Airline efficiency growth is considered one of the key factors for aviation sustainability in Africa and for creating a successful relationship between aviation activities and economic development in the continent. This paper proposes estimating the efficiency of African airlines in the period 2010-2019 using a state-of-the-art stochastic frontier model disentangling persistent efficiency, transient efficiency, and unobserved heterogeneity. We also examine the impact on both persistent and transient efficiency of (i) ownership structure, (ii) political stability, (iii) airline geographical location, (iv) airline domicile country's economic freedom, and (v) airline participation in a global alliance. We find evidence of relatively low efficiency and decreasing returns to scale, implying that it is important to achieve better utilization of inputs. Our findings also suggest that protectionism seems still an important driver of efficiency in a context characterized by a lack of liberalization. However, enhanced economic freedom is found to be more relevant in improving the efficiencies of African airlines, suggesting that policy interventions aimed at speeding up the liberalization process may help to remove the conditions that make air carriers operate inefficiently.

The main goal of this paper is to clarify a few important aspects about the aggregation issues in efficiency and productivity analysis. By doing so we also sketch a brief historical map on how the area of aggregation in efficiency and productivity analysis has developed to where it is now and its connection to some classic studies in economic theory. As a result, this paper also serves as a tribute to the great scholars I was lucky to learn from, Rolf Färe and Shawna Grosskopf, who made a profound impact on research in economics in general and the topic of aggregation in productivity and efficiency analysis in particular.

Conservation tillage (CT) options are among the most rapidly spreading land preparation and crop establishment techniques globally. In South Asia, CT has spread dramatically over the last decade, a result of strong policy support and increasing availability of appropriate machinery. Although many studies have analyzed the yield and profitability of CT systems, the technical efficiency impacts accrued by farmers utilizing CT have received considerably less attention. Employing a DEA framework, we isolated bias-corrected meta-frontier technical efficiencies and meta-technology ratios of three CT options adopted by wheat farmers in Bangladesh, including bed planting (BP), power tiller operated seeding (PTOS), and strip tillage (ST), compared to a control group of farmers practicing traditional tillage (TT). Endogenous switching regression was subsequently employed to overcome potential self-selection bias in the choice of CT, in order to robustly estimate efficiency factors. Among the tillage options studied, PTOS was the most technically efficient, with an average meta-technology ratio of 0.90, followed by BP (0.88), ST (0.83), and TT (0.67). The average predicted meta-frontier technical efficiency for the CT non-adopters under a counterfactual scenario (0.80) was significantly greater ( = 0.00) than current TE scores (0.65), indicating the potential for sizeable profitability increases with CT adoption. Conversely, the counterfactual TE of non-adopters was 23% greater than their DEA efficiency, also indicating efficiency gains from CT adoption. Our results provide backing for agricultural development programs in South Asia that aim to increase smallholder farmers' income through the application of CT as a pathway towards poverty reduction. C06 ● C14 ● Q12 ● C34 ● C51.

The goal of this article is to answer two questions: Has world agricultural convergence occurred? If not, how can this goal be fulfilled? This article introduces a model averaging method to consider both a parametric and a semi-parametric SFA model to better estimate technical efficiency. Then, three types of convergence tests are employed to check if world agricultural catch-up occurs and to determine the degree of convergence across different groups of countries. The empirical results on a balanced panel of 126 countries from 1970-2014 show that world agricultural convergence has not occurred. This article then investigates the situations in different groups of countries and discusses how to use international trade, irrigation system, and structural transformation to improve agricultural efficiency and to diminish the efficiency gap among different countries in the future.

This paper investigates the efficiency of Italian hospitals and how their performances have changed over the years 2007-2016, characterized by the great economic recession and budget constraints. We apply the Benefit of Doubt (BoD) approach to determine a composite index that considers the multi-dimensionality of the hospital outcome to be used as main output in a metafrontier production function based on a stochastic frontier framework. The efficiency score distribution is then used to construct a Theil index in order to compare, over time, the inequality of the estimated efficiency between hospitals, both within and between regions. The main findings show that the primary source of inefficiency comes from managerial inefficiency especially for hospitals located in southern regions. A clear and persistent North-South gap in efficiency performances of hospitals has been found along with an increase in the inequality in terms of efficiency between the areas of the country mostly determined by between region inequality.

