Combining Input-Output (IO) analysis with Global Vector Autoregressive (GVAR) modeling: Evidence for the USA (1992-2006)

Konstantakis, Konstantinos and Michaelides, Panayotis G. (2014): Combining Input-Output (IO) analysis with Global Vector Autoregressive (GVAR) modeling: Evidence for the USA (1992-2006).

Abstract

The purpose of this paper is to assess the interdependencies among the eight (8) main sectors of economic activity in the US economy, using quarterly data on output and labor fora period of fifteen years (1992-2006), just before the first signs of the global recession made their appearance. In this context, we set up a novel methodological framework which combines Input-Output (IO) analysis with state of the art Global Vector Autoregressive (GVAR) modeling. In addition, we use the IO matrices to provide a procedure in order to test for the existence of dominant sector(s) in the USA and estimate a GVAR model with dominant sector(s) and the exogenous variables of Global Credit and Global Trade acting as the transmission channels. Our results seem to suggest that the US economy has relatively limited connectivity, in terms of sectoral output and labor, among the various sectors.

• Item Type: MPRA Paper
• Language: English
• Keywords: GVAR, Input Output, US sectors, Weight Matrix
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C67 - Input-Output Models

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