A new nonparametric stability test with an application to major Chinese macroeconomic time series
Abstract In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new met...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cai, Nan [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Schlagwörter: |
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| Anmerkung: |
© Editorial Committee of Applied Mathematics-A Journal of Chinese Universities and Springer-Verlag Berlin Heidelberg 2013 |
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| Übergeordnetes Werk: |
Enthalten in: Applied mathematics - Berlin [u.a.] : Editorial commitee of applied mathematics, 1993, 28(2013), 1 vom: März, Seite 1-16 |
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| Übergeordnetes Werk: |
volume:28 ; year:2013 ; number:1 ; month:03 ; pages:1-16 |
| Links: |
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| DOI / URN: |
10.1007/s11766-013-3097-7 |
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| Katalog-ID: |
SPR022294686 |
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| 100 | 1 | |a Cai, Nan |e verfasserin |4 aut | |
| 245 | 1 | 2 | |a A new nonparametric stability test with an application to major Chinese macroeconomic time series |
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| 520 | |a Abstract In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new method to test the stability of bivariate relations among 92 major Chinese macroeconomic time series. We find that more than 70% bivariate relations are significantly unstable. | ||
| 650 | 4 | |a LASSO |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a stability test |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a time-varying coefficients model |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a wild bootstrap |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Cai, Zong-wu |4 aut | |
| 700 | 1 | |a Fang, Ying |4 aut | |
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10.1007/s11766-013-3097-7 doi (DE-627)SPR022294686 (SPR)s11766-013-3097-7-e DE-627 ger DE-627 rakwb eng Cai, Nan verfasserin aut A new nonparametric stability test with an application to major Chinese macroeconomic time series 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Editorial Committee of Applied Mathematics-A Journal of Chinese Universities and Springer-Verlag Berlin Heidelberg 2013 Abstract In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new method to test the stability of bivariate relations among 92 major Chinese macroeconomic time series. We find that more than 70% bivariate relations are significantly unstable. LASSO (dpeaa)DE-He213 stability test (dpeaa)DE-He213 time-varying coefficients model (dpeaa)DE-He213 wild bootstrap (dpeaa)DE-He213 Cai, Zong-wu aut Fang, Ying aut Enthalten in Applied mathematics Berlin [u.a.] : Editorial commitee of applied mathematics, 1993 28(2013), 1 vom: März, Seite 1-16 (DE-627)527579777 (DE-600)2277401-4 1993-0445 nnns volume:28 year:2013 number:1 month:03 pages:1-16 https://dx.doi.org/10.1007/s11766-013-3097-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_4753 AR 28 2013 1 03 1-16 |
| spelling |
10.1007/s11766-013-3097-7 doi (DE-627)SPR022294686 (SPR)s11766-013-3097-7-e DE-627 ger DE-627 rakwb eng Cai, Nan verfasserin aut A new nonparametric stability test with an application to major Chinese macroeconomic time series 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Editorial Committee of Applied Mathematics-A Journal of Chinese Universities and Springer-Verlag Berlin Heidelberg 2013 Abstract In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new method to test the stability of bivariate relations among 92 major Chinese macroeconomic time series. We find that more than 70% bivariate relations are significantly unstable. LASSO (dpeaa)DE-He213 stability test (dpeaa)DE-He213 time-varying coefficients model (dpeaa)DE-He213 wild bootstrap (dpeaa)DE-He213 Cai, Zong-wu aut Fang, Ying aut Enthalten in Applied mathematics Berlin [u.a.] : Editorial commitee of applied mathematics, 1993 28(2013), 1 vom: März, Seite 1-16 (DE-627)527579777 (DE-600)2277401-4 1993-0445 nnns volume:28 year:2013 number:1 month:03 pages:1-16 https://dx.doi.org/10.1007/s11766-013-3097-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_4753 AR 28 2013 1 03 1-16 |
