Likelihood Based Inference In Cointegrated Vector Autoregressive Models
By J. Schmitt. 2016
1,399 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/75f3a86aae197d4bdb2e8fe6d07f9104c622dec8
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- Matteo Barigozzi
- Marco Lippi
- David F. Hendry
- A. Onatski
- Matteo Luciani
- Søren Johansen
- Mikkel Plagborg-Møller
- Chen Wang
Citations in the corpus
- Are gold and silver a hedge against inflation? A two century perspective (2015, methodology): “The results of the Johansen (1995) (TI-VECM) and the Bierens and Martins (2010) (TV-VECM) cointegration tests for the US and the UK are summarized in Table 4.”
- A State of the Art Review of Modal-Based Damage Detection in Bridges: Development, Challenges, and Solutions (2017, methodology): “A maximum likelihood approach known as the Johansen Procedure [171] is used to identify the most stationary linear combination of the non ‐ stationary variables possible.”
- How Does Social Media Impact Bitcoin Value? A Test of the Silent Majority Hypothesis (2018, methodology): “Instead, VECM yields more efficient estimators of cointegrating time series using a vector of error correction terms that is equal in length to the number of cointegrating relationships added to the relationship [29].”
- MODEL DISCOVERY AND TRYGVE HAAVELMO’S LEGACY (2014, background): “Let the set of stochastic variables to be analyzed be denoted X1T = (x1 . . .xT ), then their joint data density fX (·) conditional on the past and for parameters 1T = (λ1 . . .λT ) can be sequentially factorized as: fX ( X1T | X0,Q1T , 1T ) = T∏ t=1 fxt ( xt | X1t−1,X0,qt ,λt ) , (1) where Q1T =…”
- Short- and long-run electricity demand elasticities at the subsectoral level: A cointegration analysis for German manufacturing industries (2015, unknown): “…β´Yt-1 represents up to (k – 1) cointegration relationships, whereas α contains the corresponding adjustment coefficients.5 Using the trace test provided by Johansen (1994, 1995) and Johansen et al. (2000), respectively, depending on whether structural breaks are incorporated or not, it is then…”
- Alternative asymptotics for cointegration tests in large VARs (2016, methodology): “Recall that, as T → ∞ while p remains fixed, the LR statistic converges in distribution to p times the trace of matrix (19):”
- A test of environmental Kuznets curve (EKC) for carbon emission and potential of renewable energy to reduce green house gases (GHG) in Malaysia (2018, methodology): “There are three main co-integration methods, namely Engle and Granger (2001) that is based on the residuals of the model and by Phillips and Hansen (1990) that is based upon the modified ordinary least square and multivariate co-integration investigation by Johansen (1995).”
- Optimal Estimation of Cointegrated Systems with Irrelevant Instruments (2014, unknown): “This is done parametrically in the reduced rank regression VAR approach (Johansen, 1988, 1995), and semiparametrically by fullymodified least squares in Phillips andHansen (1990) and by frequency domain techniques in Phillips (1991a).”
- Local Projections vs. VARs: Lessons From Thousands of DGPs (2021, methodology): “The cointegration rank of the VECM is selected by the Johansen (1995) maximum eigenvalue test, which indicates that the latent factors are driven by four common stochastic trends.”
- On the macroeconomic determinants of the housing market in Greece: a VECM approach (2016, methodology): “The cointegration test is based on Johansen (1995).”
- Economic growth, carbon dioxide emissions, renewable energy and globalization (2014, background): “In table 5 and table 6 we can observe the test of cointegration proposed by Johansen (1995). The results suggest a cointegration between variables at 5% level of significance.”
- Is the Relationship between Financial Development and Economic Growth Monotonic? Evidence from a Sample of Middle Income Countries (2015, unknown): “According to Johansen (1995); Philipps and Hansen (1990), the long-run relationships exist only in the context of cointegration among variables with the same order of integration. Nevertheless, Pesaran and Shin (1999) argue that panel ARDL can be used even with variables with different order of inte”
- Non-Stationary Dynamic Factor Models for Large Datasets (2016, methodology): “(A67) From Lemma 13.1 in Johansen (1995), we have (recall that β̌′⊥β̌ = 0r−c×c) A−1T β̃ 0 = A−1T ( β̌ + β̌⊥∗β̌ ′ ⊥β̃ 0 ) = ( Ic√ T β̌′⊥β̃ 0 ) = ( Ic√ T β̌′⊥(β̃ 0 − β̌) ) = ( Ic op(1) ) , (A68) since A−1T β̃ 0 spans a space of dimension c.”
- ardl: Estimating autoregressive distributed lag and equilibrium correction models (2018, unknown): “2 Compared with a system-based Johansen (1995) cointegration analysis, which is implemented in Stata’s vec command suite, the single-equation approach can be more efficient if the focus is on one outcome variable, in addition to the aforementioned flexibility regarding the integration orders.”
- Global Oil Prices and Local Food Prices: Evidence from East Africa (2016, unknown): “Rank tests for the maximum number of cointegrating vectors (Johansen 1991, 1995) indicate that the global price series are not cointegrated at conventional levels of significance (Appendix E has results of all cointegration tests in the paper).”