Most academic and policy commentary represents adverse selection as a severe problem in insurance, which should always be deprecated, avoided or minimised. This book gives a contrary view. It details the exaggeration of adverse selection in insurers' rhetoric and insurance economics, and presents evidence that in many insurance markets, adverse selection is weaker than most commentators suggest. A novel arithmetical argument shows that from a public policy perspective, 'weak' adverse selection can be a good thing. This is because a degree of adverse selection is needed to maximise 'loss coverage', the expected fraction of the population's losses which is compensated by insurance. This book will be valuable for those interested in public policy arguments about insurance and discrimination: academics (in economics, law and social policy), policymakers, actuaries, underwriters, disability activists, geneticists and other medical professionals.

One of the major functions of statistical analysis is to describe the data in a way that is easy to comprehend and communicate. This can be done both by presenting the data in graphical form and by calculating various summary statistics, such as; the measures of central tendency and the measures of variability. The graphical techniques described in this book come under the broad category of Data Visualization that enables the analyst to describe a data set graphically that is more concise than the original data. The techniques in this book will help you reveal the essential characteristics of the data using graphs which are critical in effective decision making.

This edition of the Export Essentials statistical series looks at export clearances through February for Canada, the United States and Australia. Gaining perspective about actual quantities of specialty crops being shipped from these countries has become more critical in the face of worries about weather in numerous key production areas in the world.

In this next volume of Progress in Economics Research, chapters discuss risk measurement methods in financial investments; the expansion of intellectual property rights and foreign direct investments; the role of process in policy-making in the maritime sector with reference to corporate social responsibility and how issues of flexibility, movement, change, and the increasing speed of these events can be accommodated in a new governance framework that takes account of the changed situation for nation-states; enhanced cooperation and the progressive process of differentiated integration in the European Union and its implications; personal metaphors expressed using a sample of MBA students who are preparing for their future careers as directors; mobilisers' problematising economic inequality in Hong Kong.; and home purchase decisions of the younger generation in Hong Kong.

This book mainly focuses on why data analytics fails in business. It provides an objective analysis and root causes of the phenomenon, instead of abstract criticism of utility of data analytics. The author, then, explains in detail on how companies can survive and win the global big data competition, based on actual cases of companies. Having established the execution and performance-oriented big data methodology based on over 10 years of experience in the field as an authority in big data strategy, the author identifies core principles of data analytics using case analysis of failures and successes of actual companies. Moreover, he endeavors to share with readers the principles regarding how innovative global companies became successful through utilization of big data. This book is a quintessential big data analytics, in which the author's knowhow from direct and indirect experiences is condensed. How do we survive at this big data war in which Facebook in SNS, Amazon in e-commerce, Google in search, expand their platforms to other areas based on their respective distinct markets? The answer can be found in this book.

Nonparametric statistics provide a scientific methodology for cases where customary statistics are not applicable. Nonparametric statistics are used when the requirements for parametric analysis fail, such as when data are not normally distributed or the sample size is too small. The method provides an alternative for such cases and is often nearly as powerful as parametric statistics. Another advantage of nonparametric statistics is that it offers analytical methods that are not available otherwise. Nonparametric methods are intuitive and simple to comprehend, which helps researchers in the social sciences understand the methods in spite of lacking mathematical rigor needed in analytical methods customarily used in science. This book is a methodology book and bypasses theoretical proofs while providing comprehensive explanations of the logic behind the methods and ample examples, which are all solved using direct computations as well as by using Stata. It is arranged into two integrated volumes. Although each volume, and for that matter each chapter, can be used separately, it is advisable to read as much of both volumes as possible; because familiarity with what is applicable for different problems will enhance capabilities.

Nonparametric statistics provide a scientific methodology for cases where customary statistics are not applicable. Nonparametric statistics are used when the requirements for parametric analysis fail, such as when data are not normally distributed or the sample size is too small. The method provides an alternative for such cases and is often nearly as powerful as parametric statistics. Another advantage of nonparametric statistics is that it offers analytical methods that are not available otherwise. Nonparametric methods are intuitive and simple to comprehend, which helps researchers in the social sciences understand the methods in spite of lacking mathematical rigor needed in analytical methods customarily used in science. This book is a methodology book and bypasses theoretical proofs while providing comprehensive explanations of the logic behind the methods and ample examples, which are all solved using direct computations as well as by using Stata. It is arranged into two integrated volumes. Although each volume, and for that matter each chapter, can be used separately, it is advisable to read as much of both volumes as possible; because familiarity with what is applicable for different problems will enhance capabilities.

Modern economies are full of uncertainties and risk. Economics studies resource allocations in an uncertain market environment. As a generally applicable quantitative analytic tool for uncertain events, probability and statistics have been playing an important role in economic research. Econometrics is statistical analysis of economic and financial data. In the past four decades or so, economics has witnessed a so-called 'empirical revolution' in its research paradigm, and as the main methodology in empirical studies in economics, econometrics has been playing an important role. It has become an indispensable part of training in modern economics, business and management.This book develops a coherent set of econometric theory, methods and tools for economic models. It is written as a textbook for graduate students in economics, business, management, statistics, applied mathematics, and related fields. It can also be used as a reference book on econometric theory by scholars who may be interested in both theoretical and applied econometrics.

