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The main aim of this paper is to examine labour productivity trends in Italy over the period 1981‐2004.

To this end, relying on recent developments in the analysis of non‐stationary dependent panels, the paper develops a new method for estimating total factor productivity (TFP) trends.

The conclusions confirm the view that the recent decline in Italian labour productivity growth is mostly due to a widespread fall in TFP growth.

The main assumption underlying the proposed TFP estimation method is that technology growth is driven by a single trend common to all units included in the panel (industries, regions or countries).

The paper provides two distinct contributions: empirically, it provides robust evidence that TFP slow‐down is the main cause of recent negative trends in labour productivity in Italy. Methodologically, the paper proposes an approach to estimating TFP that enjoys several advantages: only basic data for input and output flows are needed, the non‐stationary nature of the data is explicitly taken into account, and confidence intervals for TFP growth can be computed. This method can thus be easily applied to many routinely available datasets, to either corroborate existing growth accounting estimates or to obtain previously unavailable estimates.

Conferences bring scientists together and provide one of the most timely means for disseminating new ideas and cutting-edge works. The importance of conferences in many scientific areas is testified by quantitative indexes. The main goal of this paper is to investigate a novel research question: is there any correlation between the impact of scientific conferences and the venue where they took place?

To measure the impact of conferences, the authors conducted a large scale analysis on the bibliographic data extracted from 3,838 Computer Science conference series and over 2.5 million papers spanning more than 30 years of research. To quantify the “touristicity'' of a venue, the authors exploited indexes about the attractiveness of a venue from reports of the World Economic Forum, and have extracted four country-wide and two city-wide touristic indexes, which measure the attractiveness and the touristicity of any country or city.

The authors found out that the two aspects are related, and the correlation with conference impact is stronger when considering country-wide touristic indexes, achieving a correlation value of more than 0.5 when considering the average citations, and more than 0.8 when considering the total citations. Moreover the almost linear correlation with the Tourist Service Infrastructure index attests the specific importance of tourist/accommodation facilities in a given country.

There are two main limitations of this work: (1) the use of citations to evaluate the attractiveness of the conferences and (2) the difficulty to formally define the touristic attractiveness of a venue.

Starting from the results concerning the correlation between different touristicity indicators and the outcome of a conference in terms of citations, it would be possible to support conference organizers in their decisions. For instance, they could plan in advance conference venues considering the same touristicity indicators, comparing different options and selecting cities which have high scores. This will allow for rapid planning of a conference venue, encompassing the easiness of travel and the attractivity of a venue, hence increasing the potential outcomes of the conference.

Regarding the social implications, this study will enable the possibility for municipalities and conference organizers to understand what it can be improved in a specific venue to make it more attractive. This may include better transport connections or selecting cities which show a high potential regarding the touristicity index. Regarding the willingness of a researcher to submit a paper to a specific conference, it would be unaltered, meaning that what the results show is that there is already a mental process, before submitting a paper to a conference, which considers these indicators.

This is the first attempt to focus on the relationship of venue characteristics to conference papers. The results open up new possibilities, such as supporting conference organizers in their organization efforts.

This work aims to study the break-even inflation rates (BEIRs), a widely used market-based measure of expected inflation. The authors focus on Italian Government bonds, one of the most liquid debt markets in the euro area.

The authors set up an auto-regressive distributed lag model and regress the BEIR on a set of variables that proxy inflation, market risk aversion, protection against deflation, credit as well as liquidity risk to get some insights into the importance of these factors. Subsequently, to disentangle market participants’ inflation expectations from their associated risk premia, the authors estimate a term structure model for the joint pricing of the Italian Government’s nominal and real yield curves, considering also a credit and a liquidity pricing factor.

The results show that BEIRs could be a misleading measure of the expected inflation due to the importance of the inflation risk premium and the credit risk effect. According to the estimates, the decrease of market-based measures of inflation observed in the last part of the sample period seems to reflect a lowering of both inflation expectations and risk premia. Inflation premia co-move with a measure of the tail risk of the long-term inflation distribution, signalling that investors become more concerned with downside risks.

This study complements the existing literature primarily based on the USA and euro area data focusing on the Italian market. To this end, the authors modify and adapt a well-known term structure model developed for nominal and real curves.