Econometría de las series de tiempo, cointegración y heteroscedasticidad condicional autoregresiva

Abstract

Empirical research in economics, as well as in financial economics, uses time series as a fundamental tool. The renowned economic work of Trygve Haavelmo, considered as a standard vision, considers economic time series as realizations of stochastic processes. This approach allows the modeler the use of statistical inference in the construction and verification of equations that characterize the relationships between economic variables. This year's Nobel Prize (2003) recognizes two contributions that have deepened our understanding of two central properties of many economic time series - non-stationarity and variable volatility over time - allowing for a large number of applications.