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Injuries have become devastating and often under-recognized public health concerns. In Canada, injuries are the leading cause of potential years of life lost before the age of 65. The geographical patterns of injury, however, are evident both over space and time, suggesting the possibility of spatial optimization of policies at the neighborhood scale to mitigate injury risk, foster prevention, and control within metropolitan regions. In this paper, Canada’s National Ambulatory Care Reporting System is used to assess unintentional and intentional injuries for Toronto between 2004 and 2010, exploring the spatial relations of injury throughout the city, together with Wellbeing Toronto data. Corroborating with these findings, spatial autocorrelations at global and local levels are performed for the reported over 1.7 million injuries. The sub-categorization for Toronto’s neighborhood further distills the most vulnerable communities throughout the city, registering a robust spatial profile throughout. Individual neighborhoods pave the need for distinct policy profiles for injury prevention. This brings one of the main novelties of this contribution. A comparison of the three regression models is carried out. The findings suggest that the performance of spatial regression models is significantly stronger, showing evidence that spatial regressions should be used for injury research. Wellbeing Toronto data performs reasonably well in assessing unintentional injuries, morbidity, and falls. Less so to understand the dynamics of intentional injuries. The results enable a framework to allow tailor-made injury prevention initiatives at the neighborhood level as a vital source for planning and participatory decision making in the medical field in developed cities such as Toronto.
Eric Vaz; Michael D. Cusimano; Fernando Bação; Bruno Damásio; Elissa Penfound. Open data and injuries in urban areas—A spatial analytical framework of Toronto using machine learning and spatial regressions. PLoS ONE 2021, 16, e0248285 .
AMA StyleEric Vaz, Michael D. Cusimano, Fernando Bação, Bruno Damásio, Elissa Penfound. Open data and injuries in urban areas—A spatial analytical framework of Toronto using machine learning and spatial regressions. PLoS ONE. 2021; 16 (3):e0248285.
Chicago/Turabian StyleEric Vaz; Michael D. Cusimano; Fernando Bação; Bruno Damásio; Elissa Penfound. 2021. "Open data and injuries in urban areas—A spatial analytical framework of Toronto using machine learning and spatial regressions." PLoS ONE 16, no. 3: e0248285.
This article assesses the effectiveness of the labour market reforms implemented in Portugal as part of the Troika’s structural reform package. Using an ARDL-bounds test model to perform the econometric estimation, this investigation examines the long-run relationship between unemployment, capital accumulation and labour market variables for the 1985–2013 period. The econometric estimation suggests that capital accumulation has been the main driver of long-run unemployment, whilst labour market variables have played a minor explanatory role. These results suggest that Portuguese NAIRU is endogenous to capital accumulation and do not support the Troika’s emphasis on labor market reforms as a strategy to reduce long-term unemployment.
Diogo Martins; Bruno Damásio. One Troika fits all? Job crash, pro-market structural reform and austerity-driven therapy in Portugal. Empirica 2019, 47, 495 -521.
AMA StyleDiogo Martins, Bruno Damásio. One Troika fits all? Job crash, pro-market structural reform and austerity-driven therapy in Portugal. Empirica. 2019; 47 (3):495-521.
Chicago/Turabian StyleDiogo Martins; Bruno Damásio. 2019. "One Troika fits all? Job crash, pro-market structural reform and austerity-driven therapy in Portugal." Empirica 47, no. 3: 495-521.
Bruno Damasio; Francisco Louçã; João Nicolau. The changing economic regimes and expected time to recover of the peripheral countries under the euro: A nonparametric approach. Physica A: Statistical Mechanics and its Applications 2018, 507, 524 -533.
AMA StyleBruno Damasio, Francisco Louçã, João Nicolau. The changing economic regimes and expected time to recover of the peripheral countries under the euro: A nonparametric approach. Physica A: Statistical Mechanics and its Applications. 2018; 507 ():524-533.
Chicago/Turabian StyleBruno Damasio; Francisco Louçã; João Nicolau. 2018. "The changing economic regimes and expected time to recover of the peripheral countries under the euro: A nonparametric approach." Physica A: Statistical Mechanics and its Applications 507, no. : 524-533.
The struggle between sail and steam is a long-standing theme in economic history. But this technological competition story has only partly tackled, since most studies have appreciated the rivalry between the two alternative modes of commercial sea carriage in the late 19th century while the early period has remained relatively under-analysed. This paper models the early dynamics between the two capital goods using a vector autoregression approach (VAR) and a Multivariate Markov Chain approach (MMC). We find evidence that the relationship was non-linear, with a strong indication of complementarities and cross-technology learning effects.
