Person:
Maloney, William

Office of the Chief Economist Latin America and the Caribbean Region
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Innovation, Labor Economics, Trade, Productivity, Private Sector Development, Financial Sector, Spatial economics
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Office of the Chief Economist Latin America and the Caribbean Region
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Last updated: October 9, 2024
Biography
William F. Maloney is Chief Economist for the Latin America and Caribbean (LAC) region. Mr. Maloney, a U.S. national, joined the Bank in 1998 as Senior Economist for the Latin America and Caribbean Region. He held various positions including Lead Economist in the Office of the Chief Economist for Latin America, Lead Economist in the Development Economics Research Group, Chief Economist for Trade and Competitiveness and Global Lead on Innovation and Productivity. He was most recently Chief Economist for Equitable Growth, Finance and Institutions (EFI) Vice Presidency. From 2011 to 2014 he was Visiting Professor at the University of the Andes and worked closely with the Colombian government on innovation and firm upgrading issues. Mr. Maloney received his PhD in Economics from the University of California Berkeley (1990), his BA from Harvard University (1981), and studied at the University of the Andes in Bogota, Colombia (1982-83). His research activities and publications have focused on issues related to international trade and finance, developing country labor markets, and innovation and growth, including several flagship publications about Latin America and the Caribbean.He has published in academic journals on issues related to international trade and finance, developing country labor markets, and innovation and growth as well as several flagship publications of the Latin American division of the Bank, including Informality: Exit and Exclusion;  Natural Resources: Neither Curse nor Destiny and Lessons from NAFTA, Does What you Export Matter: In Search of Empirical Guidance for Industrial Policy. Most recently, he published The innovation paradox: Developing Country Capabilities the Unrealized Potential of Technological Catch-Up and Harvesting Prosperity: Technology and Productivity Growth in Agriculture as part of the World Bank Productivity Project.  
Citations 202 Scopus

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  • Publication
    Heterogeneity in Subjective Wellbeing : An Application to Occupational Allocation in Africa
    (World Bank, Washington, DC, 2012-10) Falco, Paolo; Maloney, William F.; Rijkers, Bob; Sarrias, Mauricio
    Using an extraordinarily rich panel dataset from Ghana, this paper explores the nature of self-employment and informality in developing countries through the analysis of self-reported happiness with work and life. Subjective job satisfaction measures allow assessment of the relative desirability of different jobs in ways that, conditional wage comparisons cannot. By exploiting recent advances in mixed (random parameter) ordered probit models, the distribution of subjective well-being across sectors of employment is quantified. There is little evidence for the overall inferiority of the small firm informal sector: there is not a robust average satisfaction premium for formal work vs. self-employment or informal salaried work, and owners of informal firms that employ others are on average significantly happier than workers in the formal private sector. Moreover, the estimated distribution of parameters predicting satisfaction reveal substantial heterogeneity in subjective well-being within sectors that conventional fixed parameter models, such as standard ordered probit models, cannot detect: Whatever the average satisfaction premium in a sector, all job categories contain both relatively happy and disgruntled workers. Specifically, roughly 67, 50, 40 and 59 percent prefer being a small-firm employer, sole proprietor, informal salaried, civic worker respectively, than formal work. Hence, there is a high degree of overlap in the distribution of satisfaction across sectors. The results are robust to the inclusion of fixed effects and alternate measures of satisfaction. Job characteristics, self-perceived autonomy and experimentally elicited measures of attitudes toward risk do not appear to explain these distributional patterns.