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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.

EU countries, including those in Central and Eastern Europe, seem to have increasingly similar economies, allowing for the study of real convergence as a process of equalising income levels (measured by GDP per capita). Studies of income convergence in the European Union also have a regional dimension and often focus on convergence at the NUTS2 or NUTS3 regional level. The level of development and income in Polish regions differ significantly. The regional policy implemented at the national and EU level focuses on reducing these differences.

The main aim of the chapter is to analyse the income convergence process among regions in Poland and verify the effectiveness of regional policy implemented at the national and EU level.

The study uses Barro type regression for panel data, log t convergence test, and club clustering algorithm introduced by Phillips and Sul to identify patterns of club convergence in Polish regions. The data used for the study is the Local Data Bank provided by Statistics Poland, which includes gross domestic product per capita at the NUTS-3 level for 73 Polish regions over the period of 2000–2020.

The results of the study indicate a very weak convergence process for all Polish NUTS-3 regions and suggest a club convergence. The club convergence is characterised by regions with similar income levels clustering together. The regional distribution of clubs is similar to the regional distribution of income. The study's findings provide important insights into the effectiveness of regional policy in Poland and suggest that policymakers need to focus on policies that promote catch-up growth in less developed regions. The study also highlights the importance of supporting the most developed regions in the country as they can play a crucial role in driving the country's economic growth and prosperity.

This chapter examines the influence of external public borrowing resources on economic progress in Tunisia. The study focuses on two stages: First, the influence is studied in a direct sense and then in an indirect sense, i.e., through a transmission channel of this influence. By applying the autoregressive distributed technique with staggered lags (ARDL), over a period ranging from 1986 to 2019, the results showed that the influence of external borrowing resources on growth seems to be unfavorable in the short term but positive in the long term, hence the importance of the empirical technique chosen. Second, three interaction variables were tested, namely total government expenditure, government investment expenditure, and the real effective exchange rate. The results obtained call for better attention to the channels identified to maximize the positive influence of external public debt on the country's economic progress.

Recalling that the introductory chapter (Chapter 1) wanted to carry out similar types of analysis for the major states in India. Thus, the present chapter tries to examine the trends of a bank branch, deposit, credit, the credit–deposit ratio, sectoral shares of credit, magnitudes of banking transactions, credit concentration, etc., for the selected 15 states and Delhi as the only union territory for the period 1972–2019. The study period covers the pre-reform period from 1972 to 1992 and the post-reform period 1993–2019. The observations show that the branch, deposit and credit did not grow significantly during the post-reform period. As a result, the credit–deposit ratio did not increase significantly during the reform period. But, the magnitude of banking transactions increased in most of the states during the reform period. Regarding the sector-wise share of credit, AP, Maharashtra, UP and TN are the leading states in agricultural credit, WB, Gujarat and Maharashtra are in industrial credit and Kerala, Assam and Delhi are in the service sector. On the other hand, the study finds rising magnitudes credit concentrations of the states during the post-reform period in contrast to the declining concentration in the pre-reform period. Maharashtra is the state which holds around 25 per cent of all states’ credit throughout the entire period of 1972–2019. Hence, there are the notions of rising disparity and inequality in credit as well as incomes of the states and all India levels.

In recent years, the airline industry has been growing and transforming rapidly in the Asia-Pacific area. This study analyzes and benchmarks the comparative operational efficiencies of the major Asian air carriers. Data envelopment analysis model and disaggregate output efficiency measures are used to evaluate the operational efficiencies of 31 Asian airlines from 2015 to 2019. The findings suggest that nonflag carriers, low-cost carriers, and high-income regions' carriers have significantly higher levels of efficiency than flag carriers, full-service carriers, and low-income regions' carriers in overall, revenue, and passenger traffic efficiencies. The efficiencies between alliance carriers and nonalliance carriers along with those of ASEAN and non-ASEAN carriers are not significantly different.

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.