Non-standard work schedules and health outcomes in Australia : some evidence from the HILDA Panel

What does the around-the-clock economic activity mean for workers' health? Despite the fact that non-standard work accounts for an increasing share of the job opportunities, relatively little is known about the potential consequences for health and the existing evidence is ambiguous. In this paper I examine the associations between non-standard job schedules and workers' physical and mental health outcomes using longitudinal data from the Household, Income and Labour Dynamics in Australia (HILDA). Specifically, the four health indicators considered are self-rated health and the SF-36 health indices for general health, mental health and physical functioning. Overall results generally suggest a negative relationship between non-standard work schedules and better health for both males and females. Regarding the statistical significance and magnitudes of the associations, however, we observe apparent differences between males and females. Among females, most of the coefficients in all models are statistically insignificant, which implies very small magnitudes in terms of the correlation between non-standard working hours and health. These results apply uniformly to all health measures investigated. Among males, on the other hand, the negative relationship is more noticeable for self-rated health, general health and physical functioning than for mental health. The pooled OLS and random effects coefficients are usually larger in magnitude and more significant than the fixed effects parameters. Nonetheless, even the more significant coefficients do not imply large effects in absolute terms.

The J-curve : evidence from Fiji

This article provides new evidence on both long run and short-run determinants of trade balance for Fiji and investigates evidence of J-curve adjustment behaviour in the aftermath of a devaluation. We adopt a partial reduced form model that models the real trade balance directly as a function of the real exchange rate and real domestic and foreign incomes. Cointegration analysis is based on a recently developed autoregressive distributed lag approach—shown to provide robust results in finite samples. The long run elasticities are also estimated using a dynamic ordinary least squares approach and the Fully Modified Ordinary Least Squares (FM-OLS) approach. Amongst our key results we find that there is a long-run relationship between trade balance and its determinants. There is evidence of the J-curve pattern; growth in domestic income affects Fiji's trade balance adversely while foreign income improves it.

The allocation of development aid assistance : do new donors have old motives?

The aid allocation literature explores the motives behind development aid  assistance. This literature is enormous, yet surprisingly, the extant empirical  studies have in the main only focused on the motives of established donors. Consequently, relatively little is known of the motives of new donors. This paper explores the aid allocation motives of three relatively new DAC donors: Greece, Luxembourg, and Portugal. Both OLS and Tobit two-way effects estimators are used to model their aid allocation process. The results indicate that humanitarian concerns are not an important factor for these three donors. Greece contributes aid predominately to its neighbors and to transitional East European nations. Portugal is motivated by commercial interests and former colony status. The bandwagon effect exists in reverse for Portugal. Commercial interests operate also for Luxembourg. Additionally, Luxembourg appears to donate to smaller more developed countries and is less inclined to donate to East European nations.

A disposable multiplex polymerase chain reaction (PCR) chip and device

Malaysian patent application number PCT/MY2008/000190 Australian application number : 2009203047

The underpricing of US REIT IPOs : 1996–2010

This study examines the underpricing cost of 123 US REIT IPOs over the period 1996 until June 2010, including the period of the global financial crisis. The study uses OLS multivariate regression to determine some potential factors behind underpricing. The underpricing cost of raising REIT external equity averaged 3.18% using an equal weighting for each of the 123 REIT IPOs. The study finds offer size is positively related to underpricing. A value weighted approach finds that underpricing averages 4.67% and suggests larger offer size is an important determinant for leaving more money on the table. Higher reputation underwriters, the industry differentiated auditor and post offer ownership structure negatively influence underpricing. The study documents declining underpricing over time with the period of 2007–2010 experiencing negative underpricing (overpricing) during the global financial crisis (GFC). Offers during the hot periods of 1997 and 2004 and the office/industrial property type were more highly underpriced. The 10-year treasury interest rate is identified as another significant positive determinant of underpricing.

Assessment of spatiotemporal varying relationships between rainfall, land cover and surface water area using geographically weighted regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R 2 and lower corrected Akaike information criterion (AICC). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R 2 and lower AICC. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.

Optimal hedge ration with moving least squares - an empirical study using Indian single stock futures data

The use of commodity, currency and stock index futures to hedge risky exposures in the underlying assets is well documented in financial literature. However single stock futures are a relatively new addition to the family of futures and as such, academic research on its use as a hedging tool is relatively thin. In this study we have explored the efficacy of two different methodological approaches that may be applied when hedging a long position in the underlying stock with a single stock future. We use daily trading data covering years 2002 to 2007 from the Indian market, where single stock futures have been really thriving in terms of volume of trade, to extract the optimal hedge ratios using both static OLS as well as 30-day, 60-day and 90-day moving least squares. The method of moving least squares has been in use by market practitioners for some time primarily as a trend analysis and charting tool. Our results indicate that the moving least squares approach outperforms the static OLS in terms of the hedging efficiency, which has been measured by the root mean square hedging error.

Sectoral analysis on capital structure determinants among the Malaysian listed firms

This study highlights the sensitivity of capital structure determinants in each sector within the ensembles of Malaysia Listed Companies. Based on pooled OLS, fixed effect and Generalized Method of Moments analysis, the findings revealed that capital structure determinants vary across sectors due to its nature or characteristics.

The direct costs of raising external equity capital for US REIT IPOs

Purpose – The purpose of this paper is to investigate the total direct costs of raising external equity capital for US real estate investment trust (REIT) initial public offerings (IPOs).

