One learns two main lessons from studying the great quantity of banking efficiency literature. These lessons regard the heterogeneity in results and the absence of a comprehensive review aimed at understanding the reasons for this variability. Surprisingly, although this issue is well-known, it has not been systematically analyzed before. In order to fill this gap, we perform a MetaRegression-Analysis (MRA) by examining 1661 efficiency scores retrieved from 120 papers published over the period 2000-2014. The meta-regression is estimated by using the Random Effects Multilevel Model (REML) because it controls for within-and between-study heterogeneity. The analysis yields four main results. First, parametric methods yield lower levels of banking efficiency than nonparametric studies. This holds true even after controlling for the approach used in selecting the inputs and outputs of the frontier. Secondly, we show that banking efficiency is highest when using the value-added approach, followed by estimates from studies based on the intermediation method, whereas those based on the hybrid approach are the lowest. Thirdly, efficiency scores are also determined by the quality of studies and the number of observations and variables used in the primary papers. As far as the effects of sample size, dimension and quality of papers are concerned, there are significant differences in sign and magnitude between parametric and nonparametric studies. Finally, cost efficiency is found to be higher than profit efficiency. Interestingly, MRA results are robust to the potential outliers in efficiency and sample size distributions.

Abstract. This study reviews the empirical literature on banking efficiency by conducting a meta-regression analysis. The meta-dataset consists of 1661 observations retrieved from 120 papers published over the period [2000][2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013][2014]. While the role of study design and method-specific characteristics of primary studies is evaluated, the focus concerns regulation in banking. The results are fourfold. First, parametric methods always yield lower levels of banking efficiency than nonparametric studies. Second, banking efficiency is higher in studies using the value-added approach rather than the intermediation method. Third, efficiency scores also depend on the journal's ranking and on the number of observations and variables used in the primary papers. Finally, regulation matters: primary papers focusing on countries with a liberalized banking industry provide higher values for efficiency scores.

This study evaluates the cost and the profit efficiency of Italian banking sector over the period 2006-2011. Translog stochastic frontiers are used for this purpose. Following the intermediation approach, efficiency scores are computed from estimating a model with three inputs and three outputs. Results show that the average levels of cost and profit efficiency are both around 90% and they are quite stable over time. However, there is high heterogeneity in results. Differences have been found when banks are classified by size (efficiency tends to decrease with size), legal type (cooperatives perform better than others) and area (the best performers are in the North East of the country).

This note focuses on the impact of coronavirus on Italian tourism. Using a sample of 1056 travellers, we find a positive relationship between the security of destination and the probability to accommodate in hotels and B&B. Furthermore, regional contagion is negatively associated to the willingness to pay for accommodation services. The policy implications are twofold. Firstly, hotels/B&B claim for financial support to ensure social distancing and, thus, security that will attract tourists. Secondly, public finance could sustain the demand of tourist services in hotels and B&B which is lowering because of coronavirus.