Browsing by Subject "panel data"

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    The effects of the tobacco products control amendment act of 1999 on restaurant revenues in South Africa: a panel data approach
    (Wiley, 2006) Blecher, Evan H
    Prior to the implementation of this legislation the restaurant industry lobbied that a full-scale ban would severely hurt business. Their lobbying resulted in a restrictive restaurant smoking policy rather than a full-scale ban. Nevertheless the industry argued that this would still severely hurt business citing international evidence in support. The objective of this paper is to investigate the change in restaurant revenues after the implementation of a public smoking ban in South Africa. We use a fixed effects panel model to explore the response of restaurant revenues to the imposition of the ban. Provincial data is used over the period 1995 to 2003 and VAT receipts are used as a proxy of restaurant turnover. We conclude that restrictive restaurant smoking policies have not had a negative effect on restaurant revenue, indicating that claims of countrywide restaurant business declines under such a policy are unwarranted.
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    The Firm-Specific Determinants of Capital Structure in Public Sector and Private Sector Banks in India
    (2019) Garach, Jatin Bijay; Rajaratnam, Kanshukan; Modack, Goolam
    The banking industry in India has undergone many phases in its history; evolving from a regulated, decentralised system in the early 1800’s, to a regulated, centralised system during British rule, to a nationalised system following India’s independence, and finally a combination of a nationalised and private system adopting global standards as it currently stands. This study has two main aims. Firstly, it will assess the relationship between the firm-specific determinants of capital structure, based on the prevailing literature, and the capital structure of public and private sector banks in India. Secondly, it will determine whether there is a difference in the firm-specific factors that contribute to the determination of the capital structure of public sector banks and private sector banks. This study adopts quantitative methods, similar to previous studies on the relationship between capital structure and its firm-specific determinants. The dependent variable, being total leverage, is regressed against multiple independent variables, being profitability, growth, firm size and credit risk (hereinafter referred to as “risk” unless otherwise indicated) in a multivariate linear regression model. This study adds to the current literature by applying the same firm-specific independent variables to the case of private and public sector banks and then to evaluate and compare the similarities and differences between the regression outputs. The results show that for private sector banks, all independent variables are statistically significant in explaining total leverage, where all the independent variables conform to the current literature on capital structure – profitability (-), firm size (-), growth (+) and credit risk (-). Conversely, for public sector banks, all independent variables were considered to be statistically significant, except for credit risk – profitability (-), firm size (+) and growth (+). These results imply that credit risk is not an important determination in a nationalised banks’ capital structure; thus, providing evidence for the moral hazard theory of public sector banks.
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    Using cross country panel regression analysis to relook at the relationship between armed conflict and HIV prevalence in Africa
    (2010) Hove, Fidelis
    This paper explores the relationship between armed conflict and HIV prevalence in Africa. We review the literature suggesting that conflict can exacerbate the HIV epidemic (through sex with infected soldiers, war-related rape, poverty-related unsafe sex, transactional sex, etc) and the literature arguing the contrary (such as that militaries do not always have higher prevalence rates than the surrounding populations and that war can disrupt sexual networks). Building on past econometric contributions on the debate, our parsimonious cross-country panel data regression analysis of HIV prevalence casts doubt on the argument that conflict worsens the epidemic, particularly at a country level. We do, however, find a negative, albeit statistically weak association between armed conflict, militarization, and HIV prevalence. Fully acknowledging the limitations of our analysis, we stress the importance of looking at the association between HIV prevalence and conflict on a case by case basis, taking lessons from the experiences of other conflict afflicted countries.