Stimulating Non-Energy Exports in Trinidad and Tobago: Evidence from a Small Petroleum-Exporting Economy Experiencing the Dutch Disease

The motivation for this study hinges around the fact that Trinidad and Tobago (T&T) is suffering from the Dutch disease which inadvertently hinders the growth of non-energy exports. This paper examines measures that can be adopted for a small petroleum-exporting economy to dampen the effect of Dutch disease by promoting non-energy trade. This paper is novel and contributes to the literature in using panel data for the T&T case, as it investigates the effect of a devaluation of the TT dollar in order to stimulate non-energy exports (a combination of agriculture and manufacturing trade). Note that previous studies would have examined the Marshall–Lerner condition on the aggregate trade balance which is heavily influenced by energy revenues. The panel autoregressive distributed lag (ARDL) method is used for ten of T&T’s main trading partners for the period 1991 to 2019 to establish findings. The results show that the Marshall–Lerner condition does not hold for aggregate trade in the long run, as expected. However, when non-energy trade is isolated, it is found that a devaluation of the TT dollar does have a positive impact on non-energy trade and the Marshall–Lerner condition holds. Other measures are also recommended to stimulate non-energy exports in the long run.

Non-Performing Loans and Macroeconomics Factors: The Italian Case

The purpose of this work is to investigate the influence of macroeconomics determinants on non-performing loans (NPLs) in the Italian banking system over the period 2008Q3–2020Q4. We mainly contribute to the literature by being the first empirical article to study this relationship in the Italian context in the recent period, thus providing fresh evidence on the macroeconomic impact on NPLs, i.e., on the credit risk of Italian banks. By employing the Autoregressive Distributed Lag (ARDL) cointegration model, we are able to investigate the short and long-run effects of macroeconomic factors on NPLs. The empirical findings show that gross domestic product and public debt have a negative impact on NPLs. On the other hand, we find that the unemployment rate and domestic credit positively influence impaired loans. Finally, we find evidence of the “gamble for resurrection” approach, i.e., Italian banks tend to support “zombie firms”.

Impact of COVID-19 Vaccines on Tourism Demand and Culture

The low supply of vaccines for COVID-19 has disrupted tourism development in Asia. The question is if the vaccine may change cultural divergence into cultural convergence at the tourist destination. The purpose of this study is to examine the culture and price elasticity of hotel demand to find the cultural convergence. The study has conducted autoregressive distributed lag model to test whether the vaccine would change the price and income elasticities of hotel demand to find the cultural transformation from divergence to convergence through tourism. Findings indicate that the impact of the vaccine on transferring culture from divergence to convergence was confirmed. Tourists from the divergent cultures specified by less levels of Hofstede's cultural dimensions will visit the country destination with high levels of Hofstede's cultural dimensions after COVID vaccination. Japan and the US that possess divergent levels of power will visit Vietnam for power convergence. China, Korea, and Russia that possess divergent levels of indulgence will visit Vietnam for indulgence convergence.

Ragweed Pollen Concentration Predict Seasonal Oculo-rhinitis and Asthma Severity in Subjects Allergic to Ragweed.

Objectives: 1. To investigate the correlation between ragweed pollen concentration and conjunctival, nasal and asthma symptoms severity in patients allergic to ragweed using ambient pollen exposure in the Milan area during the 2014 ragweed season; 2. to calculate the pollen / symptom thresholds and 3. to assess the effectiveness of ragweed Allergen Immuno Therapy (AIT).Patients: 66 subjects allergic to Amb a 1 enrolled in the study and were divided into two cohorts: AIT treated (24) and non-AIT treated (42).Measurements: Pollen counts and daily symptom/medication patient diaries. Autoregressive Distributed Lag Models were used to develop predictive models of daily symptoms and to evaluate the short-term effects of temporal variations in pollen concentration on the onset of symptoms. Results: We found significant correlations between ragweed pollen load and the intensity of symptoms, for all three symptom categories respectively, both in non-AIT treated (𝛕= 0.341, 0.352, 0.721 and ρ = 0.48, 0.432, 0.881, p-value < 0.001) and in AIT treated patients (O= 0.46, 0.610, 0.66 and ρ = 0.692, 0.805, 0.824; p-value < 0.001). In both cohorts, we observed a positive correlation between the number of symptoms reported and drug use. Mean symptom levels were significantly greater in non-AIT treated than in AIT treated patients (p < 0.001) for all symptom categories. Pollen concentration thresholds for three symptom severity levels were calculated.Conclusions: Ragweed pollen concentration is predictive of symptom severity in ragweed (Amb a 1) allergy patients. AIT treated patients had significantly reduced mean symptom levels compared to non-AIT patients.