Predicting Poverty Rates with Consumer Survey Results: A MIDAS Approach

Consumer surveys (CSs) conducted in accordance with The Joint Harmonized European Union Program of Business and Consumer Surveys produce very useful data for economic modeling and forecasting, especially within the area of macroeconomic and financial applications. One part of the application is the investigation of poverty levels and social problems. Therefore, the purpose of this chapter is to examine if the monthly data available from CS can be used to forecast future poverty rates of a country. This research utilizes the mixed sampling (MIDAS) regression approach of modeling and forecasting the yearly poverty rates of a country by using monthly data on the financial situation from the CS data. Results of the analysis show that the potential of using such an approach exists. This means that policymakers of emerging markets could use the MIDAS regression to forecast future poverty rates so that timely decisions and moves can be made, which will reduce costs and achieve the country’s goals of better and faster development.