Technological Spillovers and Productivity in Italian Manufacturing Firms

We study whether a firm’s total factor productivity dynamics is positively influenced by its own R&D activity and by the technological spillovers generated at the intra- and inter-sectorial level. Our approach corrects simultaneously for the endogeneity and the selectivity biases introduced by the use of a firm’s own R&D as a regressor. A firm’s involvement in R&D activities accounts for significant productivity gains. Firms also benefit from spillovers originating from their own industries, as well as from innovative upstream sectors.R&D, TFP, selectivity, treatment effect

Technological Spillovers and Productivity in Italian Manufacturing Firms

We study whether a firm’s total factor productivity dynamics is positively influenced by its own R&D activity and by the technological spillovers generated at the intra- and inter-sectorial level. Our approach corrects simultaneously for the endogeneity and the selectivity biases introduced by the use of a firm’s own R&D as a regressor. A firm’s involvement in R&D activities accounts for significant productivity gains. Firms also benefit from spillovers originating from their own industries, as well as from innovative upstream sectors.R&D, TFP, selectivity, treatment effect

On the Relationship between R&D and Productivity: a Treatment Effect Analysis

This study uses firm level data from two detailed surveys of Italian manufacturing firms to study the relationship between R&D expenditures and productivity growth. The analysis considers the different contributions of various forms of R&D (product, process, internal, external in collaboration with universities, research centres and other firms) to Total Factor Productivity (TFP). Thus, this paper answers the call for more research on the links between a firm’s external R&D and its productivity. In the cross-section econometric analysis, we estimate a Treatment Effects model based on the assumption that the decision to carry out R&D is endogenous. We found evidence supporting such a methodological approach. The main restlts reveal a positive and statistically significant relationship between the detailed measures of R&D and TFP. It is noteworthy that among external R&D investments, only expenditures for projects run in collaboration with other firms turn out to be highly significant, while cooperation in R&D with universities does not seem to lead to productivity enhancements. Because of the public good nature of research, firms may resort to do R&D within laboratories run by universities only when the outcome of the research does not have important strategic consequences.Total factor productivity, selectivity, manufacturing, firm level

On the Relationship between R&D and Productivity: a Treatment Effect Analysis

This study uses firm level data from two detailed surveys of Italian manufacturing firms to study the relationship between R&D expenditures and productivity growth. The analysis considers the different contributions of various forms of R&D (product, process, internal, external in collaboration with universities, research centres and other firms) to Total Factor Productivity (TFP). Thus, this paper answers the call for more research on the links between a firm's external R&D and its productivity. In the cross-section econometric analysis, we estimate a Treatment Effects model based on the assumption that the decision to carry out R&D is endogenous. We found evidence supporting such a methodological approach. The main results reveal a positive and statistically significant relationship between the detailed measures of R&D and TFP. It is noteworthy that among external R&D investments, only expenditures for projects run in collaboration with other firms turn out to be highly significant, while cooperation in R&D with universities does not seem to lead to productivity enhancements. Because of the public good nature of research, firms may resort to do R&D within laboratories run by universities only when the outcome of the research does not have important strategic consequences.

Assessing the Returns to Collaborative Research: Firm-Level Evidence from Italy

We use firm-level data from Italian manufacturing firms to assess the relationship between various types of R&D and total factor productivity growth, including collaborative research with other firms and universities. A novel twist to our empirical analysis is that we estimate a treatment effects model, which enables us to treat the decision to conduct R&D as endogenous. We find strong evidence of positive returns to collaborative research with companies, while collaborative research with universities does not appear to enhance productivity. This result implies that firms may conduct R&D with universities when appropriability conditions are weak and the outcomes of such research projects do not yield direct strategic benefits.

Technological spillovers and productivity in Italian manufacturing firms

We study whether a firm’s total factor productivity dynamics is positively influenced by its own R&D activity and by the technological spillovers generated at the intra- and inter-sectorial level. Our approach corrects simultaneously for the endogeneity and the selectivity biases introduced by the use of a firm’s own R&D as a regressor. A firm’s involvement in R&D activities accounts for significant productivity gains. Firms also benefit from spillovers originating from their own industries, as well as from innovative upstream sectors

Effects of additives and ingredient sizing on the shelf-life of "Amaretti" cookies

Cookies are characterised by moisture and water activity (aw) higher than 7% and 0.5, respectively. Cookies have the capacity of bending after baking, when they are fresh, unlike biscuits that break when bent. Hardening is the main cause of quality deterioration of cookies, which change from soft and pliable to firm and crumbly within a few days or even hours after baking. Little research has been done on cookies. "Amaretti" are typical Italian cookies, found in several regions of Italy. Freshly baked "Amaretti" are soft and delicious but undergo severe hardening after seven to ten days, thus limiting the shelf-life, so Amaretti can be marketed only locally. In the present work several attempts have been made in order to extend the shelf-life of Sardinian "Amaretti". In particular, changes to the formulation and to the almond particle size were made. The traditional formulation was, in fact, modified by adding rice starch (thickening agent) or mono-diglyceride of fatty acids (emulsifier). Almonds were grinded to a particle size lower or higher than 1 mm. Amaretti baked with the traditional recipe were used as control. After baking and cooling cookies were wrapped with an aluminium foil and stored at controlled temperature and humidity. Evolution of texture (as hardness) and aw during storage were followed instrumentally by a texture analyser and a hygrometer, respectively

Are all online hotel prices created dynamic? An empirical assessment

Understanding how tourist firms set their online prices is important due to their growing reliance on Online Travel Agencies (OTA). Little is known, however, about whether differences exist in the online pricing approaches adopted by hotels using an OTA. The article tests, using a big data approach, whether the diffuse narrative of a pervasive presence of dynamic pricing provides a realistic description of hotels’ pricing behavior and thus challenges the view that dynamic pricing should be considered the prevailing norm for the industry. The evidence suggests a heterogenous attitude across hotels, with uniform pricing being more widespread in most hotels of our sample, namely, the 3-star or less, while dynamic pricing is more likely applied in higher quality hotels

Are all online hotel prices created dynamic? An empirical assessment

Understanding how tourist firms set their online prices is important due to their growing reliance on Online Travel Agencies (OTA). Little is known, however, about whether differences exist in the online pricing approaches adopted by hotels using an OTA. The article tests, using a big data approach, whether the diffuse narrative of a pervasive presence of dynamic pricing provides a realistic description of hotels’ pricing behavior and thus challenges the view that dynamic pricing should be considered the prevailing norm for the industry. The evidence suggests a heterogenous attitude across hotels, with uniform pricing being more widespread in most hotels of our sample, namely, the 3-star or less, while dynamic pricing is more likely applied in higher quality hotels

Split-Boost Neural Networks

The calibration and training of a neural network is a complex and time-consuming procedure that requires significant computational resources to achieve satisfactory results. Key obstacles are a large number of hyperparameters to select and the onset of overfitting in the face of a small amount of data. In this framework, we propose an innovative training strategy for feed-forward architectures - called split-boost - that improves performance and automatically includes a regularizing behaviour without modeling it explicitly. Such a novel approach ultimately allows us to avoid explicitly modeling the regularization term, decreasing the total number of hyperparameters and speeding up the tuning phase. The proposed strategy is tested on a real-world (anonymized) dataset within a benchmark medical insurance design problem