The determinants of demand for tourism in Turkey: Does terror-threat matter? A Markov Regime Switching-VAR approach

2021 ◽  
Vol 71 (4) ◽  
pp. 587-607
Keyword(s):  
Exchange Rates ◽  
Regime Switching ◽  
Negative Impact ◽  
Income Level ◽  
Var Models ◽  
Short Term ◽  
Markov Regime Switching ◽  
Monthly Data ◽  
Vector Auto Regression ◽  
Auto Regression

Abstract This paper investigates the impacts of potential determinants of demand for tourism in Turkey through Markov Regime Switching-Vector Auto Regression (MS-VAR) estimations from 1999 to 2017 on monthly data. The determinants are income level, exchange rates and the threat of terror incidences. The terror variable, following the Global Terrorism Index (GTI) 2017 report, is calculated for Turkey by the author. This research has conducted two separate MS-VAR models to observe the relevant parameters’ signs of the demand for tourism function. Both MS-VAR models revealed that income level and exchange rates have positive influences on tourism while the terror threat has a negative impact on tourism in Turkey. Terror adversely affects the demand for tourism in the short-term in which terror has occurred in the nearest past (i.e., a month ago). The MS-VAR models also yield that a similar negative impact of terror on tourism activities does not appear over the longer periods.

scholarly journals World Oil Prices and Indonesia Macroeconomic

2015 ◽  
Vol 15 (1) ◽  
pp. 27
Author(s):  
M. Ichsandimas W. ◽  
Malik Cahyadin
Keyword(s):  
Exchange Rates ◽  
Real Exchange Rates ◽  
Impulse Response Function ◽  
Variance Decomposition ◽  
Oil Price ◽  
Positive Relation ◽  
Real Gdp ◽  
Vector Auto Regression ◽  
The Impact ◽  
Auto Regression

The goal of this study is to look at the relation and contribution value, while the impact of world oil price on the macroeconomic Indonesian form 1980 to 2010. This Study used Vector Auto Regression (VAR) method and tool of VAR used are Impulse Response Function (IRF) and Variance Decomposition. The results of study finds a positive relation and statistically significant impact of world oil price on inflation and real GDP Indonesian, but not significant and negative relation on real exchange rates. World oil price has contribution value on the inflation, real exchange rates, Indonesia real GDP after first period.

scholarly journals A Markov Regime Switching Model for Ultra-Short-Term Wind Power Prediction Based on Toeplitz Inverse Covariance Clustering

2021 ◽  
Vol 9 ◽  
Author(s):  
Hang Fan ◽  
Xuemin Zhang ◽  
Shengwei Mei ◽  
Junzi Zhang
Keyword(s):  
Time Series ◽  
Prediction Model ◽  
Wind Power ◽  
Regime Switching ◽  
Wind Farms ◽  
Power Prediction ◽  
Short Term ◽  
Markov Regime Switching ◽  
Switching Model ◽  
Switching Method

The rapid development of wind energy has brought a lot of uncertainty to the power system. The accurate ultra-short-term wind power prediction is the key issue to ensure the stable and economical operation of the power system. It is also the foundation of the intraday and real-time electricity market. However, most researches use one prediction model for all the scenarios which cannot take the time-variant and non-stationary property of wind power time series into consideration. In this paper, a Markov regime switching method is proposed to predict the ultra-short-term wind power of multiple wind farms. In the regime switching model, the time series is divided into several regimes that represent different hidden patterns and one specific prediction model can be designed for each regime. The Toeplitz inverse covariance clustering (TICC) is utilized to divide the wind power time series into several hidden regimes and each regime describes one special spatiotemporal relationship among wind farms. To represent the operation state of the wind farms, a graph autoencoder neural network is designed to transform the high-dimensional measurement variable into a low-dimensional space which is more appropriate for the TICC method. The spatiotemporal pattern evolution of wind power time series can be described in the regime switching process. Markov chain Monte Carlo (MCMC) is used to generate the time series of several possible regime numbers. The Kullback-Leibler (KL) divergence criterion is used to determine the optimal number. Then, the spatiotemporal graph convolutional network is adopted to predict the wind power for each regime. Finally, our Markov regime switching method based on TICC is compared with the classical one-state prediction model and other Markov regime switching models. Tests on wind farms located in Northeast China verified the effectiveness of the proposed method.

