Nowcasting Gdp

Nowcasting GDP and Inflation

Panel Nowcasting for Countries Whose Quarterly GDPs are Unavailable

Quarterly GDP statistics facilitate timely economic assessment, but the availability of such data are limited for more than 60 developing economies, including about 20 countries in sub-Saharan Africa as well as more than two-thirds of fragile and conflict-affected states. To address this limited data availablity, this paper proposes a panel approach that utilizes a statistical relationship estimated from countries where data are available, to estimate quarterly GDP statistics for countries that do not publish such statistics by leveraging the indicators readily available for many countries. This framework demonstrates potential, especially when applied for similar country groups, and could provide valuable real-time insights into economic conditions supported by empirical evidence.

Nowcasting and Near-Term Forecasting Cambodia’s Economy

Assessing the current state of the economy and forecast the economic outlook in the next few quarters are important inputs for policymakers. This paper presents a suite of models with an integrated approach to forecast Cambodia’s economy in the current and next few quarters. First, we estimate historical quarterly GDP using information extracted from high-frequency indicators to construct quarterly nowcasting model. Second, we forecast current economic activities using a high-frequency data such as credit, export, tourist arrival, foreign reserves, and trading partner’s GDP. Third, we present inflation forecasting models for Cambodia. Fourth, the paper present a vector autoregression model to forecast Cambodia’s GDP in the next few quarters using global forecasts of China’s and US’s economy as well as oil and rice price. This paper showcase how high-frequency data set can be utilized in assessing current economic activities in countries with limited and lagged data.