Statistical Year Book

This 2018 yearbook issue of International Financial Statistics (IFS) is a standard source of statistics on all aspects of international and domestic finance. The IMF publishes calculated effective exchange rates data only for countries that have given their approval. The country, euro area, and world tables provide measures of effective exchange rates, compiled by the IMF’s Research Department, Statistics Department, and area departments. The real effective exchange rate index in line rec is derived from the nominal effective exchange rate index, adjusted for relative changes in consumer prices. Consumer price indices, often available monthly, are used as a measure of domestic costs and prices for these countries.

The Statistical Yearbook is an annual compilation of a wide range of international economic, social and environmental statistics on over 200 countries and areas, compiled from sources including UN agencies and other international, national and specialized organizations. The 2016 edition contains data available to the Statistics Division as of 31 July 2016 and presents them in 26 tables on topics such as: communication; crime; development assistance; education; energy; environment; finance; gender; international merchandise trade; international tourism; labor force; national accounts; population and migration; price and production indices; and science and technology. Most tables covering the period up to 2016. Accompanying the tables are technical notes providing brief descriptions of major statistical concepts, definitions and classifications.

This publication offers a synthesis of the major factors at play in the global food and agricultural landscape. Statistics are presented in four thematic chapters, covering the economic importance of agricultural activities, inputs, outputs and factors of production, their implications for food security and nutrition and their impacts on the environment. The Yearbook is meant to constitute a primary tool for policy makers, researchers and analysts, as well as the general public interested in the past, present and future path of food and agriculture.

This fully updated edition of the China Ethnic Statistic Yearbook, comprised of entirely original research, presents data on the socioeconomic situation of China’s 56 ethnic groups. Although the majority of China’s population is of the Han nationality (which accounts for more than 90% of China’s population), the non-Han ethnic groups have a population of more than 100 million. China has officially identified, except for other unknown ethnic groups and foreigners with Chinese citizenship, 55 ethnic minorities. In addition, ethnic minorities vary greatly in size. With a population of more than 15 million, the Zhuang are the largest ethnic minority, and the Lhoba, with a population of only about three thousand, the smallest. China’s ethnic diversity has resulted in a special socioeconomic landscape for China itself. How different have China’s ethnic groups been in every sphere of daily life and economic development during China’s fast transition period? In order to answer these questions, we have created a detailed and comparable set of data for each of China’s ethnic groups. This book presents, in an easy-to-use format, a broad collection of social and economic indicators on China’s 56 ethnic groups. This useful resource profiles the general social and economic situations for each of these ethnic groups. These indicators are compiled and estimated based on the regional and local data gathered from a variety of sources up to 2016 with up to date analysis. This Yearbook also includes a new chapter on China’s spatial (dis)integration as a multiethnic paradox.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

This annual publication, jointly produced by the African Development Bank (AfDB), the African Union Commission (AUC) and the United Nations Economic Commission for Africa (ECA), is a result of the fruitful collaboration that exists among the three pan-African organizations within the field of statistics. This synergistic collaboration has two principal benefits: (1) it minimizes the risk of inconsistent information being produced by the three organizations, and (2) it reduces the reporting burden on member states, who might otherwise be obliged to submit data separately to each institution. The yearbook continues to serve the intended purpose of bringing together, in one volume, data on African countries for policy-makers, researchers and other users. The present edition presents a time series showing how African countries performed on several economic and social indicators over the period 2011-2019.