Economics - Research Publications
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ItemHow to proxy the unmodellable: Analysing granular insurance claims in the presence of unobservable or complex drivers(Institute of Actuaries, Australia, 2018)The estimation of claim and premium liabilities is a key component of an actuary's role and plays a vital part of any insurance company’s operations. In practice, such calculations are complicated by the stochastic nature of the claims process as well as the impracticality of capturing all relevant and material drivers of the observed claims data. In the past, computational limitations have promoted the prevalence of simplified (but possibly sub-optimal) aggregate methodologies. However, in light of modern advances in processing power, it is viable to increase the granularity at which we analyse insurance data sets so that potentially useful information is not discarded. By utilising more granular and detailed data (that is usually readily available to insurers), model predictions may become more accurate and precise. Unfortunately, detailed analysis of large insurance data sets in this manner poses some unique challenges. Firstly, there is no standard framework to which practitioners can refer and it can be challenging to tractably integrate all modelled components into one comprehensive model. Secondly, analysis at greater granularity or level of detail requires more intense levels of scrutiny as complex trends and drivers that were previously masked by aggregation and discretisation assumptions may emerge. This is particularly an issue with claim drivers that are either unobservable to the modeller or very difficult/expensive to model. Finally, computation times are a material concern when processing such large volumes of data as model outputs need to be obtained in reasonable time-frames. Our proposed methodology overcomes the above problems by using a Markov-modulated non-homogeneous Poisson process framework. This extends the standard Poisson model by allowing for over-dispersion to be captured in an interpretable, structural manner. The approach implements a flexible exposure measure to explicitly allow for known/modelled claim drivers while the hidden component of the Hidden Markov model captures the impact of unobservable or practicably non-modellable information. Computational developments are made to drastically reduce calibration times. Theoretical findings are illustrated and validated in an empirical case study using Australian general insurance data in order to highlight the benefits of the proposed approach.
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ItemOn the Impact, Detection and Treatment of Outliers in Robust Loss Reserving(Actuaries Institute, 2016)The sensitivity of loss reserving techniques to outliers in the data or deviations from model assumptions is a well known challenge. For instance, it has been shown that the popular chain-ladder reserving approach is at significant risk to such aberrant observations in that reserve estimates can be significantly shifted in the presence of even one outlier. In this paper we firstly investigate the sensitivity of reserves and mean squared errors of prediction under Mack's Model. This is done through the derivation of impact functions which are calculated by taking the first derivative of the relevant statistic of interest with respect to an observation. We also provide and discuss the impact functions for quantiles when total reserves are assumed to be lognormally distributed. Additionally, comparisons are made between the impact functions for individual accident year reserves under Mack's Model and the Bornhuetter-Ferguson methodology. It is shown that the impact of incremental claims on these statistics of interest varies widely throughout a loss triangle and is heavily dependent on other cells in the triangle. We then put forward two alternative robust bivariate chain-ladder techniques (Verdonck and VanWouwe, 2011) based on Adjusted-Outlyingness (Hubert and Van der Veeken, 2008) and bagdistance (Hubert et al., 2016). These techniques provide a measure of outlyingness that is unique to each individual observation rather than largely relying on graphical representations as is done under the existing bagplot methodology. Furthermore the Adjusted Outlyingness approach explicitly incorporates a robust measure of skewness into the analysis whereas the bagplot captures the shape of the data only through a measure of rank. Results are illustrated on two sets of real bivariate data from general insurers.
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ItemCharitable Giving in the Laboratory: Advantages of the Piecewise Linear Public Goods Game(The MIT Press, 2018)The vast majority of US households make significant charitable contributions. When examining the effectiveness of the mechanisms fundraisers use to solicit such funds, it is often essential that researchers elicit or control the donor’s return from giving. While much can be gained from examining data on actual donations, insights on giving increasingly result from laboratory studies. An advantage of the laboratory is that it permits control of the donor’s return from giving and thus facilitates the identification of donor motives as well as their responses to different fundraising or solicitation strategies (see Vesterlund 2016 for a review).
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ItemConstructing occupation‐specific life tables for China(Society of Actuaries, 2019)This report documents the “Constructing Occupation-Specific Life Tables for China” project commissioned by the Society of Actuaries under the “China Research Topics” proposal. The purpose of the project is to construct the most up-to-date occupational life tables for male and female urban employees in China based on administrative data from the Beijing Public Pension System for the period 2005–2009.
