Futures basis,inventory and commodity price volatility: An empirical analysis

We employ a large dataset of physical inventory data on 21 different commodities for the period 1993–2011 to empirically analyze the behavior of commodity prices and their volatility as predicted by the theory of storage. We examine two main issues. First, we analyze the relationship between inventory and the shape of the forward curve. Low (high) inventory is associated with forward curves in backwardation (contango), as the theory of storage predicts. Second, we show that price volatility is a decreasing function of inventory for the majority of commodities in our sample. This effect is more pronounced in backwardated markets. Our findings are robust with respect to alternative inventory measures and over the recent commodity price boom.     

The Deterrent Effect of Whistleblowing on Tax Collections

Abstract

Many countries use tax-related whistleblowing programs, but the evidence on these programs suggests information provided by whistleblowers yields modest tax collections. However, when every citizen could become a whistleblower, deterrence from tax evasion can by itself increase tax collections. We find that tax collections significantly increased after the introduction of the whistleblowing mechanism in Israel in February 2013, although this mechanism directly yielded little or no tax collections. In support of the hypothesis that deterrence led to the increase in tax collections, we find that collections increased in industries with high tax-evasion risk, but not in industries with low tax-evasion risk. Furthermore, the increase in tax collections occurred in corporations, where the timing and magnitude of tax payments are more discretionary, but not from employees, for whom employers directly deduct taxes. Eventually, following reports that the whistleblowing mechanism is ineffective, deterrence diminished and tax collections decreased, suggesting the deterrence effect was temporary.     

Are Private Vices Public Finance Virtues? An Empirical Investigation

The article investigates the impact of widely accepted private vices (smoking and alcohol and gasoline consumption) on public finance. Introducing the concept of “vice-related deficit,” which aggregates the positive effects on public finance on the revenue side (cash inflows) and the negative effects on the expenditures side (cash outflows), the article looks upon cigarette, alcohol, and gasoline consumption as determinants of vice-related deficit for a number of 68 countries for year 2012. We found that smoking had a negative effect on vice-related budget balance, while alcohol and gasoline consumption had a positive effect. As control variables, we used life expectancy and size of the economy, both having been found with negative effects. The results prove robust to different sample adjustments. We also found that the negative effect of private vices on public finance is stronger for Christian countries than for non-Christian countries. Policy recommendations were made accordingly.     

Modelling Regime‐Specific Stock Price Volatility*

Single‐state generalized autoregressive conditional heteroscedasticity (GARCH) models identify only one mechanism governing the response of volatility to market shocks, and the conditional higher moments are constant, unless modelled explicitly. So they neither capture state‐dependent behaviour of volatility nor explain why the equity index skew persists into long‐dated options. Markov switching (MS) GARCH models specify several volatility states with endogenous conditional skewness and kurtosis; of these the simplest to estimate is normal mixture (NM) GARCH, which has constant state probabilities. We introduce a state‐dependent leverage effect to NM‐GARCH and thereby explain the observed characteristics of equity index returns and implied volatility skews, without resorting to time‐varying volatility risk premia. An empirical study on European equity indices identifies two‐state asymmetric NM‐GARCH as the best fit of the 15 models considered. During stable markets volatility behaviour is broadly similar across all indices, but the crash probability and the behaviour of returns and volatility during a crash depends on the index. The volatility mean‐reversion and leverage effects during crash markets are quite different from those in the stable regime.     

Statistical Issues in fMRI for Brain Imaging

Functional magnetic resonance imaging is a technique developed in the last decade and used in the fields of cognitive psychology and neuroscience, among others, to study the processes underlying the working of the human brain. In this paper we examine some of the statistical issues in functional magnetic resonance imaging for brain research. We start by giving a brief introduction to the physics of magnetic resonance imaging. Using a psychological experiment as a case study, we then describe questions of design and statistical analysis. The data obtained from functional magnetic resonance imaging studies are of a highly complex nature, displaying both spatial and temporal correlation, as well as high levels of noise from different sources. Given this, the scope for statistics is vast, and is not limited to simple analysis of the data, once collected.     

Fiscal policy and economic activity in South Asia

This paper analyzes whether fiscal policy in South Asia amplifies or smoothens business cycle fluctuations. It estimates several econometric models to explore the cyclicality of government spending and tax buoyancy. In South Asia, tax revenue increases less than one to one with changes in gross domestic product (GDP), but public spending increases more than proportionally. For each percentage point change in GDP growth, government expenditure changes by 1.3 percentage points. While changes in tax revenue have no significant impact on economic activity, the government spending multiplier is positive and significant: each additional US dollar (USD) of spending leads to an immediate increase in GDP of 0.2 USD and to an increase of 0.4 USD in the medium run. The impact of public spending on economic activity is entirely due to capital expenditure, which is also more procyclical. Procyclical public spending and a positive expenditure multiplier imply that fiscal policy in South Asia amplifies boom‐and‐bust cycles. These results are in line with those of other emerging markets and developing economies and robust to different model specifications and estimation strategies.     

Normal mixture GARCH(1,1): applications to exchange rate modelling

Some recent specifications for GARCH error processes explicitly assume a conditional variance that is generated by a mixture of normal components, albeit with some parameter restrictions. This paper analyses the general normal mixture GARCH(1,1) model which can capture time variation in both conditional skewness and kurtosis. A main focus of the paper is to provide evidence that, for modelling exchange rates, generalized two‐component normal mixture GARCH(1,1) models perform better than those with three or more components, and better than symmetric and skewed Student's t‐GARCH models. In addition to the extensive empirical results based on simulation and on historical data on three US dollar foreign exchange rates (British pound, euro and Japanese yen), we derive: expressions for the conditional and unconditional moments of all models; parameter conditions to ensure that the second and fourth conditional and unconditional moments are positive and finite; and analytic derivatives for the maximum likelihood estimation of the model parameters and standard errors of the estimates. Copyright © 2006 John Wiley & Sons, Ltd.     

Regulator's Determination of Return on Equity in the Absence of Public Firms: The Case of Automobile Insurance in Ontario

In a regulated market, such as automobile insurance (AI), regulators set the return on equity that insurers are allowed to achieve. Most insurers are engaged in a variety of insurance lines of business, and thus the full information beta methodology (FIB) is commonly employed to estimate the AI beta. The FIB uses two steps: first, the beta of each insurer is estimated, and then the beta of each line of business is estimated, as the beta of an insurer is a weighted average of the betas of the lines of business. When there are a sufficient number of public companies, company and market returns are used. Otherwise, researchers have resorted to using accounting data in the FIB. Theoretically, the two steps are not separable and the estimation should be done with one step. We introduce the one‐step methodology in our article. The one‐step and two‐step methodologies are compared empirically for the Ontario market of AI. Insurers in Ontario are predominantly private companies; thus, accounting data are used to estimate the AI beta. We show that a significant bias is introduced by the traditional, two‐step FIB methodology in estimating the betas for different lines of business, while insurers’ betas are very similar under both methods. This has a significant application to the estimation of betas of “pure players” in classic corporate finance. It implies that their betas and hence the resulting, required rates of return used in the net present value calculations should be estimated based on the one‐step method that we develop in this article.