​Department of Economics Management and Statistics

time series of selected macroeconomic variables used as observables in our estimation exercise.

Stata data set

This dataset contains the data from the a set of laboratory experiments with human subjects run at the University of Milano Bicocca. The experiment was programmed using zTree (Fischbacher, 2007). Our experimental design involved four sessions of each of our two treatments. As we have 27 subjects per session, we have collected data from a total of 216 subjects, from October 2014 to January 2015. Subjects were recruited from the undergraduate population of the University of Milano-Bicocca, via the ORSEE software (Greiner, 2004). No subject participated in more than one session of this experiment. In December 2015 we have run two additional sessions per treatment where the order of the games played by the subject was reversed.

The above are two of the main codes written in RATS which are used to carry empirical estimates and bootstrapping analysis of the baseline regression (Table 3) used in our study.

Abstract of associated article: According to the Rockets and Feathers Hypothesis (RFH), the transmission mechanism of positive and negative changes in the price of crude oil to the price of gasoline is asymmetric. Although there have been many contributions documenting that downstream prices are more reactive to increases than to decreases in upstream prices, little is known about the forecasting performance of econometric models incorporating asymmetric price transmission from crude oil to gasoline. In this paper we fill this gap by comparing point, sign and probability forecasts from a variety of Asymmetric-ECM (A-ECM) and Threshold Autoregressive ECM (TAR-ECM) specifications against a standard ECM. Forecasts from A-ECM and TAR-ECM subsume the RFH, while the ECM implies symmetric price transmission from crude oil to gasoline. We quantify the forecast accuracy gains due to incorporating the RFH in predictive models for the prices of gasoline and diesel. We show that, as far as point forecasts are involved, the RFH does not lead to significant improvements, while it can be exploited to produce more accurate sign and probability forecasts. Finally, we highlight that the forecasting performance of the estimated models is time-varying.

Full version of the SCIROCCO tool. (DOCX 181 kb)

Abstract Background The Scaling Integrated Care in Context (SCIROCCO) tool has been developed to facilitate knowledge transfer and learning about the implementation and scaling-up of integrated care in European regions. To adequately test the functionality of the tool in assessing the maturity for integrated care within regions, this study evaluated its structural validity, internal consistency and convergent validity. Methods Exploratory factor analysis was used to investigate the structural validity of the 12-items of the SCIROCCO tool. Hereafter, the internal consistency was assessed by calculating Cronbach’s and ordinal alpha. The convergent validity was explored by testing 23 pre-hypothesized relationships between items of the SCIROCCO tool and items of an instrument measuring a similar construct. Results Factor analysis revealed a one-factor structure. Cronbach’s alpha of the overall instrument was 0.92, ordinal alpha was 0.94. Only 30.34% of the hypotheses for testing the convergent validity were met. Conclusion The one-factor structure is considered relevant in representing the structural validity of the SCIROCCO tool. The scale of the SCIROCCO tool shows good internal consistency. The tool (DMIC Quickscan) used to assess the convergent validity might measure a different aspect of integrated care than the SCIROCCO tool. Further research is needed to continue investigating the validity and reliability of the tool.

The authors study the effect of corporate board gender quotas on firm performance in France, Italy, and Spain. The identification strategy exploits the exogenous variation in mandated gender quotas within country and over time and uses a counterfactual methodology. Using firm-level accounting data and a difference-in-difference estimator, the authors find that gender quotas had either a negative or an insignificant effect on firm performance in the countries considered with the exception of Italy, where they find a positive impact on productivity. The authors then focus on Italy. Using a novel data set containing detailed information on board members’ characteristics, they offer possible explanations for the positive effect of gender quotas. The results provide an important contribution to the policy debate about the optimal design of legislation on corporate gender quotas.

Supplemental material, ILRR_Pagani_Suppl_Online_Appendix for Where Women Make a Difference: Gender Quotas and Firms’ Performance in Three European Countries by Simona Comi, Mara Grasseni, Federica Origo and Laura Pagani in ILR Review

23 predefined hypotheses on expected moderate correlations between items of the SCIROCCO tool and the DMIC Quickscan. (DOCX 30 kb)