$U_p>U_{\rm crit} = 0.094$ as unpredictable [@marhuenda2005comparison].

We find that 284 products ($56\%$) are predictable while the remaining 224 ($44\%$) are unpredictable by the model simulations with $\rho=400$. The number of predictable products was smaller for other selected values of $\rho$. More products are classified as predictable if the model prediction is made for a shorter period than $T=38$ years. Most of the unpredictable products display large positive or negative excess growth rate (Fig. \[fig:application\] (a)). Interestingly, such deviations are correlated with the nature of the products, as identified in the SITC framework: Growth rates for raw materials and agricultural commodities tend to be smaller than the predicted growth rates, showing the mean excess growth rate $\langle R_p\rangle=T^{-1}\sum_t R_p(t)$ negative, while manufactured and especially high-end products such as medical appliances have $\langle R_p\rangle$ positive. Figure \[fig:application\] (b) shows the mean excess growth rates of 66 product categories based on the first two digits of SITC. Chemicals (SITC codes beginning with 5), manufactured goods (6 and 8) and machinery (7) have grown faster than the model prediction while the growth of the share of crude materials (2) was slower than the prediction. The fraction of unpredictable products is larger among manufactured 