Aggregation in large dynamic panels

Pesaran, M. Hashem; Chudík, Alexander

doi:10.1016/j.jeconom.2013.08.027

Cited by 44 publications

(15 citation statements)

References 32 publications

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“…The paper also presents a simple test of the degree of pervasiveness of the most dominant units in the network, which are shown to have satisfactory size and power properties when N is large, even if T is quite small. The analysis of this paper has been static, but the proposed statistical framework can be extended to allow for dynamics, along similar lines as in Pesaran and Chudik (2014) who consider aggregation of large dynamic panels.…”

Section: Discussionmentioning

confidence: 99%

Econometric Analysis of Production Networks with Dominant Units

Pesaran

Yang

2016

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. (2012) and considers a production network with unobserved common technological factor and establishes general conditions under which the network structure contributes to aggregate fluctuations. It introduces the notions of strongly and weakly dominant units, and shows that at most a finite number of units in the network can be strongly dominant, while the number of weakly dominant units can rise with N (the cross section dimension). This paper further establishes the equivalence between the highest degree of dominance in a network and the inverse of the shape parameter of the power law. A new extremum estimator for the degree of pervasiveness of individual units in the network is proposed, and is shown to be robust to the choice of the underlying distribution. Using Monte Carlo techniques, the proposed estimator is shown to have satisfactory small sample properties. Empirical applications to US input-output tables suggest the presence of production sectors with a high degree of pervasiveness, but their effects are not sufficiently pervasive to be considered as strongly dominant. Terms of use: Documents inJEL-Codes: C120, C130, C230, C670, E320.

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Section: Discussionmentioning

confidence: 99%

Econometric Analysis of Production Networks with Dominant Units

Pesaran

Yang

2016

SSRN Journal

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“…Notice here that, as shown in Pesaran and Chudik (2014) and Chudik and Pesaran (2015), if slope heterogeneity is not extreme (i.e., if the coefficient matrices Φ i do not differ too much across i) and C decays exponentially in , the infinite order distributed lag functions inz ω,t can be truncated. In practice, Pesaran and Chudik (2014) and Chudik and Pesaran (2015) recommend a lag length equal to T 1/3 , where T is the time dimension of the panel.…”

Section: A Dynamic Multi-country Heterogeneous Modelmentioning

confidence: 90%

“…In practice, Pesaran and Chudik (2014) and Chudik and Pesaran (2015) recommend a lag length equal to T 1/3 , where T is the time dimension of the panel.…”

Section: A Dynamic Multi-country Heterogeneous Modelmentioning

confidence: 99%

Uncertainty and Economic Activity: A Multi-Country Perspective

2018

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Measures of economic uncertainty are countercyclical, but economic theory does not provide definite guidance on the direction of causation between uncertainty and the business cycle. This paper proposes a new multi-country approach to the analysis of the interaction between uncertainty and economic activity, without a priori restricting the direction of causality. We develop a multi-country version of the Lucas tree model with time-varying volatility and show that in addition to common technology shocks that affect output growth, higher-order moments of technology shocks are also required to explain the cross country variations of realized volatility. Using this theoretical insight, two common factors, a 'real' and a 'financial' one, are identified in the empirical analysis assuming different patterns of cross-country correlations of country-specific innovations to real GDP growth and realized stock market volatility. We then quantify the absolute and the relative importance of the common factor shocks as well as country-specific volatility and GDP growth shocks. The paper highlights three main empirical findings. First, it is shown that most of the unconditional correlation between volatility and growth can be accounted for by the real common factor, which is proportional to world growth in our empirical model and linked to the risk-free rate. Second, the share of volatility forecast error variance explained by the real common factor and by country-specific growth shocks amounts to less than 5 percent. Third, shocks to the common financial factor explain about 10 percent of the growth forecast error variance, but when such shocks occur, their negative impact on growth is large and persistent. In contrast, country-specific volatility shocks account for less than 1-2 percent of the growth forecast error variance. Terms of use: Documents inJEL-Codes: E440, F440, G150.

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“…Finally, the RA assumption also induces additional difficulties on testing grounds, because whenever one tests a proposition delivered by a RA model, one is also jointly testing the very RA hypothesis. Hence, one tests together the rejection of the latter with the rejection of the specific model proposition (more on that in Lippi, 1997, 1999;Pesaran and Chudik, 2011).…”

Section: Towards a Complexity Macroeconomicsmentioning

confidence: 99%

More is different ... and complex! the case for agent-based macroeconomics

2019

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This work nests the Agent-Based macroeconomic perspective into the earlier history of macroeconomics. We discuss how the discipline in the 70's took a perverse path relying on models grounded on fictitious rational representative agent in order to try to pathetically circumvent aggregation and coordination problems. The Great Recession was a natural experiment for macroeconomics, showing the inadequacy of the predominant theoretical framework grounded on DSGE models. After discussing the pathological fallacies of the DSGE-based approach, we claim that macroeconomics should consider the economy as a complex evolving system, i.e. as an ecology populated by heterogenous agents, whose far-from-equilibrium interactions continuously change the structure of the system. This in turn implies that more is different: macroeconomics cannot be shrink to representative-agent micro, but agents' complex interactions lead to emergence of new phenomena and hierarchical structure at the macro level. This is what is taken into account by agent-based models, which provide a novel way to model complex economies from the bottom-up, with sound empirically-based microfoundations. We present the foundations of Agent-Based macroeconomics and we discuss how the contributions of this special issue push its frontier forward. Finally, we conclude by discussing the ways ahead for the fully acknowledgement of agent-based models as the standard way of theorizing in macroeconomics.

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Aggregation in large dynamic panels

Cited by 44 publications

References 32 publications

Econometric Analysis of Production Networks with Dominant Units

Econometric Analysis of Production Networks with Dominant Units

Uncertainty and Economic Activity: A Multi-Country Perspective

More is different ... and complex! the case for agent-based macroeconomics

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