The Meaning of Total Factor Productivity

Conceptually, total factor productivity refers to how efficiently and intensely inputs are used in the production process. Total factor productivity (TFP) is sometimes referred to as "multi-factor productivity," and, under certain assumptions, can be thought of as a measure of level of technology or knowledge.

Given the macro model: Y_t = Z_tF(K_t,L_t), Total Factor Productivity (TFP) is defined to be Y_t/F(K_t,L_t)

Likewise, given Y_t = Z_tF(K_t,L_t,E_t,M_t), TFP is Y_t/F(K_t,L_t,E_t,M_t)

The Solow residual is a measure of TFP. TFP presumably changes over time. There is disagreement in the literature over the question of whether the Solow residual measures technology shocks. Efforts to change the inputs, like K_t, to adjust for utilization rate and so forth, have the effect of changing the Solow residual and thus the measure of TFP. But the idea of TFP is well defined for each model of this kind.

TFP is not necessarily a measure of technology since the TFP could be a function of other things like military spending, or monetary shocks, or the political party in power.

"Growth in total-factor productivity (TFP) represents output growth not accounted for by the growth in inputs." — Hornstein and Krusell (1996).

Disease, crime, and computer viruses have small negative effects on TFP using almost any measure of K and L, although with absolutely perfect measures of K and L they might disappear.

Reason: crime, disease, and computer viruses make people AT WORK less productive.