Public–private partnerships in Social Impact Bonds: facilitating competition or hindering transparency?

ABSTRACT

The use of Social Impact Bonds (SIBs), which introduces the potential for investor profit in public service provision, has been widely discussed. Some argue that SIBs might promote government transparency because outcome data collection and evaluation are part of contractual terms. On the other hand, some argue that SIBs might hinder government transparency because more contractual parties might lead to more uncertain data ownership and because the profit motive transforms information into a competitive advantage. This paper looks at SIBs in five countries, examining how transparency differed between SIB and non-SIB financed programmes at the same social service provider. On the positive side, SIBs led to more and longer collection of outcome data and the publication of evaluations. On the negative side, it was found that SIBs tend to generate significant obstacles to the release of data to academic researchers and that sponsored evaluations do not measure impacts.     

A Typology of Reverse Innovation

Reverse innovation commonly refers to an innovation initially launched in a developing country and later introduced to an advanced country. Adopting a linear innovation model with the four sequential phases of concept ideation, product development, primary target market introduction, and subsequent secondary market introduction, this study expands the espoused definition of reverse innovation beyond its market‐introduction focus with reversals in the flow of innovation in the ideation and product development phases. Recognizing that each phase can take place in different geographical locations, the paper then introduces a typology of global innovation with 16 different types of innovation flows between advanced and emerging countries, 10 of which are reverse innovation flows. The latter are further differentiated into weak and strong reverse innovation, depending on the number of innovation phases taking place in an emerging country. This analytical framework allows recasting of current research at the intersection between innovation and international business. Of the 10 reverse innovation flows, six are new and have not been covered in the literature to date. The study addresses questions of ethnocentrism and the continuity of the flow of innovation, and discusses possible extensions of the model with respect to the number of geographical categories and phases of innovation. Four research propositions highlight areas for future investigation, especially in the context of optimizing a firm's portfolio of global innovation competence and capability. The implications for management are concerned with internal and external resistance to reverse innovation. Most significantly, while greater recognition and power of innovation in formerly subordinate organizational units is inconvenient to some, the ability to leverage the potential of reverse innovation makes a firm more likely to succeed in global innovation overall.     

Home sweet host: A cross‐country perspective on prudential and monetary policy spillovers through global banks

Prudential regulation of banks is multi‐layered: policy changes by home‐country authorities affect banks’ global operations across many jurisdictions; policy changes by host‐country authorities shape banks’ operations in the host jurisdiction regardless of the nationality of the parent bank. Do these policies create (unintended) cross‐border spillovers? Similarly, monetary policy actions by major central banks may also have effects on the behaviour of banks in other countries. This paper examines the effect that changes in home‐ and host‐country prudential measures have on cross‐border dollar credit provision, and how these interact with US monetary policy. We first run panel regressions with both layers of regulation, to examine which has a greater effect on cross‐border lending. We then use a novel approach to decompose growth in cross‐border bank lending into separate home, host and common components, and then match each with the corresponding home or host policies. Our results suggest that prudential policies can have spillover effects, which depend on the instrument used and on whether a bank's home or host country implemented them. Home policies tend to have larger spillovers on cross‐border US dollar lending than host policies. We also find that a tightening of US monetary policy can compound the spillovers of some prudential measures.     

Productivity Dispersion and Measurement Error

Several reasons have been put forward to explain the high dispersion of productivity across establishments: quality of management, different input usage and market distortions, to name but a few. Although it is acknowledged that a sizable portion of productivity dispersion may also be due to measurement error, little research has been devoted to identifying how much they contribute. We outline a novel procedure for identifying the role of measurement error in explaining the empirical dispersion of productivity across establishments. The starting point of our framework is the errors-in-variable model consisting of a measurement equation and a structural equation for latent productivity. We estimate the variance of the measurement error and subsequently estimate the variance of the latent productivity variable, which is not contaminated by measurement error. Using Norwegian data on the manufacture of food products, we find that about one percent of the measured dispersion stems from measurement error.