We provide an overview of productivity development and other related indicators in Asia and Pacific (APAC) countries, with comparisons with the Europe region. We use the seventh vintage firm-level data from the Productivity Research Network in the APAC region and CompNet in Europe for our study. The overall results show that the productivity growth in developed APAC countries (Australia, New Zealand, and the Republic of Korea) is significantly ahead of the growth in developing APAC countries (India and the People’s Republic of China) and on par with the EU’s growth. There is an ongoing process of bottom firms catching up with top firms in the Republic of Korea and the richest EU countries. Regarding employment and labor skills, employment growth has generally been quite stagnant in all regions. Labor skills, for which we use the wage premium as a proxy, are quite similar across most regions, with the richest EU countries showing a higher premium than the rest. Our test of the productivity–employment link indicates that the size of employment tends to have a greater impact on productivity in APAC countries, while labor skills have greater emphasis in the EU.

We present the first evidence on the role of occupational choices and acquired skills for migrant selection. Combining novel data from a representative Mexican task survey with rich individual-level worker data, we find that Mexican migrants to the United States have higher manual skills and lower cognitive skills than nonmigrants. Results hold within narrowly defined region–industry–occupation cells and for all education levels. Consistent with a Roy/Borjas-type selection model, differential returns to occupational skills between the United States and Mexico explain the selection pattern. Occupational skills are more important to capture the economic motives for migration than previously used worker characteristics.

The value of social network analysis is critically dependent on the comprehensive and reliable identification of actors and their relationships. We compare regional knowledge networks based on different types of data sources, namely, co-patents, co-publications, and publicly subsidized collaborative R&D projects. Moreover, by combining these three data sources, we construct a multilayer network that provides a comprehensive picture of intraregional interactions. By comparing the networks based on the data sources, we address the problems of coverage and selection bias. We observe that using only one data source leads to a severe underestimation of regional knowledge interactions, especially those of private sector firms and independent researchers.