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Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of developed and developing countries over 1995–2010. A distinctive feature of the empirical strategy followed is that it allows the measurement of the resource reallocation directly attributable to infrastructure provision. To achieve this, a two-level top-down decomposition of aggregate productivity that combines and extends several strands of the literature is proposed. The empirical application reveals significant production losses attributable to misallocation of inputs across firms, especially among African countries. Also, the results show that infrastructure provision has stimulated aggregate total factor productivity growth through both within and between industry productivity gains.

The standard method to estimate a stochastic frontier (SF) model is the maximum likelihood (ML) approach with the distribution assumptions of a symmetric two-sided stochastic error v and a one-sided inefficiency random component u. When v or u has a nonstandard distribution, such as v follows a generalized t distribution or u has a χ2 distribution, the likelihood function can be complicated or untractable. This chapter introduces using indirect inference to estimate the SF models, where only least squares estimation is used. There is no need to derive the density or likelihood function, thus it is easier to handle a model with complicated distributions in practice. The author examines the finite sample performance of the proposed estimator and also compare it with the standard ML estimator as well as the maximum simulated likelihood (MSL) estimator using Monte Carlo simulations. The author found that the indirect inference estimator performs quite well in finite samples.

The aim of this chapter is to investigate the immigrant women entrepreneurship phenomenon in Italy by focusing on the Polish experience. Stemming from the most current data on immigration in Italy and on immigrant women entrepreneurs and women-led firms, by analysing the regions in which these firms are grounded and the economic sectors in which they are mostly involved, this chapter presents the research programme the two authors of this book have been involved in over the last year and the first preliminary results. Specifically, the two authors engaged to compare the experiences, difficulties and opportunities of immigrant women entrepreneurs of different ethnicities/communities located in Italy. The final goal is to analyse if and how the socio-cultural background of these women counts, if and how it affects their way of doing business and what is the influence of the socio-cultural Italian context. The first group of immigrant women entrepreneurs that the authors decided to analyse are the Polish. Accordingly, this chapter presents data on Polish women entrepreneurs based in Italy and the results of an interview with an expert on this community.

Moving away from the stories of financial disaster we encountered in Chapter 2, Chapter 3 examines what it means for fans when their club is suddenly awash with more financial muscle than some nation-states due to the generosity of a wealthy benefactor who is seemingly more interested in sporting glory than in financial gain. This chapter engages with the notion of the football club as a billionaire’s plaything. Roman Abramovich’s acquisition of Chelsea in 2003 saw the West London club embark on an eye-watering spending spree and a sustained period of on-field successes, one that was unknown in the club’s history to that point. As a result, we take Chelsea during the Abramovich era as a starting point for considering how this model of ownership affects the relationship between fans and the connection that they have with their club. The evident success that financial muscle can bring shows owners what a happy fanbase is capable of, what they are capable of doing, and what they are capable of ignoring. The success of the financially doped teams of the 2000s created a precedent for winning over a fanbase with a successful football club, but nevertheless sat awkwardly with the normative ideals of how a football club should exist in the world and relate to its supporters.

The aim of this chapter is to investigate the immigrant women entrepreneurship phenomenon by analysing management academic literature on the issue. Stemming from the most current data on immigration and from the awareness that entrepreneurship is a viable instrument of immigrant (women) integration and inclusion, this chapter analyses the most updated management results on the issue. The analysis is mainly centred on works published after 2019, and some interesting insights emerge. Among them, we can refer to the awareness that research on immigrant women entrepreneurship is still in its infancy. Although, indeed, immigrant entrepreneurs and women entrepreneurs have been analysed considerably by researchers, it has been mainly in isolation. Therefore, room for investigating still exists, and this chapter uncovers some possible future research avenues. Moreover, by reviewing the selected papers, it clearly emerges that not all immigrant women entrepreneurs are alike; different targets (that is, different ethnicities) must be addressed differently by policy makers when policy measurements are identified. In other words, generic programmes aimed at increasing entrepreneurship among immigrant women cannot necessarily be successful.

This chapter is focused on what we can learn from oppressive governance, in this case specifically relating to university governance in terms of vice chancellors and presidents, to the deputy vice chancellor and deputy president and down the ever-growing university hierarchy to deans and heads of schools and their deputies, from a Freirean perspective. Freire wrote at length about how leaders ‘controlled’ education and why they did so, but he also wrote at length about how governments control populations – himself being both a political prisoner and a person in exile to escape persecution. This chapter subsequently examines Freire's ideas around what techniques people employ to control populations and applies them to a higher education setting because the similarities are numerous and the tactics familiar.