scholarly journals CAPITAL MARKET DEVELOPMENT AND ECONOMIC GROWTH IN NIGERIA

2021 ◽  
pp. 16-38
Keyword(s):  
Financial Development ◽  
Capital Market ◽  
Wald Test ◽  
Market Development ◽  
Var Models ◽  
Market Capitalization ◽  
Augmented Dickey Fuller ◽  
Vector Auto Regression ◽  
Stationarity Tests ◽  
Auto Regression

The motivation behind this study is to experimentally look at the connection between capital market improvement and monetary development in Nigeria. The examination investigated the Central Bank of Nigeria quarterly information from 1981Q1 to 2017Q4 with the E-sees programming bundle (variant 9.0). The Vector Auto Regression (VAR) procedure was utilized to investigate the information, while theory testing depended on the Block Exogeneity Wald test. The predetermined models included stationarity tests, diminished structure VAR gauge, and primary examination. The Augmented Dickey-Fuller Test demonstrates that the examination factors are fixed at first contrast or I(1). The VAR establishes plot corresponding to unit circle demonstrates that our predetermined diminished structure VAR models are steady. The Lagrange Multiplier (LM) symptomatic tests demonstrate that our predetermined VAR models are effectively indicated. The p-esteem shows that market capitalization proportion is critical in clarifying varieties in financial development (p = 0.0205). Notwithstanding, the worth of stock proportion and banking framework capitalization proportion is not huge in deciding the Real Gross Domestic Product in Nigeria. All in all, capital market advancement in Nigeria is worked with by vigorous market capitalization. Nonetheless, it is restricted by diminishing volume of stock and lessening banking framework capitalization. It is suggested that the monetary area ought to take on forceful capital market drives and vigorous monetary development approaches to support financial development in an arising economy.

scholarly journals Research on Performance and Valuation of Enterprises Placarded by Others Based on the Improved Panel Vector Auto-Regression Model

2018 ◽  
Vol 5 (3) ◽  
pp. 34
Author(s):  
Na Luo
Keyword(s):  
Impulse Response Function ◽  
Stable State ◽  
Point Of View ◽  
Secondary Market ◽  
Short Term ◽  
Dummy Variable ◽  
Long Run ◽  
Vector Auto Regression ◽  
Good Signal ◽  
Auto Regression

In recent years, enterprises, which were placarded, have become a heated issue in the secondary market in China. However, there still lack researches about the performance and valuation of those enterprises which were placarded. Therefore, it seems that it is lack of persuasion to use the word “barbarians” to define the enterprises which carry out placard. For the reasons above, this paper makes the use of the improved PVAR model to give an empirical analysis on the performance and valuation of the enterprises placarded, based on the samples between 2011 and 2015. First, this paper divides the whole samples into two subsample groups by the dummy variable, according to the certain point of time whether the enterprise has been placarded. After that, it build two PVAR models combining the performance indicators and the valuation indicators. The results show that the sensitivity of the target enterprise’s performance is not as good as its valuation. Second, the two subsample groups are analyzed by the impulse response function. It explains that placard creates an incentive effect for the target enterprise in the short term. Third, by using the variance decomposition, this paper achieves a conclusion that placard reduces the dependence of the target enterprise on the aspects of its valuation, profitability, size and risk. Therefore, placard is a good signal for those target enterprises on the whole, which brings a nice momentum for the enterprises on the valuation, profitability, size and risk in the short term. In the long run, the enterprises will adjust to a stable state based on the short-term changes. From this point of view, “barbarians at the gate” bring the motivation rather than chaos.

scholarly journals The Impact of the US Dollar and the Euro on Currencies in Europe and Asia

2013 ◽  
Author(s):  
Malgorzata Doman ◽  
Ryszard Doman
Keyword(s):  
Exchange Rates ◽  
Regime Switching ◽  
Tail Dependence ◽  
Markov Regime Switching ◽  
Copula Models ◽  
Opposite Case ◽  
The Us ◽  
Us Dollar ◽  
Area Of Influence ◽  
The Impact

