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Production and Efficiency Analysis with R
This textbook introduces essential topics and techniques in production and efficiency analysis and shows how to apply these methods using the statistical software R. Numerous small simulations lead to a deeper understanding of random processes assumed in the models and of the behavior of estimation techniques. Step-by-step programming provides an understanding of advanced approaches such as stochastic frontier analysis and stochastic data envelopment analysis. The text is intended for master students interested in empirical production and efficiency analysis. Readers are assumed to have a general background in production economics and econometrics, typically taught in introductory microeconomics and econometrics courses.
Investment and Liquidity Constraints
Based on a unique database of German firms, the Deutsche Bundesbank's Corporate Balance Sheet Statistics, Andreas Behr explores the link between financial factors and a firm's investment decision within the framework of the Q-theory of investment.
Theory of Sample Surveys with R
Das englischsprachige Buch vermittelt Kenntnisse der wichtigsten Methoden der modernen design-basierten Stichprobentheorie. Alle Methoden werden mit Hilfe von numerischen Beispielen illustriert und deren Umsetzung mit Hilfe der statistischen Software R dargestellt. Zahlreiche empirische Beispiele und Simulationen helfen, die Eigenschaften von Schätzfunktionen zu beurteilen. This textbook provides an up-to-date treatment of modern design based theory of survey sampling. All methods are illustrated with numerical examples and applied using the statistical software R. Numerous empirical examples and simulations provide insights into the properties of estimation functions.
The Confessions of Harry Lorrequer
I rambled through the streets for some hours, revolving such thoughts as pressed upon me involuntarily by all I saw. The same little grey homunculus that filled my "prince's mixture" years before, stood behind the counter at Lundy Foot's, weighing out rappee and high toast, just as I last saw him. The fat college porter, that I used to mistake in my school-boy days for the Provost, God forgive me!
The Confessions of Harry Lorrequer
It is now many--do not ask me to say how many--years since I received from the Horse Guards the welcome intelligence that I was gazetted to an ensigncy in his Majesty's th Foot, and that my name, which had figured so long in the "Duke's" list, with the words "a very hard case" appended, should at length appear in the monthly record of promotions and appointments. Since then my life has been passed in all the vicissitudes of war and peace. The camp and the bivouac--the reckless gaiety of the mess-table --the comfortless solitude of a French prison--the exciting turmoils of active service--the wearisome monotony of garrison duty, I have alike partaken of, and experienced.
The Confessions of Harry Lorrequer; Fiction
Reproduction of the original.
Prediction of highly lucrative companies using annual statements: A Data Mining based approach
The intention of this study is to predict one year in advance whether a regarded firm will grow extraordinarily in the next year. This is crucial for private investors and fund managers who need to decide whether they should invest in a certain firm. Companies like Apple and Amazon have shown that people who recognized the potential of such companies at the right time earned a lot of money. The applied prediction models can also be used by politicians to identify companies which are eligible for funding, because growing companies oftentimes hire many employees. Since annual reports are often publically available for free, it is reasonable to take advantage of them for such a prediction. The prediction models are based on classification trees and forests because they have some very substantial advantages over other methods like neural networks, which are frequently used in literature. For instance, they do not have distributional assumptions, accept both quantitative and qualitative inputs, and are not sensitive with respect to outliers. Furthermore, they are easy to understand by humans and can deal with missing values, which is crucial for practical applications.
