918 resultados para PETROLEUM PRICES
Resumo:
Developer paid fees or charges are a commonly used mechanism for local governments to pay for new infrastructure. However, property developers claim that these costs are merely passed on to home buyers, with adverse effects to housing affordability. Despite numerous government reports and many years of industry advocacy, there remains no empirical evidence in Australia to confirm or quantify this passing on effect to home buyers. Hence there remains no data from which governments can base policy decision on, and the debate continues. This paper examines the question of the impact of infrastructure charges on housing affordability in Australia. It presents the findings of a hedonic house price model that provides the first empirical evidence that infrastructure charges do increase house prices in Australia. This research is consistent with international findings, that support the proposition that developer paid infrastructure charges are passed on to home buyers and are a significant contributor to increasing house prices and reduced housing affordability.
Resumo:
This article analyses co-movements in a wide group of commodity prices during the time period 1992–2010. Our methodological approach is based on the correlation matrix and the networks inside. Through this approach we are able to summarize global interaction and interdependence, capturing the existing heterogeneity in the degrees of synchronization between commodity prices. Our results produce two main findings: (a) we do not observe a persistent increase in the degree of co-movement of the commodity prices in our time sample, however from mid-2008 to the end of 2009 co-movements almost doubled when compared with the average correlation; (b) we observe three groups of commodities which have exhibited similar price dynamics (metals, oil and grains, and oilseeds) and which have increased their degree of co-movement during the sampled period.
Resumo:
Air pollution is a persistent problem in urban areas, and traffic emissions are a major cause of poor air quality. Policies to curb pollution levels often involve raising the price of using private vehicles, for example, congestion charges. We were interested in whether higher fuel prices were associated with decreased air pollution levels. We examined an association between diesel and petrol prices and four traffic-related pollutants in Brisbane from 2010 to 2013. We used a regression model and examined pollution levels up to 16 days after the price change. Higher diesel prices were associated with statistically significant short-term reductions in carbon monoxide and nitrogen oxides. Changes in petrol prices had no impact on air pollution. Raising diesel taxes in Australia could be justified as a public health measure. As raising taxes is politically unpopular, an alternative political approach would be to remove schemes that put a downward pressure on fuel prices, such as industry subsidies and shopping vouchers that give fuel discounts.
Resumo:
As fossil fuel prices increase and environmental concerns gain prominence, the development of alternative fuels from biomass has become more important. Biodiesel produced from microalgae is becoming an attractive alternative to share the role of petroleum. Currently it appears that the production of microalgal biodiesel is not economically viable in current environment because it costs more than conventional fuels. Therefore, a new concept is introduced in this article as an option to reduce the total production cost of microalgal biodiesel. The integration of biodiesel production system with methane production via anaerobic digestion is proved in improving the economics and sustainability of overall biodiesel stages. Anaerobic digestion of microalgae produces methane and further be converted to generate electricity. The generated electricity can surrogate the consumption of energy that require in microalgal cultivation, dewatering, extraction and transesterification process. From theoretical calculations, the electricity generated from methane is able to power all of the biodiesel production stages and will substantially reduce the cost of biodiesel production (33% reduction). The carbon emissions of biodiesel production systems are also reduced by approximately 75% when utilizing biogas electricity compared to when the electricity is otherwise purchased from the Victorian grid. The overall findings from this study indicate that the approach of digesting microalgal waste to produce biogas will make the production of biodiesel from algae more viable by reducing the overall cost of production per unit of biodiesel and hence enable biodiesel to be more competitive with existing fuels.
Resumo:
The study monitored the emissions of volatile organic compounds (VOCs) from the exhaust of cars fuelled by liquefied petroleum gas (LPG) and unleaded petrol (ULP). Six cars, four fuelled by LPG and two by ULP, were tested on a chassis dynamometer at two different cruising modes of operation (60 km h−1 and 80 km h−1) and idle. A total of 33 VOCs were identified in the exhaust of both types of fuels by the use of GC/MS. Due to the complexity of the dataset, Multi Criteria Decision Making (MCDM) software PROMETHEE and GAIA was used to rank the least polluting mode and fuel. The 60 km h−1 driving speed was identified as the cleaner mode of driving as was LPG fuel. The Ozone Formation Potential (OFP) of the VOCs was also calculated by using the incremental reactivity scale. Priority VOCs leading to ozone formation were identified according to the three incremental reactivity scales: MIR, MOIR and EBIR. PROMETHEE was applied to assess the most preferred scale of reactivity for predicting ozone formation potential under different scenarios. The results enhance the understanding of the environmental value of using LPG to power passenger cars.
