Tests For Structural Change Research Articles

Searching for the EMU core member countries

This study uses techniques of cointegration analysis and tests for structural change to search for changes to sovereign credit risk in some relevant member states of the European Monetary Union (EMU) trying to identify core countries. While there are a number of core countries the empirical findings presented in this study seem to provide some evidence that might be interpreted as a sign for bond markets not believing anymore that France is belonging to this prestigious group of EMU member states.

Power monotonicity in detecting volatility levels change

We show that the CUSUM and LM tests for structural change in the volatility process enjoy monotonic power. The framework is general including many recently proposed non-stationary GARCH-type models. The result is in contrast to the well-known issue of non-monotonic power for the CUSUM-based tests for changing mean. Simulations and an empirical example provide further support.

Structural change in urban Chinese food preferences

AbstractWe undertake a range of tests for structural food preference change in urban China, using provincial‐level panel data from 2002 to 2010. We introduce a time transition function into the Generalized Quadratic Almost Ideal Demand System (GQAIDS) to represent consumer preferences. We apply this system to evaluate the demand structure for seven food groups. The use of the GQAIDS specification relaxes many empirical demand system restrictions associated with previous analyses of structural preference change. Our findings suggest that Chinese food preferences are continuing to evolve.

On the application of new tests for structural changes on global minimum-variance portfolios

We investigate if portfolios can be improved if the classical Markowitz mean–variance portfolio theory is combined with recently proposed change point tests for dependence measures. Taking into account that the dependence structure of financial assets typically cannot be assumed to be constant over longer periods of time, we estimate the covariance matrix of the assets, which is used to construct global minimum-variance portfolios, by respecting potential change points. It is seen that a recently proposed test for changes in the whole covariance matrix is indeed partially useful whereas pairwise tests for variances and correlations are not suitable for these applications without further adjustments.

Detecting multiple breaks in long memory the case of U.S. inflation

Multiple structural change tests by Bai and Perron (Econometrica 66:47–78, 1998) are applied to the regression by Demetrescu et al. (Econ Theory 24:176–215, 2008) in order to detect breaks in the order of fractional integration. With this instrument we tackle time-varying inflation persistence as an important issue for monetary policy. We determine not only the location and significance of breaks in persistence, but also the number of breaks. Only one significant break in U.S. inflation persistence (measured by the long-memory parameter) is found to have taken place in 1973, while a second break in 1980 is not significant.

Sex differences and structural brain maturation from childhood to early adulthood

Recent advances in structural brain imaging have demonstrated that brain development continues through childhood and adolescence. In the present cross-sectional study, structural MRI data from 442 typically developing individuals (range 8–30) were analyzed to examine and replicate the relationship between age, sex, brain volumes, cortical thickness and surface area. Our findings show differential patterns for subcortical and cortical areas. Analysis of subcortical volumes showed that putamen volume decreased with age and thalamus volume increased with age. Independent of age, males demonstrated larger amygdala and thalamus volumes compared to females. Cerebral white matter increased linearly with age, at a faster pace for females than males. Gray matter showed nonlinear decreases with age. Sex-by-age interactions were primarily found in lobar surface area measurements, with males demonstrating a larger cortical surface up to age 15, while cortical surface in females remained relatively stable with increasing age. The current findings replicate some, but not all prior reports on structural brain development, which calls for more studies with large samples, replications, and specific tests for brain structural changes. In addition, the results point toward an important role for sex differences in brain development, specifically during the heterogeneous developmental phase of puberty.

A toolbox of permutation tests for structural change

The sup $$LM$$ test for structural change is embedded into a permutation test framework for a simple location model. The resulting conditional permutation distribution is compared to the usual (unconditional) asymptotic distribution, showing that the power of the test can be clearly improved in small samples. Furthermore, the permutation test is embedded into a general framework that encompasses tools for binary and multivariate dependent variables as well as model-based permutation testing for structural change. It is also demonstrated that the methods can not only be employed for analyzing structural changes in time series data but also for recursive partitioning of cross-section data. The procedures suggested are illustrated using both artificial data and empirical applications (number of youth homicides, employment discrimination data, carbon flux in tropical forests, stock returns, and demand for economics journals).

