283 resultados para OLS
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This thesis consists of a summary and five self-contained papers addressing dynamics of firms in the Swedish wholesale trade sector. Paper [1] focuses upon determinants of new firm formation in the Swedish wholesale trade sector, using two definitions of firms’ relevant markets, markets defined as administrative areas, and markets based on a cost minimizing behavior of retailers. The paper shows that new entering firms tend to avoid regions with already high concentration of other firms in the same branch of wholesaling, while right-of-the-center local government and quality of the infrastructure have positive impacts upon entry of new firms. The signs of the estimated coefficients remain the same regardless which definition of relevant market is used, while the size of the coefficients is generally higher once relevant markets delineated on the cost-minimizing assumption of retailers are used. Paper [2] analyses determinant of firm relocation, distinguishing between the role of the factors in in-migration municipalities and out-migration municipalities. The results of the analysis indicate that firm-specific factors, such as profits, age and size of the firm are negatively related to the firm’s decision to relocate. Furthermore, firms seems to be avoiding municipalities with already high concentration of firms operating in the same industrial branch of wholesaling and also to be more reluctant to leave municipalities governed by right-of-the- center parties. Lastly, firms seem to avoid moving to municipalities characterized with high population density. Paper [3] addresses determinants of firm growth, adopting OLS and a quantile regression technique. The results of this paper indicate that very little of the firm growth can be explained by the firm-, industry- and region-specific factors, controlled for in the estimated models. Instead, the firm growth seems to be driven by internal characteristics of firms, factors difficult to capture in conventional statistics. This result supports Penrose’s (1959) suggestion that internal resources such as firm culture, brand loyalty, entrepreneurial skills, and so on, are important determinants of firm growth rates. Paper [4] formulates a forecasting model for firm entry into local markets and tests this model using data from the Swedish wholesale industry. The empirical analysis is based on directly estimating the profit function of wholesale firms and identification of low- and high-return local markets. The results indicate that 19 of 30 estimated models have more net entry in high-return municipalities, but the estimated parameters is only statistically significant at conventional level in one of our estimated models, and then with unexpected negative sign. Paper [5] studies effects of firm relocation on firm profits of relocating firms, employing a difference-in-difference propensity score matching. Using propensity score matching, the pre-relocalization differences between relocating and non-relocating firms are balanced, while the difference-in-difference estimator controls for all time-invariant unobserved heterogeneity among firms. The results suggest that firms that relocate increase their profits significantly, in comparison to what the profits would be had the firms not relocated. This effect is estimated to vary between 3 to 11 percentage points, depending on the length of the analyzed period.
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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.
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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.
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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.
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Malaysian patent application number PCT/MY2008/000190 Australian application number : 2009203047
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.