ORCID Profile
0000-0002-7297-1557
Current Organisation
Deakin University
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Publisher: Elsevier BV
Date: 2010
Publisher: Elsevier BV
Date: 06-2014
Publisher: Elsevier BV
Date: 02-2019
Publisher: Elsevier BV
Date: 12-2011
Publisher: Elsevier BV
Date: 03-2020
Publisher: Elsevier BV
Date: 09-2019
Publisher: Elsevier BV
Date: 08-2009
Publisher: Elsevier BV
Date: 12-2018
Publisher: Elsevier BV
Date: 09-2019
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 10-2021
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 11-2014
Publisher: Elsevier BV
Date: 2020
Publisher: Wiley
Date: 06-01-2019
DOI: 10.1111/FIRE.12171
Publisher: Elsevier BV
Date: 11-2010
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 12-2016
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 2014
Publisher: Informa UK Limited
Date: 25-07-2020
Publisher: Elsevier BV
Date: 05-2015
Publisher: Informa UK Limited
Date: 25-08-2015
Publisher: Elsevier BV
Date: 2016
Publisher: Elsevier BV
Date: 04-2014
Publisher: Elsevier BV
Date: 03-2014
Publisher: Elsevier BV
Date: 07-2015
Publisher: Elsevier BV
Date: 07-2015
Publisher: Bank Indonesia, Central Banking Research Department - Digital Commons
Date: 28-02-2019
Abstract: Using monthly time-series data and both short- and long-run models, our paper examines the determinants of Indonesia’s income velocity of money. Our findings strongly suggest that in the long-run, tax revenue, short-term interest rates, and industrial production, and in the short-run, money demand significantly determines income velocity of money. Our analysis suggests that the effect on income velocity is mostly over the long-run as most determinants are dormant in the short-run. The implication from a policy perspective is that shocks that are transitory are unlikely to burden income velocity.
Publisher: Elsevier BV
Date: 09-2016
Publisher: Elsevier BV
Date: 07-2018
Publisher: Elsevier BV
Date: 07-2013
Publisher: World Scientific Pub Co Pte Lt
Date: 06-2015
DOI: 10.1142/S0219091515500095
Abstract: In this paper, we examine the evidence of herding behavior on the Chinese stock market. Our main findings are as follows. First, we find strong evidence of herding behavior on both the Shanghai and Shenzhen stock exchanges. Second, we document evidence of asymmetric herding behavior with greater magnitude of herding behavior on up markets than on down markets. Third, our findings suggest that herding behavior is sector-specific and predominant in the industrial and properties sectors. Finally, we unravel strong evidence suggesting that herding behavior is time-varying and in some sectors time-varying herding behavior is more prevalent than in other sectors.
Publisher: Elsevier BV
Date: 06-2015
Publisher: Elsevier BV
Date: 2011
Publisher: Informa UK Limited
Date: 07-12-2020
Publisher: Elsevier BV
Date: 10-2013
Publisher: Elsevier BV
Date: 06-2021
Publisher: Informa UK Limited
Date: 03-05-2021
Publisher: Informa UK Limited
Date: 11-06-2012
Publisher: Elsevier BV
Date: 11-2015
Publisher: Elsevier BV
Date: 12-2017
Publisher: Elsevier BV
Date: 10-2013
Publisher: Elsevier BV
Date: 02-2014
Publisher: Elsevier BV
Date: 06-2009
Publisher: Elsevier BV
Date: 2015
Publisher: Elsevier BV
Date: 12-2021
Publisher: Bank Indonesia, Central Banking Research Department - Digital Commons
Date: 30-04-2019
Abstract: We use an exhaustive list of Indonesia’s macroeconomic variables in a comparative analysis to determine which predictor variables are most important in forecasting Indonesia’s inflation rate. We use monthly time-series data for 30 macroeconomic variables. Using both in-s le and out-of-s le predictability evaluations, we report consistent evidence of inflation rate predictability using 11 out of 30 macroeconomic variables.
Publisher: Elsevier BV
Date: 2021
Publisher: Elsevier BV
Date: 12-2019
Publisher: Elsevier BV
Date: 03-2016
Publisher: Elsevier BV
Date: 10-2013
Publisher: Bank Indonesia, Central Banking Research Department - Digital Commons
Date: 10-09-2020
Abstract: This study examines the predictability of Indonesia’s aggregate demand using palm oil price. We conduct both in-s le and out-of-s le forecasting evaluations. These evaluations are based on time-series quarterly and monthly data frequencies and cover three different forecasting horizons. Overall, we find that palm oil price predicts real GDP, consumption expenditure, total investment, net spending from overseas, while predictability of government spending is sensitive to the use of forecasting approaches and horizons.
Publisher: Elsevier BV
Date: 05-2018
Publisher: Elsevier BV
Date: 11-2019
Publisher: Elsevier BV
Date: 06-2016
Publisher: Elsevier BV
Date: 11-2019
No related grants have been discovered for Susan Sharma.