Non-Fundamentalness in Structural Econometric Models: A Review

Abstract

Current economic theory typically assumes that all the macroeconomic variables belonging to a given economy are driven by a small number of structural shocks. As recently argued, apart from negligible cases, the structural shocks can be recovered if the information set contains current and past values of a large, potentially infinite, set of macroeconomic variables. However, the usual practice of estimating small size causal Vector AutoRegressions can be extremely misleading as in many cases such models could fully recover the structural shocks only if future values of the few variables considered were observable. In other words, the structural shocks may be non-fundamental with respect to the small dimensional vector used in current macroeconomic practice. By reviewing a recent strand of econometric literature, we show that, as a solution, econometricians should enlarge the space of observations, and thus consider models able to handle very large panels of related time series. Among several alternatives, we review dynamic factor models together with their economic interpretation, and we show how non-fundamentalness is non-generic in this framework. Finally, using a factor model, we provide new empirical evidence on the effect of technology shocks on labour productivity and hours worked.

Government purchases reloaded: Informational insufficiency and heterogeneity in fiscal VARs

“…n fact, contrary to what is generally assumed in theoretical models, government consumption and invest-5 The issue of non-fundamentalness in VARs was originally studied by Hansen and Sargent (1980), and Reichlin (1993, 1994). A comprehensive review is in Alessi et al (2011).…”

Size Effects of Fiscal Policy and Business Confidence in the Euro Area

“…3 An additional advantage of factor analysis is that the responses to a spending shock do not suffer from foresight issues 4 (see Forni and Gambetti 2010;Forni et al 2009), a problem further alleviated in this paper through the use of a business confidence indicator. Additionally, as Forni et al (2009) and Alessi et al (2011) have shown, the inclusion of more information about the economy through the factors avoids potential VAR non-fundamentalness issues that might arise, such as the ones presented in Lippi and Reichlin (1993).…”

Measuring nonfundamentalness for structural VARs

“…DSGE, anticipated shocks and nonfundamentalness Yet Lippi and Reichlin (1993) argue that economic models can lead to nonfundamental representations of the data. As surveyed in Alessi et al (2011) and Lütkepohl (2012), nonfundamentalness is basically of two kinds: one which is peculiar to the story-telling of the DSGE and the other which arises as an omitted variable problem. In the former case, nonfundamentalness is model-based and the economic shocks may well be nonfundamental with respect to any set of observables (models with imperfect information where the agents are faced with a ltering problem to infer the structural shocks).…”