Will a rise in consumption tax share increase the effectiveness of government spending?

The Australian tax reform in July 2000 gave heavier weights to consumption tax in the tax mix at the expense of the income tax. This paper shows that the trade off among the tax-mix policy parameters depends on the structure of the economy. Given that the reform is tax-revenue neutral and no change in monetary stance, a rise in the share of consumption tax in the tax mix may increase the effectiveness of government spending in stabilising the economy if certain contain is fulfilled. A numerical example is included for illustration purpose

IS-LM model with a general consumption tax

OECD tax revenue statistics show that on average the share of consumption tax is almost equal to that of income tax. However, consumption tax hardly attracts any attention from intermediate macroeconomic textbooks, not to mention its inclusion in IS-LM model. This paper compares the IS curves under an income tax regime and a general consumption tax regime. It also examines the trade off between the income tax rate and the consumption tax rate in a dual tax regime

Skewness is the name of the game

Theoretical models of risk taking attempt to explain why risk-averse individuals participate in unfair gambles. This paper evaluates the two explanations as to why rational individuals would accept gambles with negative expected returns. It is found that it is skewness, not the mean or the variance of the prize distribution that attracts risk-averse gamblers. However, evidence shows that there seems to be an optimal trade-off between operators’ sales revenues and skewness of the pay-off; a point that designer of gambling games needs to heed to

Nonperturbative Determination of Heavy Meson Bound States

In this paper we obtain a heavy meson bound state equation from the heavy quark equation of motion in heavy quark effective theory (HQET) and the heavy meson effective field theory we developed very recently. The bound state equation is a covariant extention of the light-front bound state equation for heavy mesons derived from light-front QCD and HQET. We determine the covariant heavy meson wave function variationally by minimizing the binding energy $\bar{\Lambda}$. Subsequently the other basic HQET parameters $\lambda_1$ and $\lambda_2$, and the heavy quark masses $m_b$ and $m_c$ can also be consistently determined.Comment: 15 pages, 1 figur

Science communication in the media and human mobility during the COVID-19 pandemic: a time series and content analysis

Objectives The relationship between human mobility and nature of science (NOS) salience in the UK news media was examined. Study design This is a mixed-method study. Methods A time series NOS salience data set was established from the content analysis of 1520 news articles related to non-pharmaceutical interventions of COVID-19. Data were taken from articles published between November 2021 and February 2022, which correlates with period of the change from pandemic to endemic status. Vector autoregressive model fitting with human mobility took place. Results The findings suggest that it was not the number of COVID-19 news articles nor the actual number of cases/deaths, but the specific NOS content that was associated with mobility change during the pandemic. Data indicate a Granger causal negative direction (P 0.1). Conclusions The findings of the study suggest that the ways in which the news media discuss epidemics can influence changes in human mobility. It is therefore essential that public health communicators emphasise the basis of scientific evidence to eliminate potential media bias in health and science communication for the promotion of public health policy. The present study approach, which combines time series and content analysis and uses an interdisciplinary lens from science communication, could also be adopted to other interdisciplinary health-related topics

Probabilistic rank-one tensor analysis with concurrent regularizations

Subspace learning for tensors attracts increasing interest in recent years, leading to the development of multilinear extensions of principal component analysis (PCA) and probabilistic PCA (PPCA). Existing multilinear PPCAs are based on the Tucker or CANDECOMP/PARAFAC (CP) models. Although both kinds of multilinear PPCAs have shown their effectiveness in dealing with tensors, they also have their own limitations. Tucker-based multilinear PPCAs have a restrictive subspace representation and suffer from rotational ambiguity, while CP-based ones are more prone to overfitting. To address these problems, we propose probabilistic rank-one tensor analysis (PROTA), a CP-based multilinear PPCA. PROTA has a more flexible subspace representation than Tucker-based PPCAs, and avoids rotational ambiguity. To alleviate overfitting for CP-based PPCAs, we propose two simple and effective regularization strategies, named as concurrent regularizations (CRs). By adjusting the noise variance or the moments of latent features, our strategies concurrently and coherently penalize the entire subspace. This relaxes unnecessary scale restrictions and gains more flexibility in regularizing CP-based PPCAs. To take full advantage of the probabilistic framework, we further propose a Bayesian treatment of PROTA, which achieves both automatic feature determination and robustness against overfitting. Experiments on synthetic and real-world datasets demonstrate the superiority of PROTA in subspace estimation and classification, as well as the effectiveness of CRs in alleviating overfitting