Bruno Damásio; Sandro Mendonça. Modelling insurgent-incumbent dynamics: Vector autoregressions, multivariate Markov chains, and the nature of technological competition. Applied Economics Letters 2018, 26, 843 -849.
AMA StyleBruno Damásio, Sandro Mendonça. Modelling insurgent-incumbent dynamics: Vector autoregressions, multivariate Markov chains, and the nature of technological competition. Applied Economics Letters. 2018; 26 (10):843-849.
Chicago/Turabian StyleBruno Damásio; Sandro Mendonça. 2018. "Modelling insurgent-incumbent dynamics: Vector autoregressions, multivariate Markov chains, and the nature of technological competition." Applied Economics Letters 26, no. 10: 843-849.
Bruno Damásio; João Nicolau. Combining a regression model with a multivariate Markov chain in a forecasting problem. Statistics & Probability Letters 2014, 90, 108 -113.
AMA StyleBruno Damásio, João Nicolau. Combining a regression model with a multivariate Markov chain in a forecasting problem. Statistics & Probability Letters. 2014; 90 ():108-113.
Chicago/Turabian StyleBruno Damásio; João Nicolau. 2014. "Combining a regression model with a multivariate Markov chain in a forecasting problem." Statistics & Probability Letters 90, no. : 108-113.
This paper analyses foreign direct investment (FDI) of Angola in Portugal. The reverse investment of African countries in Europe is a recent economic event that needs to be analysed, theoretically explained and empirically tested. A dynamic theoretical model is presented and a Bayesian model tests the model validating it. The results reveal that imports and corruption increase Angola FDI in Portugal. Some variables affect negatively Angola FDI in Portugal such as lagged Angola FDI, signifying an autoregressive negative effect in Portugal; the Portuguese official development assistance (ODA) to Angola, which are direct transfers from Portugal to Angola; and Angola's GDP. Policy implications are discussed.
Carlos Pestana Barros; Bruno Damásio; João Ricardo Faria. Reverse FDI in Europe: An Analysis of Angola's FDI in Portugal. African Development Review 2014, 26, 160 -171.
AMA StyleCarlos Pestana Barros, Bruno Damásio, João Ricardo Faria. Reverse FDI in Europe: An Analysis of Angola's FDI in Portugal. African Development Review. 2014; 26 (1):160-171.
Chicago/Turabian StyleCarlos Pestana Barros; Bruno Damásio; João Ricardo Faria. 2014. "Reverse FDI in Europe: An Analysis of Angola's FDI in Portugal." African Development Review 26, no. 1: 160-171.
This paper analyses FDI in 27 Asian countries in the period 2003-2011using a panel data quantile regression method and taking into account the heterogeneity in the data. Robustness tests are carried out by allowing for the endogeneity of the GDP growth rate (Harding and Lamarche, 2009). Overall, there is clear evidence of heterogeneity as indicated by the differences in the relative importance of the factors affecting FDI in the various countries. Moreover, the analysis by quantile confirms that bigger economies tend to attract more sizeable FDI inflows than smaller ones, as one would expect.
Guglielmo Maria Caporale; Carlos Pestana Barros; Bruno Damasio. Foreign direct investment in the Asian economies. 2013, 1 .
AMA StyleGuglielmo Maria Caporale, Carlos Pestana Barros, Bruno Damasio. Foreign direct investment in the Asian economies. . 2013; ():1.
Chicago/Turabian StyleGuglielmo Maria Caporale; Carlos Pestana Barros; Bruno Damasio. 2013. "Foreign direct investment in the Asian economies." , no. : 1.
This paper analyses investment from Angola in Portugal. An open economy model with money laundering is proposed and then tested with a time series Bayesian regression. The result reveals that exports and corruption are the positive determinants of Angola FDI in Portugal. Policy implications are derived.
Carlos Barros; Bruno Damásio; João Faria. Reverse FDI in Europe: An Analysis of Angola’s FDI in Portugal. 2011, 1 .
AMA StyleCarlos Barros, Bruno Damásio, João Faria. Reverse FDI in Europe: An Analysis of Angola’s FDI in Portugal. . 2011; ():1.
Chicago/Turabian StyleCarlos Barros; Bruno Damásio; João Faria. 2011. "Reverse FDI in Europe: An Analysis of Angola’s FDI in Portugal." , no. : 1.