In this paper, we analyze dependencies between the currencies of chosen emerging countries and the major (global) currencies – the euro and the American dollar. The idea is taken from a paper by Eun and Lai proposing a method to verify an opinion that currencies systematically co-move and the pattern of co-movement is significantly driven by the relative influence of the two global currencies. The observation by Eun and Lai is that in the case when a minor currency XYZ is driven by the US dollar, the exchange rates XYZ/EUR and USD/EUR co-move very closely. In the opposite case, i.e. when the XYZ is influenced by the euro, the exchange rates XYZ/USD and EUR/USD show strong interdependence. In our approach, the dynamics of dependencies is modeled by means of 3-regime Markov regime switching copula models, and the considered measures of the strength of the linkages are dynamic Spearman’s rho and tail dependence coefficients. Applying the Markov regime switching copula models allows us to capture temporal changes in the impact of the global currencies on the analyzed minor ones. Our results show that the euro area of influence is widening, and that during the considered period some of the analyzed currencies are releasing from the US dollar impact.

scholarly journals Macroeconomic Policies Interaction & the Symmetry of Financial Markets’ Responses

2016 ◽  
Vol 5 (1) ◽  
pp. 53-69 ◽  
Author(s):  
Muhammad Ali Nasir ◽  
Alaa M. Soliman ◽  
Milton Yago ◽  
Junjie Wu
Keyword(s):  
Financial Markets ◽  
Sovereign Debt ◽  
Macroeconomic Policy ◽  
Var Model ◽  
Macroeconomic Policies ◽  
Monthly Data ◽  
Policy Interaction ◽  
The United Kingdom ◽  
Vector Auto Regression ◽  
Auto Regression

Abstract This concise study analyses the symmetry of financial markets’ responses to macroeconomic policy interaction in the United Kingdom. Employing the Vector Auto-regression (VAR) model on monthly data of the British financial sector and macroeconomic policies from January 1985 to August 2008, this study found that the equity and sovereign debt markets showed identical symmetry in response to macroeconomic policy interaction.

The effect of international energy market shocks on coal price of China based on the fuzzy integrated vector auto regressive and error correction model

2021 ◽  
Vol 40 (4) ◽  
pp. 8451-8461
Author(s):  
Ruyi Shi ◽  
Di Wang ◽  
Yueying Zhao
Keyword(s):  
Var Model ◽  
Energy Market ◽  
Short Term ◽  
Coal Price ◽  
Coal Market ◽  
Term Basis ◽  
Vector Auto Regression ◽  
Market Shocks ◽  
Auto Regression

From the perspective of external market shocks, this paper proposed fuzzy integrated vector auto regression (FVAR) model that determines the long-term basis and short-term basis interactions of China’s coal price with international energy prices. The proposed FVAR preform coal price fluctuation based on long-term and short term span in six stages including unit root testing, Johansen cointegration test, vector auto regression (VAR) model construction, fuzzification of VAR model, vector error correction (VEC) model and an impulse response function(IRF). It is observed that there is a steady long-term stability and equilibrium bond between the China’s domestic coal price, international coal price and the international crude (unrefined) oil price. The international coal and international crude oil price have an opposite effect on China’s domestic coal price. In addition, the former has a stronger fuzzy price discovery function on China’s domestic coal market than the latter. In the short term, China’s domestic coal price is more complex to instability reactions and is affected by market expectations. The international energy market is more effective than domestic coal market, and there is a relatively stable price adjustment mechanism between the two, with the international coal price playing a leading role in the fuzzy guidance of China’s coal price. Therefore, in reference to international energy pricing models, the paper proposes a fuzzy pricing model for a coal futures index based on the coal futures trading price and supplemented by the premium and discount agreed to by both trading parties.

Alternative Models for Forecasting Macroeconomic Indicators in Kazakhstan

2017 ◽  
Vol 4 (1) ◽  
pp. 1-15
Author(s):  
Saken Pirmakhanov
Keyword(s):  
Time Series ◽  
Regression Model ◽  
Regression Models ◽  
Error Prediction ◽  
Optimal Model ◽  
Short Term ◽  
Macroeconomic Indicators ◽  
Vector Auto Regression ◽  
In Virtue Of ◽  
Auto Regression

This paper indicates special aspects of using vector auto-regression models to forecast rates of basic macroeconomic indicators in short term. In particular, traditional vector auto-regression model, Bayesian vector auto-regression model and factor augmented vector auto-regression model are shown. For parameter estimation of these models the author uses time series of Kazakhstani macroeconomic indicators between 1996 and 2015 quarterly. In virtue of mean-root-square error prediction the conclusion of optimal model is going to be chosen.

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