BE – Journal Articles: Pre-Prints (Pre-Refereeing Author Versions) – Business and Economicshttp://hdl.handle.net/11129/21982024-03-28T08:32:01Z2024-03-28T08:32:01ZCausal Effects of the United States and Japan on Pacific-Rim Stock Markets: Nonparametric Quantile Causality ApproachBalcılar, MehmetGupta, RanganNguyen, Duc K.Wohar, Mark E.http://hdl.handle.net/11129/20582016-03-07T06:21:25Z2015-12-01T00:00:00ZCausal Effects of the United States and Japan on Pacific-Rim Stock Markets: Nonparametric Quantile Causality Approach
Balcılar, Mehmet; Gupta, Rangan; Nguyen, Duc K.; Wohar, Mark E.
This paper adopts a nonparametric quantile causality approach to examine the causal
effects of the U.S. and Japan stock markets on the stock markets of the Pacific‐Rim
region. This approach allows us to detect not only nonlinear causalities in conditional
return (mean) and conditional volatility (variance), but also the asymmetries of
causalities under extreme market conditions (bullish vs. bearish states). Our results
provide significant evidence of causality in return and volatility at different points of the
conditional distributions of returns, with the greater effects from the U.S. than from
Japan. Asymmetric quantile causality patterns are particularly pronounced in the case
of Japan.
2015-12-01T00:00:00ZComparing the Forecasting Ability of Financial Conditions Indices: The Case of South AfricaMehmet, BalcılarRangan, GuptaRenee van, EydenKirsten, Thompsonhttp://hdl.handle.net/11129/20022016-03-07T06:21:34Z2015-01-01T00:00:00ZComparing the Forecasting Ability of Financial Conditions Indices: The Case of South Africa
Mehmet, Balcılar; Rangan, Gupta; Renee van, Eyden; Kirsten, Thompson
In this paper we test the forecasting ability of three estimated financial conditions indices (FCIs) with respect to key macroeconomic variables of output growth, inflation and interest rates. We do this by forecasting the aforementioned macroeconomic variables based on the information contained in the three
alternative FCIs using a Bayesian VAR (BVAR), nonlinear logistic vector smooth transition auto regression (VSTAR) and non parametric (NP) and semi-parametric (SP) regressions, and compare the results with the standard benchmarks of random-walk, uni variate auto regressive and classical VAR models. The three FCIs are constructed using rolling-window principal component analysis (PCA), dynamic model averaging
(DMA) in the context of a time-varying parameter factor-augmented vector auto regressive (TVP-FAVAR) model, and a time-varying parameter vector auto regressive (TVP-VAR) model with constant factor
loadings. Our results suggest that the VSTAR model performs best in the case of forecasting manufacturing production and inflation, while a SP specification proves to be the best for forecasting the
interest rate. More importantly, statistics testing for significant differences in forecast errors across models corroborate the finding of superior predictive ability of the nonlinear models.
The file in this item is the pre-print version of the article (author’s copy; unrefereed Author’s Version).
2015-01-01T00:00:00ZForecasting South African Macroeconomic Variables with a Markov-Switching Small Open-Economy Dynamic Stochastic General Equilibrium ModelMehmet, BalcılarRangan, GuptaKevin, Kotzehttp://hdl.handle.net/11129/20012016-03-07T06:21:44Z2016-01-01T00:00:00ZForecasting South African Macroeconomic Variables with a Markov-Switching Small Open-Economy Dynamic Stochastic General Equilibrium Model
Mehmet, Balcılar; Rangan, Gupta; Kevin, Kotze
The aim of this paper is to investigate structural changes in the South African economy using an estimated small open-economy dynamic stochastic general equilibrium(DSGE) model. The structure of the model follows recent work in this area and incorporates the expectations of agents and a number of shocks that are assumed to affect the economy at various points in time. In addition, the dynamic linkages between the respective variables in the model may be explained in terms of the micro foundations that characterize the behavior of firms, households and the central bank. After estimating the model, we allow for the parameters in a number of different structural equations to change periodically over time. Different versions of the model are assessed using various statistical criteria to identify the model that is able to explain the changing dynamics in the South African economy. The results suggest that the central bank has responded in a consistent manner over the sample period; however, there are
periods of time where it does not focus too greatly on output pressure. This impacts on some of the impulse response functions where we note that a monetary policy shock has a slightly larger effect on inflation, while the risk-premium shock has a larger effect on output, inflation and interest rates.
The file in this item is the pre-print version of the article (author’s copy; unrefereed Author’s Version).
2016-01-01T00:00:00ZSources of Macroeconomic Fluctuations in MENA CountriesMehmet, BalcılarKemal, Bağzıbağlıhttp://hdl.handle.net/11129/19452016-03-07T06:21:54Z2010-01-01T00:00:00ZSources of Macroeconomic Fluctuations in MENA Countries
Mehmet, Balcılar; Kemal, Bağzıbağlı
A close examination of the MENA region economies reveals a number of
fundamental sources of macroeconomic fluctuations. These include economic factors
such as exchange rate instability, large public debt, current account deficits, and
escalation of inflation. The political factors such as government instability,
corruption, bureaucracy, and internal conflicts also are major sources of
macroeconomic instability. Thus, the sources of macroeconomic fluctuations in these
countries are expected to be inhomogeneous. This paper determines sources of
macroeconomic fluctuations for 16 MENA economies using a structural VAR model.
By imposing long-run restrictions on a VAR model, we identify four structural
shocks: nominal demand, relative demand, supply, the world output, and imported
input price shocks. Overall, the results show some similarities for the source of
macroeconomic fluctuations in these, but also some important differences as well.
We find important differences even among countries with similar macroeconomic
conditions, such as the oil exporters and oil importers. Although, oil prices and world
output are significant sources of macroeconomic fluctuations in oil exporters, in
almost all countries they do not have the highest share. There is one clear common
finding of the paper: For all countries, the long-run sources of output fluctuations are
the real supply and/or real demand shocks. External shocks are secondary for all
countries. The sources of short-run and price fluctuations are inhomogeneous and
dominant variables are mostly determined by country specific factors.
The file in this item is the pre-print version of the article (unrefereed author’s copy).
2010-01-01T00:00:00Z