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Roughly, the first 5 chapters and the seventh could be thought in first part, chapter resfarch and the last four in the second part. This book would not have been possible without their fundamental inputs.

Dynamic macroeconomics is in part about intertemporal substitution.

I also have an intellectual debit with Ed Prescott. Enviado por Gilmar flag Denunciar. To all goes my thanks.

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.

Chapter 3 discusses procedures used to obtain interesting information about secular and cyclical fluctuations in the data. I have methoes a lot through the process of writing this book and teaching its material, probably as much as students have learned from the lectures and practical sessions.

I always like to argue with him because his unconventional views helped to bring out often forgotten methodological and practical aspects. 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.


Given our empirical perspective, formal results are often stated without proofs and em- phasis is given to their use in particular macroeconomic applications. Chapter 2 presents a number of macroeconomic models currently ii used in the profession and discusses numerical methods needed to solve them.

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

Chapter 4 describes minimalist vector autoregressive VAR approaches, where a limited amount of economic theory is used to structure the data.

Those who feel comfortable with these topics can skip. The first three chapters of the book are macrooeconomic and review material extensively used in later chapters.

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. Adrian Pagan shaped my somewhat cynical view of what should and can be done with the data and the models.

The book is largely self-contained but presumes methdos basic knowledge of modern macroeco- nomic theory say, one or two quarters of a Ph. In the remaining chapters we present various methodologies to confront models to the data and discuss how they can be used to address other interesting economic questions.


And on most issues of interest to applied macroeconomists he was more app,ied right than wrong. As mentors, there was no one comparable to them.

Fabio Canova (Author of Methods for Applied Macroeconomic Research)

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. This is the setup I have macroecoonmic in teaching this material over a number years and it seems the natural division between what I consider basic and advanced material.

Most of the examples and exercises of this book are based on versions of these models. 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.

Patience is probably built on the same principle. Chapter 6 examines full information Maximum Likeli- hood and in chapter 7 Calibration techniques are discussed.