Saikkonen, Pentti
Overview
Works:  113 works in 171 publications in 2 languages and 402 library holdings 

Roles:  Editor, Author 
Publication Timeline
.
Most widely held works by
Pentti Saikkonen
Essays in nonlinear time series econometrics(
Book
)
10 editions published in 2014 in English and held by 164 WorldCat member libraries worldwide
This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, timevarying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semiautomatic general to specific model selection for nonlinear dynamic models, highdimensional data analysis for parametric and semiparametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession
10 editions published in 2014 in English and held by 164 WorldCat member libraries worldwide
This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, timevarying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semiautomatic general to specific model selection for nonlinear dynamic models, highdimensional data analysis for parametric and semiparametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession
On the estimation of Euler equations in the presence of a potential regime shift by
Pentti Saikkonen(
Book
)
6 editions published in 1999 in English and Undetermined and held by 9 WorldCat member libraries worldwide
Tiivistelmä: Eulerin yhtälöiden estimoinnista mahdollisten regiimin muutosten tapauksessa
6 editions published in 1999 in English and Undetermined and held by 9 WorldCat member libraries worldwide
Tiivistelmä: Eulerin yhtälöiden estimoinnista mahdollisten regiimin muutosten tapauksessa
Comparing asymptotic properties of some tests used in the specification of time series models by
Pentti Saikkonen(
Book
)
4 editions published in 1985 in English and held by 9 WorldCat member libraries worldwide
4 editions published in 1985 in English and held by 9 WorldCat member libraries worldwide
Comparison of unit root tests for time series with level shifts by
Markku Lanne(
Book
)
3 editions published in 1999 in English and German and held by 6 WorldCat member libraries worldwide
Unit root tests are considered for time series which have a level shift at a known point in time. The shift can have a very general nonlinear form and additional deterministic mean and trend terms are allowed for. Prior to the tests the deterministic parts and other nuisance parameters of the data generation process are estimated in a first step. Then the series are adjusted for these terms and unit root tests of the DickeyFuller type are applied to the adjusted series. The properties of previously suggested tests of this sort are analyzed and a range of modifications is proposed which take into account estimation errors in the nuisance parameters. An important result is that estimation under the null hypothesis is preferable to estimation under local alternatives. This contrasts with results obtained by other authors for time series without level shifts
3 editions published in 1999 in English and German and held by 6 WorldCat member libraries worldwide
Unit root tests are considered for time series which have a level shift at a known point in time. The shift can have a very general nonlinear form and additional deterministic mean and trend terms are allowed for. Prior to the tests the deterministic parts and other nuisance parameters of the data generation process are estimated in a first step. Then the series are adjusted for these terms and unit root tests of the DickeyFuller type are applied to the adjusted series. The properties of previously suggested tests of this sort are analyzed and a range of modifications is proposed which take into account estimation errors in the nuisance parameters. An important result is that estimation under the null hypothesis is preferable to estimation under local alternatives. This contrasts with results obtained by other authors for time series without level shifts
Stability results for nonlinear vector autoregressions with an application to a nonlinear error correction model by
Pentti Saikkonen(
Book
)
3 editions published in 2001 in English and held by 6 WorldCat member libraries worldwide
This paper improves previous sufficient conditions for stationarity obtained in the context of a general nonlinear vector autoregressive model with nonlinear autoregressive conditional heteroskedasticity. The results are proved by using the stability theory developed for Markov chains. Stationarity, existence of second moments of the stationary distribution, and useful mixing results are obtained by establishing appropriate versions of geometric ergodicity. The results are applied to a nonlinear error correction model to obtain an analog of Granger's representation theorem.  Geometric ergodicity ; Markov chain ; Mixing ; Nonlinear error correction model ; Nonlinear vector autoregressive process ; Stability
3 editions published in 2001 in English and held by 6 WorldCat member libraries worldwide
This paper improves previous sufficient conditions for stationarity obtained in the context of a general nonlinear vector autoregressive model with nonlinear autoregressive conditional heteroskedasticity. The results are proved by using the stability theory developed for Markov chains. Stationarity, existence of second moments of the stationary distribution, and useful mixing results are obtained by establishing appropriate versions of geometric ergodicity. The results are applied to a nonlinear error correction model to obtain an analog of Granger's representation theorem.  Geometric ergodicity ; Markov chain ; Mixing ; Nonlinear error correction model ; Nonlinear vector autoregressive process ; Stability
