Subnational fiscal sustainability analysis : what can we learn from Tamil Nadu ?

In the late 1990s the Indian state of Tamil Nadu experienced an unprecedented fiscal deterioration, which was part of the widespread fiscal deterioration in Indian states. This deterioration was troubling because current expenditure outgrew total revenue, leaving little fiscal space for infrastructure spending. The paper presents a framework for subnational fiscal sustainability analysis and applies it to Tamil Nadu where subsequent fiscal adjustment has been ambitious and politically challenging, but has promised to put state finance on a sustainable path and create fiscal space for infrastructure investment. The paper emphasizes the differences between fiscal sustainability analysis at the national and subnational levels, attempts to take into account uncertainty, and discusses the key components of the state's fiscal accounts and how they respond to reforms and shocks. Risks to Tamil Nadu's fiscal outlook include interest rate shocks, pressures on the primary balance, and contingent liabilities. Though the state's efforts to remove constraints to economic growth, minimize recurrent expenditures and maximize its revenue potential will be critical for fiscal sustainability, national policies feature prominently in subnational fiscal adjustment. Tamil Nadu's quest for fiscal sustainability is relevant for other countries. Decentralization has given subnational governments in developing countries significant spending and taxation responsibilities, and the capacity to incur debt. The fiscal stress of the Indian states echoed the fiscal crises of subnational governments in several other major emerging economies.Banks&Banking Reform,Fiscal Adjustment,Public Sector Economics&Finance,Economic Theory&Research,Economic Stabilization

Plane-Wave-Based Stochastic-Deterministic Density Functional Theory for Extended Systems

Traditional finite-temperature Kohn-Sham density functional theory (KSDFT) has an unfavorable scaling with respect to the electron number or at high temperatures. The evaluation of the ground-state density in KSDFT can be replaced by the Chebyshev trace (CT) method. In addition, the use of stochastic orbitals within the CT method leads to the stochastic density functional theory [Phys. Rev. Lett. 111, 106402 (2013)] (SDFT) and its improved theory, mixed stochastic-deterministic density functional theory [Phys. Rev. Lett. 125, 055002 (2020)] (MDFT). We have implemented the above four methods within the first-principles package ABACUS. All of the four methods are based on the plane-wave basis set with the use of norm-conserving pseudopotentials and the periodic boundary conditions with the use of $k$-point sampling in the Brillouin zone. By using the KSDFT calculation results as benchmarks, we systematically evaluate the accuracy and efficiency of the CT, SDFT, and MDFT methods via examining a series of physical properties, which include the electron density, the free energy, the atomic forces, stress, and density of states for a few condensed phase systems. The results suggest that our implementations of CT, SDFT, and MDFT not only reproduce the KSDFT results with a high accuracy, but also exhibit several advantages over the tradition KSDFT method. We expect these methods can be of great help in studying high-temperature and large-size extended systems such as warm dense matter and dense plasma

Characterization of the Hydrogen-Bond Network in High-Pressure Water by Deep Potential Molecular Dynamics

The hydrogen-bond (H-bond) network of high-pressure water is investigated by neural-network-based molecular dynamics (MD) simulations with the first-principles accuracy. The static structure factors (SSFs) of water at three densities, i.e., 1, 1.115 and 1.24 g/cm3 are directly evaluated from 512-water MD trajectories, which are in quantitative agreement with the experiments. We propose a new method to decompose the computed SSF and identify the changes in SSF with respect to the changes in H-bond structures. We find a larger water density results in a higher probability for one or two non-H-bonded water molecules to be inserted into the inner shell, explaining the changes in the tetrahedrality of water under pressure. We predict that the structure of the accepting end of water molecules is more easily influenced by the pressure than the donating end. Our work sheds new light on explaining the SSF and H-bond properties in related fields

Promoting Open-domain Dialogue Generation through Learning Pattern Information between Contexts and Responses

Recently, utilizing deep neural networks to build the opendomain dialogue models has become a hot topic. However, the responses generated by these models suffer from many problems such as responses not being contextualized and tend to generate generic responses that lack information content, damaging the user's experience seriously. Therefore, many studies try introducing more information into the dialogue models to make the generated responses more vivid and informative. Unlike them, this paper improves the quality of generated responses by learning the implicit pattern information between contexts and responses in the training samples. In this paper, we first build an open-domain dialogue model based on the pre-trained language model (i.e., GPT-2). And then, an improved scheduled sampling method is proposed for pre-trained models, by which the responses can be used to guide the response generation in the training phase while avoiding the exposure bias problem. More importantly, we design a response-aware mechanism for mining the implicit pattern information between contexts and responses so that the generated replies are more diverse and approximate to human replies. Finally, we evaluate the proposed model (RAD) on the Persona-Chat and DailyDialog datasets; and the experimental results show that our model outperforms the baselines on most automatic and manual metrics

A radio structure resolved at the deca-parsec scale in radio-quiet quasar PDS 456 with an extremely powerful X-ray outflow

Active galactic nuclei (AGN) accreting at rates close to the Eddington limit can host radiatively driven mildly relativistic outflows. Some of these X-ray absorbing but powerful outflows may produce strong shocks resulting in a significant non-thermal emission. This outflow-driven radio emission may be detectable in the radio-quiet quasar PDS 456 since it has a bolometric luminosity reaching the Eddington limit and a relativistic wide-aperture X-ray outflow with a kinetic power high enough to quench the star formation in its host galaxy. To investigate this possibility, we performed very-long-baseline interferometric (VLBI) observations of the quasar with the European VLBI Network (EVN) at 5 GHz. The EVN image with the full resolution reveals two faint and diffuse radio components with a projected separation of about 20 pc and an average brightness temperature of around two million Kelvin. In relation to the optical sub-mas-accuracy position measured by the Gaia mission, the two components are very likely on opposite sides of an undetected radio core. The VLBI structure at the deca-pc scale can thus be either a young jet or a bidirectional radio-emitting outflow, launched in the vicinity of a strongly accreting central engine. Two diffuse components at the hecto-pc scale, likely the relic radio emission from the past AGN activity, are tentatively detected on each side in the low-resolution EVN image.Comment: 6 pages, 2 figures, 1 table. Accepted for publication in MNRA