Unique in its coverage, Urban Economics and Real Estate allows an instructor to teach separate courses in either urban economics or urban real estate, or a blend of the two topics. The portion on urban economics focuses on urban/suburban growth―physical as well as job growth. The interplay of federal government and local authorities is discussed, and the effects of social problems, such as crime, poverty, and education that often accompany these changes are discussed. 
While the latest data sets available are utilized, Urban Economics’ emphasis is on economic analysis. The real estate chapters emphasize housing markets, appraisal, business investments, and their relationship to finance. New to this edition is extensive coverage of international issues in cities around the planet. Given the rapidly changing empirical side of urban demography, the text is accompanied by a website with new examples added annually and various discussions/tips about the latest data sets that become available.

Urban Economics and Real Estate: Theory and Policy

Business & Money

McDonald, John F.

McMillen, Daniel P.

Economics

wiley

Quantile regression analysis differs from more conventional regression models in its emphasis on distributions. Whereas standard regression procedures show how the expected value of the dependent variable responds to a change in an explanatory variable, quantile regressions imply predicted changes for the entire distribution of the dependent variable. Despite its advantages, quantile regression is still not commonly used in the analysis of spatial data. The objective of this book is to make quantile regression procedures more accessible for researchers working with spatial data sets. The emphasis is on interpretation of quantile regression results. A series of examples using both simulated and actual data sets shows how readily seemingly complex quantile regression results can be interpreted with sets of well-constructed graphs. Both parametric and nonparametric versions of spatial models are considered in detail.

Quantile Regression for Spatial Data (SpringerBriefs in Regional Science)

Reference

Springer

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Books by McMillen, Daniel P.