Resumo:
This paper examines the question of whether the imposition of developer infrastructure charges on housing developers affects the price of residential land. Developer paid fees or charges are a commonly used mechanism for local governments to fund new infrastructure as a “user pays” method of funding new urban infrastructure. Some argue these costs are passed back to the original land owner by way of lower land prices. However, property developers claim these charges are added on to new land prices, with flow on negative impact to housing affordability. This paper presents the findings of a hedonic land price model that provides the first empirical evidence that infrastructure charges do increase residential land prices in Brisbane, Australia. This research is consistent with international findings and supports the proposition that developer paid infrastructure charges are over-passed to home buyers and are a significant contributor to reduced housing affordability.
Resumo:
One imperfection in housing markets is imperfect knowledge about legal interests such as ground leases. Both actual reduced legal interest as well as uncertainty surrounding rights and future lease payments for houses constructed on leased land may affect prices relative to houses built on freehold land. We use regression analysis of sales prices of condominium transactions in Helsinki to examine the effect ground leases have on house prices. We find that prices on condominiums constructed on leased lots are discounted at least 5 %, on average. In addition, we see that the announcement of potentially large increases in base rents upon renewal contributes to the discount.
Resumo:
The purpose of the study was to analyse factors affecting the differences in land prices between regions. The key issue was to find out the policy effects on farmland prices. In addition to comprehensive literature review, a theoretical analysis as well as modern panel and spatial econometric techniques were utilized. The study clearly pointed out the importance of taking into account the possible spatial dependence. The data were exceptionally large, comprising more than 6 000 observations. Thus, it allowed a thorough econometric estimation including the possibility to take into account the spatial nature of the data. This study supports the view that there are many other factors that affect farmland prices besides pure agricultural returns. It was also found that the support clearly affects land prices. However, rather than assuming the discount rates for support and market returns to be similar, the rough analysis refers to the discount rate for support being a little lower. If this were true it would indicate that farmers rely more on support income than market returns. The results support the view presented in literature that land values are more responsive to government payments when these payments are perceived to be permanent. An important result of this study is that the structural differences between regions and the structural change in agriculture seemed to have a considerable role in affecting land prices. Firstly, the present structure affects the competition in the land market: the more dense farms are in the region the more there are potential buyers, and the land price increases. Secondly, the change in farm structure (especially in animal husbandry) connected to the policy changes that increase area-based support affects land prices. The effect comes from two sources. Growing farms need more land for the manure, and the proportion of retiring farmers may be lower. The introduction of the manure density variable proved to be an efficient way to aggregate the otherwise very difficult task of taking into account the environmental pressure caused by structural change in animal husbandry. Finally, infrastructure also has a very important role in determining the price level of agricultural land. If other industries are prospering in the surrounding area, agricultural viability also seems to improve. The non-farm opportunities offered to farm families make continuing and developing farming more tempting.
Resumo:
This paper investigates multiple roles of transfer prices for shipments of goods and services between entities of a multinational enterprise. At the center is the role of transfer pricing (TP) in tax manipulation, but other roles having to do with internal operations or strategic delegation, etc. are also considered. The interesting question is to what extent and how the different roles of TPs interfere with each other. The answer depends on whether companies use one or two books, i.e. whether they (can) apply different TPs for different purposes. We illustrate, in a stylized model, the competing aims of tax manipulation and strategic delegation. Finally, we briefly look at selected reform proposals, concluding that either TP problems are not addressed, or else new distortions will be introduced instead.