Maximum eigenvalue versus trace tests for the cointegrating rank of a VAR process by
Helmut Lütkepohl(
Book
)
3 editions published in 2000 in English and held by 6 WorldCat member libraries worldwide
The properties of a range of maximum eigenvalue and trace tests for the cointegrating rank of a vector autoregressive process are compared. The tests are alilikelihood ratio type tests and operate under different assumptions regarding the deterministic part of the data generation process. The asymptotic distributions under local alternatives are given and the local power is derived. It is found that the local power of corresponding maximum eigenvalue and trace tests is very similar. A Monte Carlo comparison shows, however, that there may be slight differences in small sampies. The trace tests tend to have more distorted sizes whereas their power is in some situations superior to that of the maximum eigenvalue tests
3 editions published in 2000 in English and held by 6 WorldCat member libraries worldwide
The properties of a range of maximum eigenvalue and trace tests for the cointegrating rank of a vector autoregressive process are compared. The tests are alilikelihood ratio type tests and operate under different assumptions regarding the deterministic part of the data generation process. The asymptotic distributions under local alternatives are given and the local power is derived. It is found that the local power of corresponding maximum eigenvalue and trace tests is very similar. A Monte Carlo comparison shows, however, that there may be slight differences in small sampies. The trace tests tend to have more distorted sizes whereas their power is in some situations superior to that of the maximum eigenvalue tests
Unit root tests in the presence of innovational outliers by
Markku Lanne(
Book
)
3 editions published in 2001 in English and held by 6 WorldCat member libraries worldwide
Unit root tests are considered for time series with innovational outliers. The function representing the outliers can have a very general nonlinear form and additional deterministic mean and trend terms are allowed for. Prior to the tests the deterministic parts and other nuisance parameters of the data generation process are estimated in a first step. Then the series are adjusted for these terms and unit raot tests of the DickeyFuller type are applied to the adjusted series. The properties of previously suggested tests of this sort are analyzed and modifications are proposed which take into account estimation errors in the nuisance parameters. An important result is that estimation under the null hypothesis is preferable to estimation under local alternatives. This contrasts with results obtained by other authors for time series without outliers. A comparison with additive outlier models is also performed.  Univariate time series ; unit root ; structural shift ; autoregression
3 editions published in 2001 in English and held by 6 WorldCat member libraries worldwide
Unit root tests are considered for time series with innovational outliers. The function representing the outliers can have a very general nonlinear form and additional deterministic mean and trend terms are allowed for. Prior to the tests the deterministic parts and other nuisance parameters of the data generation process are estimated in a first step. Then the series are adjusted for these terms and unit raot tests of the DickeyFuller type are applied to the adjusted series. The properties of previously suggested tests of this sort are analyzed and modifications are proposed which take into account estimation errors in the nuisance parameters. An important result is that estimation under the null hypothesis is preferable to estimation under local alternatives. This contrasts with results obtained by other authors for time series without outliers. A comparison with additive outlier models is also performed.  Univariate time series ; unit root ; structural shift ; autoregression
Comparison of tests for the cointegrating rank of VAR process with a structural shift by
Helmut Lütkepohl(
Book
)
3 editions published in 2000 in English and held by 6 WorldCat member libraries worldwide
Two different types of tests for the cointegrating rank of VAR processes with a deterministic shift in the level have been proposed in the literature. The first proposal is based on the LR principle using a specific Gaussian model setup. In the second proposal the time series are adjusted for deterministic terms first and then LR type tests are applied to the adjusted series. The local power of the two types of tests is derived and compared. Moreover, the small sample size and power properties of the tests are explored. It is found that the tests based on adjusted series generally have superior local power and size properties.  local power ; test size ; cointegration ; vector autoregressive process ; error correction model
3 editions published in 2000 in English and held by 6 WorldCat member libraries worldwide
