5 min. read. Machine Learning techniques are proving to be a practical method to generate data. These techniques are being increasingly used by data generation and research teams,offering quicker and less expensive alternatives to traditional data collection and processing methods. They are also a great tool to complement official estimates for key socioeconomic indicators, … [Read more...] about Machine learning, a key tool to inform future policy in Haiti
Laura Giles Álvarez
Laura Giles Álvarez is the Country Economist at the Inter-American Development Bank (IDB) in Colombia, having previously worked as a Country Economist in Haiti, Barbados, and The Bahamas. Laura started her career at the IDB as a young professional in the Social Protection and Health Division and the Economics Team at the Caribbean Country Department. Before joining the IDB, Laura worked as a public financial management consultant, where she designed and executed projects on macro-fiscal policy, expenditure management, and the budget cycle in Kenya, Mozambique, Timor Leste, and Angola. Additionally, she served as an ODI Fellow in the fiscal team within the Macroeconomic Policy Department at the Ministry of Finance in Timor Leste. Laura holds a double master's degree in economic development from the University of Carlos III, Madrid, and Lund University.