for the development of allocation rules to the Organ Procurement and Transplantation Network (OPTN), which engages stakeholders in the process. In 2018, the OPTN committed to replacing categorical allocation rules with continuous distribution, a new framework that sought to eliminate inefficiencies and inequities at categorical boundaries. The transparency of the OPTN provides an opportunity to observe this attempt to implement a consequential planned organizational change. The process reveals the extent to which the stakeholder rulemaking of the OPTN, an example of constructed collaboration, can implement radical as well as incremental change. More generally, it offers insight into the roles of expertise and values in high-stakes and complex organizational decision-making.
The OPTN draws on a variety of expertise in designing organ allocation rules. Expertise arises from both explicit and tacit knowledge. Explicit knowledge includes generally accepted theories and empirical regularities that are accessible without first-hand experience of practice in some domain of knowledge. Tacit knowledge arises from experience, such as professional practice. In addition to this contributory tacit knowledge, it may also arise through interaction among participants in some domain of knowledge. Through its committee system, the OPTN taps the contributory knowledge of practitioners and patients and creates interactional tacit knowledge, especially among committee staff. Explicit knowledge arises from analysis of near universal longitudinal data on transplant candidates and other data collected within the transplantation system. These data support predictions of policy outcomes through simulation models and optimization tools utilizing machine learning.
Digital financial inclusion (DFI) has been widely recognized for its potential role in reducing poverty by fostering entrepreneurship. However, whether DFI benefits all social classes equally remains an open question. Integrating technology adoption and income stratification research, this study investigates the impact of DFI on income stratification – specifically lower-, middle-, and upper-income classes – across key entrepreneurial stages, including venture creation, investment, and performance. Using data from 36,557 household-wave observations in the China Household Financial Survey (CHFS), we find that (1) lower-class households are less likely to establish entrepreneurial ventures compared to upper-class households but are more likely to do so than middle-class households, and (2) they make lower investments in entrepreneurial ventures compared to their upper-class counterparts, and experience lower entrepreneurial performance than middle- and upper-class households. The results also show that, whereas DFI positively influences entrepreneurial venture creation, investment, and performance for lower-class households, these effects are less pronounced compared to those observed in middle- and upper-class households. The study advances an integrated view of DFI by examining its differential impacts across income classes and entrepreneurial stages and contributes to the ongoing debate about its effectiveness as a universal poverty reduction solution.
Chapter 3 tackles issues that are not necessarily directly related to the business cycle but will be important at various points in the historical section of the volume that covers every US business cycle since 1954. These include inflation, monetary policy, fiscal policy, tradeable securities, and secular stagnation. Because it is so poorly understood and since it will play a key role in the cycles of the 1970s and 1980s, more than half of this space is devoted solely to understanding inflation. The idea that it is a function of money supply growth is challenged, and a new set of definitions and classifications is offered.