Resumo:
Topics in Spatial Econometrics — With Applications to House Prices Spatial effects in data occur when geographical closeness of observations influences the relation between the observations. When two points on a map are close to each other, the observed values on a variable at those points tend to be similar. The further away the two points are from each other, the less similar the observed values tend to be. Recent technical developments, geographical information systems (GIS) and global positioning systems (GPS) have brought about a renewed interest in spatial matters. For instance, it is possible to observe the exact location of an observation and combine it with other characteristics. Spatial econometrics integrates spatial aspects into econometric models and analysis. The thesis concentrates mainly on methodological issues, but the findings are illustrated by empirical studies on house price data. The thesis consists of an introductory chapter and four essays. The introductory chapter presents an overview of topics and problems in spatial econometrics. It discusses spatial effects, spatial weights matrices, especially k-nearest neighbours weights matrices, and various spatial econometric models, as well as estimation methods and inference. Further, the problem of omitted variables, a few computational and empirical aspects, the bootstrap procedure and the spatial J-test are presented. In addition, a discussion on hedonic house price models is included. In the first essay a comparison is made between spatial econometrics and time series analysis. By restricting the attention to unilateral spatial autoregressive processes, it is shown that a unilateral spatial autoregression, which enjoys similar properties as an autoregression with time series, can be defined. By an empirical study on house price data the second essay shows that it is possible to form coordinate-based, spatially autoregressive variables, which are at least to some extent able to replace the spatial structure in a spatial econometric model. In the third essay a strategy for specifying a k-nearest neighbours weights matrix by applying the spatial J-test is suggested, studied and demonstrated. In the final fourth essay the properties of the asymptotic spatial J-test are further examined. A simulation study shows that the spatial J-test can be used for distinguishing between general spatial models with different k-nearest neighbours weights matrices. A bootstrap spatial J-test is suggested to correct the size of the asymptotic test in small samples.
Resumo:
Financial crises have shown that dramatic movements in one financial market can have a powerful impact on other markets. The paper proposes to use cobreaking to model comovements between financial markets during crises and to test for conta-gion. It finds evidence of cobreaking between stock returns in developed markets. Finding cobreaking has implications for the diversification of international investments. For emerging mar-ket stock returns the evidence of cobreaking is mainly due to the non-financial event of the 9/11 terrorist attacks in 2001. Fi-nancial crises originating in one emerging market do not spread to other markets, i.e., no contagion.
Resumo:
This paper investigates the persistent pattern in the Helsinki Exchanges. The persistent pattern is analyzed using a time and a price approach. It is hypothesized that arrival times are related to movements in prices. Thus, the arrival times are defined as durations and formulated as an Autoregressive Conditional Duration (ACD) model as in Engle and Russell (1998). The prices are defined as price changes and formulated as a GARCH process including duration measures. The research question follows from market microstructure predictions about price intensities defined as time between price changes. The microstructure theory states that long transaction durations might be associated with both no news and bad news. Accordingly, short durations would be related to high volatility and long durations to low volatility. As a result, the spread will tend to be larger under intensive moments. The main findings of this study are 1) arrival times are positively autocorrelated and 2) long durations are associated with low volatility in the market.
Resumo:
Uncombined elemental sulphur in petroleum products such as kerosene, diesel, furnace and gear oil has been determined by conversion into copper(I) sulphide at 150–170°. The copper(I) sulphide can be weighed, or its sulphur content determined by the iodimetric method.
Resumo:
In this paper, we use reinforcement learning (RL) as a tool to study price dynamics in an electronic retail market consisting of two competing sellers, and price sensitive and lead time sensitive customers. Sellers, offering identical products, compete on price to satisfy stochastically arriving demands (customers), and follow standard inventory control and replenishment policies to manage their inventories. In such a generalized setting, RL techniques have not previously been applied. We consider two representative cases: 1) no information case, were none of the sellers has any information about customer queue levels, inventory levels, or prices at the competitors; and 2) partial information case, where every seller has information about the customer queue levels and inventory levels of the competitors. Sellers employ automated pricing agents, or pricebots, which use RL-based pricing algorithms to reset the prices at random intervals based on factors such as number of back orders, inventory levels, and replenishment lead times, with the objective of maximizing discounted cumulative profit. In the no information case, we show that a seller who uses Q-learning outperforms a seller who uses derivative following (DF). In the partial information case, we model the problem as a Markovian game and use actor-critic based RL to learn dynamic prices. We believe our approach to solving these problems is a new and promising way of setting dynamic prices in multiseller environments with stochastic demands, price sensitive customers, and inventory replenishments.