The impact of serial correlation on testing for structural change in binary choice model: Monte Carlo evidence

This paper examines the finite sample properties of structural change tests with an unknown breakpoint for the probit model in the presence of serial correlation. The combination of structural change and serial correlation renders model estimation challenging, affecting the consistency of coefficient estimates. Although there is vast literature concerning structural change tests for linear time series models, the literature for such tests in the context of binary choice models is somewhat sparse. More importantly, the empirical literature has applied the standard tests of structural change on the discrete choice model, despite the fact that most of these tests were developed specifically for the linear regression model. Subsequently, the theoretical properties of these tests in the context of non-linear models are unknown. This includes the class of discrete choice models, such as probit and logit. The issue becomes even more complicated in the presence of serial correlation, since typical tests for structural change often require the assumption of independence in the error terms. Even when the tests allow for a weakly dependent structure in the data, their finite sample performance remains unknown. This paper conducts simulation analysis on the size of ‘supremum’ Wald, LR and LM tests for structural change in the context of the probit model with varying levels of serial correlation. It is found that the shortcomings of the tests in linear models are magnified in probit models. In particular, the tests exhibit greater size distortion for the probit model than the linear model with the same level of serial correlation. Bootstrapping is also considered as an alternative approach to obtaining critical values, and though it reduces the size distortion in finite samples, it is unable to accommodate the distortion associated with a high level of serial correlation.

Recursive predictive tests for structural change of long-memory ARFIMA processes with unknown break points

This paper considers the theoretical justifications of Lütkpohl’s (1988) test statistics when the data-generating process is relaxed to be a stationary ARFIMA process. Under suitable regularity conditions, we prove the applicability of Lütkpohl’s (1988) method to the stationary ARFIMA (p, d, q) process with d∈ (−0.5, 0.5). The practical advantages of our results imply that the potential one or more change points of an ARFIMA process can be detected via recursive predictive tests based on AR regression, even though the exact order of the ARFIMA (p, d, q) is unknown. The spurious break considered in Kuan and Hsu (1998) can also be resolved by Lütkpohl’s (1988) predictive tests, and the simulations conducted in this paper confirm our theoretical results.

Powerful tests for structural changes in volatility

Detecting structural changes in volatility is important for understanding volatility dynamics and stylized facts observed for financial returns such as volatility persistence. We propose modified CUSUM and LM tests that are built on a robust estimator of the long-run variance of squared series. We establish conditions under which the new tests have standard null distributions and diverge faster than standard tests under the alternative. The theory allows smooth and abrupt structural changes that can be small. The smoothing parameter is automatically selected such that the proposed test has good finite-sample size and meanwhile achieves decent power gain.

Testing for Structural Change in Heterogeneous Panels with an Application to the Euro's Trade Effect

AbstractThis paper presents a structural change test for panel data models in which the break (or the change) affects some, but not all, cross-section units in the panel. The test is robust to non-normal, heteroskedastic and autocorrelated errors, as well as end-of-sample structural change. The test amounts to computing and comparing pre- and post-break sample statistics as Chow (1960) type F statistics averaged over cross-section units. The cases of known and unknown break date are both considered. Under mild assumptions, the test has a limiting standard normal distribution as the number of cross-sections tends to infinity. Monte Carlo experiments show that the test has good size and power under a wide range of circumstances, including when the break date is unknown and differs across individual units, and when errors exhibit cross-section dependence. Finally, the test is illustrated by seeking a break in the dynamics of trade among euro area countries following the introduction of the euro.

