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Market States and Pre-IPO Marketing Expenditures in Japanese IPOs MarketChu, Yu-Chen 14 July 2011 (has links)
Prior studies show the evidence of non-financial variables such as marketing affects investor¡¦s response to risky asset pricing, and indicate that the distribution of risky asset returns is asymmetric and non-nomality, implying using Ordinary Least Squares (OLS) method with the assumption of normal distributions may lead to unreliable estimates. This study tries to apply quantile regression to the analysis of the sample in order to avoid estimation bias. This study examines whether a firm¡¦s pre-IPO marketing expenditures affects its¡¦ initial public offering (IPO) underpricing in Japan and examine whether market states influence the existing relation between pre-IPO marketing expenditures and IPO underpricing. The empirical results shows: (1) pre-IPO marketing expenditures significantly reduce IPO underpricing levels, (2) pre-IPO marketing expenditures can reduce IPO underpricing levels following bear markets as it cannot reduce IPO underpricing levels following bull markets. Therefore, as firms decide to use marketing strategies to make their firm remarkable, and in turns without concerning for market states to reduce the degree of IPO underpricing, their objective may not be reached.
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Three empirical essays on movie admissions in the french motion picture industry / Trois essais empiriques sur les entrées des films en salle dans l'industrie du cinéma en FranceBellego, Christophe 21 December 2016 (has links)
A la frontière entre les industries du divertissement et la production culturelle, grand fournisseur de contenu à l'économie numérique, l'industrie du cinéma soulève des questions intéressantes dans le champ de l'économie et du marketing. Cette thèse répond à trois questions empiriques importantes sur ce sujet à l'aide de différentes méthodes adaptées (économétrie des données de panel, différence-de-différences, économétrie structurelle) et propose un nouveau développement théorique du modèle nested logit. Le premier chapitre étudie l'effet des notes des consommateurs sur Internet, et analyse la complémentarité et la substituabilité de ces notes avec l'information disponible avant la sortie des films en salle. Le deuxième chapitre étudie l'effet redistributif de la loi anti-piratage Hadopi sur les entrées des films en salle, en écartant minutieusement les phénomènes alternatifs pouvant affecter les résultats. Le troisième chapitre considère la saisonnalité dans l'industrie française du cinéma et décompose séparément les entrées des films en salle en le niveau de l'offre (le nombre et la qualité des films), la demande saisonnière sous-jacente, les variations météorologiques, et les promotions nationales en estimant un modèle nested logit à trois étages tenant compte de la congestion des films dans les salles de cinéma. Le modèle est utilisé pour identifier les dates de sortie optimales en fonction des types de film. / At the frontier between entertainment industries and cultural production, vital content provider of digital economy, the motion picture industry raises several interesting questions in the field of economics and marketing. This dissertation tackles three important empirical questions in the motion picture industry using different methods (panel data models, difference-in-differences, and structural econometrics) and brings a new theoretical development about the nested logit model. The first chapter deals with online consumer reviews, also known as electronic word of mouth (eWOM), and focuses on the extent to which prerelease information alters the effect of eWOM on movie sales. The second chapter studies the collateral damages of the French anti-piracy law known as Hadopi on box office performances of movies, by carefully ruling out alternative explanations of the result. The third chapter investigates on seasonality in the French movie industry. The analysis separately identifies and decomposes movie sales into the number and quality of available movies, underlying seasonal demand, weather shocks, and national sales promotion by estimating a three-level nested logit model of weekly demand accounting for congestion on movie theaters' screens. The model is used to identify optimal release periods depending on the types of movie.
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