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10.1007/s11766-013-3097-7 doi (DE-627)SPR022294686 (SPR)s11766-013-3097-7-e DE-627 ger DE-627 rakwb eng Cai, Nan verfasserin aut A new nonparametric stability test with an application to major Chinese macroeconomic time series 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Editorial Committee of Applied Mathematics-A Journal of Chinese Universities and Springer-Verlag Berlin Heidelberg 2013 Abstract In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new method to test the stability of bivariate relations among 92 major Chinese macroeconomic time series. We find that more than 70% bivariate relations are significantly unstable. LASSO (dpeaa)DE-He213 stability test (dpeaa)DE-He213 time-varying coefficients model (dpeaa)DE-He213 wild bootstrap (dpeaa)DE-He213 Cai, Zong-wu aut Fang, Ying aut Enthalten in Applied mathematics Berlin [u.a.] : Editorial commitee of applied mathematics, 1993 28(2013), 1 vom: März, Seite 1-16 (DE-627)527579777 (DE-600)2277401-4 1993-0445 nnns volume:28 year:2013 number:1 month:03 pages:1-16 https://dx.doi.org/10.1007/s11766-013-3097-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_4753 AR 28 2013 1 03 1-16 |
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10.1007/s11766-013-3097-7 doi (DE-627)SPR022294686 (SPR)s11766-013-3097-7-e DE-627 ger DE-627 rakwb eng Cai, Nan verfasserin aut A new nonparametric stability test with an application to major Chinese macroeconomic time series 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Editorial Committee of Applied Mathematics-A Journal of Chinese Universities and Springer-Verlag Berlin Heidelberg 2013 Abstract In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new method to test the stability of bivariate relations among 92 major Chinese macroeconomic time series. We find that more than 70% bivariate relations are significantly unstable. LASSO (dpeaa)DE-He213 stability test (dpeaa)DE-He213 time-varying coefficients model (dpeaa)DE-He213 wild bootstrap (dpeaa)DE-He213 Cai, Zong-wu aut Fang, Ying aut Enthalten in Applied mathematics Berlin [u.a.] : Editorial commitee of applied mathematics, 1993 28(2013), 1 vom: März, Seite 1-16 (DE-627)527579777 (DE-600)2277401-4 1993-0445 nnns volume:28 year:2013 number:1 month:03 pages:1-16 https://dx.doi.org/10.1007/s11766-013-3097-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_4753 AR 28 2013 1 03 1-16 |
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Cai, Nan |
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Cai, Nan misc LASSO misc stability test misc time-varying coefficients model misc wild bootstrap A new nonparametric stability test with an application to major Chinese macroeconomic time series |
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A new nonparametric stability test with an application to major Chinese macroeconomic time series LASSO (dpeaa)DE-He213 stability test (dpeaa)DE-He213 time-varying coefficients model (dpeaa)DE-He213 wild bootstrap (dpeaa)DE-He213 |
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misc LASSO misc stability test misc time-varying coefficients model misc wild bootstrap |
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A new nonparametric stability test with an application to major Chinese macroeconomic time series |
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10.1007/s11766-013-3097-7 |
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new nonparametric stability test with an application to major chinese macroeconomic time series |
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A new nonparametric stability test with an application to major Chinese macroeconomic time series |
| abstract |
Abstract In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new method to test the stability of bivariate relations among 92 major Chinese macroeconomic time series. We find that more than 70% bivariate relations are significantly unstable. © Editorial Committee of Applied Mathematics-A Journal of Chinese Universities and Springer-Verlag Berlin Heidelberg 2013 |
| abstractGer |
Abstract In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new method to test the stability of bivariate relations among 92 major Chinese macroeconomic time series. We find that more than 70% bivariate relations are significantly unstable. © Editorial Committee of Applied Mathematics-A Journal of Chinese Universities and Springer-Verlag Berlin Heidelberg 2013 |
| abstract_unstemmed |
Abstract In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new method to test the stability of bivariate relations among 92 major Chinese macroeconomic time series. We find that more than 70% bivariate relations are significantly unstable. © Editorial Committee of Applied Mathematics-A Journal of Chinese Universities and Springer-Verlag Berlin Heidelberg 2013 |
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A new nonparametric stability test with an application to major Chinese macroeconomic time series |
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https://dx.doi.org/10.1007/s11766-013-3097-7 |
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Cai, Zong-wu Fang, Ying |
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Cai, Zong-wu Fang, Ying |
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| doi_str |
10.1007/s11766-013-3097-7 |
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2024-07-04T02:35:25.171Z |
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| score |
7.3998594 |