Lines in the Sand on the Australian Political Beach

Spatial models of voting behaviour are the dominant paradigm in political science. Consistent with this approach, it will be the case that, ceteris paribus, voters should vote for the party nearest to them on the political spectrum. A key question is how we measure nearness or distance. We investigate this issue by estimating discrete choice models for voting outcomes using the 2001 Australian Election Study survey data. The evidence supports the proposition that it is perceived and not actual distance that performs best. Our findings also suggest that where a voter locates on the political spectrum is almost as good a predictor of their voting outcome as how close they are to the partiesSpatial Competition, Distance Measures, Discrete Choice

A tale of two logits, compositional data analysis and zero observations

The application of compositional data analysis through log ratio trans-formations corresponds to a multinomial logit model for the shares themselves.This model is characterized by the property of Independence of Irrelevant Alter-natives (IIA). IIA states that the odds ratio in this case the ratio of shares is invariant to the addition or deletion of outcomes to the problem. It is exactlythis invariance of the ratio that underlies the commonly used zero replacementprocedure in compositional data analysis. In this paper we investigate using thenested logit model that does not embody IIA and an associated zero replacementprocedure and compare its performance with that of the more usual approach ofusing the multinomial logit model. Our comparisons exploit a data set that com-bines voting data by electoral division with corresponding census data for eachdivision for the 2001 Federal election in AustraliaGeologische Vereinigung; Institut d’Estadística de Catalunya; International Association for Mathematical Geology; Patronat de l’Escola Politècnica Superior de la Universitat de Girona; Fundació privada: Girona, Universitat i Futur; Càtedra Lluís Santaló d’Aplicacions de la Matemàtica; Consell Social de la Universitat de Girona; Ministerio de Ciencia i Tecnología

The DOGEV Model

At present, there appears to be no qualitative dependent model that can simultaneously account for data sets in which the variable of interest is potentially ordered but also has strong heterogeneity of the observed outcomes. This heterogeneity of particular outcomes, inherently attracts individuals to them, in addition to that determined by the individual's observed characteristics. An example of such unobserved heterogeneity would be brand-loyalty (or "captivity") in a model of consumer choice. Such heterogeneity of the outcomes, may well result in a pronounced multi-modal distribution of the variable of interest. This paper introduces the Dogit Ordered Generalized Extreme Value (DOGEV) model, which does account for both ordering and captivity (and/or multiple modes) in the data. In the spirit of Manski (1977), the DOGEV model combines a model for choice set generation with the Ordered Generalized Extreme Value model. We illustrate the model using three different empirical examples: a model of employment contract types; an inflationary expectations data set and; a survey of students' evaluations of teaching. These three examples are chosen as they represent different values that the additional ancillary parameters are likely to take in practice

Compositional Data Analysis and Zeros in Micro Data

The application of compositional data analysis methods in economics has some attraction. In particular, this methodology ensures that the stochastic component of budget share models will satisfy the restriction of shares to the unit simplex. The methodology relies upon the use of log-ratios in the statistical analysis. Such an approach is not possible when the data to be analyzed includes observations where the observed budget share is zero. We therefore extend the methods of compositional data analysis to the situation where the data to be analyzed includes observations where the observed budget share is zero. The modified compositional data methods are discussed both in statistical terms and through potential economic interpretations of the method. Further, the modified methodology is applied to the 1988 Australian Household Expenditure Survey yielding estimates for a system of Engel curves.Engel Curves, Modified Almost Ideal Demand System, Composi- tional Data Analysis, Australian H E S data

The significance of financial self-efficacy in explaining women’s personal finance behaviour