Two different types of tests for the cointegrating rank of VAR processes with a deterministic shift in the level have been proposed in the literature. The first proposal is based on the LR principle using a specific Gaussian model setup. In the second proposal the time series are adjusted for deterministic terms first and then LR type tests are applied to the adjusted series. The local power of the two types of tests is derived and compared. Moreover, the small sample size and power properties of the tests are explored. It is found that the tests based on adjusted series generally have superior local power and size properties.  local power ; test size ; cointegration ; vector autoregressive process ; error correction model
Test procedures for unit roots in time series with level shifts at unknown time by
Markku Lanne(
Book
)
3 editions published in 2001 in English and held by 6 WorldCat member libraries worldwide
Two types of unit root tests which accommodate a structural level shift at a known point in time are extended to the situation where the break date is unknown. It is shown that for any estimator for the break date the tests have the same asymptotic distribution as the corresponding tests under the known break date assumption. Different estimators of the break date are compared in a Monte Carlo experiment and a recommendation for choosing the break date in small samples is given. It is also shown that ignoring the fact that a break has occurred and applying a standard unit root test may lead to substantial size distortion and total loss of power. Example series from the NelsonPlosser data set are used to illustrate the performance of our tests.  Univariate time series ; unit root ; structural shift ; autoregression
3 editions published in 2001 in English and held by 6 WorldCat member libraries worldwide
Two types of unit root tests which accommodate a structural level shift at a known point in time are extended to the situation where the break date is unknown. It is shown that for any estimator for the break date the tests have the same asymptotic distribution as the corresponding tests under the known break date assumption. Different estimators of the break date are compared in a Monte Carlo experiment and a recommendation for choosing the break date in small samples is given. It is also shown that ignoring the fact that a break has occurred and applying a standard unit root test may lead to substantial size distortion and total loss of power. Example series from the NelsonPlosser data set are used to illustrate the performance of our tests.  Univariate time series ; unit root ; structural shift ; autoregression
Comparing asymptotic properties of some tests used in the specification of time series models by
Pentti Saikkonen(
Book
)
1 edition published in 1985 in English and held by 5 WorldCat member libraries worldwide
1 edition published in 1985 in English and held by 5 WorldCat member libraries worldwide
Cointegrating smooth transition regressions with application to the Asian currency crisis by
Pentti Saikkonen(
Book
)
3 editions published in 2000 in English and held by 5 WorldCat member libraries worldwide
This paper studies the smooth transition regression model where regressors are I(1) and errors are I(0). The regressors and errors are assumed to be dependent both serially and contemporaneously. Using the triangular array asymptotics, the nonlinear least squares estimator is shown to be consistent and its asymptotic distribution is derived. It is found that the asymptotic distribution involves a bias under the regressorerror dependence, which implies that the nonlinear least squares estimator is inefficient and unsuitable for use in hypothesis testing. Thus, this paper proposes a GaussNewton type estimator which uses the NLLS estimator as an initial estimator and is based on regressions augmented by leadsandlags. Using leadsandlags enables the GaussNewton estimator to eliminate the bias and have a mixture normal distribution in the limit, which makes it efficient and suitable for use in hypothesis testing. Simulation results indicate that the results obtained from the triangular array asymptotics provide reasonable approximations for the Þnite sample properties of the estimators and ttests when sample sizes are moderately large. The cointegrating smooth transition regression model is applied to the Korean and Indonesian data from the Asian currency crisis of 1997. SigniÞcant nonlinear effects of interest rate on spot exchange rate are found to be present in the Korean data, which partially supports the interest Laffer curve hypothesis. But overall the effects of interest rate on spot exchange rate are shown to be quite negligible in both the nations
3 editions published in 2000 in English and held by 5 WorldCat member libraries worldwide
