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Many employers and employees believe that non-cognitive skills are an important contributor to labor market success. This study has assessed the empirical evidence for such a claim in the case of Bangladesh by evaluating unique employer-employee matched labor market data. The analysis is based on data collected from 6,981 workers in 500 formal sector firms in Bangladesh's five largest formal economic sectors. Using ordinary least squares and firm fixed-effect models, the study assesses correlations between wages and the so-called "big five" personality traits, and augments the analysis with the latent personality scores captured by the Rasch model. Comparing the ordinary least squares and fixed-effect models reveals statistically significant correlations between personality traits and wages, within and across firms. The results appear to indicate that non-cognitive skills are correlated with a worker's likelihood of achieving success in the labor market. Although many of the findings are consistent with the literature, the analysis reveals specific patterns that appear to be unique to Bangladesh, including a positive correlation between "emotional stability" and wages and a negative correlation between "grit" and wages, especially among manufacturing workers. Differences across firms could indicate that firms that offer higher wages may tend to attract workers with distinct types of non-cognitive skills, whereas differences within firms may indicate that variations in non-cognitive skills are associated with disparities in firm-level wage structures. Correlations between wages and personality traits are more prominent among large firms than among small or medium-sized firms.

Firm-Fixed Effects --- Occupations --- Personality Traits --- Wages

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This paper studies the sharp increase in violence experienced in Mexico after 2006, known as "The War on Drugs," and its effects on human capital accumulation. The upsurge in violence is expected to have direct effects on individuals' schooling decisions, but not indirect effects, because there was no severe destruction of infrastructure. The fact that the marked increases in violence were concentrated in some municipalities (and not in others) allows for implementation of a fixed-effects methodology to study the effects of violence on educational outcomes. Different from several recent studies that have found significant negative effects of violence on economic outcomes in Mexico, the paper finds evidence that this is not the case, at least for human capital accumulation. The paper uses several sources of data on homicides and educational outcomes and shows that, at most, there are very small effects on total enrollment. These small effects may be driven by some students being displaced from high-violence municipalities to low-violence municipalities; but the education decisions of individuals do not seem to be highly impacted. The analysis discards the possibility that the effects on enrollment of young adults appear small because of a counteracting effect from ex-workers returning to school. The results stand in contrast with recent evidence of the negative effects of violence on short-term economic growth, since minimal to null effects on human capital accumulation today should have little to no adverse effects on long-term growth outcomes in Mexico.

Crime --- Crime and Society --- Education --- Education for All --- Fixed Effects --- Population Policies --- Tertiary Education --- Violence

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Retirement induces major changes in the lifestyle of elderly people and understanding its influences is crucial to promote successful cognitive ageing. In this analysis, I estimate the effect of retiring on cognitive functioning using an instrumental variable strategy, instrumenting for retirement with legal eligibility ages. I exploit the panel dimension of the Survey on Health, Ageing and Retirement in Europe (SHARE) to control for individual heterogeneity and find a positive effect of retirement on memory. I also show suggestive evidence that the beneficial effect of retirement on cognition is larger for women and high-educated indivuals, altough heterogeneous across regions of Europe.

cognition --- ageing --- retirement --- SHARE --- panel estimation --- IV fixed-effects --- Sciences économiques & de gestion > Microéconomie --- Sciences sociales & comportementales, psychologie > Psychologie cognitive & théorique --- Sciences économiques & de gestion > Domaines particuliers de l'économie (santé, travail, transport...)