AbstractMuch policy attention has been placed on enhancing individuals’ financial knowledge and literacy, chiefly through financial education programs. However, managing one’s personal finances takes more than financial knowledge and literacy: an individual also needs a sense of self-assuredness, or ‘self-belief’, in their own capabilities. This personal attribute is known within the psychology literature as ‘self-efficacy’. This paper examines the significance of an individual’s financial self-efficacy in explaining their personal finance behaviour, through the application of a psychometric instrument. Using a 2013 survey of Australian women, financial self-efficacy emerges as one of the strongest predictors of the type and number of financial products that a woman holds. Specifically, our analysis reveals that women with higher financial self-efficacy – that is, with greater self-assuredness in their financial management capacities – are more likely to hold investment and savings products, and less likely to hold debt-related products. Even alongside other important factors – such as education, financial risk preferences, age and household income – the explanatory power of financial self-efficacy is found to be significant at the 1% critical level. Moreover, the significance of financial self-efficacy is independently identified from that of financial literacy factors, which bears important implications for the development of policies aiming to improve financial outcomes

Are Pro-Reformers Better Performers?

There appears to be widespread consensus in industry and government that a switch from centralized bargaining to an enterprise based system benefits productivity. However, research suggests that the link between bargaining structures and worker productivity is dubious and that empirical research has been unable to discover a relationship between them. In this paper we use data from Australian companies at the enterprise level and examine the links between performance and a range of human resources, industrial relations and management variables to determine whether bargaining structures do impact on performance. In particular, we investigate whether organisations that have incorporated aspects of the industrial relations reform agenda have outperformed organisations that have not. The results from the application of a treatment effects regression model show evidence that organisations adopting the industrial relations reform agenda report significantly higher levels of self-assessed labour productivity relative to their competitors, even after controlling for a number of different factors.

GARCH modelling of individual stock data: The impact of censoring, firm size and trading volume

This paper explores the problems of testing and estimating GARCH models with particular emphasis on the impact of data censoring, firm size and trading volume. We conduct our investigation by analysing 1 year of daily returns data on 1014 Australian companies. Generally, our results indicate that GARCH model testing and estimation are impacted by the degree of censoring, firm size and trading volume. Specifically, our analysis produces three major findings. First, we find that low trading volume, small firm size and high censoring tend to be associated with a reduction in the presence of GARCH effects detected in the data by the LM test. Second, according to the estimation of a 'response surface' regression, the degree of censoring is found to be the dominant factor and stocks having a level of censoring less than 42.2% are predicted to have significant GARCH errors. Third, we find that low trading volume, small firm size and high censoring lead to a higher persistence of GARCH effects in the estimated models

The DOGEV Model

At present, there appears to be no qualitative dependent model that can simultaneously account for data sets in which the variable of interest is potentially ordered but also has strong heterogeneity of the observed outcomes. This heterogeneity of particular outcomes, inherently attracts individuals to them, in addition to that determined by the individual's observed characteristics. An example of such unobserved heterogeneity would be brand-loyalty (or "captivity") in a model of consumer choice. Such heterogeneity of the outcomes, may well result in a pronounced multi-modal distribution of the variable of interest. This paper introduces the Dogit Ordered Generalized Extreme Value (DOGEV) model, which does account for both ordering and captivity (and/or multiple modes) in the data. In the spirit of Manski (1977), the DOGEV model combines a model for choice set generation with the Ordered Generalized Extreme Value model. We illustrate the model using three different empirical examples: a model of employment contract types; an inflationary expectations data set and; a survey of students' evaluations of teaching. These three examples are chosen as they represent different values that the additional ancillary parameters are likely to take in practice

Untangling supply and demand in occupational choice

In this paper we present an econometric framework for modeling occupational choice that allows us to separately, and simultaneously, model supply-side and demand-side influences whilst allowing for potential ordering with regard to skill levels across occupations.

Compositional data analysis of vote shares in the 2001 Australian Federal election

First application of compositional data analysis techniques to Australian election dataGeologische Vereinigung; Institut d’Estadística de Catalunya; International Association for Mathematical Geology; Patronat de l’Escola Politècnica Superior de la Universitat de Girona; Fundació privada: Girona, Universitat i Futur; Càtedra Lluís Santaló d’Aplicacions de la Matemàtica; Consell Social de la Universitat de Girona; Ministerio de Ciencia i Tecnología