97 resultados para Panel Cointegration Test


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This article proposes Lagrange multiplier-based tests for the null hypothesis of no cointegration. The tests are general enough to allow for heteroskedastic and serially correlated errors, deterministic trends, and a structural break of unknown timing in both the intercept and slope. The limiting distributions of the test statistics are derived, and are found to be invariant not only with respect to the trend and structural break, but also with respect to the regressors. A small Monte Carlo study is also conducted to investigate the small-sample properties of the tests. The results reveal that the tests have small size distortions and good power relative to other tests. © 2007 The Authors Journal compilation 2007 Blackwell Publishing Ltd.

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The ripple effect of house prices within metropolitan areas has recently been recognised by researchers. However, it is very difficult to formulate and measure this effect using conventional house price theories particularly in consideration of the spatial locations of cities. Based on econometrics principles of the cointegration test and the error correction model, this research develops an innovative approach to quantitatively examine the diffusion patterns of house prices in mega-cities of a country. Taking Australia's eight capital cities as an example, the proposed approach is validated in terms of an empirical study. The results show that a 1-1-2-4 diffusion pattern exists within these cities. Sydney is on the top tier with Melbourne in the second; Perth and Adelaide are in the third level and the other four cities lie on the bottom. This research may be applied to predict the regional housing market behavior in a country.

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The ripple effect of house prices within metropolitan areas has recently been recognised by researchers. However, it is very difficult to formulate and measure this effect using conventional house price theories particularly in consideration of the spatial locations of cities. Based on econometrics principles of the cointegration test and the error correction model, this research develops an innovative approach to quantitatively examine the diffusion patterns of house prices in mega-cities of a country. Taking Australia's eight capital cities as an example, the proposed approach is validated in terms of an empirical study. The results show that a 1-1-2-4 diffusion pattern exists within these cities. Sydney is on the top tier with Melbourne in the second; Perth and Adelaide are in the third level and the other four cities lie on the bottom. This research may be applied to predict the regional housing market behavior in a country.

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Testing the integrational properties of visitor arrivals has important implications for policy, for if visitor arrivals are integrated of order one (nonstationary) then it implies that shocks to visitor arrivals are permanent. However, if visitor arrivals are found to be integrated or order zero (stationary) then this implies that shocks to visitor arrivals are temporary. In this paper we examine whether visitor arrivals to Australia are stationary or nonstationary, using the recently developed univariate and panel Lagrange multiplier tests, and the Im, Pesaran and Shin [Im, K.S., Pesaran, M.H., Shin, Y., 1997. Testing for Unit Roots in Heterogeneous Panels. Manuscript, Department of Applied Economics, University of Cambridge; Im, K.S., Pesaran, M.H., Shin, Y., 2003. Testing for Unit Roots in Heterogeneous Panels. Journal of Econometrics, 115, 53–74] panel t-test. Our exercise involves Australia’s 28 tourist source markets. Our main findings are: (1) that visitor arrivals to Australia from 28 tourist source markets are stationary, implying that any shock will have only a temporary effect and (2) the second structural break, which mainly coincides with the September 11 terrorist attacks and the Asian financial crisis, has slowed down the growth rate in visitor arrivals to Australia from 22 out of 28 (79%) of the tourism source markets.

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This paper investigates the existence of house price bubbles in Australia's eight capital cities in recent years by using quantitative analyses including Johansen cointegration test, Granger causality test, impulse response and Chow forecast test. While interactions between house prices and market fundamentals are discussed in long-run and causal estimations, shocks from the market fundamentals to house prices are investigated in generalized impulse response analyses. Findings from estimating house price bubbles for eight capital cities suggest that there was an obvious house price bubble in Perth, while a slight house price bubble occurred in Sydney. In contrast, house prices in Adelaide and Darwin can be explained very well by market fundamentals, while house prices in Melbourne, Brisbane, Hobart and Canberra were undervalued in the study period.

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Many test results are found inconsistent with the expectations hypothesis of the term structure. The aim of this paper is to re-examine the expectations hypothesis of the term structure using the Australian interest rate data from 1969(7) to 1995(7). We start with the cointegration test on Rt, rt, and St followed by the Granger causality test from St to ∇ rt. Finally we carry out the VAR model of cross-equation restrictions test. Our findings show that there is no conclusive rejection of the expectations hypothesis of the term structure.

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In this paper, our goal is to examine the unit root null hypothesis in energy consumption for Australian states and territory. We consider sectoral energy consumption for Australia and its six states and one territory using time series data for the period 1973-2007. This is the first study that does this. Generally, except for some cases in South Australia, we find strong support that shocks to energy consumption have a temporary effect on energy consumption in Australia. © 2009 Elsevier Ltd. All rights reserved.

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This article analyses the determinants of renewable energy consumption in six major emerging economies who are proactively accelerating the adoption of renewable energy. The long-run elasticities from both panel methods (fully modified ordinary least square and dynamic least square) and the time series method (autoregressive distributed lag) seem to be pretty consistent. For Brazil, China, India and Indonesia, in the long-run, renewable energy consumption is significantly determined by income and pollutant emission. However, for Philippines and Turkey, income seems to be the main driver for renewable energy consumption. In the short-run, for Brazil and China bi-directional causalities between renewable energy and income; and between renewable energy and pollutant emission are found. This research justifies the efforts undertaken by emerging countries to reduce the carbon intensity by increasing the energy efficiency and substantially increasing the share of renewable in the overall energy mix

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This article proposes a bias-adjusted estimator for use in cointegrated panel regressions when the errors are cross-sectionally correlated through an unknown common factor structure. The asymptotic distribution of the new estimator is derived and is examined in small samples using Monte Carlo simulations. For the estimation of the number of factors, several information-based criteria are considered. The simulation results suggest that the new estimator performs well in comparison to existing ones. In our empirical application, we provide new evidence suggesting that the forward rate unbiasedness hypothesis cannot be rejected. © The Author 2007.

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In this paper we propose a simple procedure for data dependent determination of the number of lags and leads to use in feasible estimation of cointegrated panel regressions. Results from Monte Carlo simulations suggests that the feasible estimators considered enjoys excellent precision in terms of root mean squared error and reasonable power with effective size hovering close to the nominal level. The good performance of the feasible estimators is verified empirically through an application to the long run money demand.

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This paper investigates the cointegrating and long-term causal relationships between the Shanghai A and B-share market, and between these two markets and the Hong Kong, the Taiwanese, the Japanese and the US market of two sub periods between July 1993 and March 2007. On the basis of a new Granger non-causality test procedure developed by Toda-Yamamoto (1995) and Johansen’s (1988) cointegration test, my results suggest that a long-term equilibrium relationship measured by cointegration has been merged between
the Chinese A-share market and the other markets in greater China region as well as the US market during the post-crisis period which covers the period since Chinese A-share market was opened to the Qualified Foreign Institutional Investors (QFII) in 2002. I also found that the Shanghai A-share market uni-directionally Granger-causes the other regional markets after the Asian financial crisis, while the A-share market and Hong Kong H-share market have had a significant feedback relationship since then. However, I found no evidence there has been cointegrating relationship between Shanghai B-share market and any other market ever since the B-share market was opened to the local retail investors in 2001.

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One of the single most cited studies within the field of nonstationary panel data analysis is that of LLC (Levin et al. in J Econom 98:1 - 24, 2002), in which the authors propose a test for a common unit root in the panel. Using both theoretical arguments and simulation evidence, we show that this test can be misleading unless it is based on the same bandwidth selection rule used by LLC. © Springer-Verlag 2008.