More powerful threshold cointegration tests

Threshold cointegration tests have made a big splash in the literature by allowing for asymmetric adjustment in linear cointegration tests. This paper contributes to this literature by proposing new tests to improve the power of the conventional threshold cointegration tests. The new tests intuitively resolve one of the possible reasons that attribute to the low power of existing threshold cointegration tests and are easy to implement since they do not require any additional information outside of the system. Our simulation results show that the proposed tests improve the power of the existing threshold cointegration tests, especially as the signal-to-noise ratio increases, in contrast to other considered procedures. The efficiency gains are achieved regardless of sample size, the number of cointegrated variables, and the types of threshold specifications. The newly developed tests are applied to examine long-run purchasing power parity in the Pacific nations. In contrast to conventional cointegration tests, the proposed tests found long-run PPP holds in 5 out of 7 countries with appropriate asymmetric adjustments.     

IV threshold cointegration tests and the Taylor rule

The usual cointegration tests often entail nuisance parameters that hinder precise inference. This problem is even more pronounced in a nonlinear threshold framework when stationary covariates are included. In this paper, we propose new threshold cointegration tests based on instrumental variables estimation. The newly suggested IV threshold cointegration tests have standard distributions that do not depend on any stationary covariates. These desirable properties allow us to formally test for threshold cointegration in a nonlinear Taylor rule. We perform this analysis using real-time U.S. data for several sample periods from 1970 to 2005. In contrast to the linear model, we find strong evidence of cointegration in a nonlinear Taylor rule with threshold effects. Overall, we find that the Federal Reserve is far more policy active when inflation is high than when inflation is low. In addition, we reaffirm the notion that the response to counteract high inflation was weakest in the 1970s and strongest in the Greenspan era.     

Detecting cointegration relationships under nonlinear models: Monte Carlo analysis and some applications

Testing for cointegration in the presence of nonlinear adjustments or structural breaks is important for examining the equilibrium relationship among economic variables. It is known that standard cointegration tests perform poorly when a cointegration relationship has nonlinear adjustments or structural breaks. However, it is not clear how some cointegration tests allowing for nonlinearity perform under other classes of nonlinear cointegration models. This paper investigates which cointegration tests help detect a cointegration relationship with nonlinear adjustments or structural breaks. Our Monte Carlo simulation results demonstrate that the cointegration test with threshold adjustment generally has better power performance under most cointegration relationships with nonlinearity. We also provide empirical applications to the money demand and term structure of the U.S. interest rates. The empirical results show that the test allowing for threshold adjustment provides strong evidence of the cointegration relationships of money demand and the term structure of interest rates.     

On the application of the rank tests for nonlinear cointegration to PPP: The case of Papua New Guinea

Much interest has been paid recently to the nonlinear cointegrating relations existing among economic variables. Various testing procedures are already available to test for the existence of nonlinear cointegration. For example, Breitung (2001) proposes rank tests and his testing procedure has been broadly applied. In this study, we warn against a blind application of the rank cointegration tests, particularly to economic variables that evidence certain behavior. As an illustration, we employ the nominal exchange rates and relative prices of Papua New Guinea against her major trading partners with the objective of testing the validity of purchasing power parity for the country. Our simulation results also confirm our warnings. Additionally, we provide some simple solutions to the problem we encounter herein.     

Taiwan's exports and trade imbalance against US and Japan: an empirical investigation based on error correction model

This study employs recent advances in time-series analysis, cointegration and error correction model, to examine the long-run and short-run determinants of the exports and trade imbalance between the USA, Japan, and Taiwan. The unit root tests reveal nonstationary in most of the variables. The cointegration tests affirm positive the long-run associations are between the exchange rate changes and the exports as well as the trade imbalance. Once these long-run effects are accounted for, it is found that there are evidences of short-run relationship between these variables.     

