Threshold effect in varying coefficient models with unknown heteroskedasticity
This paper extends the threshold regression to threshold effect in varying coefficient model. We allow for either cross-section or time series observations. Estimation of the regression parameters is considered. An asymptotic distribution theory for the regression estimates (the threshold and the re...
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Veröffentlicht in: | Computational statistics 2024-05, Vol.39 (3), p.1165-1181 |
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description | This paper extends the threshold regression to threshold effect in varying coefficient model. We allow for either cross-section or time series observations. Estimation of the regression parameters is considered. An asymptotic distribution theory for the regression estimates (the threshold and the regression slopes) is developed. The distribution of threshold estimates is found to be non-standard. Under some sufficient conditions, we show that the proposed estimator for regression slopes is root-n consistent and asymptotically normally distributed, and that the proposed estimator for the varying coefficient is consistent and also asymptotically normal distributed but at a rate slower than root-n. Consistent estimators for the asymptotic variances of the proposed estimators are provided. Monte Carlo simulations are presented to assess the performance of the asymptotic approximations. The empirical relevance of the theory is illustrated through an application to the relationship between environmental regulation and regional technological innovation study. |
doi_str_mv | 10.1007/s00180-023-01335-7 |
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The empirical relevance of the theory is illustrated through an application to the relationship between environmental regulation and regional technological innovation study.</description><subject>Asymptotic properties</subject><subject>Coefficients</subject><subject>Data analysis</subject><subject>Economic Theory/Quantitative Economics/Mathematical Methods</subject><subject>Estimates</subject><subject>Estimators</subject><subject>Mathematics and Statistics</subject><subject>Monte Carlo simulation</subject><subject>Original Paper</subject><subject>Probability and Statistics in Computer Science</subject><subject>Probability Theory and Stochastic Processes</subject><subject>Regression</subject><subject>Statistics</subject><subject>Time series</subject><issn>0943-4062</issn><issn>1613-9658</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kMlOwzAQhi0EEqXwApwscQ6MPYnjHFHFJlVwKWcry7hJl6TYLlXfHkOQuHEaafT9s3yMXQu4FQD5nQcQGhKQmIBAzJL8hE2EEpgUKtOnbAJFikkKSp6zC-9XAFLmUkzY66J15Nth03CylurAu55_lu7Y9UteD7HX1R31gW-HhjaeH7rQ8n2_7odDz1sK5Aa_pqb0IXLheMnObLnxdPVbp-z98WExe07mb08vs_t5UsscQiIbQpU2NiVbaStT1dgKUddVDaXQlcpTVWDa5FkpLGYCgTQWIDOhKZN5SjhlN-PcnRs-9uSDWQ1718eVBgGxkIXOVKTkSNXxSu_Imp3rtvE5I8B8ezOjNxO9mR9vJo8hHEM-wv2S3N_of1Jf8INwyA</recordid><startdate>20240501</startdate><enddate>20240501</enddate><creator>Zhang, Yuanqing</creator><creator>Ai, Chunrong</creator><creator>Feng, Yaqin</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20240501</creationdate><title>Threshold effect in varying coefficient models with unknown heteroskedasticity</title><author>Zhang, Yuanqing ; Ai, Chunrong ; Feng, Yaqin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c270t-2de364df4efb8f246dfb338cbc0a18b6746934d75a1f35130e83902518e5274e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Asymptotic properties</topic><topic>Coefficients</topic><topic>Data analysis</topic><topic>Economic Theory/Quantitative Economics/Mathematical Methods</topic><topic>Estimates</topic><topic>Estimators</topic><topic>Mathematics and Statistics</topic><topic>Monte Carlo simulation</topic><topic>Original Paper</topic><topic>Probability and Statistics in Computer Science</topic><topic>Probability Theory and Stochastic Processes</topic><topic>Regression</topic><topic>Statistics</topic><topic>Time series</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Yuanqing</creatorcontrib><creatorcontrib>Ai, Chunrong</creatorcontrib><creatorcontrib>Feng, Yaqin</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computational statistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Yuanqing</au><au>Ai, Chunrong</au><au>Feng, Yaqin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Threshold effect in varying coefficient models with unknown heteroskedasticity</atitle><jtitle>Computational statistics</jtitle><stitle>Comput Stat</stitle><date>2024-05-01</date><risdate>2024</risdate><volume>39</volume><issue>3</issue><spage>1165</spage><epage>1181</epage><pages>1165-1181</pages><issn>0943-4062</issn><eissn>1613-9658</eissn><abstract>This paper extends the threshold regression to threshold effect in varying coefficient model. 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subjects | Asymptotic properties Coefficients Data analysis Economic Theory/Quantitative Economics/Mathematical Methods Estimates Estimators Mathematics and Statistics Monte Carlo simulation Original Paper Probability and Statistics in Computer Science Probability Theory and Stochastic Processes Regression Statistics Time series |
title | Threshold effect in varying coefficient models with unknown heteroskedasticity |
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