ScholarGate
어시스턴트

방법 비교

선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.

시변수 비선형 자기회귀분포지연 (TVP-NARDL)×ARDL 경계 검정 (Pesaran 경계 검정)×
분야계량경제학계량경제학
계열Regression modelRegression model
기원 연도2019 (TVP extension); 2014 (NARDL base)2001
창시자Bagnai & Ospina-Rojas (TVP extension); NARDL base by Shin, Yu & Greenwood-NimmoPesaran, Shin & Smith
유형Nonlinear time-series model with time-varying coefficientsCointegration test / Autoregressive distributed lag model
원전Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In W. Horrace & R. Sickles (Eds.), Festschrift in Honor of Peter Schmidt (pp. 281–314). Springer. link ↗Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16(3), 289–326. DOI ↗
별칭TVP-NARDL, time-varying NARDL, rolling NARDL, dynamic asymmetric ARDLPesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)
관련34
요약The Time-Varying Parameter NARDL (TVP-NARDL) model extends the Nonlinear ARDL framework by allowing the coefficients on positive and negative partial sums of a regressor to change over time. This combination captures both asymmetric responses and structural instability in long-run and short-run relationships within a single cointegrating specification.The ARDL bounds test is an autoregressive distributed lag method that tests for a cointegrating (long-run level) relationship between time series, introduced by Pesaran, Shin and Smith in 2001. Unlike the Johansen procedure, it remains valid whether the variables are I(0), I(1) or a mix of the two, and it is more reliable than Johansen in small samples of roughly 30 to 80 observations.
ScholarGate데이터셋
  1. v1
  2. 2 출처
  3. PUBLISHED
  1. v1
  2. 2 출처
  3. PUBLISHED

검색으로 이동 슬라이드 다운로드

ScholarGate방법 비교: Time-varying parameter NARDL · ARDL Bounds Test. 2026-06-17에 다음에서 검색함: https://scholargate.app/ko/compare