This paper studies the smooth transition regression model where regressors are I(1) and errors are I(0). The regressors and errors are assumed to be dependent both serially and contemporaneously. Using the triangular array asymptotics, the nonlinear least squares estimator is shown to be consistent and its asymptotic distribution is derived. It is found that the asymptotic distribution involves a bias under the regressorerror dependence, which implies that the nonlinear least squares estimator is inefficient and unsuitable for use in hypothesis testing. Thus, this paper proposes a GaussNewton type estimator which uses the NLLS estimator as an initial estimator and is based on regressions augmented by leadsandlags. Using leadsandlags enables the GaussNewton estimator to eliminate the bias and have a mixture normal distribution in the limit, which makes it efficient and suitable for use in hypothesis testing. Simulation results indicate that the results obtained from the triangular array asymptotics provide reasonable approximations for the Þnite sample properties of the estimators and ttests when sample sizes are moderately large. The cointegrating smooth transition regression model is applied to the Korean and Indonesian data from the Asian currency crisis of 1997. SigniÞcant nonlinear effects of interest rate on spot exchange rate are found to be present in the Korean data, which partially supports the interest Laffer curve hypothesis. But overall the effects of interest rate on spot exchange rate are shown to be quite negligible in both the nations
Testing for the cointegrating rank of a VAR process with level shift at unknown time by
Helmut Lütkepohl(
Book
)
2 editions published in 2001 in English and held by 5 WorldCat member libraries worldwide
A systems cointegration rank test is proposed which is applicable for vector autoregressive (VAR) processes with a structural shift at unknown time. The structural shift is modeled as a simple shift in the mean of the process. It is proposed to estimate the break date first on the basis of a full unrestricted VAR model. Two alternative estimators are considered and their asymptotic properties are derived. In the next step the deterministic part of the process including the shift size is estimated with a GLS procedure. Then the series are adjusted by subtracting the estimated deterministic part and a Johansen type test for the cointegrating rank is applied to the adjusted series. The test statistic is shown to have a wellknown asymptotic null distribution which does not depend on the break date. The performance of the procedure in small samples is investigated by simulations. Finally, the procedure is applied for two sets of example series to illustrate its virtue for econometric analyses.  Cointegration ; structural break ; vector autoregressive process ; error correction model
2 editions published in 2001 in English and held by 5 WorldCat member libraries worldwide
A systems cointegration rank test is proposed which is applicable for vector autoregressive (VAR) processes with a structural shift at unknown time. The structural shift is modeled as a simple shift in the mean of the process. It is proposed to estimate the break date first on the basis of a full unrestricted VAR model. Two alternative estimators are considered and their asymptotic properties are derived. In the next step the deterministic part of the process including the shift size is estimated with a GLS procedure. Then the series are adjusted by subtracting the estimated deterministic part and a Johansen type test for the cointegrating rank is applied to the adjusted series. The test statistic is shown to have a wellknown asymptotic null distribution which does not depend on the break date. The performance of the procedure in small samples is investigated by simulations. Finally, the procedure is applied for two sets of example series to illustrate its virtue for econometric analyses.  Cointegration ; structural break ; vector autoregressive process ; error correction model
Nonlinear GARCH models for highly persistent volatility by
Markku Lanne(
Book
)
3 editions published in 2002 in English and held by 5 WorldCat member libraries worldwide
In this paper we study new nonlinear GARCH models mainly designed for time series with highly persistent volatility. For such series, conventional GARCH models have often proved unsatisfactory because they tend to exaggerate volatility persistence and exhibit poor forecasting ability. Our main emphasis is on models that are similar to previously introduced smooth transition GARCH models except for the novel feature that a lagged value of conditional variance is used as the transition variable. This choice of the transition variable corresponds to the idea that high persistence in conditional variance is related to relatively infrequent changes in regime. U sing the theory of Markov chains we provide sufficient conditions for the stationarity and existence of moments of the considered smooth transition GARCH models and even some more general nonlinear GARCH models. Empirical applications to two exchange rate return series show that the new models can be superior to conventional GARCH models especially in longer term forecasting
3 editions published in 2002 in English and held by 5 WorldCat member libraries worldwide
In this paper we study new nonlinear GARCH models mainly designed for time series with highly persistent volatility. For such series, conventional GARCH models have often proved unsatisfactory because they tend to exaggerate volatility persistence and exhibit poor forecasting ability. Our main emphasis is on models that are similar to previously introduced smooth transition GARCH models except for the novel feature that a lagged value of conditional variance is used as the transition variable. This choice of the transition variable corresponds to the idea that high persistence in conditional variance is related to relatively infrequent changes in regime. U sing the theory of Markov chains we provide sufficient conditions for the stationarity and existence of moments of the considered smooth transition GARCH models and even some more general nonlinear GARCH models. Empirical applications to two exchange rate return series show that the new models can be superior to conventional GARCH models especially in longer term forecasting
