Earnings management in response to the introduction of the Australian gold tax

Earnings from gold mining in Australia remained tax-exempt for almost seven decades until January 1, 1991. In the early 1980s, rapid economic prosperity induced by escalated gold prices brought the Australian gold-mining industry under intense political scrutiny. Using a variant of the modified Jones model, this paper provides evidence of significant downward earnings management by Australian gold-mining firms, which is consistent with their attempts to mitigate political costs during the period from June 1985 to May 1988. In contrast, test of earnings management over a similar period in a control sample of Canadian gold-mining firms produced insignificant results. Further, empirical results are robust to several sensitivity tests performed. During the period from June 1988 to December 1990, the Australian firms were found to have engaged in economic earnings management. This is consistent with the sample firms' incentive of maximizing economic earnings immediately prior to the introduction of income tax on gold mining. The findings of this study help to understand the impact of earnings management on the efficient resource allocation in an economy. They also contribute toward understanding the linkage between regulation of accounting for special purposes and general-purpose financial. reporting.

The price elasticity of the Euro to movements in foreign reserves through European Central Bank intevention

The Euro has been used as the largest weighting element in a basket of currencies for forex arrangements adopted by several Central European countries outside the European Union (EU). The paper uses a new time-series approach to examine the relationship between the Euro exchange rate and the level of foreign reserves. It employs Zero-no-zero (ZNZ) patterned vector error-correction (VECM) modelling to investigate Granger causal relations among foreign reserves, the European Monetary Union money supply and the Euro exchange rate. The findings confirm that foreign reserves may influence movements in the Euro's exchange rate. Further, ZNZ patterned VECM modelling with exogenous variables is used to estimate the amount of foreign reserves currently required in order to again achieve a targetted Euro exchange rate

Stock index reaction to large price changes:evidence frommajor Asian stock indexes

We examine the short-term price behavior of ten Asian stock market indexes following large price changes or “shocks”. Under the standard OLS regression, there is stronger support for return continuations particularly following positive and negative price shocks of less than 10% in absolute size. The results under the GJR-GARCH method provide stronger support for market efficiency, especially for large price shocks. For example, for the Hong Kong stock index, negative shocks of less than -5% but more than -10% generate a significant one day cumulative abnormal return (CAR) of-0.754% under the OLS method, but an insignificant CAR of 0.022% under the GJR-GARCH. We find no support for the uncertainty information hypothesis. Furthermore, the CARs following the period after the Asian financial crisis adjust more quickly to price shocks.

Techniques to improve forecasting models: applications to energy demand and price

This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.

Earnings differences between Chinese and Indian wage earners, 1987-2004

This paper is one of the first comprehensive attempts to compare earnings in urban China and India over the recent period. While both economies have grown considerably, we illustrate significant cross-country differences in wage growth since the late 1980s. For this purpose, we make use of comparable datasets, estimate Mincer equations and perform Oaxaca–Blinder decompositions at the mean and at different points of the wage distribution. The initial wage differential in favor of Indian workers, observed in the middle and upper part of the distribution, partly disappears over time. While the 1980s Indian premium is mainly due to higher returns to education and experience, a combination of price and endowment effects explains why Chinese wages have caught up, especially since the mid-1990s. The price effect is only partly explained by the observed convergence in returns to education; the endowment effect is driven by faster increase in education levels in China and significantly accentuates the reversal of the wage gap in favor of this country for the first half of the wage distribution.

Does move to market have an impact on earnings gap across gender? Some evidence from India

We use Indian National Sample Survey employment–unemployment data for the urban sector for the years 1987 and 1999. Our results indicate that the gender wage gap had narrowed considerably between these two years, for all earnings deciles and for all education cohorts. The narrowing of the earnings gap can be attributed largely to a sharp increase in the returns to the labour market experience of women.