Long-term asset tail risks in developed and emerging markets

A power law typically governs the tail decay of financial returns but the constancy of the so-called tail index which dictates the tail decay remains relatively unexplored. We study the finite sample properties of some recently proposed endogenous tests for structural change in the tail index. Given that the finite sample critical values strongly depend on the tail parameters of the return distribution we propose a bootstrap-based version of the structural change test. Our empirical application spans developed and emerging financial asset returns. Somewhat surprisingly, emerging stock market tails are not more inclined to structural change than their developed counterparts. Emerging currency tails, on the contrary, do exhibit structural shifts in contrast to developed currencies. Our results suggest that extreme value theory (EVT) applications in hedging tail risks can assume stationary tail behavior over long time spans provided one considers portfolios that solely consist of stocks or bonds.

Testing structural change in partially linear single-index models with error-prone linear covariates

Motivated by an analysis of a real data set from Duchenne Muscular Dystrophy (Andrews and Herzberg, 1985), we propose a new test of structural change for a class of partially linear single-index models with error-prone linear covariates. Based on the local linear estimation for the unknowns in these semiparametric models, we develop a new generalized F-test statistics for the nonparametric part in the partially linear single-index models with error-prone linear covariates. Asymptotic properties of the newly proposed test statistics are proved to follow asymptotically the chi-squared distribution. The new Wilks’ phenomenon is unveiled in a class of semiparametric measure error models. Simulations are conducted to examine the performance of our proposed method. The simulation results are consistent with our theoretical findings. Real data examples are used to illustrate the proposed methodology.

Testing for Breaks in Cointegrated Panels with Common and Idiosyncratic Stochastic Trends

In this paper, we develop tests for structural change in cointegrated panel regressions with common and idiosyncratic trends. We consider both the cases of observable and nonobservable common trends, deriving a Functional Central Limit Theorem for the partial sample estimators under the null of no break. We show that tests based on sup-Wald statistics are powerful versus breaks of size , also proving that power is present when the time of change differs across units and when only some units have a break. Our framework is extended to the case of cross correlated regressors and endogeneity. Monte Carlo evidence shows that the tests have the correct size and good power properties.

Country Survey: Defense Policy and Military Spending in Taiwan, 1952–2009

In this article we survey military spending, the evolution of national defense policy, and the role that defense spending played in economic activities in Taiwan from 1952 to 2009. With the ongoing cross-Strait dialogue and closer commercial ties between Taiwan and China, the share of military spending in government expenditures (or GDP) has tended to gradually decline, which is in accordance with the change in defense policy from an offensive posture to a defensive-oriented attitude. In addition, we investigate the defense spending–inflation nexus in Taiwan. The multivariate structural change test identifies two break points and three regimes are categorized accordingly. The Granger causality test based on the VAR model reveals that the heavy defense burden in Taiwan during 1952–71 (the first regime) is essentially an important factor causing the higher price levels. However, when the tension across the Taiwan Strait is alleviated as well as the defense-oriented policy adopted, the military spending no longer plays a crucial role in determining inflation in the recent two regimes. Sensitivity analysis confirms that our results are robust to different model specifications.

WALD TESTS FOR DETECTING MULTIPLE STRUCTURAL CHANGES IN PERSISTENCE

This paper considers the problem of testing for multiple structural changes in the persistence of a univariate time series. We propose sup-Wald tests of the null hypothesis that the process has an autoregressive unit root throughout the sample against the alternative hypothesis that the process alternates between stationary and unit root regimes. We derive the limit distributions of the tests under the null and establish their consistency under the relevant alternatives. We further show that the tests are inconsistent when directed against the incorrect alternative, thereby enabling identification of the nature of persistence in the initial regime. We also propose hybrid testing procedures that allow ruling out of stable stationary processes or ones that are subject to only stationary changes under the null, thereby aiding the researcher in interpreting a rejection as emanating from a switch between a unit root and stationary regime. The computation of the test statistics as well as asymptotic critical values is facilitated by the dynamic programming algorithm proposed in Perron and Qu (2006, Journal of Econometrics134, 373–399) which allows imposing within- and cross-regime restrictions on the parameters. Finally, we present Monte Carlo evidence to show that the proposed procedures perform well in finite samples relative to those available in the literature.

