José Ramos Pires Manso

Crude Oil Price Forecasting Techniques: A Comprehensive Review of Literature

The goal of this article is to review the existing literature on crude oil price forecasting. We categorized the existing forecasting techniques into the two main groups of quantitative and qualitative methods; and then we performed an almost comprehensive survey on the available literature with respect to these two main forecasting techniques.

Determinants of Regional Growth in Portugal : an Empirical Analysis

IntroductionRegional growth or development1 result not from a single factor, condition or agent, but from their joint action although in different ways. Is has been analyzed by several classical authors that advocated the theories of growth poles (Perroux, 1950) and cumulative causation (Myrdall, 1957) and emphasized the importance of transaction costs (Krugman, 1989; Scott, 1998). Regional growth occurs as a result of the interaction of multiple economic, social, cultural, institutional and environmental dimensions which, in turn, are also multifaceted, thence the intensity and form of development of each region being shaped by their depth and level of articulation (Becker and Wittemann, 2008).Among other factors, national and regional growth are determined by innovation, competitiveness, technology, human capital, tourism, infrastructures and equipments, as documented by Bronzini and Piselli (2008), Shapiro (2006), Rutten and Boekema (2007) and Jackson and Murphy (2006). Technology arises as an essential but not sufficient or exclusive condition to explain regional economic growth (Rutten and Boekema, 2007). The interaction between innovation, social networks and tangible and intangible assets of the region, such as knowledge and technology, are also factors of economic growth (Cooke, 2002; Teece, 2000).Since the reduction of economic and social inequalities between member countries and regions is one of the central objectives of the European Regional Policy, many researchers have chosen to study this subject (e.g. Goletsis and Chletsos, 2011). Authors such as Campo et al. (2008) proposed a classification of European regions adjusted to the different axis of socio-economic development, while Goletsis and Chletsos (2011) measured the development and regional disparities on the Greek periphery.Several authors studied the relationship between human capital and economic development (Barro, 1991; Barro, 2001; Barro and Sala-i-Martin, 1995; Benhabib and Spiegel, 1994; Gemmell, 1996; Bils and Klenow, 2000; Tamura, 2006) while Barrios and Strobl (2009) analyzed the relationship between regional inequality and per capita GDP in the 12 european countries2.Regional social capital and innovation networks are important elements of regions economic growth for Rutten and Boekema (2006), while technology and knowledge are crucial factors for Teece (2000) and Cooke (2002) and Liberto (2008) mentions education as a key factor for regional development in Italy.At the same time, Tuan and Ng (2007) focused on foreign direct investment (FDI) and regional development in China and Fu and Gabriel (2012) analyzed the contribution of migration and human capital for the regional development of this same country.At a national level, Ramos (2009) analyzed regional development and sustainability indicators, Crespo and Fontoura (2006; 2009) studied regional convergence at the municipal level, Antunes and Soukiazis (2006) highlighted the important role of European Structural Funds for convergence at the NUTS III level and Soukiazis and Proenca (2008), based on empirical evidence, considered tourism as a factor of regional convergence.This study aims to identify the main determinants of regional (NUT III) growth in Portugal. In terms of specific goals we can mention the following: (i) deepen the concepts, similarities and differences between growth and development; (ii) identify the key determinants that explain growth of Portuguese regions, considering them as defined in NUT III; (iii) identify the direction (positive or negative) of this influences; and (iv) assess whether the panel data approach is appropriate or suitable for this study.This research tests the following hypotheses:* Hypothesis 1: There is a positive association between per capita GDP and the following individual variables: population density, natural growth rate, resident population, employment, GVA, exports, electricity consumption, number of doctors, hospitals and health centers, number of museums and publications, number of higher education institutions, expenditure on culture, financial transfers from public administration3, number of landline phone accesses and hotel accommodation capacity;* Hypothesis 2 : There is a negative association between per capita GDP and the following individual variables: aging index, pension amount paid by Social Security, imports and crime rate;* Hypothesis 3: The panel data methodology is appropriate and has some advantages over other methodologies in order to analyze the economic regional growth. …

The Role of Regional Innovation Systems (RIS) in Translating R&D Investments into Economic and Employment Growth

The emergence of the so-called “European Paradox” shows that increasing Governmental R&D Investment is far from being a ‘panacea’ for stagnant growth. It is worth noting that Governmental R&D Investment does not have a statistically significant impact on employment, indicating the need to assess the trade-offs of policies that could lead to significant increases in government expenditure. Surprisingly, Governmental R&D Employment does not contribute to ‘mass-market’ employment, despite its quite important role in reducing Youth-Unemployment. Despite the negative side-effects of Governmental R&D Employment on both GVA and GDP, University R&D Employment appears to have a quite important role in reducing Unemployment, especially Youth-Unemployment, while it also does not have a downside in terms of economic growth. Technological Capacity enhancement is the most effective instrument for reducing Unemployment and is a policy without any downside regarding sustainable economic development.

Determinant factors of dairy production in the productive agglomerate of Alto Paraguay

The milk production in Mato Grosso State (Brazil) presents growth in most regions, and the Productive Agglomerate of the Alto Paraguay is the only space that obtained differentiated institutional support during the last decade, becoming a source for reflection on the current socio-economic condition of the milk producers. With an on-site research base and Multivariate Analysis basements, this study aims to define an underlying framework of the determinant factors for the activity’s development in the region. Results show a family activity in the limited stage, mostly in view of managerial problems. The productivity is low because the operational factors and the prices charged do not allow suitable investments to overcome these limitations.

O mercado de commodities na América e na Europa: condicionantes de produção e comercialização sob a perspectiva de dados em painel

Este estudo objetiva avaliar alguns dos principais fatores que influenciam na producao e nos mercados de arroz, feijao, milho e trigo, a partir do impacto da integracao internacional das cadeias produtivas. Exigencias supranacionais, associada ao aumento na demanda e qualidade dos alimentos, pressionam o setor produtivo no Brasil, Estados Unidos, Argentina e em alguns paises europeus, como Alemanha, Franca, Espanha, Holanda, Italia e Portugal, expressivos produtores, consumidores, exportadores e/ou importadores destas commodities. Sob estes aspectos, torna-se oportuno conhecer alguns dos principais condicionantes, bem como, provaveis impactos sobre a agricultura, setor chave para a seguridade alimentar. A ferramenta empregada consiste em um Painel de Dados, no sentido de identificar quais categorias sao responsaveis pelas alteracoes na oferta nestes mercados. Os resultados apontam para a necessidade de politicas moderadas de ajuste de câmbio, incentivo as exportacoes e ao consumo, pois tratam-se dos fatores mais importantes no que se refere a impactos sobre a producao. Ha uma correlacao favoravel destes fatores para com as economias em questao, sendo que variacoes positivas tendem a estimular os setores produtivos avaliados.