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This study aims to investigate the amount and direction of economic policy uncertainty (EPU) spillover among six emerging market economies (EMEs), and to also ascertain arguments on the increased volatilities of uncertainty in most EMEs.

This study adopts a recent methodology developed by Baruník and Krehlík’s (2018) methodology to measure pairwise, composite and net spillover. This methodology helps investigate the size and direction of EPU spillover in EMEs. The unique feature of this methodology is its ability to capture frequency domain as well as time-frequency dynamics.

Inter-country static spillover connectedness among the EPU of the selected EMEs show that Korea-EPU is the main transmitter and recipient of spillover shocks among the EMEs across all frequency bands. The findings from this study also show evidence of spillover between EPU, GDP and SPX across the EMEs. The time-varying total spillover index analysis shows evidence of overall connectedness across the selected EMEs. Overall connectedness is highest in the short term. We document that global economic and financial events intensify the volatility of the total spillover across the selected EMEs.

This study extends the literature on studies conducted on EMEs as studies on EPU spillover has mainly focused on advanced economies. To address the limitation of previous empirical studies that were unable to address the amount and direction of spillover from a country to other countries, this study offers new insight on country-specific spillover amounts and causal patterns “to” and “from” the selected EMEs. The findings throw more light on the network connectedness across EMEs and hence aids investors to undertake precise investment decisions and intelligently plan their portfolio diversification strategies. We then introduce two new variables to the analysis and record evidence of high connectedness between EPU, gross domestic product and share price index in all the frequency bands.

The purpose of this paper is to investigate the interdependence between economic policy uncertainty (EPU) and business cycles within and among six emerging market economies (EMEs) from January 1999 to December 2018.

This study adopts the wavelet multiple correlations and wavelet multiple cross-correlation (WMCC) based on the maximal overlap discrete transform estimator. This methodology simultaneously investigates how two or more time series variables move together continuously at both time and frequency domains.

The empirical results show that business cycles comove with EPU for both intra- and inter-country analysis, with the long term showing the greatest degree of interdependence. In intra-country comparisons, EPU has a positive correlation with consumer price index and a negative correlation with share price index. According to the WMCC results, EPU does not have any leading or lagging power within each EME, but rather import has both lead and lag power. The inter-country WMCC results are all significant, with Korea’s EPU leading/following all EMEs across all scales.

This study contributes to the ongoing debate about what causes business cycles to comove by investigating business cycle indicators (leader/follower) using a robust wavelet methodology. The authors propose new variables that can clearly reflect the outcome of economic policy actions and translate information about EPU shocks. The inclusion of the variables has altered the understanding of the relationship between EPU and business cycle fluctuations. Policymakers also gain new insights into the trends and patterns of EPU and business cycles, which will help them formulate and implement fiscal and monetary policies more effectively.