Economic growth with coal, oil and renewable energy consumption in China: prospects for fuel substitution

We examine the relationship between Chinese aggregate production and consumption of three main energy commodities: coal, oil and renewable energy. Both autoregressive distributed lag (ARDL) and vector error correction modeling (VECM) show that Chinese growth is led by all three energy sources. Economic growth also causes coal, oil and renewables consumption, but with negative own-price effects for coal and oil and a strong possibility of fuel substitution through positive cross-price effects. The results further show coal consumption causing pollution, while renewable energy consumption reduces emissions. No significant causation on emissions is found for oil. Hence, making coal both absolutely and relatively expensive compared to oil and renewable energy encourages shifting from coal to oil and renewable energy, thereby improving economic and environmental sustainability.

Applied econometrics and implications for energy economics research

Developments in applied econometrics, particularly with regard to unit root tests and cointegration tests, have motivated a rich empirical literature on energy economics over the last decade. This study reviews recent developments in time series econometrics applications in the energy economics literature. We first consider the literature on the integration properties of energy variables. We begin with a discussion of the implications of whether energy variables contain a unit root and proceed to examine how results differ according to the specific unit root or stationarity test employed. We then proceed to examine recent developments in the literature on cointegration, Granger causality and long-run estimates between (disaggregated) energy consumption and economic growth. We review both single country and panel studies and pay particular attention to studies which have expanded the literature through adding variables such as financial development and trade, in addition to energy consumption to the augmented production function, as well as studies which have extended the literature through examining disaggregated energy consumption by type. In each case we highlight best practice in the literature, point to limitations in the literature, including econometric modeling challenges, and suggest recommendations for future research. A key message of our survey is that the profession needs to guard against 'overload' of research in these areas as most applied studies are no longer adding anything more to what is already known. © 2014 Elsevier B.V. All rights reserved.

Fifteen to twenty percent of HIV substitution mutations are associated with recombination

HIV undergoes high rates of mutation and recombination during reverse transcription, but it is not known whether these events occur independently or are linked mechanistically. Here we used a system of silent marker mutations in HIV and a single round of infection in primary T lymphocytes combined with a high-throughput sequencing and mathematical modeling approach to directly estimate the viral recombination and mutation rates. From >7 million nucleotides (nt) of sequences from HIV infection, we observed 4,801 recombination events and 859 substitution mutations (≈1.51 and 0.12 events per 1,000 nt, respectively). We used experimental controls to account for PCR-induced and transfection-induced recombination and sequencing error. We found that the single-cycle virus-induced mutation rate is 4.6 × 10(-5) mutations per nt after correction. By sorting of our data into recombined and nonrecombined sequences, we found a significantly higher mutation rate in recombined regions (P = 0.003 by Fisher's exact test). We used a permutation approach to eliminate a number of potential confounding factors and confirm that mutation occurs around the site of recombination and is not simply colocated in the genome. By comparing mutation rates in recombined and nonrecombined regions, we found that recombination-associated mutations account for 15 to 20% of all mutations occurring during reverse transcription.

Predicting the likely response of data-poor ecosystems to climate change using space-for-time substitution across domains

Predicting ecological response to climate change is often limited by a lack of relevant local data from which directly applicable mechanistic models can be developed. This limits predictions to qualitative assessments or simplistic rules of thumb in data-poor regions, making management of the relevant systems difficult. We demonstrate a method for developing quantitative predictions of ecological response in data-poor ecosystems based on a space-for-time substitution, using distant, well-studied systems across an inherent climatic gradient to predict ecological response. Changes in biophysical data across the spatial gradient are used to generate quantitative hypotheses of temporal ecological responses that are then tested in a target region. Transferability of predictions among distant locations, the novel outcome of this method, is demonstrated via simple quantitative relationships that identify direct and indirect impacts of climate change on physical, chemical and ecological variables using commonly available data sources. Based on a limited subset of data, these relationships were demonstrably plausible in similar yet distant (>2000 km) ecosystems. Quantitative forecasts of ecological change based on climate-ecosystem relationships from distant regions provides a basis for research planning and informed management decisions, especially in the many ecosystems for which there are few data. This application of gradient studies across domains - to investigate ecological response to climate change - allows for the quantification of effects on potentially numerous, interacting and complex ecosystem components and how they may vary, especially over long time periods (e.g. decades). These quantitative and integrated long-term predictions will be of significant value to natural resource practitioners attempting to manage data-poor ecosystems to prevent or limit the loss of ecological value. The method is likely to be applicable to many ecosystem types, providing a robust scientific basis for estimating likely impacts of future climate change in ecosystems where no such method currently exists.

Mental health care system optimization from a health-economics perspective: where to sow and where to reap?

Health care expenditure (as % of GDP) has been rising in all OECD countries over the last decades. Now, in the context of the economic downturn, there is an even more pressing need to better guarantee the sustainability of health care systems. This requires that policy makers are informed about optimal allocation of budgets. We take the Dutch mental health system in the primary care setting as an example of new ways to approach optimal allocation.

On the use of panel cointegration tests in energy economics

There is a burgeoning literature based on using panel cointegration techniques to study the relationship between energy consumption and GDP. Most panel cointegration tests employed take no cointegration as the null hypothesis. The current paper illustrates how a rejection by such a test cannot be taken as evidence of cointegration for the panel as a whole, a fact that seems to have gone largely unnoticed in the literature. Hence, even if the no cointegration null is rejected, this evidence is not enough to ensure that the relationship can be meaningfully estimated, as most (if not all) estimators in the literature require that the panel is cointegrated as a whole.

Two Essays on the economics of Education

We develop a job-market signaling model where signals may convey two pieces of information. This model is employed to study the GED exam and countersignaling (signals non-monotonic in ability). A result of the model is that countersignaling is more expected to occur in jobs that require a combination of skills that differs from the combination used in the schooling process. The model also produces testable implications consistent with evidence on the GED: (i) it signals both high cognitive and low non-cognitive skills and (ii) it does not affect wages. Additionally, it suggests modifications that would make the GED a more effective signal.

Inflation and income inequality: a shopping-time aproach: (Forthcoming, Journal of Development Economics)

Our work is based on a simpliÖed heterogenous-agent shoppingtime economy in which economic agents present distinct productivities in the production of the consumption good, and di§erentiated access to transacting assets. The purpose of the model is to investigate whether, by focusing the analysis solely on endogenously determined shopping times, one can generate a positive correlation between ináation and income inequality. Our main result is to show that, provided the productivity of the interest-bearing asset in the transacting technology is high enough, it is true true that a positive link between ináation and income inequality is generated. Our next step is to show, through analysis of the steady-state equations, that our approach can be interpreted as a mirror image of the usual ináation-tax argument for income concentration. An example is o§ered to illustrate the mechanism.

The diversity of diversity: further methodological considerations on the use of the concept in cultural economics

The implications of diversity still raise confusion in the cultural debate. We address them from both a formal and conceptual viewpoints, putting in check the validity of some arguments. We conclude that: measuring diversity demands key decisions and careful statistical procedures; ignorance on optimal diversity levels and on ways to generate them is widespread in the cultural field; there is no support for cultural diversity as something associated to fair economic and political systems; restriction to sheer economics requires the establishment of links between diversity and measurable properties – something rather incipient. Diversity, as a social choice, should be distinguished from it as an economic value.