Benjamin Carton, Mr. Joannes Mongardini, and Yiqun Li
The enormous global demand for smartphones in recent years has created a new global tech cycle. In 2016 alone, global smartphone sales reached close to 1.5 billion, one for every fifth person on earth. In turn, this has engendered complex and evolving supply chains across Asia. We show that the new tech cycle cannot be captured by standard seasonality, but depends on smartphone product release dates. Decomposing cycle from trend, we also show that the sale of smartphones may have peaked in late 2015. Asia, however, continues to gain in importance as the global tech manufacturer.
This paper presents a multisector growth model where education enhances general human capital, which is essential for increasing or maintaining the mobility of workers across industries. The paper shows that education, combined with international trade, can affect growth positively in the long run by raising workers’ ability to adapt and move easily to industries with the greatest productivity in each period. Depending on the initial ratio of general-to-specific human capital stock, multiple equilibrium growth paths can exist, including a poverty trap. If the ratio is not substantially low, trade liberalization can allow an economy in a poverty trap to transform into one with continuous education and higher output growth.
Automated trade execution systems are examined with respect to the degree to which they automate the price discovery process. Seven levels of automation of price discovery are identified, and 47 systems are classified according to these criteria. Systems operating at various levels of automation are compared with respect to age, geographical location, and type of securities traded. Information provided to market participants, and asymmetries of information between traders with direct access to the automated market and outside investors also are examined. It is found, for example, that the degree of asymmetric information increases with the level of automation of price discovery. The potential for trading abuses related to prearranged trading, noncompetitive execution, and trading ahead of customers is analyzed for each level of automation. Certain levels of automation widen the opportunities for trading abuses in some respects, but may narrow them in others.