34 resultados para Economic and conservation benefits


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The present paper presents a meta-analysis of the economic and agronomic performance of genetically modified (GM) crops worldwide. Bayesian, classical and non-parametric approaches were used to evaluate the performance of GM crops v. their conventional counterparts. The two main GM crop traits (herbicide tolerant (HT) and insect resistant (Bt)) and three of the main GM crops produced worldwide (Bt cotton, HT soybean and Bt maize) were analysed in terms of yield, production cost and gross margin. The scope of the analysis covers developing and developed countries, six world regions, and all countries combined. Results from the statistical analyses indicate that GM crops perform better than their conventional counterparts in agronomic and economic (gross margin) terms. Regarding countries’ level of development, GM crops tend to perform better in developing countries than in developed countries, with Bt cotton being the most profitable crop grown.

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This paper addressed the degree of autonomy experienced by the planning regimes of London, Paris and Berlin. What variation exists in the governance of these cities and how do national, local, political, business and community interests effect planning decisions? The discussion is placed in the context of the literature on world cities and growth coalitions and the debate over whether economic forces compel cities to follow similar strategies. The paper concludes that in the case of the three cities examined there is considerable variation of planning approach due to different historical, cultural and political factors.

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The emergence and spread of infectious diseases reflects the interaction of ecological and economic factors within an adaptive complex system. We review studies that address the role of economic factors in the emergence and spread of infectious diseases and identify three broad themes. First, the process of macro-economic growth leads to environmental encroaching, which is related to the emergence of infectious diseases. Second, there are a number of mutually reinforcing processes associated with the emergence/spread of infectious diseases. For example, the emergence and spread of infectious diseases can cause significant economic damages, which in turn may create the conditions for further disease spread. Also, the existence of a mutually reinforcing relationship between global trade and macroeconomic growth amplifies the emergence/spread of infectious diseases. Third, microeconomic approaches to infectious disease point to the adaptivity of human behavior, which simultaneously shapes the course of epidemics and responds to it. Most of the applied research has been focused on the first two aspects, and to a lesser extent on the third aspect. With respect to the latter, there is a lack of empirical research aimed at characterizing the behavioral component following a disease outbreak. Future research should seek to fill this gap and develop hierarchical econometric models capable of integrating both macro and micro-economic processes into disease ecology.

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This paper models the determinants of integration in the context of global real estate security markets. Using both local and U.S. Dollar denominated returns, we model conditional correlations across listed real estate sectors and also with the global stock market. The empirical results find that financial factors, such as the relationship with the respective equity market, volatility, the relative size of the real estate sector and trading turnover all play an important role in the degree of integration present. Furthermore, the results highlight the importance of macro-economic variables in the degree of integration present. All four of the macro-economic variables modeled provide at least one significant result across the specifications estimated. Factors such as financial and trade openness, monetary independence and the stability of a country’s currency all contribute to the degree of integration reported.

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In this paper we discuss the current state-of-the-art in estimating, evaluating, and selecting among non-linear forecasting models for economic and financial time series. We review theoretical and empirical issues, including predictive density, interval and point evaluation and model selection, loss functions, data-mining, and aggregation. In addition, we argue that although the evidence in favor of constructing forecasts using non-linear models is rather sparse, there is reason to be optimistic. However, much remains to be done. Finally, we outline a variety of topics for future research, and discuss a number of areas which have received considerable attention in the recent literature, but where many questions remain.

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This paper employs a vector autoregressive model to investigate the impact of macroeconomic and financial variables on a UK real estate return series. The results indicate that unexpected inflation, and the interest rate term spread have explanatory powers for the property market. However, the most significant influence on the real estate series are the lagged values of the real estate series themselves. We conclude that identifying the factors that have determined UK property returns over the past twelve years remains a difficult task.