A Cointegrating approach to budget deficits and long-term interest rates

A cointegrating approach is undertaken in this study to determine if there is a long-run equilibrium relationship between budget deficits and long-term interest rates for the United States and nine European countries. The cointegration approach consists of conducting cointegration tests and then testing several hypothesized values for the deficit and price expectations variables. The cointegration results suggest the existence of several significant cointegrating vectors for each of the ten countries, which would seem to appeal to the view of budget deficits having a positive impact on long-term interest rates. The hypothesized values for the deficit and price expectations variables are found to be too strict since the hypotheses are rejected in every case but one.     

The Feldstein–Horioka Puzzle and structural breaks: Evidence from EU members

The purpose of this paper is to investigate the level of capital mobility in European Union members using the Feldstein–Horioka puzzle proposed by Feldstein and Horioka (1980) in order to investigate relations between saving and investment flows. In this paper, data for 23 European countries were used over the period of 1995–2009 on the quarterly basis. Two different tests were used to estimate the stationarity of the model variables, which are the Ng and Perron (2001) unit root test procedure and approach proposed by Zivot and Andrews (1992) for unit root test allowing for a structural shift. Then the Kejriwal and Perron (2008, 2010) structural break test was applied to determine the presence of structural breaks in series. In most countries except Belgium and Finland UDmax and WDmax tests rejected the hypothesis of no breaks. To test the cointegration relationships between investment and saving flows of European Union members three different cointegration techniques were applied to the data. Firstly, the Johansen (1988) cointegration approach was used for the case of no cointegration shifts, then the Gregory and Hansen (1996) cointegration test was applied, which allows for one structural shift. Finally, again the Johansen' cointegration approach was used; however, this time with the inclusion of dummy variables related to earlier selected structural break locations. The empirical results provided stronger evidence of cointegration between investment and saving variables in the case of structural break accommodation compared to the case where the presence of structural breaks was ignored. The estimated saving retention coefficient in the presence of structural breaks using the Kejriwal and Perron (2008, 2010) approach appeared relatively low in many cases, illustrating by this the openness of estimated countries. In general, world and European countries with time have a tendency to a higher level of their capital market openness. Estimations of a saving retention coefficient in the presence of structural changes do not support the existence of the Feldstein–Horioka Puzzle in the considered EU countries, except Belgium.     

Cointegration and detectable linear and nonlinear causality: analysis using the London Metal Exchange lead contract

This study applies linear and nonlinear Granger causality tests to examine the dynamic relation between London Metal Exchange (LME) cash prices and three possible predictors. The analysis uses matched quarterly inventory, UK Treasury bill interest rates, futures prices and cash prices for the commodity lead traded on the LME. The effects of cointegration on both linear and nonlinear Granger causality tests is also examined. When cointegration is not modelled, evidence is found of both linear and nonlinear causality between cash prices and analysed predictor variables. However, after controlling for cointegration, evidence of significant nonlinear causality is no longer found. These results contribute to the empirical literature on commodity price forecasting by highlighting the relationship between cointegration and detectable linear and nonlinear causality. The importance of interest rate and inventory as well as futures price in forecasting cash prices is also illustrated. Failure to detect significant nonlinearity after controlling for cointegration may also go some way to explaining the reason for the disappointing forecasting performances of many nonlinear models in the general finance literature. It may be that the variables are correct, but the functional form is overly complex and a standard VAR or VECM may often apply.     

Energy consumption,employment, output,and temporal causality: evidence from Taiwan based on cointegration and error-correction modelling techniques

In this study, a cointegration analysis and a vector autoregressive model (VAR) are used to examine the causal relationships among energy consumption, employment, and output for Taiwan over the period January 1982 to November 1997. Johansen (1988) and Johansen and Juselius (1990) cointegration test result indicates these three variables are cointegrated with one cointegrating vector. The results from Granger causality tests based on vector error-correction models (VECM) suggest bidirectional Grange causality for employment-output and employment-energy consumption, but only unidirectional causality running from energy consumption to output. Furthermore, the impulse responses and variance decompositions are also incorporated into the analysis. The results from impulsive response and variance decomposition analysis tell similar stories. Energy consumption appears to have led to output growth in Taiwan over this period. The policy implication of this finding is that energy conservation will restrain the output growth in Taiwan.     

