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High Frequency Financial Econometrics : Recent Developments
This exciting volume presents cutting-edge developments in high frequency financial econometrics, spanning a diverse range of topics: market microstructure, tick-by-tick data, bond and foreign exchange markets and large dimensional volatility modelling. The chapters on market microstructure deal with liquidity, asymmetries of information, and limit order aggressiveness in pure limit order book markets. The chapters on tick-by-tick data present statistical techniques for the analysis of the discrete nature of price movements, the intraday seasonal patterns of financial durations, and the joint probability law of prices, volume and durations. Bond markets are brought into focus through the analysis of macroeconomic announcements in the future bond market as a function of the business cycle.
Econometric Analysis of Count Data
The book provides graduate students and researchers with an up-to-date survey of statistical and econometric techniques for the analysis of count data, with a focus on conditional distribution models. Proper count data probability models allow for rich inferences, both with respect to the stochastic count process that generated the data, and with respect to predicting the distribution of outcomes. The book starts with a presentation of the benchmark Poisson regression model. Alternative models address unobserved heterogeneity, state dependence, selectivity, endogeneity, underreporting, and clustered sampling. Testing and estimation is discussed from frequentist and Bayesian perspectives. Finally, applications are reviewed in fields such as economics, marketing, sociology, demography, and health sciences. The fifth edition contains several new topics, including copula functions, Poisson regression for non-counts, additional semi-parametric methods, and discrete factor models. Other sections have been reorganized, rewritten, and extended.
Differential Undercounts in the U.S. Census : Who is Missed?
This book describes the differences in US census coverage, also referred to as “differential undercount”, by showing which groups have the highest net undercounts and which groups have the greatest undercount differentials, and discusses why such undercounts occur. In addition to focusing on measuring census coverage for several demographic characteristics, including age, gender, race, Hispanic origin status, and tenure, it also considers several of the main hard-to-count populations, such as immigrants, the homeless, the LBGT community, children in foster care, and the disabled. However, given the dearth of accurate undercount data for these groups, they are covered less comprehensively than those demographic groups for which there is reliable undercount data from the Census Bureau. This book is of interest to demographers, statisticians, survey methodologists, and all those interested in census coverage.
