This paper provides an outlook for the Indian economy in the light of the extraordinary global financial crisis, that started in the US, but which has now transformed into the worst economic downturn since the Great Depression. The Indian economy was slowing down even before the onset of global...

Despite signs of recovery from the global financial crisis, the GDP growth rate for the Indian economy is likely to be between 5.8 to 6.1 per cent in 2009-10, below the 6.7 per cent recorded in fiscal 2008-09. While there has been an improvement in Indian industry, particularly the manufacturing...

This empirical work aims to determine whether the government expenditure shocks on consumption have impacts on macroeconomic factors. This study prepares four quarterly period datasets associated with macroeconomic activities in Indonesia with 24 data started in 2017 until 2022, such as...

Following Giraitis, Kapetanios, and Yates (2014b), this paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the data set constructed by Smets and Wouters (2007). We apply an indirect inference method to map from this TV VAR to time...

In this paper we propose to use the common trends of the Mexican economy in order to predict economic activity one and two steps ahead. We exploit the cointegration properties of the macroeconomic time series, such that, when the series are I(1) and cointegrated, there is a factor...

Structural vector autoregressive analysis aims to trace the contemporaneous linkages among (macroeconomic) variables back to underlying orthogonal structural shocks. In homoskedastic Gaussian models the identification of these linkages deserves external and typically notdata-based information....

Structural vector autoregressive analysis aims to trace the contemporaneous linkages among (macroeconomic) variables back to underlying orthogonal structural shocks. In homoskedastic Gaussian models the identification of these linkages deserves external and typically notdata-based information....

In this paper, we propose a new method to forecast macroeconomic variables that combines two existing approaches to mixed-frequency data in DSGE models. The first existing approach estimates the DSGE model in a quarterly frequency and uses higher frequency auxiliary data only for forecasting...

In high-dimensional vector autoregressive (VAR) models, it is natural to have large number of predictors relative to the number of observations, and a lack of efficiency in estimation and forecasting. In this context, model selection is a difficult issue and standard procedures may often be...