This paper provides evidence of the causal impact of oil discoveries on development. Novel data on the drilling of 20,000 oil wells in Brazil allows us to exploit a quasi-experiment: Municipalities where oil was discovered constitute the treatment group, while municipalities with drilling but no discovery are the control group. The results show that oil discoveries significantly increase per capita GDP and urbanization. We find positive spillovers to non-oil sectors, specifically, an increase in services GDP which stems from higher output per worker. The results are consistent with greater local demand for non-tradable services driven by highly paid oil workers.
In their contributions, the autors elaborate on research and cultural practices. For that, they take a closer look at specific regularities by focusing on historical texts, art, literature, music in past and present.
Master Python techniques and libraries to reduce run times, efficiently handle huge datasets, and optimize execution for complex machine learning applications. Fast Python is a toolbox of techniques for high performance Python including: Writing efficient pure-Python code Optimizing the NumPy and pandas libraries Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing Fast Python is your guide to optimizing every part of your Python-based data analysis process, from the pure Python code you write to managing the resources of modern hardware and GPUs. You'll learn to rewrite inefficient data structures, improve underperforming code with multithreading, and simplify your datasets without sacrificing accuracy. Written for experienced practitioners, this book dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working. About the Technology Face it. Slow code will kill a big data project. Fast pure-Python code, optimized libraries, and fully utilized multiprocessor hardware are the price of entry for machine learning and large-scale data analysis. What you need are reliable solutions that respond faster to computing requirements while using less resources, and saving money. About the Book Fast Python is a toolbox of techniques for speeding up Python, with an emphasis on big data applications. Following the clear examples and precisely articulated details, you’ll learn how to use common libraries like NumPy and pandas in more performant ways and transform data for efficient storage and I/O. More importantly, Fast Python takes a holistic approach to performance, so you’ll see how to optimize the whole system, from code to architecture. What’s Inside Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing About the Reader For intermediate Python programmers familiar with the basics of concurrency. About the Author Tiago Antão is one of the co-authors of Biopython, a major bioinformatics package written in Python. Table of Contents: PART 1 - FOUNDATIONAL APPROACHES 1 An urgent need for efficiency in data processing 2 Extracting maximum performance from built-in features 3 Concurrency, parallelism, and asynchronous processing 4 High-performance NumPy PART 2 - HARDWARE 5 Re-implementing critical code with Cython 6 Memory hierarchy, storage, and networking PART 3 - APPLICATIONS AND LIBRARIES FOR MODERN DATA PROCESSING 7 High-performance pandas and Apache Arrow 8 Storing big data PART 4 - ADVANCED TOPICS 9 Data analysis using GPU computing 10 Analyzing big data with Dask
In Law of Value and Theories of Value, Tiago Camarinha Lopes presents the genesis of Karl Marx’s understanding of the law of value by showing that Classical and Neoclassical economics are equally hit by Marx’s Critique of Political Economy.
This book analyzes different facets of anuran amphibian distribution in South America. We integrate alternative biological metrics employing cutting-edge methods to understand the dynamic processes underlying species distribution patterns. By using the modern biogeographic toolbox, we explore how richness gradients, phylogenetic diversity, functional diversity, and range size/endemism distribution of amphibians vary along the continent. Moreover, we present a robust proposal for priority areas for conservation of anurans in South America that maximizes representativeness of distinct biodiversity facets.
This paper provides evidence of the causal impact of oil discoveries on development. Novel data on the drilling of 20,000 oil wells in Brazil allows us to exploit a quasi-experiment: Municipalities where oil was discovered constitute the treatment group, while municipalities with drilling but no discovery are the control group. The results show that oil discoveries significantly increase per capita GDP and urbanization. We find positive spillovers to non-oil sectors, specifically, an increase in services GDP which stems from higher output per worker. The results are consistent with greater local demand for non-tradable services driven by highly paid oil workers.
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