Is It Possible to Discriminate between Different Switching Regressions Models: an Empirical Investigation?
نویسندگان
چکیده
In this paper we study, using the sup LR test, the possibility of discrimination between two classes of models: the Markov switching models of Hamilton (1989) and the Threshold Auto-Regressive Models (TAR) of Lim and Tong (1980). This work is motivated by the fact that generally practicians use, in applications, switching models without any statistical justi cation. Using experiment simulations, we show that it is very di cult to discriminate between the MSAR and the SETAR models specially using large samples. This means that when the null hypothesis is rejected, it appears that di erent switching models are signi cant. Moreover, the results show that the power of the sup LR test is sensitive to the mean, the noise variance and the delay parameter. Finally, we apply this methodology to two time series: the US GNP growth rate and the US/UK exchange rate. We shall retain a Markov switching process for the US GNP growth rate and the US/UK exchange rate (monthly data). For the US/UK exchange rate (quarterly data), we accept the null hypothesis of a random walk. JEL classi cation: C12;C15;F31
منابع مشابه
Investigation and Statistical comparison of the soil empirical desalinization models for salin-sodic soils (Case study: Khuzestan province)
Accumulation of soluble salts in arid areas which are similar to most regions of Iran is inevitable in soil surface and profile because of low precipitation and high evaporation. High concentration of soluble salts in soil profile caused severe problems for root water uptake thus plant growth stopped. Reducing soil salinity to optimized content by leaching and avoiding soil pounding must be con...
متن کاملSpatial analysis of annual precipitation of Khuzestan province; An approach of spatial regressions analysis
Knowing of precipitation values in different regions is always of main and strategic issues of human which has important role in short- term and long-term decisions. In order to determine of precipitation model and forecasting it, there are different models, but given that the precipitation data have a spatial autocorrelation, the spatial statistic is a powerful tool to recognition of spatial b...
متن کاملDays- of- Week Effect on Tehran Stok Exchange Returns: An Empirical Analysis
The purpose of this study is to concentrate on the investigation of days-of-week effect on Tehran Stock Exchange and its comparison with other emerging markets. Using Classical Linear Regression (CLR) as well as Autoregressive Conditional Heteroskedasticity (ARCH) models it in indicated has indicated that there is significantly positive total return on Saturdays and significantly negative total...
متن کاملDating Business Cycle in Oil Exporting Countries
In this paper, we empirically investigate the relationship between oil price changes and output in a group of oil exporting countries. The dynamics of business cycles in Libya, Saudi Arabia, Nigeria, Kuwait, Venezuela and Qatar are modeled by alternative regime switching models. We show that the extension of uni-variate Markov Switching model in order to include oil revenue improves dating busi...
متن کاملEstimating Stock Price in Energy Market Including Oil, Gas, and Coal: The Comparison of Linear and Non-Linear Two-State Markov Regime Switching Models
A common method to study the dynamic behavior of macroeconomic variables is using linear time series models; however, they are unable to explain nonlinear behavior of the series. Given the dependency between stock market and derivatives, the behavior of the underlying asset price can be modeled using Markov switching process properties and the economic regime significance. In this paper, a two-...
متن کامل