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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.

Despite the fact that the U.S. food sector is a key component of U.S. manufacturing, it has attracted limited attention in the literature, so far. In fact, the recent food crisis shed some light on different aspects of the food sector, its products and its influence on millions of people. The sector is characterised by increasing concentration, changes in relative prices, shifts in consumer preferences and changes in government regulations. However, key issues related to technological change and the cyclical regularities of economic time series in the sector have been neglected or even unexplored in the literature. Our study provides robust evidence supporting the fact that technological change has explanatory power for output and profitability in the Granger-causal sense at various leads or lags. Also, the timing pattern of technological change indicates that the peak correlations appear at moderate lags. This implies that the technology shocks are transmitted in the economy relatively quickly. Also, the various economic time series in the sector seem to follow a cyclical pattern characterized by periodicities exhibiting a short-term cycle, a mid-term cycle and a long-term cycle.

The present paper discusses the transition from linear modelling to the first nonlinear models in economic analysis. In this vein, an important contribution was J. Hicks’s A Contribution to the Theory of the Trade Cycle where he developed his own endogenous model of the cycle. Hicks thought that fluctuations in investment,– caused by nonlinear changes in autonomous investment and the acceleration principle governing induced investment – led to an adjustment process taking place throughout many periods. In this paper we introduce some modifications regarding the econometric estimation of Hicks’s nonlinear model and an empirical application for Greece (1960-2007) takes place demonstrating the almost ideal fit of the model.