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This analysis assesses the role of skills, human capital endowment, and migration as determinants of Sub-Saharan Africa's participation in manufacturing global value chains. Due to lack of reliable data on skilled labor, skilled and unskilled labor contents in exports were generated from the Global Trade Analysis Project database. A panel of 23 countries for which data on skills and manufacturing global value chains are available for 19 subsectors was constructed. A fixed-effect gravity model was used to estimate the determinants of backward and forward global value chain participation. The estimates obtained from the sample are compared with global data covering 115 countries for benchmarking purposes. The results indicate that for economies in Sub-Saharan Africa, skilled labor seems to be the strongest determinant of participation in backward and forward global value chains. Similarly, initial human capital endowment has a strong positive impact on global value chain participation at the global level. However, countries with relatively high initial capital endowment benefit more by incorporating foreign value-added products in their manufacturing exports. Finally, countries that receive net inflows of migrants tend to engage better in backward and forward global value chains than those with net outflows of migrants. The findings suggest that policies to improve Sub-Saharan Africa's integration in manufacturing global value chains should target: shifting from unskilled to skilled labor-intensive backward and forward global value chain activities; upgrading the quality of the labor force, since unskilled workers are so far the most available and the most used in manufacturing global value chains; investing in the quality of human capital; and promoting intraregional skills mobility.

Export Competitiveness --- Fixed Effects Estimation --- General Manufacturing --- Global Value Chain --- Global Value Chains and Business Clustering --- Gravity Model --- Human Capital --- Industrial Economics --- Industry --- International Economics and Trade --- Labor Content --- Labor Markets --- Labor Mobility --- Manufacturing --- Migration --- Private Sector Development --- Skilled Labor --- Skills Development and Labor Force Training --- Unskilled Labor

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"The measurement infrastructure for the production of economic statistics in the United States largely was established in the middle part of the 20th century. As has been noted by a number of commentators, the data landscape has changed in fundamental ways since this infrastructure was developed. Obtaining survey responses has become increasingly difficult, leading to increased data collection costs and raising concerns about the quality of the resulting data. At the same time, the economy has become more complex and users are demanding ever more timely and granular data. In this new environment, there is increasing interest in alternative sources of data that might allow the economic statistics agencies to better address users' demands for information. Recent years have seen a proliferation of natively digital data that have enormous potential for improving economic statistics. These include item-level transactional data on price and quantity from retail scanners or companies' internal systems, credit card records, bank account records, payroll records and insurance records compiled for private business purposes; data automatically recorded by sensors or mobile devices; and a growing variety of data that can be obtained from websites and social media platforms. Staggering volumes of digital information relevant to measuring and understanding the economy are generated each second by an increasing array of devices that monitor transactions and business processes as well as track the activities of workers and consumers. Incorporating these non-designed Big Data sources into the economic measurement infrastructure holds the promise of allowing the statistical agencies to produce more accurate, more timely and more disaggregated statistics, with lower burden for data providers and perhaps even at lower cost for the statistical agencies. The agencies already have begun to make use of novel data to augment traditional data sources. Modern data science methods for using Big Data have advanced sufficiently to make the more systematic incorporation of these data into official statistics feasible. Indeed, the availability of new sources of data offers the opportunity to redesign the underlying architecture of official statistics. Considering the threats to the current measurement model arising from falling survey response rates, increased survey costs and the growing difficulties of keeping pace with a rapidly changing economy, fundamental changes in the architecture of the statistical system will be necessary to maintain the quality and utility of official statistics. This volume presents cutting edge research on the deployment of big data to solve both existing and novel challenges in economic measurement. The papers in this volume show that it is practical to incorporate big data into the production of economic statistics in real time and at scale. They report on the application of machine learning methods to extract usable new information from large volumes of data. They also lay out the challenges-both technical and operational-to using Big Data effectively in the production of economic statistics and suggest means of overcoming those challenges. Despite these challenges and the significant agenda for research and development they imply, the papers in the volume point strongly toward more systematic and comprehensive incorporation of Big Data to improve official economic statistics in the coming years"--

Big data. --- Economics --- BUSINESS & ECONOMICS / General. --- Statistical methods --- Data processing. --- Economic theory --- Political economy --- Social sciences --- Economic man --- Data sets, Large --- Large data sets --- Data sets --- Statistical methods. --- Economic statistics --- Econometrics --- Economics - Statistical methods - Data processing --- Big data --- Machine learning. --- Learning, Machine --- Artificial intelligence --- Machine theory --- E-books --- price indexes, economic statistics, transaction data, consumer spending, machine learning, industrial classification, economics of digitization, Big Data, economic indicators, fixed effects.