Dependence and information flow among U.S technology industries

Abstract

The technology sector serves as a fundamental pillar for all industry sectors in the economy and plays a central role in driving the worldwide economic growth. It particularly distinguishes itself in the U.S., representing approximately one-third of the global technology market. Consequently, this paper examines the relationships among U.S. technology industries, capturing both linear and nonlinear characteristics by combining Vine copulas and transfer entropy. Our results reveal heterogeneous, moderate to strong positive dependence with Semiconductors as a key player, which is influencing the remaining industries. Tail dependence manifests in both the upper and lower tail, with the latter being stronger, as the dependence among technology industries intensifies more in market downturns. In addition, significant asymmetrical information flow is detected between Semiconductors and other technology industries in both directions. The information transmission from Semiconductors to other industries is statistically significant in all cases, confirming its predictive power within the entire sector. Contrarily, in the opposite direction, the information flow is statistically significant in only 3 out of 5 cases. The identification of Semiconductors as a central variable is particularly significant due to its global importance, as shifts in this industry could readily propagate beyond the technology sector, influencing the broader economy

Keywords: Vine copula, Semiconductors, Technology sector, Dependence modeling