3,000,160 research outputs found

    Survey data on household finance and consumption - research summary and policy use

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    The first part of this paper provides a brief survey of the recent literature that employs survey data on household finance and consumption. Given the breadth of the topic, it focuses on issues that are particularly relevant for policy, namely i) wealth effects on consumption, ii) housing prices and household indebtedness, iii) retirement income, consumption and pension reforms, iv) access to credit and credit constraints, v) financial innovation, consumption smoothing and portfolio selection and vi) wealth inequality. The second part uses concrete examples to summarise how results from such surveys feed into policy-making within the central banks that already conduct such surveys. JEL Classification: C42, D12, D14.Household finance, consumption, survey data.

    Materials Selection of 3D Printing Filament and Utilization of Recycled Polyethylene Terephthalate (PET) in a Redesigned Breadboard

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    The demand for a novel and sustainable alternative materials for 3D printer filaments has been knowingly increasing. One alternative source for the filament is to reuse and recycle post-consumer plastic products, which is also a compelling approach to conserve energy and sustain the environment. Thus, this study is focused on the materials selection of virgin polymer resins and recycled post-consumer plastics for use in 3D printer filaments. A multi-criteria decision method of Elimination and Choice Expressing the Reality (ELECTRE) was utilized to determine the best materials for 3D printer filaments. The study has shown that the virgin low-density polyethylene (LDPE) and recycled polyethylene terephthalate (PET) are optimal materials as an alternative filament among other options such as virgin high-density polyethylene (HDPE), virgin PET, virgin polypropylene (PP) and recycled HDPE. Aside from the different options of the type of materials, the various properties considered in the calculation include tensile strength, melting point, glass transition temperature, melt flow index, coefficient of thermal expansion, and cost. Moreover, a redesigned breadboard was produced thru 3D printing using a recycled PET as filament source

    Are Consumers Forward-Looking?

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    Are consumers forward-looking? According to the certainty-equivalence version of the life cycle/permanent income hypothesis, consumption is a function of the expected present value of income. Using longitudinal data from the PSID, I invert this function and compare the realized present value of income to consumption. Consumption proves to be a very poor predictor of future income, despite future income being predictable by past income. Under rational expectations, information known to the consumer should not enter the regression of present value on consumption. However, as an empirical matter lagged income does enter. The conclusion is that consumers act "as if" they are not forward-looking. Available data being imperfect much of the paper is devoted to robustness tests, none of which change the basic conclusion.

    Consumption Matters

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    Simulation of Energy Consumption in Multi Cluster Wireless Sensor Networks

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    Energy conserving protocols in wireless sensor networks (WSNs), such as S-MAC, introduce multi-cluster network. The border nodes in multi cluster WSNs have more active time than the other nodes in the network; hence have more energy depletion rate. Since battery replacement in most networks is considered difficult, one or more nodes running out of energy prematurely will affect the network connectivity and decrease the overall network performance severely. This paper aims to (1) analyze the energy consumption in a multi-cluster sensor network and compare it to the single cluster scenario (2) investigate the merging time in a single cluster network. The result shows that, in average the energy needed to deliver a packet in the multi cluster networks is about 150% more than the energy needed in the single cluster networks. Moreover, the merging time in the single cluster network using schedule offset as the merging criteria in average is slightly smaller than one in the network using schedule ID as the merging criteria

    Consumption Insurance or Consumption Mobility?

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    The theory of full consumption insurance posits that households are insulated from all idiosyncratic shocks so that the ratio of the marginal utilities of consumption of any two households is constant over time. Consumption insurance therefore implies absence of consumption mobility between any two time periods. This implication requires knowledge of the evolution of the entire consumption distribution, not just its mean as in standard tests of complete markets. We test this unexplored prediction of the theory using a panel drawn from the Bank of Italy Survey of Household Income and Wealth. We design an appropriate non-parametric test and find substantial mobility of consumption even controlling for possible preference shifts and measurement error in consumption. The findings strongly reject the theory of full consumption insurance.Consumption insurance, mobility

    Consumption

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    Macroeconomic research on consumption has been influenced profoundly by rational expectations. First, rational expectations together with the hypothesis of constant expected real interest rates implies that consumption should evolve as a random walk. Much of the research of the past decade has been devoted to testing the random walk hypothesis and to explaining its failure. Three branches of the literature have developed. The first relies on the durability of consumption to explain deviations from the random walk property. The second invokes liquidity constraints which block consumers from the credit market transactions needed to make consumption follow a random walk when income fluctuates up and down. The third branch dispenses with the assumption that expected real interest rates are constant. It attempts to explain deviations from the random walk in terms of intertemporal substitution.

    Coal Consumption Sources

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