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Dynamic macroeconomics fanova in part about intertemporal substitution. Yet, when I found a new example or an application where the ideas of this book could be used, I regained the excitement of the first days.

Adrian Pagan shaped my somewhat cynical view of what should and can be done with the data and the models. Given our empirical perspective, formal results are often stated without proofs and em- phasis is given to their use in particular macroeconomic applications.

Methods for applied macroeconomic research – Canova F. (PUP, 2007)

This is the setup I have used in teaching this material over a number years and it seems the natural division between what I consider macroecobomic and advanced material. In particular, chapter 1 presents basic time series and probability concepts, a list of useful law of large numbers and central limit theorems, which are employed in the discussions of chapters 4 to 8, and gives a brief overview of the basic elements of spectral analysis, heavily used in chapters 3, 5 and 7.


Three people taught me to approach empirical problems in a sensible but rigorous way, combining economic theory with advanced statistical tools and numerical methods, and to be suspicious and critical of analyses which leave out one of the main ingredients of the cake. I always like to argue with him because his unconventional views helped to bring out often forgotten methodological and practical aspects. And on most issues of interest to applied macroeconomists he was more often right than wrong.

In the remaining chapters we present various methodologies to confront models to the data and discuss how they can be macroeconomicc to address other interesting economic questions. Patience is probably built on the same principle. Most of the examples and reaearch of this book are based on versions of these models. This book would not have been possible without their fundamental inputs.

Roughly, the first 5 chapters and the seventh could be thought in first part, chapter 6 and the last four in the second part.

Fabio Canova (Author of Methods for Applied Macroeconomic Research)

I also have an intellectual debit with Ed Prescott. As mentors, there was no one comparable to them. I need to thank my restricted and extended family for the patience they endured during the long process that lead to the completion of this book. I have learned a lot through the process of writing this book and teaching its material, probably as reesearch as students have learned from the lectures and practical sessions. Preliminaries This chapter is introductory and it is intended for readers who are unfamiliar with time series concepts, with the properties of stochastic processes, with basic asymptotic theory results and with the a-b-c of spectral analysis.


Chapter 2 presents a number of macroeconomic models currently ii used in the profession and discusses numerical methods needed to solve them. The first three chapters of the book are introductory and review material extensively used in later chapters. Chapter 4 describes minimalist vector autoregressive VAR approaches, where a limited amount of economic theory is used to structure the data. Enviado por Gilmar flag Denunciar. Chapter 6 examines full information Maximum Likeli- hood and in chapter 7 Calibration techniques are discussed.

To all goes my thanks. Chapter 3 discusses procedures used to obtain interesting information about secular and cyclical fluctuations in the data. Those who feel comfortable with these metohds can skip. The book is largely self-contained but presumes a basic knowledge of modern macroeco- nomic theory say, one or two quarters of a Ph.