2016, Volume 69 - Issue 1
RSS feed citation: at CitEc
Publication date: 23 February 2016
EFFECT OF RECENT U.S. MONETARY POLICY ON THE BALANCE OF TRADE.Read the article
CAN DEBT CEILING AND GOVERNMENT SHUTDOWN PREDICT US REAL STOCK RETURNS? A BOOSTRAP ROLLING WINDOW APPROACHRead the article
CHARACTERISING THE SOUTH AFRICA BUSINESS CYCLE: IS GDP DIFFERENCE-STATIONARY OR TREND-STATIONARY IN A MARKOV-SWITCHING SETUP?Read the article
Goodness C. AYE, Department of Economics, University of Pretoria, Pretoria, 0002, South Africa
Mehmet BALCILAR, Department of Economics, Eastern Mediterranean University, Famagusta, Turkish Republic of Northern Cyprus
Ghassen EL MONTASSER, Ecole supérieure de commerce de Tunis, University of Manouba, Tunisia
Rangan GUPTA, Corresponding author. Department of Economics, University of Pretoria, Pretoria, 0002, South Africa. Email: firstname.lastname@example.org
Nangamso C. MANJEZI, Department of Economics, University of Pretoria, Pretoria, 0002, South Africa
This paper investigates the in-sample predictability of debt ceiling and government shutdown for real stock returns in the U.S, using rolling window Granger non-causality estimation. Causal links often evolve over time so the use of the bootstrap rolling window approach will account for potential time variations in the relationships. We use monthly time series data on measures of debt ceiling and government shutdown, and real stock returns, covering the period of 1985:M2 to 2013:M9. Since the debt ceiling and government shutdown variables under analysis are exogenous, the use of the in-sample predictability to analyse the relation-ship running from debt ceiling to real stock returns, as well as, from government shutdown to real stock returns will provide evidence of not only whether in-sample predictability exists, but also how predictability varies over time i.e. significance in episodes of high values of index. The full sample bootstrap non-Granger causality test results suggest existence of no in-sample predictability of debt ceiling or government shutdown for real stock returns in the U.S. economy. The stability tests show evidence of parameter instability in the estimated equations. Therefore, we make use of the bootstrap rolling window (24 months) approach to investigate the changes in the in-sample predictability of the relationship, and detect signifi-cant in-sample predictability of debt ceiling and government shutdown for real stock returns at different sub-periods, corresponding especially after the phases where there were sharp increases in the indexes of debt ceiling and government shutdown.
Debt Ceiling, Government Shutdown, Real Stock Returns, Rolling Window, Bootstrap
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