Export-led Growth and Import Compression: Further Time Series Evidence From LDCs

This paper conducts tests of the export-led growth and the import-compression hypotheses for four less developed countries (LDCs) – India, Nigeria, Fiji and Papua New Guinea (PNG). Based on Johansen's multiple cointegration test preceded by unit root tests, we test for cointegration between real output, exports and imports. Non-rejection of cointegration between the variables excludes the possibility of Granger non-causality and suggests at least one way Granger causality. Real output, exports and imports are found to be cointegrated in two of the countries and the resulting error-correction models suggest that Granger causality runs from exports and imports to real output in these cases. Exogeneity tests are conducted for exports with respect to real output. However, while the assumption of weak exogeneity is validated in two of the countries, the null hypothesis of super exogeneity is rejected. The test results therefore cast doubts on policy recommendations for the LDCs based on the export-led growth hypothesis.     

Import demand in heterogeneous panel setting

To study the elasticities of import demand function, a heterogeneous panel is built with data of 40 countries and using panel unit root tests (Im et al., 1997) and panel cointegration tests (Pedroni, 2004). The model is tested with two previously used activity variables: GDP and GDP minus Export for a performance comparison. To estimate elasticities, use is made of two modified panel versions of FMOLS and DOLS developed by Pedroni (1996, 2000, 2001). The tests prove that GDP outperforms GDP minus Exports as an activity variable in the cointegration context. FMOLS and DOLS give close results when individual estimates are done. When between‐dimension estimators are used, conflicting results are obtained. Then, the sample is split into developed and developing countries and it is shown that income elasticity in developing countries are not different than unity on average and are higher than in developed countries contradicting previous literature results.     

Do Financial and Institutional Variables Enhance the Impact of Remittances on Economic Growth in Latin America and the Caribbean? A Panel Cointegration Analysis

Using recently developed panel unit root and panel cointegration tests and the Fully-Modified OLS methodology (FMOLS), this paper estimates the impact of remittances on the economic growth of selected upper and lower income Latin American & Caribbean (LAC) countries over the 1990–2007 period. Despite the large flow of remittances to the region, there have been relatively few empirical studies assessing the impact of remittances on economic growth in LAC. Panel unit root tests suggest that several of the macro variables included in the model exhibit unit roots, yet, at the same time, Pedroni’s panel cointegration test determined that there is a cointegrating relationship among the variables in the estimated model. The FMOLS estimates suggest that remittances have a positive and significant effect on economic growth in both groups of countries. The estimates also indicate that both the degree of economic freedom and credit provided by the banking system have a positive and significant effect on economic growth in upper (middle) income LAC countries. The sign of the interaction term between remittances and the credit (and EFI) variables suggest that remittances act as substitutes for these variables. Finally, the effect of remittances on both sets of countries is stronger in the presence of a financial (credit) variable.     

New panel results on cointegration of international health expenditure and GDP

This article tests for existence of cointegration between health expenditure and GDP using data from 25 OECD countries for the period 19607ndash;1997. The empirical modelling is based on a heterogeneous bivariate vector error correction panel model that allows for trending data as well as intercepts and trends in the cointegrating relations. Univariate country-by-country and panel unit root tests generally fail to reject the null of a unit root in the health expenditure and GDP variables. Country-by-country results based on the Johansen multivariate likelihood-based inference indicate somewhat mixed results on country-specific cointegration with a rank of one found for 12 countries and a rank of zero for the remaining 13 countries. Application of a new panel test for cointegration rank with higher power than the individual tests indicates that health expenditure and GDP are cointegrated around linear trends.     

Mexico's Economic Growth and the Balance of Payments Constraint: A cointegration analysis

This paper applies the basic balance-of-payments constraint model (BPCmodel), developed by A.P. Thirlwall, to the analysis of Mexico's economic growth in 1950-96.With the use of unit-root tests and cointegration analysis it estimates the long-run association between the growth of Mexico's real exports and real output in 1950-96, and selected subperiods. The results tend to show significant and positive cointegration between these two variables, thus giving support to the BPC-model as a relevant hypothesis to explain Mexico's long-term economic growth. Moreover, the findings of cointegration tests for selected subperiods suggest that the slowdown in its economic growth since 1982 is associated with an increase in the long-term income elasticity of imports that made more binding the balance-of-payments constraint on the expansion of domestic output.     