The effect of timeliness and credit ratings on the information content of earnings announcements

Abstract: This paper investigates the impact of timeliness and credit ratings on the information content of the earnings announcements of Greek listed firms from 2001 to 2008. Using the classical event study methodology and regression analysis, we find that firms tend to release good news on time and are inclined to delay the release of bad news. We also provide evidence that the level of corporate risk differentiates the information content of earnings according to the credit rating category. Specifically, firms displaying high creditworthiness enjoy positive excess returns on earnings announcement dates. In contrast, firms with low creditworthiness undergo significant share price erosions on earnings announcement days. We also observe a substitution effect between timeliness and credit ratings in relation to the information content of earnings announcements. Specifically, we find that as the credit category of earnings-announcing firms improves, the informational role of timeliness is mitigated.

Fair price and its effect on willingness to purchase

The purpose of the present research is to demonstrate the influence of a fair price (independent of the subjective evaluation of the price magnitude) on buyers' willingness to purchase. The perceived fairness of a price is conceived to have three components: perceived equity, perceived need, and inferred compliance of the seller to the process rules of pricing. These components reflect the Theories of Distributive Justice (as adjusted for conditions of need) and Procedural Justice.^ The effect of the three components of a fair price on willingness to purchase is depicted in a theoretically causal chain model. Based on the Theories of Dissonance and Attribution, conditions of inequity and need activate concerns for Procedural Justice. Under conditions of inequity and need, buyers tend to infer that the seller has not complied with the generally accepted pricing practices, thus violating the social norms of Procedural justice. Inferred violations of Procedural Justice influence the buyer's attitude toward the seller. As predicted by the Theory of Reasoned Action, attitude is then positively related to willingness to purchase.^ The model was tested with a survey-based experiment conducted with 408 respondents. Two levels of both equity and need were manipulated with scenarios, a common research method in studies of Distributive and Procedural Justice. The data were analyzed with a structural equation model using LISREL. Although the effect of the "need" manipulation was insignificant, the results indicated a good fit of the model (Chi-square = 281, Degrees of Freedom = 104, Goodness of Fit Index =.924). The conclusion is that the fairness of a price does have a significant effect on willingness to purchase, independent of the subjective evaluation of the objective price. ^

Branch and price solution approach for order acceptance and capacity planning in make -to -order operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.

The Financialization of Food: An Inquiry into the 2008-2011 Food Price Spikes

This dissertation investigates the question: has financial speculation contributed to global food price volatility since the mid 2000s? I problematize the mainstream academic literature on the 2008-2011 food price spikes as being dominated by neoclassical economic perspectives and offer new conceptual and empirical insights into the relationship between financial speculation and food. Presented in three journal style manuscripts, manuscript one uses circuits of capital to conceptualize the link between financial speculators in the global north and populations in the global south. Manuscript two argues that what makes commodity index speculation (aka ‘index funds’ or index swaps) novel is that it provides institutional investors with what Clapp (2014) calls “financial distance” from the biopolitical implications of food speculation. Finally, manuscript three combines Gramsci’s concepts of hegemony and ‘the intellectual’ with the concept of performativity to investigate the ideological role that public intellectuals and the rhetorical actor the market play in the proliferation and governance of commodity index speculation. The first two manuscripts take an empirically mixed method approach by combining regression analysis with discourse analysis, while the third relies on interview data and discourse analysis. The findings show that financial speculation by index swap dealers and hedge funds did indeed significantly contribute to the price volatility of food commodities between June 2006 and December 2014. The results from the interview data affirm these findings. The discourse analysis of the interview data shows that public intellectuals and rhetorical characters such as ‘the market’ play powerful roles in shaping how food speculation is promoted, regulated and normalized. The significance of the findings is three-fold. First, the empirical findings show that a link does exist between financial speculation and food price volatility. Second, the findings indicate that the post-2008 CFTC and the Dodd-Frank reforms are unlikely to reduce financial speculation or the price volatility that it causes. Third, the findings suggest that institutional investors (such as pension funds) should think critically about how they use commodity index speculation as a way of generating financial earnings.