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ItemGambling with Stimulus Payments: Feeding Gaming Machines with Federal Dollars(Department of Economics, The University of Melbourne, 2013)In late 2008 and early 2009 the Australian Federal Government introduced a series of economic stimulus packages designed to maintain consumer spending in the early days of the Great Recession. When these packages were initiated the media suggested that the wide-spread availability of electronic gaming machines (EGMs, eg. slot machines, poker machines, video lottery terminals) in Australia would result in stimulating the EGMs. Using state level monthly data we estimate the degree to which the stimulus payments influenced EGM expenditure and the implications for state and territory gaming tax revenues.
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ItemSecondary School Fee Inflation: An Analysis of Private High Schools in Victoria, Australia(Carfax Publishing Ltd., 2017)The recent growth in privately administered secondary education in many developed countries has been a widely observed phenomenon. The Australian private secondary school sector has grown faster than those in any other OECD nation, even though the average tuition fees charged by these schools have increased at double the nation’s overall rate of inflation. In this paper, we employ a panel data set to estimate a set of hedonic price indices for private secondary schools that cater to different segments of the population in order to determine if and how changes in their characteristics influence the changes in fees.
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ItemInverse test confidence intervals for turning-points: A demonstration with higher order polynomials(Emerald Publishing, 2012)In this chapter we demonstrate the construction of inverse test confidence intervals for the turning points in estimated nonlinear relationships by the use of the marginal or first derivative function. First, we outline the inverse test confidence interval approach. Then we examine the relationship between the traditional confidence intervals based on the Wald test for the turning-points for a cubic, a quartic and fractional polynomials estimated via regression analysis and the inverse test intervals. We show that the confidence interval plots of the marginal function can be used to estimate confidence intervals for the turning points that are equivalent to the inverse test. We also provide a method for the interpretation of the confidence intervals for the second derivative function to draw inferences for the characteristics of the turning-point. This method is applied to the examination of the turning points found when estimating a quartic and a fractional polynomial from data used for the estimation of an Environmental Kuznets Curve. The Stata do files used to generate these examples are listed in the appendix along with the data.
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ItemThe influence of student experiences on post-graduation surveys(ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2016-02-17)This study attempts to establish the extent to which in-class teaching quality instruments can be used to predict post-graduation survey results. It examines the responses for the Good Teaching Scale of the Course Experience Questionnaire administered to 10,433 students who completed their studies at a major Australian tertiary institution from 2003 to 2005 using a unique data-set that matched student records and measures of class characteristics to the individual survey responses. The findings indicate that the overall degree experiences of particular students can be predicted by measures of class differences as measured by teaching quality instruments and the grade distributions of the classes they completed. These factors are in addition to the effects of students’ own performance as measured by their grades, their field of study and their post-graduation experience. It was found that in-class administered teaching quality instruments have an asymmetric influence on post-graduation survey results. Higher than expected scores appear to have little impact, and lower than expected results were found to have a significant negative impact on post-graduation recollections. The grade distribution in classes taken was also found to be an important factor in explaining variation in degree satisfaction.
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ItemInverting the indirect-The ellipse and the boomerang: Visualizing the confidence intervals of the structural coefficient from two-stage least squares(ELSEVIER SCIENCE SA, 2017-08-01)In the just-identified model,the exact distribution of the two-stage least squares (2SLS) estimator of the coefficient of the endogenous regressor is a ratio of two normally distributed random variables. used Fieller's 1932 result to derive the density function of the estimator. In this paper, we present a novel graphical exposition of Fieller's 1954 technique to approximate the confidence interval for the 2SLS estimator. We use this approach to examine how the degree of endogeneity and instrument relevance influences the correspondence between the Fieller and traditional asymptotic confidence intervals for the estimator.
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ItemConfidence Intervals for Ratios: Econometric Examples with Stata(Elsevier BV, 2018)Ratios of parameter estimates are often used in econometric applications. However, the test of these ratios when estimated can cause difficulties since the ratio of asymptotically normally distributed random variables have a Cauchy distribution for which there are no finite moments. This paper presents a method for the estimation of confidence intervals based on the Fieller approach that has been shown to be preferable to the usual Delta method. Using example applications in both Stata and R, we demonstrate that a few extra steps in the examination of the estimate of the ratio may provide a confidence interval with superior coverage.