Political institutions and sovereign borrowing: evidence from nineteenth-century Argentina

I study the relationship between political institutions and sovereign borrowing when constitutional constraints are systematically chosen to obtain better credit conditions. I argue that the impact of institutional constraints on country risk premia depends on the gov- ernment's concern with the country's creditworthiness and its "willingness to repay"; two variables that are hardly observable. To properly evaluate the relationship between political institutions and sovereign borrowing, I focus on the link between institutional constraints and the risk premia of Argentine bonds between 1822 and 1913. Specifically, I analyze whether a "structural break" in the government's cost of borrowing time-series exists. I use the Perron-Volesang test for structural change with unknown break dates. The statistical analysis indicates that the adoption of institutional constraints led to significant improve- ments in borrowing terms: the series has a single structural change; and the distinctive break point is associated with the country's adoption of constitutional checks and balances. Time- series regressions and instrumental variables (IV) estimation reinforce these findings.

STRUCTURAL CHANGE TESTS BASED ON IMPLIED PROBABILITIES FOR GEL CRITERIA

This paper proposes Pearson-type statistics based on implied probabilities to detect structural change. The class of generalized empirical likelihood estimators (see Smith 1997, The Economic Journal107, 503–519) assigns a set of implied probabilities to each observation such that moment conditions are satisfied. The proposed test statistics for structural change are based on the information content in these implied probabilities. We consider cases of structural change with unknown breakpoint that can occur in the parameters of interest or in the overidentifying restrictions used to estimate these parameters. We also propose a structural change test based on implied probabilities that is robust to weak identification or cases in which parameters are completely unidentified. The test statistics considered here have competitive size and power properties. Moreover, they are computed in a single step, which eliminates the need to compute the weighting matrix required for generalized method of moments estimation.

The Housing Bubble: Monetary Policy or Global Imbalances?

Two recent empirical papers have presented results indicating that the U.S. Federal Reserve deserved much blame as a cause of the latest boom and bust in house prices and activity. Both papers are important contributions, but neither study allows for the impact of long-term interest rates, which are more affected by global factors than the Fed-controlled federal funds rate. In this paper, we include both the thirty-year mortgage rate as well as the fed funds rate as determinants of housing variables. Our results indicate that the long-term rate has independent predictive power for housing when included in equations along with the short-term funds rate. Indeed in some cases, the long-term rate is highly significant while the funds rate is not. We also show that in more recent years, the impact of the funds rate on housing has fallen relative to that of the mortgage rate; indeed in the case of house prices, the mortgage rate is highly significant while the funds rate exhibits barely any effect. Finally, we demonstrate through structural change tests that the mortgage rate does not simply proxy for monetary policy, and that the impact of the funds rate on long-term borrowing costs has also fallen through time. This latter finding is in accord with research showing the increased impotence of individual central banks with respect to long term interest rates.

Long-Term Asset Tail Risk in Developed and Emerging Markets

The tail of financial returns is typically governed by a power law (i.e. “fat tails”). However, the constancy of the so-called tail index α which dictates the tail decay has been hardly investigated. We study the finite sample properties of some recently proposed endogenous tests for structural change in α. Given that the finite sample critical values strongly depend on the tail parameters of the return distribution we propose a bootstrap-based version of the structural change test. Our empirical application spans a wide variety of long-term developed and emerging financial asset returns. Somewhat surprisingly, the tail behavior of emerging stock markets is not more strongly inclined to structural change than their developed counterparts. Emerging currencies, on the contrary, are more prone to shifts in the tail behavior than developed currencies. Our results suggest that extreme value theory (EVT) applications in hedging tail risks or in assessing the (changing) propensity to financial crises can assume stationary tail behavior over long time spans provided one considers portfolios that solely consist of stocks or bonds. However, our break results also indicate it is advisable to use shorter estimation windows when applying EVT methods to emerging currency portfolios.