Nowcasting Economic Activity Using Electricity Market Data: The Case of Lithuania

Traditional forecasting methods usually rely on historical macroeconomic indicators with significant delays. To address this problem, new opportunities for economic modeling and forecasting are emerging by using real-time data and making nowcasting of economic activity. This research aims to assess the usefulness of electricity market data to nowcast the economic activity in Lithuania. Various MIDAS regression models are used to nowcast nine monthly macroeconomic indicators. In general, electricity market indicators are useful to nowcast certain macroeconomic indicators. Electricity consumption is the most useful among electricity market indicators and brings benefits when nowcasting imports, industrial production, consumer confidence, wholesale and retail trade, and the repair of motor vehicles and motorcycles. Electricity production is beneficial in nowcasting the industrial production. Meanwhile, electricity price is useful for nowcasting exports, exports of goods of Lithuanian origin, imports, and industrial production. Meanwhile, electricity market data do not improve the prediction of the unemployment rate, economic sentiment indicator, and CPI-based consumer price in comparison with an autoregressive model.