Testing for unit roots in time series with level shifts by
Pentti Saikkonen(
Book
)
2 editions published in 1999 in English and held by 5 WorldCat member libraries worldwide
Tests for unit roots in univariate time series with level shifts are proposed and investigated. The level shift is assumed to occur at a known time. It may be a simple onetime shift which can be captured by a dummy variable or it may have a more general form which can be modeled by some general nonlinear transition function. There may also be more than one shift point and there may be other deterministic terms such as a linear trend term or seasonal components. It is proposed to estimate the deterministic parts of the series in a first step by a generalized least squares procedure subtract the estimated deterministic terms from the series and apply standard unit root tests to the residuals. It is shown that the tests have known asymptotic distributions under the null hypothesis of a unit root and nearly optimal asymptotic power under local alternatives. The procedure is applied to German macroeconomic time series which have a level shift in 1990 where the reunification took place.  unit root ; structural shift ; autoregression ; Univariate time series
2 editions published in 1999 in English and held by 5 WorldCat member libraries worldwide
Tests for unit roots in univariate time series with level shifts are proposed and investigated. The level shift is assumed to occur at a known time. It may be a simple onetime shift which can be captured by a dummy variable or it may have a more general form which can be modeled by some general nonlinear transition function. There may also be more than one shift point and there may be other deterministic terms such as a linear trend term or seasonal components. It is proposed to estimate the deterministic parts of the series in a first step by a generalized least squares procedure subtract the estimated deterministic terms from the series and apply standard unit root tests to the residuals. It is shown that the tests have known asymptotic distributions under the null hypothesis of a unit root and nearly optimal asymptotic power under local alternatives. The procedure is applied to German macroeconomic time series which have a level shift in 1990 where the reunification took place.  unit root ; structural shift ; autoregression ; Univariate time series
Modeling the U.S. shortterm interest rate by mixture autoregressive processes by
Markku Lanne(
Book
)
3 editions published in 2000 in English and held by 5 WorldCat member libraries worldwide
A new kind of mixture autoregressive model with GARCH errors is introduced and applied to the U.S. shortterm interest rate. According to the diagnostic tests developed in the paper and further informal checks the model is capable of capturing both of the typical characteristics of the shortterm interest rate: volatility persistence and the dependence of volatility on the level of the interest rate. The model also allows for regime switches whose presence has been a third central result emerging from the recent empirical literature on the U.S. shortterm interest rate. Realizations generated from the estimated model seem stable and their properties resemble those of the observed series closely. The drift and diffusion functions implied by the new model are in accordance with the results in much of the literature on continuoustime diffusion models for the shortterm interest rate, and the term structure implications agree with historically observed patterns
3 editions published in 2000 in English and held by 5 WorldCat member libraries worldwide
A new kind of mixture autoregressive model with GARCH errors is introduced and applied to the U.S. shortterm interest rate. According to the diagnostic tests developed in the paper and further informal checks the model is capable of capturing both of the typical characteristics of the shortterm interest rate: volatility persistence and the dependence of volatility on the level of the interest rate. The model also allows for regime switches whose presence has been a third central result emerging from the recent empirical literature on the U.S. shortterm interest rate. Realizations generated from the estimated model seem stable and their properties resemble those of the observed series closely. The drift and diffusion functions implied by the new model are in accordance with the results in much of the literature on continuoustime diffusion models for the shortterm interest rate, and the term structure implications agree with historically observed patterns
Cointegrated vector autoregressive process with continuous structural changes by
Antti Ripatti(
Book
)
4 editions published in 1998 in English and Undetermined and held by 4 WorldCat member libraries worldwide
Tiivistelmä: Jatkuvat rakennemuutokset yhteisintegroituvissa VARmalleissa
4 editions published in 1998 in English and Undetermined and held by 4 WorldCat member libraries worldwide
