In an environment in which growth and employment prospects in many countries remain subdued and a number of high-profile corruption cases have fueled moral outrage, and amid a growing consensus that corruption can seriously undermine a country’s ability to deliver inclusive economic growth in a number of different areas, addressing corruption globally—in both developed and developing countries—has become increasingly urgent. When corruption impairs government functions, it can adversely affect a number of important determinants of economic performance, including macrofinancial stability, investment, human capital accumulation, and total factor productivity. Moreover, when systemic corruption affects virtually all state functions, distrust of government can become so pervasive that it can lead to violence, civil strife, and conflict, with devastating social and economic implications. This Staff Discussion Note focuses on corruption that arises from the abuse of public office for private gain, whether it manifests itself transactionally (for example, a bribe) or through powerful networks between business and government that effectively result in the privatization of public policy. While designing and implementing an anticorruption strategy requires change on many different levels, the IMF's experience in assisting member countries suggests that several elements need to be given priority: transparency, rule of law, and economic reform policies designed to eliminate excessive regulation. Perhaps most important, however, addressing corruption requires building effective institutions, with the clear objective of developing a competent civil service that takes pride in being independent of both private influence and public interference.

Utilizando datos individualmente sobre la composición de tareas en el trabajo para 30 economías avanzadas y emergentes, encontramos que las mujeres, en promedio, realizan tareas más rutinarias que los hombres, tareas que son más propensas a la automatización. Para cuantificar el impacto en los trabajos, se relacionaron los datos sobre la composición de las tareas en el trabajo con las estimaciones de nivel de ocupación y la probabilidad de automatización, controlando un conjunto de características individuales (por ejemplo, educación, edad, alfabetización y habilidades de cálculo). Los resultados indican que las trabajadoras tienen un riesgo significativamente mayor de desplazamiento por automatización que los trabajadores masculinos, con un 11 % de la fuerza laboral femenina en alto riesgo de ser automatizadas dado el estado actual de la tecnología, aunque con una heterogeneidad significativa entre países. La probabilidad de automatización es menor para las cohortes de mujeres más jóvenes y para aquellas en puestos gerenciales.