Design/methodology/approach – The study provides recent evidence on total direct costs for a comprehensive dataset of 125 US REIT IPOs from 1996 until June 2010. A multivariate OLS regression is performed to determine significant factors influencing the level of total direct costs and also underwriting fees and non-underwriting direct expenses.

Findings – The study finds economies of scale in total direct costs, underwriting fees and non-underwriting expenses. The equally (value) weighted average total direct costs are 8.33 percent (7.52 percent), consisting of 6.49 percent (6.30 percent) underwriting fees and 1.87 percent (1.22 percent) non-underwriting direct expenses. The study finds a declining trend of total direct costs for post 2000 IPOs which is attributed to the declining trend in both underwriting fees and non-underwriting direct expenses. Offer size is a critical determinant for both total direct costs and their individual components and inversely affects these costs. The total direct costs are found significantly higher for equity REITs than for mortgage REITs and are also significantly higher for offers listed in New York Stock Exchange (NYSE). Underwriting fees appear to be negatively influenced by the offer price, the number of representative underwriters involved in the issue, industry return volatility and the number of potential specific risk factors but positively influenced by prior quarter industry dividend yield and ownership limit identified in the prospectus. After controlling for time trend, the paper finds REIT IPOs incur higher non-underwriting direct expenses in response to higher industry return volatility prior to the offer.

Originality/value – This paper adds to the international REIT IPO literature by exploring a number of new influencing factors behind total direct costs, underwriting fees and non-underwriting direct expenses. The study includes data during the recent GFC period.

Modeling of a stereo vision system using a genetic algorithm based fuzzy linear regression

In this paper a fuzzy linear regression (FLR) model integrated with a genetic algorithm (GA) is proposed. The proposed GA-FLR model is applied to modeling of a stereo vision system. A set of empirical data from stereo vision object measurement is collected based on the full factorial design technique. Three regression models, namely ordinary least-squares regression (OLS), FLR, and GA-FLR, are developed, and with their performances compared. The results show that the proposed GA-FLR model performs better than OLS and FLR in modeling of a stereo vision system.

Sectoral analysis on capital structure determinants among the Malaysia listed firms

This study highlights the sensitivity of capital structure determinants in each sector within the ensembles of Malaysia Listed Companies. Based on pooled OLS, fixed effect and Generalized Method of Moments analysis, the findings revealed that capital structure determinants vary across sectors due to its nature or characteristics.

On the choice of test for a unit root when the errors are conditionally heteroskedastic

It is well known that in the context of the classical regression model with heteroskedastic errors, while ordinary least squares (OLS) is not efficient, the weighted least squares (WLS) and quasi-maximum likelihood (QML) estimators that utilize the information contained in the heteroskedasticity are. In the context of unit root testing with conditional heteroskedasticity, while intuition suggests that a similar result should apply, the relative performance of the tests associated with the OLS, WLS and QML estimators is not well understood. In particular, while QML has been shown to be able to generate more powerful tests than OLS, not much is known regarding the relative performance of the WLS-based test. By providing an in-depth comparison of the tests, the current paper fills this gap in the literature.

Managerial ownership, capital structure and firm value

This paper extends prior research to examine the managerial ownership influences on firm performance through the choices of capital structures by using a new sample of S& P 500 firm in 2005. The empirical results of OLS regressions replicate the nonlinear relationship between managerial ownership and firm value. However, we found that the turning points had moved up in our sample compared with previous papers, which implies that the managerial control for pursuing self-interst, and the alignment of interests between managers and other shareholders can only be achieved now by management holding more ownership in a firm than that found in previous studies. Managerial ownership also drives the capital structure as a nonlinear shape, but with a direction opposite to the shape of firm value. the results of simultaneous regressions suggest that managerial ownership affects capital structure, which in turn affects firm value. Capital structure is endogenously determined by bith firm value and managerial ownership; while managerial ownership is not endogenously determined by the other two variables.

The value of retail rents with regression models: a case study of Shanghai

Abstract
Purpose– The purpose of this paper is to estimate the determinants of the retail space rent in Shanghai.
Design/methodology/approach – Hedonic model and spatial regression models are used in the paper. The problem of spatial autocorrelation is tested by Moran’s I statistics, and the root mean square error (RMSE) test is performed to find out the best model.
Findings – The significant explaining variables are the age, the area of retail space, the distance to the Jing An CBD centre, the type of the retail and the district of the property. A new classification of district in retail research context is suggested in this paper, and it is proved to be better than the districts set up by government to explain the retail rent variation.
Originality/value – This paper presents the first empirical study about the retail rental market in Shanghai. The research helps retail property investors and retail tenants deepen their understanding of the retail market in Shanghai. Spatial econometrics techniques are first introduced into the empirical retail rent research to produce a more precise estimation.

Exchange rate regimes and fiscal discipline: the role of trade openness

This study revisits the relationship between exchange rate regime (ERR) choice and fiscal discipline focusing on the role of trade openness. The conventional theoretical view is that fixed regimes bring about more fiscal discipline, while the recent literature argues that flexible regimes are more disciplinary. Empirical studies have provided mixed evidence. Using a panel dataset for a large number of developing and developed countries, as well as pooled panel OLS and instrumental variables (IV) estimation techniques, we find support for both views. We document that a fixed ERR is disciplinary at low levels of trade openness, while a flexible regime produces a greater fiscal discipline above a certain level of trade openness. Moreover, this relationship applies to only developing countries. These findings remain robust across different measures of fiscal outcomes, a number of controls, across different sub-samples, and are supported by both annual and five-year averaged panel data.