Tiivistelmä: Jatkuvat rakennemuutokset yhteisintegroituvissa VARmalleissa
A review of systems cointegration tests by
Kirstin Hubrich(
Book
)
2 editions published in 1998 in English and held by 4 WorldCat member libraries worldwide
2 editions published in 1998 in English and held by 4 WorldCat member libraries worldwide
Trend adjustment prior to testing for the cointegrating rank of a VAR process by
Pentti Saikkonen(
Book
)
2 editions published in 1997 in English and held by 4 WorldCat member libraries worldwide
Testing the cointegrating rank of a vector autoregressive process which may have a deterministic linear trend is considered. Previous proposals for dealing with such a situation are either to allow for a deterministic trend term in computing a suitable test statistic or else remove the linear trend first and then derive the test statistic from the trendadjusted data. In this study the latter approach is considered and a new, simple method for trend removal is proposed which is based on estimating the trend parameters under the null hypothesis. LR (likelihood ratio) and LM (Lagrange multiplier) type test statistics are derived on the basis of the trendadjusted data and their asymptotic distributions are considered under the null hypothesis and under local alternatives. A simulation comparison with other proposals is performed which demonstrates the potentially superior small sample performance of the new tests
2 editions published in 1997 in English and held by 4 WorldCat member libraries worldwide
Testing the cointegrating rank of a vector autoregressive process which may have a deterministic linear trend is considered. Previous proposals for dealing with such a situation are either to allow for a deterministic trend term in computing a suitable test statistic or else remove the linear trend first and then derive the test statistic from the trendadjusted data. In this study the latter approach is considered and a new, simple method for trend removal is proposed which is based on estimating the trend parameters under the null hypothesis. LR (likelihood ratio) and LM (Lagrange multiplier) type test statistics are derived on the basis of the trendadjusted data and their asymptotic distributions are considered under the null hypothesis and under local alternatives. A simulation comparison with other proposals is performed which demonstrates the potentially superior small sample performance of the new tests
Testing for unit roots in time series with level shift at unknown time by
Pentti Saikkonen(
Book
)
1 edition published in 1999 in English and held by 4 WorldCat member libraries worldwide
1 edition published in 1999 in English and held by 4 WorldCat member libraries worldwide
Local power of likelihood ratio tests for the cointegrating rank of a VAR process by
Pentti Saikkonen(
Book
)
2 editions published in 1997 in English and held by 4 WorldCat member libraries worldwide
Likelihood ratio (LR) tests for the cointegrating rank of a vector autoregressive (VAR) process have been developed under different assumptions regarding deterministic terms. For instance, nonzero mean terms and linear trends have been accounted for in some of the tests. In this paper we provide a general framework for deriving the local power properties of these tests. Thereby it is possible to assess the virtue of utilizing varying amounts of prior information by making assumptions regarding the deterministic terms. One interesting result from this analysis is that if no assumptions regarding the specic form of the mean term are made while a linear trend is excluded then a test is available which has the same local power as an LR test derived under a zero mean assumption
2 editions published in 1997 in English and held by 4 WorldCat member libraries worldwide
Likelihood ratio (LR) tests for the cointegrating rank of a vector autoregressive (VAR) process have been developed under different assumptions regarding deterministic terms. For instance, nonzero mean terms and linear trends have been accounted for in some of the tests. In this paper we provide a general framework for deriving the local power properties of these tests. Thereby it is possible to assess the virtue of utilizing varying amounts of prior information by making assumptions regarding the deterministic terms. One interesting result from this analysis is that if no assumptions regarding the specic form of the mean term are made while a linear trend is excluded then a test is available which has the same local power as an LR test derived under a zero mean assumption
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 Meitz, Mika Author Editor
 Haldrup, Niels Editor
 Lütkepohl, Helmut Author
 Lanne, Markku Author
 Sonderforschungsbereich Quantifikation und Simulation Ökonomischer Prozesse
 Trenkler, Carsten Author
 Ripatti, Antti Author
 European University Institute Department of Economics
 Meitz, Mika Author
 Choi, In
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Alternative Names
Pentti Saikkonen Finnish statistician
Pentti Saikkonen Finnish statistician, professor emeritus of statistics (University of Helsinki)
Pentti Saikkonen Fins statisticus
Pentti Saikkonen suomalainen tilastotieteilijä, tilastotieteen emeritusprofessori Helsingin yliopistolla
Saikkonen, Pentii
Saikkonen, Pentti Juhani, 1952
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