Investigating the semiconductor industry cycles

The aim of this article is to investigate the links between semiconductor sales and various macroeconomic, financial, industrial variables including inventories, equipment orders or semiconductor sector stock index. Statistical properties of these variables are studied. Both short-run and long-run interactions are analysed. On the short-run, our results indicate that relationships often imply feedbacks. Through the implementation of cointegration analysis, we separately identify both sales value and investments in the semiconductor market. An impulse–response analysis confirms the relevance of our choice of data and stability tests demonstrate that the parameters remain constant during the entire sample. The Vector Error Correction Models (VECMs) offer a representation respecting cycle theories and market actor analyses.     

Testing for cointegration using the Johansen methodology when variables are near-integrated: size distortions and partial remedies

We investigate the properties of Johansen’s (J Econ Dyn Control 12:231–254, 1988; Econometrica 59:1551–1580, 1991) maximum eigenvalue and trace tests for cointegration under the empirically relevant situation of near-integrated variables. Using Monte Carlo techniques, we show that in a system with near-integrated variables, the probability of reaching an erroneous conclusion regarding the cointegrating rank of the system is generally substantially higher than the nominal size. The risk of concluding that completely unrelated series are cointegrated is therefore non-negligible. We suggest ways of identifying the problem and different approaches to reduce the size distortions of the tests.     

Unit root and cointegration tests: timeseries versus panel estimates for international health expenditure models

Classical regression estimates of the determinants of the OECD health expenditures are useful for policy formulation and evaluation. However, if the underlying timeseries data are not collectively stationary in levels, the estimated parameters are faulty and can misguide health policy. Until very recently, the crucial stationarity tests were ignored in a large number of studies on international comparisons. Stationarity (ADF, Phillips-Perron, IPS heterogeneous panel) and cointegration (Engle-Granger bivariate, Johansen's multivariate) tests are conducted here using 1960–1997 health expenditures data (1998 CD ROM) of 19 OECD countries. It is found that extending the time series data length affects the order of integration and number of cointegrating vectors. However, it is arguable whether the order of integration decreases or increases as more observations are added for testing. The failure of the Johansen and Engle-Granger cointegration tests for most of the OECD countries cautions policy makers against reliance on earlier research findings that were based on unstable relationships among variables in the regression models. (This is not the case for the UK, Greece and Ireland; policy implications have been derived for the UK.) Consequently, data calibrated in growth rates may be more appropriate for investigating the long run relationships collectively in a panel of OECD health expenditure model specifications.     

Fractional integration and cointegration in US financial time series data

This paper examines several US monthly financial time series using fractional integration and cointegration techniques. The univariate analysis based on fractional integration aims to determine whether the series are I(1) (in which case markets might be efficient) or alternatively I(d) with \(d < 1\) , which implies mean reversion. The multivariate framework exploiting recent developments in fractional cointegration allows to investigate in greater depth the relationships between financial series. We show that there might exist many (fractionally) cointegrated bivariate relationships among the variables examined, for some of which only standard cointegration tests had previously been carried out.     

Tests for cointegration allowing for an unknown number of breaks

This paper introduces cointegration tests allowing for an unknown number of breaks. The introduced tests assume that the unspecified number of breaks is smaller than or equal to the maximum number of breaks set a priori. Monte Carlo simulations provide two main results. First, the proposed tests perform as well as the tests of Gregory and Hansen (1996a) and Hatemi-J (2008), which assume one or two breaks a priori, when the cointegration relationship has one or two breaks. Second, the proposed tests perform better than the tests of Gregory and Hansen (1996a) and Hatemi-J (2008) when the cointegration relationship has more than three breaks or persistent Markov switching shifts. We also provide empirical applications for the money demand of the U.S. The empirical results show that the proposed tests reject the null hypothesis of no cointegration as compared to other tests.