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The income tax consequences of the in-house development of softwareHodge, Dominic Shaughn January 2014 (has links)
The objective of this thesis was to explore the nature of expenditure incurred on the internal development of software and its treatment in terms of the accounting and taxation frameworks to which it is subject. In fulfilling the primary objective the thesis had a number of subsidiary considerations. These included, firstly, a brief analysis of the approach of the software industry in South Africa to the taxation treatment of this type of software. The second consideration was a discussion and analysis of the taxation framework which differentiates between capital and revenue and the extent to which the receipts produced by internally developed software may be informative of the nature of the expenditure. The third was an analysis of the deductibility of expenditure incurred in the production of software with the fourth analysing the tests employed in the determination of whether expenditure is capital or revenue in nature. The fifth objective was to briefly analyse the accounting standards which find application in the determination of whether or not the software created can be considered a capital asset. The final subsidiary objective of the thesis was an analysis of the taxation framework applicable to software in respect of research and development incentives, as well as the position in the United States of America. Throughout the thesis the most apparent commonality is that there exists a significant level of uncertainty as to the taxation treatment of software both in South Africa and in America. The research concludes by stating that such uncertainty is prejudicial to the interests of research and development in relation to software.
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On the empirical measurement of inequality / De la mesure empirique des inégalitésFlores, Ignacio 25 January 2019 (has links)
Le 1er chapitre présente une série de 50 ans sur les hauts revenus chiliens basée sur des données fiscales et comptes nationaux. L’étude contredit les enquêtes, selon lesquelles les inégalités diminuent les 25 dernières années. Au contraire, elles changent de direction à partir de 2000. Le Chili est parmi les pays les plus inégalitaires de l’OCDE et l’Amérique latine. Le 2ème chapitre mesure la sous-estimation des revenus factoriels dans les données distributives. Les ménages ne reçoivent que 50% des revenus du capital brut, par opposition aux firmes. L’hétérogénéité des taux de réponse et autres problèmes font que les enquêtes ne capturent que 20% de ceux-ci, contre 70% du revenu du travail. Cela sous-estime l’inégalité,dont les estimations deviennent insensibles à la "capital share" et sa distribution. Je formalise à partir d’identités comptables pour ensuite calculer des effets marginaux et contributions aux variations d’inégalité. Le 3ème chapitre présente une méthode pour ajuster les enquêtes. Celles-ci capturent souvent mal le sommet de la distribution. La méthode présente plusieurs avantages par rapport aux options précédentes : elle est compatible avec les méthodes de calibration standard ; elle a des fondements probabilistes explicites et préserve la continuité des fonctions de densité ; elle offre une option pour surmonter les limites des supports d’enquête bornées; et elle préserve la structure de micro données en préservant la représentativité des variables sociodémographiques. Notre procédure est illustrée par des applications dans cinq pays, couvrant à la fois des contextes développés et moins développés. / The 1st chapter presents historical series of Chilean top income shares over a period of half a century, mostly using data from tax statistics and national accounts. The study contradicts evidence based on survey data, according to which inequality has fallen constantly over the past 25 years. Rather, it changes direction, increasing from around the year 2000. Chile ranks as one of the most unequal countries among both OECD and Latin American countries over the whole period of study. The 2nd chapter measures the underestimation of factor income in distributive data. I find that households receive only half of national gross capital income,as opposed to corporations. Due to heterogeneous non-response and misreporting, Surveys only capture 20% of it, vs. 70% of labor income. This understates inequality estimates, which become insensitive to the capital share and its distribution. I formalize this system based on accounting identities. I then compute marginal effects and contributions to changes in fractile shares. The 3rd chapter, presents a method to adjust surveys. These generally fail to capturethe top of the income distribution. It has several advantages over previous ones: it is consistent with standard survey calibration methods; it has explicit probabilistic foundations and preserves the continuity of density functions; it provides an option to overcome the limitations of bounded survey-supports; and it preserves the microdata structure of the survey.
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