Place-based amenities, well-being and territorial competitiveness: a new approach using tourists’ happiness

The well-being generated by each place is an unobservable characteristic affecting local competitiveness and territorial growth. In evaluating local well-being, the use of residents’ perceptions may generate biased evaluations. Alternatively, a revealed-preference analysis of tourists’ happiness might be exploited to assess the quality of life at the destination. Then, we develop a hedonic utility function to analyze a huge and original dataset of foreign tourists’ satisfaction, visiting Italy over 2005-2014, on a large number of place-based amenities. Results show a great diversity in the mix of features that affect tourist well-being at each destination, indicating strong heterogeneity in place-based amenities, correlated in space. The presence of spatially correlated common factors of competitiveness asks for coordinated action plans on the part of local and regional authorities

Public subsidies, TFP and efficiency : a tale of complex relationships

This paper shows that a suitable decomposition of TFP can be applied to a large sample of subsidized firms for a relevant period of time, allowing an evaluation of the impact of subsidies on either the roles of technical progress and technical efficiency change or scale and allocative efficiency change as determinants of granted firms’ long-term growth. We measure and decompose TFP using a Stochastic Frontier Analysis (SFA). The impact of capital subsidies on the different components of TFP is captured by a quasi–experimental method (Multiple RDD), exploiting the conditions for a local random experiment created by Law 488/92 (L488), which has been an important policy instrument for reducing territorial disparities in Italy. The main findings from the case study are twofold. First, capital subsidies positively affect TFP growth in the medium-long term and not in the short term. The main reason is that allocative efficiency has a positive effect only after 2-3 years. Second, the positive impact comes especially through technical progress and not through scale impact change, as may have been expected

Utilizzo di immagini satellitari nella gestione post evento degli incendi boschivi

L’area Mediterranea è sistematicamente colpita da incendi che danneggiano vaste aree vegetate. Gli incendi boschivi hanno un impatto rilevante sugli ecosistemi e possono causare fenomeni di erosione del terreno, instabilità dei pendii, tendenza alla desertificazione. L’impatto interessa anche l’ambito economico colpito dall’inevitabile diminuzione del turismo. Ogni anno, in alcune aree del Mediterraneo, come l’Italia, la Francia, il Portogallo, la Spagna e la Grecia, centinaia di migliaia di ettari di foreste sono vittima degli incendi [1]: circa 65000 incendi bruciano approssimativamente 500000 ettari di aree vegetate. Negli ultimi 30 anni, nonostante le nuove tecniche antincendio, le diverse strategie per il contenimento e la tecnologia per l’informazione e la comunicazione, lo scenario non è cambiato. Per apportare miglioramenti nell’informazione e prevenire gli incendi boschivi, è necessario valorizzare l’uso di prodotti derivanti da misure satellitari, i sistemi di rivelazione degli incendi mediante osservazione da terra e dallo spazio ed è necessario migliorare la stima degli effetti dell’incendio sulla vegetazione per stabilire la priorità per gli interventi di ripristino. Lo scopo del progetto europeo PREFER (Space-based Information Support for Prevention and REcovery of Forest Fires Emergency in the MediteRranean Area) è generare prodotti a supporto delle attività di prevenzione incendi e la fase di recupero e ricostruzione [2], [3]. Il lavoro, svolto grazie al coinvolgimento in questo progetto Europeo, riguarda lo sviluppo di una metodologia per la generazione di mappe di severità del danno da incendio sulla vegetazione (fire damage severity maps) che rientra nell’attività di recupero e ricostruzione. Le mappe vengono ottenute mediante un algoritmo automatico che, utilizzando immagini Landsat 8 ad alta risoluzione spaziale ( 30 m) e bassa risoluzione temporale (16 giorni), calcola gli indici differential Normalized Burn Ratio (DNBR), Burn Severity Index (BSI) e Damage Severity Index (DSI) [4]. Con le soglie del danno per l’indice DSI si ottengono le soglie per gli altri indici e vengono così generate tre mappe del livello di danno per ogni area bruciata. I risultati ottenuti sono validati con immagini RapidEye ad altissima risoluzione spaziale ( 5 m) prima e dopo l’evento e con foto acquisite in situ. Viene studiata inoltre l’influenza dell’atmosfera e degli aerosol sulla stima del livello del danno

Cerebral Metabolic Dysfunction at the Acute Phase of Traumatic Brain Injury Correlates with Long-Term Tissue Loss

