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This article examines the extent to which national institutional quality affects bilateral sectoral trade flows, as well as whether the conditioning role of institutions for trade has been waxing or waning with time. Based on a new trade theory framework, we derive a sectoral gravity equation, including novel variables corresponding to the exporter's labour competitiveness levels, along with importer's price indices and sectoral incomes, and analyse industry specific bilateral trade flows of 186 countries for the period 1996-2012. We address potential endogeneity and econometric drawbacks by means of Poisson Pseudo-Maximum Likelihood estimation methods. The results indicate that both the institutional conditions at destination and the institutional distance between exporting and importing countries are relevant factors for bilateral trade. Moreover, the effect associated toinstitutional conditions at destination moderately increases over time. This is a robust outcome across economic sectors, with higher values for agriculture and raw materials than for manufacturing and services.

Distance functions are gaining relevance as alternative representations of production technologies, with growing numbers of empirical applications being made in the productivity and efficiency field. Distance functions were initially defined on the input or output production possibility sets by Shephard (1953, 1970) and extended to a graph representation of the technology by Färe, Grosskopf and Lovell (1985) through their graph hyperbolic distance function. Since then, different techniques such as non parametric-DEA and parametric-SFA have been used to calculate these distance functions. However, in the latter case we know of no study in which the restriction to input or output orientation has been relaxed. What we propose is to overcome such restrictiveness on dimensionality by defining and estimating a parametric hyperbolic distance function which simultaneously allows for the maximum equiproportionate expansion of outputs and reduction of inputs. In particular, we introduce a translog hyperbolic specification that complies with the conventional properties that the hyperbolic distance function satisfies. Finally, to illustrate its applicability in efficiency analysis we implement it using a data set of Spanish savings banks. Copyright Springer Science+Business Media, Inc. 2005production frontiers, parametric distance functions, hyperbolic efficiency, banking efficiency,

The European Union (EU) annually publishes an Innovation Union Scoreboard (IUS) as a tool to measure the innovation performance of EU Member States by means of a composite index, called the Summary Innovation Index (SII). The SII is constituted by an average of 25 indicators. The SII is claimed to rank Member States according to their innovation performance. This means that the higher the average value of the 25 indicators, the better the innovation performance is said to be. The first purpose of this article is to assess whether the SII constitutes a meaningful measure of innovation performance. Our conclusion is that it does not. Our second purpose is to develop alternative, productivity or efficiency-based, measures of innovation system performance based on a simple index number, and complement it with advanced and robust nonparametric Data Envelopment Analysis techniques. By doing so, the article offers a critical review of the SII, and proposes to put more emphasis on the identification of and relation between input and output innovation indicators. The data provided by the 2014 and 2015 editions of the IUS are here used to analyze the innovation performance of all 28 EU national innovation systems. A theoretical background and reasons for selecting the indicators used are presented, and our new ranking of the innovation performance using bias-corrected efficiency scores of all EU countries is calculated. We find that the results differ substantially between the SII and the ranking based on our method, with significant consequences for the design of innovation policies.