Tax policy options to promote private capital formation in Pakistan

The authors developed a simple two-period general equilibrium model to analyze the macroeconomic impact of tax policies in Pakistan. They analyze two scenarios. In scenario 1, the investment tax credit rate is increased from 15 percent to 30 percent. The new fiscal regime increases investment but also significantly increases inflation. In scenario 2, the original investment tax credit rate is retained but the statutory corporate tax rate is reduced. Welfare improves more than under scenario 1. The authors conclude that in Pakistan, at least, changes in corporate tax rates are probably better instruments for promoting capital formation than are increased investment tax credits. In particular, cuts in corporate taxes improve welfare more than do increases in investment tax credits. Increasing the investment tax credit stimulates more capital formation than does decreasing corporate taxes, but the tax credits also have significant macroeconomic consequences.Environmental Economics&Policies,Public Sector Economics&Finance,Banks&Banking Reform,International Terrorism&Counterterrorism,Economic Theory&Research

General equilibrium effects of investment incentives in Mexico

Mexico has experimented with several tax instruments designed to promote private capital formation. Among such initiatives were general and industry-specific tax credits, employment tax credits, and corporate tax credits. The authors examine relative efficacy of such instruments using a dynamic computable general equilibrium model. They carry out model simulations using three equal-yield investment incentive scenarios: increases in investment tax credits, increases in employment tax credits, and an equivalent reduction in the corporate tax rate. The authors present outlines of the tax policy environment with model details and they highlight alternate tax incentives regimes. Conclusions and summary results are provided by the authors.International Terrorism&Counterterrorism,Economic Theory&Research,Environmental Economics&Policies,Banks&Banking Reform,Public Sector Economics&Finance

Student-t Processes as Alternatives to Gaussian Processes

We investigate the Student-t process as an alternative to the Gaussian process as a nonparametric prior over functions. We derive closed form expressions for the marginal likelihood and predictive distribution of a Student-t process, by integrating away an inverse Wishart process prior over the covariance kernel of a Gaussian process model. We show surprising equivalences between different hierarchical Gaussian process models leading to Student-t processes, and derive a new sampling scheme for the inverse Wishart process, which helps elucidate these equivalences. Overall, we show that a Student-t process can retain the attractive properties of a Gaussian process -- a nonparametric representation, analytic marginal and predictive distributions, and easy model selection through covariance kernels -- but has enhanced flexibility, and predictive covariances that, unlike a Gaussian process, explicitly depend on the values of training observations. We verify empirically that a Student-t process is especially useful in situations where there are changes in covariance structure, or in applications like Bayesian optimization, where accurate predictive covariances are critical for good performance. These advantages come at no additional computational cost over Gaussian processes.Comment: 13 pages, 6 figures, 1 table. To appear in "The Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS), 2014.

Redox supercapacitor performance of nanocrystalline molybdenum nitrides obtained by ammonolysis of chloride- and amide-derived precursors

Reactions of MoCl5 or Mo(NMe2)4 with ammonia result in cubic ?-Mo2N or hexagonal ?1-MoN depending on reaction time and temperature. At moderate temperatures the cubic product from Mo(NMe2)4 exhibits lattice distortions. Fairly high surface areas are observed in the porous particles of the chloride-derived materials and high capacitances of up to 275 F g?1 are observed when electrodes made from them are cycled in aqueous H2SO4 or K2SO4 electrolytes. The cyclic voltammograms suggest charge is largely stored in the electrochemical double layer at the surface of these materials. Amide-derived molybdenum nitrides have relatively low surface areas and smaller capacitances, but do exhibit strong redox features in their cyclic voltammograms, suggesting that redox capacitance is responsible for a significant proportion of the charge stored

Myopericarditis in a pregnant woman with acute promyelocytic leukemia

AbstractAcute promyelocytic leukemia (APL) is a form of acute leukemia with a characteristic translocation, t(15;17), and is considered a hematologic emergency, typically treated with all-trans retinoic acid and an anthracycline. We present the case of a young, gravid woman who was diagnosed with APL in the third trimester, initiated typical treatment, and suffered uncommon cardiac complications.<Learning objective: Myopericarditis is not a side effect often encountered in the management of acute promyelocytic leukemia with alpha t-retinoic acid, and its mechanism is incompletely understood but possibly related to the differentiation syndrome. This complication can be effectively treated with systemic glucocorticoids, supportive care, and withdrawal of the offending agent, even in the pregnant population.

Improving Palliative Care with Deep Learning

Improving the quality of end-of-life care for hospitalized patients is a priority for healthcare organizations. Studies have shown that physicians tend to over-estimate prognoses, which in combination with treatment inertia results in a mismatch between patients wishes and actual care at the end of life. We describe a method to address this problem using Deep Learning and Electronic Health Record (EHR) data, which is currently being piloted, with Institutional Review Board approval, at an academic medical center. The EHR data of admitted patients are automatically evaluated by an algorithm, which brings patients who are likely to benefit from palliative care services to the attention of the Palliative Care team. The algorithm is a Deep Neural Network trained on the EHR data from previous years, to predict all-cause 3-12 month mortality of patients as a proxy for patients that could benefit from palliative care. Our predictions enable the Palliative Care team to take a proactive approach in reaching out to such patients, rather than relying on referrals from treating physicians, or conduct time consuming chart reviews of all patients. We also present a novel interpretation technique which we use to provide explanations of the model's predictions.Comment: IEEE International Conference on Bioinformatics and Biomedicine 201

A compact to revitalise large-scale irrigation systems using a leadership-partnership-ownership ‘theory of change’

In countries with transitional economies such as those found in South Asia, large-scale irrigation systems (LSIS) with a history of public ownership account for about 115 million ha (Mha) or approximately 45% of their total area under irrigation. In terms of the global area of irrigation (320 Mha) for all countries, LSIS are estimated at 130 Mha or 40% of irrigated land. These systems can potentially deliver significant local, regional and global benefits in terms of food, water and energy security, employment, economic growth and ecosystem services. For example, primary crop production is conservatively valued at about US$355 billion. However, efforts to enhance these benefits and reform the sector have been costly and outcomes have been underwhelming and short-lived. We propose the application of a 'theory of change' (ToC) as a foundation for promoting transformational change in large-scale irrigation centred upon a 'global irrigation compact' that promotes new forms of leadership, partnership and ownership (LPO). The compact argues that LSIS can change by switching away from the current channelling of aid finances controlled by government irrigation agencies. Instead it is for irrigators, closely partnered by private, public and NGO advisory and regulatory services, to develop strong leadership models and to find new compensatory partnerships with cities and other river basin neighbours. The paper summarises key assumptions for change in the LSIS sector including the need to initially test this change via a handful of volunteer systems. Our other key purpose is to demonstrate a ToC template by which large-scale irrigation policy can be better elaborated and discussed