Agricultural Statistics is published each year to meet the diverse need for a reliable reference book on agricultural production, supplies, consumption, facilities, costs, and returns. Its tables of annual data cover a wide variety of facts in forms suited to most common use. Statistics presented in many of the tables represent actual counts of the items covered. Most of the statistics relating to foreign trade and to Government programs, such as numbers and amounts of loans made to farmers, and amounts of loans made by the Commodity Credit Corporation, etc., are data of this type. A large number of other tables, however, contain data that are estimates made by the Department of Agriculture. The estimates for crops, livestock, and poultry made by the U.S. Department of Agriculture are prepared mainly to give timely current State and national totals and averages. They are based on data obtained by sample surveys of farmers and of people who do business with farmers. The survey data are supplemented by information from the Censuses of Agriculture taken every five years and check data from various sources. Being estimates, they are subject to revision as more data become available from commercial or Government sources. Unless otherwise indicated, the totals for the United States shown in the various tables on area, production, numbers, price, value, supplies, and disposition are based on official Department estimates. They exclude States for which no official estimates are compiled. Extensive table data include statistics of the following: *Statistics of Grain and Feed *Cotton, Tobacco, Sugar Crops, and Honey *Oilseeds, Fats, and Oils *Vegetables and Melons *Hay, Seeds, and Minor Field Crops *Cattle, Hogs, and Sheep *Dairy and Poultry *Insurance, Credit & Cooperatives *Agricultural Conservation & Forestry *Consumption & Family Living *Fertilizers & Pesticides Miscellaneous Agricultural Statistics such as Foreign Agricultural Trade Statistics including exports, fisheries and more. Professionals in the following fields to include farmers, ranchers, soil conservationists, surveyors, agricultural economist consultants, livestock manufacturers, livestock feedlot operators, food distributors, animal scientists, food chemists, food brokers, farm and land appraisers (and more) may have the greatest interest in this volume.

Data mining has become the fastest growing topic of interest in business programs in the past decade. This book is intended to describe the benefits of data mining in business, the process and typical business applications, the workings of basic data mining models, and demonstrate each with widely available free software.

This publication is compiled to provide quality and timely statistical data for the monitoring, evaluation, analysis, research, and promotion of the intra-African trade. It is intended to serve the needs of researchers, policy makers, and the public who work on trade issues. This seventh edition of the Compendium presents foreign trade data in sixteen chapters for all African countries for the period 2004 to 2012. Information on total, share, direction, and evolution of African trade is provided. Focusing on intra-African trade, related statistical data of trade flows are grouped by region, subregions, and Regional Economic Communities (RECs) in Africa, a unique feature that has been found nowhere else. It is hoped that the Compendium will provide the needed support to ongoing efforts aimed at ensuring the integration of the African continent.

There are several powerful statistical analysis software, such as Stata, SAS, and a host of other packages with different levels of elegance, completeness, and support. Preferred is Stata because of its extensive contributions from its users and reliable technical support. I will add Stata commands to perform all the examples of the book. The commands are simple and quick to run. I will provide an appendix with the list of the commands used in the manuscript, their syntax, and a brief description of the output they create. Updated data for all the examples using the most recent available data. Provide the solutions in Excel and Stata and explain the meanings of the output to reinforce the subject and allow users to have another set of examples using another real-life data. Increased graphical representations to reinforce and clarify the concept.

Statistics is the branch of mathematics that deals with real life problems. As such, it is an essential tool for economists. Unfortunately, the way the concept is introduced to students is not compatible with the way economists think and learn. The problem is worsened by the use of mathematical jargon and complex derivations. However, as this book demonstrates, neither is necessary. The book is written in simple English with minimal use of symbols, mostly for the sake of brevity and to make reading literature more meaningful. The second edition also incorporates Stata software for use by more technically oriented readers who have access to sophisticated software. The objective of this book is to address the fundamentals of statistical analysis in a simple and easy-to-comprehend way. Instead of covering numerous topics, the book covers interrelated subjects that are necessary for the comprehension of the presented topics. The second edition has augmented the explanations in the first to clarify the subjects even more. The examples are based on economic theory utilizing actual data. The hope is that the use of theory will prove useful in relating the subject to actual empirical applications and help with research.

This is the first volume in a two-part publication which offers a comprehensive view of the topic. Volume I: Trade by Country, compiled in May 2014, presents detailed data of 175 countries (or areas) with data on imports and exports by commodity and trading partner provided for approximateky 90 countries (or areas), representing more than 70% of world trade in 2014. Volume II: Trade by Commodity, expected to be released at the end of the year, contains the detailed tables showing international trade for 258 commodities and eleven world trade tables covering trade values and indices up to the year 2014.

The technique of regression analysis is used so often in business and economics today that an understanding of its use is necessary for almost everyone engaged in the field. This book covers essential elements of building and understanding regression models in a business/economic context in an intuitive manner. The book provides a non-theoretical treatment that is accessible to readers with even a limited statistical background. This book describes exactly how regression models are developed and evaluated. The data used in the book are the kind of data managers are faced with in the real world. The book provides instructions and screen shots for using Microsoft Excel to build business/economic regression models. Upon completion, the reader will be able to interpret the output of the regression models and evaluate the models for accuracy and shortcomings.