We study the performance of the banking system in the Eurozone over the period 2006-2017 as measured by total factor productivity growth (TFPG) and its components. We find that Total Factor Productivity growth for the median euro area bank decreased from around 2.6% in 2007 to below 1.7% in 2017, driven mainly by a decline in technical efficiency. In addition, we control for unobserved heterogeneity across banks and disentangle persistent and time-varying inefficiency in the banking sector. This modelling choice is important to avoid distorted and biased inefficiency estimates. We find that cost efficiency in the euro area banking sector amounted to around 84% on average over the 2006 to 2017 period. The largest part of bank inefficiency is persistent, suggesting that structural long-term factors (such as location, client structure, macroeconomic environment, regulation, etc.) play a bigger role than time-varying factors.

This study introduces a database for analyzing COVID-19's impacts on China's regional economies. This database contains various sectoral and regional economic outcomes at the weekly and monthly level. In the context of a general equilibrium trade model, we first formulate a mathematical representation of the Chinese regional economy and calibrate the model with China's multi-regional input-output table. We then utilize the monthly provincial and sectoral value-added and national trade series to estimate COVID-19's province-by-month labor-productivity impacts from February 2020 to September 2020. As a year-on-year comparison, relative to February 2019 levels, we find an average 39.5% decrease in labor productivity (equivalent to around 305 million jobs) and an average 25.9% decrease in welfare. Labor productivity and welfare quickly returned to the recent high-growth trends for China in the latter half of 2020. By September 2020, relative to September 2019, average labor productivity increased by 12.2% (equivalent to around 94 million jobs) and average welfare increased by 8.2%.

The paper computes and analyses some relevant indicators of economic performance of Italian farms producing/not producing renewable energy, and compares the economic results of the two set of farms. The source of data is the European Farm Accountant Data Network; the farms belonging to this network are analysed in relation to their structural differences, type of farming, geographical areas, economic size, as well as the type of renewable energy produced. After an in-depth statistical investigation, the main economic ratios are computed and analysed using also multivariate regression models, with a special focus on the production of solar and biogas energy. In terms of land and labour productivity and fixed factor remuneration, the results show that farms producing renewable energy perform better than the other farms. This positive effect is particularly accentuated in large companies that produce biogas, followed by farms that produce solar energy. There are still many obstacles that limit the production of renewable energy in agriculture; among these, still insufficient research and information on best practices in agriculture and, in Italy, the complexity and dispersion of the institutional legislative framework and of the public support systems. However, the need to increase the production of renewable energy has become a priority for many European countries both in the short- and in the medium term, especially in light of recent events related to the war in Ukraine.

The aim of this paper is to extend the literature on multisectoral industries productivity such as tourism by simultaneously analysing the multidimensional nature of the Italian tourism sector in the period 2011-2020, considering both cross-sectoral and spatial spillover effects. To further improve our analysis, we consider two fundamental features for policy decisions: high spatial detail of analysis and the multipurpose nature of the tourism industry. Empirical findings confirm the hypotheses that the productivity level of the Italian tourism industry depends on its ability to make to most of the different input factors coming from different sectors and on (positive and negative) input spillovers.

We use a stochastic frontier analysis (SFA) approach to model the propagation of the COVID-19 epidemic across geographical areas. The proposed models permit reported and undocumented cases to be estimated, which is important as case counts are overwhelmingly believed to be undercounted. The models can be estimated using only epidemic-type data but are flexible enough to permit these reporting rates to vary across geographical cross-section units of observation. We provide an empirical application of our models to Spanish data corresponding to the initial months of the original outbreak of the virus in early 2020. We find remarkable rates of under-reporting that might explain why the Spanish Government took its time to implement strict mitigation strategies. We also provide insights into the effectiveness of the national and regional lockdown measures and the influence of socio-economic factors in the propagation of the virus.