A new criteria for selecting the optimum lags in Johansen's cointegration technique

Bahmani‐Oskooee, Mohsen; Brooks, Taggert J.

doi:10.1080/00036840210129419

Cited by 33 publications

(17 citation statements)

References 16 publications

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“…Holmes and Hutton (1992) and Lee and Yang (2006) introduce techniques for selecting optimal lags by considering causality. Bahmani-Oskooee and Brooks (2003) demonstrate that when goodness of fit is used as a criterion for the choice of lag length and the cointegrating vector, the sign and size of the estimated coefficients are in line with theoretical expectations. The lag structure in the VAR models described by Jacobson (1995) is based on tests of residual autocorrelation; Winker (2000) uses information criteria, such as AIC and BIC.…”

Section: Introductionsupporting

confidence: 65%

SAFE: An early warning system for systemic banking risk

Oet

Bianco

Gramlich

et al. 2013

Journal of Banking & Finance

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This paper builds on existing microprudential and macroprudential early warning systems (EWSs) to develop a new, hybrid class of models for systemic risk, incorporating the structural characteristics of the fi nancial system and a feedback amplifi cation mechanism. The models explain fi nancial stress using both public and proprietary supervisory data from systemically important institutions, regressing institutional imbalances using an optimal lag method. The Systemic Assessment of Financial Environment (SAFE) EWS monitors microprudential information from the largest bank holding companies to anticipate the buildup of macroeconomic stresses in the fi nancial markets. To mitigate inherent uncertainty, SAFE develops a set of medium-term forecasting specifi cations that gives policymakers enough time to take ex-ante policy action and a set of short-term forecasting specifi cations for verifi cation and adjustment of supervisory actions. This paper highlights the application of these models to stress testing, scenario analysis, and policy.

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Section: Introductionsupporting

confidence: 65%

SAFE: An early warning system for systemic banking risk

Oet

Bianco

Gramlich

et al. 2013

Journal of Banking & Finance

View full text Add to dashboard Cite

show abstract

Section: Introductionsupporting

confidence: 65%

SAFE: An Early Warning System for Systemic Banking Risk

Oet

Eiben²,

Bianco

et al. 2011

Working Paper (Federal Reserve Bank of Cleveland)

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Advisory: This article is based in whole or in part on the CFSI (Cleveland Financial Stress Indicator), an indicator that was discontinued by the Federal Reserve Bank of Cleveland in 2016 due to the discovery of errors in the indicator's construction. These errors overestimated stress in the real estate and securitization markets. As a result, readers should be cautious and interpret any analysis based on CFSI data with those errors in mind.This paper builds on existing microprudential and macroprudential early warning systems (EWSs) to develop a new, hybrid class of models for systemic risk, incorporating the structural characteristics of the fi nancial system and a feedback amplifi cation mechanism. The models explain fi nancial stress using both public and proprietary supervisory data from systemically important institutions, regressing institutional imbalances using an optimal lag method. The Systemic Assessment of Financial Environment (SAFE) EWS monitors microprudential information from the largest bank holding companies to anticipate the buildup of macroeconomic stresses in the fi nancial markets. To mitigate inherent uncertainty, SAFE develops a set of medium-term forecasting specifi cations that gives policymakers enough time to take ex-ante policy action and a set of short-term forecasting specifi cations for verifi cation and adjustment of supervisory actions. This paper highlights the application of these models to stress testing, scenario analysis, and policy.

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“…The issue of finding the appropriate lag length for each of the underlying variables in the ARDL model is very important because we want to have Gaussian error terms (that is, standard normal error terms that do not suffer from non-normality and non-stability). According to Bahmani-Oskooee and Brooks (2003), selecting the appropriate model of the long run underlying equation, it is necessary to determine the optimum lag length (k) by using proper model order selection criteria such as; the Akaike information criterion (AIC), Schwarz information criterion (SIC) or Hannan-Quinn information criterion (HQC). The appropriate lag length to be used is presented in Table 3.…”

Section: Optimal Lag Order Checkmentioning

confidence: 99%

Government education expenditure and primary school enrolment in Nigeria: An impact analysis

Ihugba¹,

Ukwunna²,

Sandralyn³

2019

J. Econ. Int. Finance

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This study investigated the impact of government education expenditure on primary school enrolment in Nigeria by applying the bounds testing (ARDL) approach to cointegration for the period of 1970 to 2017. The model was constructed to identify the relationship between the two variables while also considering the interaction with control variables; per capita income, remittances, investment and population growth. The bounds tests suggest that the variables of interest are bound together in the long-run when primary school enrolment is the dependent variable. Interesting observations were made which are explained by government low spending on education. It was observed that an insignificant relationship exists between government education expenditure on primary school enrolment while a positive relationship exists between remittances and primary school enrolment. Population growth has positive relationship in the short run, but a negative relationship in the long run. The speed of adjustment to equilibrium is 88% within a year when the variables wander away from their equilibrium values. The study recommends that government policies directed at improving the expenditure towards education should largely increase, and money meant for the education sector should be disbursed with high degree of transparency.

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A new criteria for selecting the optimum lags in Johansen's cointegration technique

Cited by 33 publications

References 16 publications

SAFE: An early warning system for systemic banking risk

SAFE: An early warning system for systemic banking risk

SAFE: An Early Warning System for Systemic Banking Risk

Government education expenditure and primary school enrolment in Nigeria: An impact analysis

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