Following traumatic brain injury (TBI), cerebral metabolic dysfunction, characterized by an elevated cerebral microdialysis (CMD) lactate/pyruvate (LP) ratio, is associated with poor outcome. However, the exact pathophysiological mechanisms underlying this association are not entirely established. In this pre-planned analysis of the BIOmarkers of AXonal injury after Traumatic Brain Injury (BIO-AX-TBI) prospective study, we investigated any associations of LP ratio with brain structure volume change rates at 1 year. Fourteen subjects underwent acute-phase (0-96 h post-TBI) CMD monitoring and had longitudinal magnetic resonance imaging (MRI) quantification of brain volume loss between the subacute phase (14 days to 6 weeks) and 1 year after TBI, recalculated as an annual rate. On average, CMD showed an elevated (>25) LP ratio (31 [interquartile range (IQR) 24-34]), indicating acute cerebral metabolic dysfunction. Annualized whole brain and total gray matter (GM) volume change rates were abnormally reduced (-3.2% [-9.3 to -2.2] and -1.9% [-4.4 to 1.7], respectively). Reduced annualized total GM volume correlated significantly with elevated CMD LP ratio (Spearman's ρ = -0.68, p-value = 0.01) and low CMD glucose (ρ = 0.66, p-value = 0.01). After adjusting for age, admission Glasgow Coma Scale (GCS) score and CT Marshall score, CMD LP ratio remained strongly associated with 1-year total GM volume change rate (p < 0.001; multi-variable analysis). No relationship was found between WM volume changes and CMD metabolites. We demonstrate a strong association between acute post-traumatic cerebral metabolic dysfunction and 1-year gray matter atrophy, reinforcing the role of CMD LP ratio as an early biomarker of poor long-term recovery after TBI

Mechanisms responsible for endothelial dysfunction induced by fasting hyperhomocystinemia in normotensive subjects and patients with essential hypertension

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Public subsidies, TFP and Efficiency: A tale of complex relationships

This paper evaluates the impact of subsidies on the different components of TFP for granted firms’ long-term growth. The impact of capital subsidies is captured by a quasi–experimental method (Multiple RDD), exploiting the conditions for a local random experiment created by an Italian industrial policy. Results show that capital subsidies negatively affect TFP growth in the short term, and signals of positive effects appear only after 3-4 years. This positive medium-long term impact comes especially through technological change and not through scale impact change, as may have been expected

Alzheimer's disease marker phospho-tau181 is not elevated in the first year after moderate-to-severe TBI

BACKGROUND: Traumatic brain injury (TBI) is associated with the tauopathies Alzheimer's disease and chronic traumatic encephalopathy. Advanced immunoassays show significant elevations in plasma total tau (t-tau) early post-TBI, but concentrations subsequently normalise rapidly. Tau phosphorylated at serine-181 (p-tau181) is a well-validated Alzheimer's disease marker that could potentially seed progressive neurodegeneration. We tested whether post-traumatic p-tau181 concentrations are elevated and relate to progressive brain atrophy. METHODS: Plasma p-tau181 and other post-traumatic biomarkers, including total-tau (t-tau), neurofilament light (NfL), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP), were assessed after moderate-to-severe TBI in the BIO-AX-TBI cohort (first sample mean 2.7 days, second sample within 10 days, then 6 weeks, 6 months and 12 months, n=42). Brain atrophy rates were assessed in aligned serial MRI (n=40). Concentrations were compared patients with and without Alzheimer's disease, with healthy controls. RESULTS: Plasma p-tau181 concentrations were significantly raised in patients with Alzheimer's disease but not after TBI, where concentrations were non-elevated, and remained stable over one year. P-tau181 after TBI was not predictive of brain atrophy rates in either grey or white matter. In contrast, substantial trauma-associated elevations in t-tau, NfL, GFAP and UCH-L1 were seen, with concentrations of NfL and t-tau predictive of brain atrophy rates. CONCLUSIONS: Plasma p-tau181 is not significantly elevated during the first year after moderate-to-severe TBI and levels do not relate to neuroimaging measures of neurodegeneration

Industrial policy evaluation in the presence of spillovers

The shortage of studies on spatial spillovers of capital subsidy policies is rather surprising, considering that such policies are usually designed to generate spatial externalities. We propose a new framework that allows positive agglomeration effects to be contrasted with the negative cross-sectional substitution and the crowding-out effect. The global evaluation of the ATT and the spillover parameters shifts the spotlight from the policy effect on subsidised firms to the global effect of capital subsidy policies on the targeted territory. The empirical evaluation of a policy in Italy mainly directed towards small- and medium-sized firms shows that the impact on investments, turnover and employment is positive and large, but is negative on TFP. However, the employment growth is partially determined to the detriment of the untreated firms

Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR &lt; 60 mL/min/1.73 m2) or eGFR reduction &gt; 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR &lt; 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR &gt; 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening

Comparing continuous treatment matching methods in policy evaluation

The paper evaluates the statistical properties of two different matching estimators in the case of continuous treatment, using a Montecarlo experiment. The traditional generalized propensity score matching estimator is compared whit a new two steps matching estimator for the continuous treatment case, recently developed (Adorno, Bernini, Pellegrini, 2007). It compares treatment and control units similar in terms of their observable characteristics in both selection processes (the participation decision and the treatment level assignment), where the generalized propensity score matching estimator collapses the two processes into one single step matching. The results show that the two steps estimator has better finite sample properties if some institutional rules define the level of treatment with respect to the characteristics of treated units