Statistics — Page 68
Explore statistical methods, their assumptions, interpretation and limitations.
Research field
Method family
Structural Break OLS
Structural Break OLS extends ordinary least squares to allow regression coefficients to shift at one or more breakpoints in time or across regimes. Rather than forcing a single coefficient vector across the entire sample, the model partitio...
Structural Break Panel Data Analysis
Structural break panel data analysis detects and estimates points in time — break dates — where the underlying regression coefficients shift permanently across a panel of cross-sectional units observed over multiple periods. By jointly expl...
Structural Break Quantile-on-Quantile Regression
Structural Break Quantile-on-Quantile Regression (SB-QQR) extends the quantile-on-quantile framework of Sim and Zhou (2015) by allowing regression slopes to differ across regimes separated by structural breaks. It maps how the effect of a p...
Structural Break Random Effects Model
The structural break random effects model extends standard panel RE estimation by allowing one or more breakpoints at which slope coefficients or error variances shift across time. It combines structural change detection (e.g., Bai-Perron)...
Structural Break SARIMA Model
The Structural Break SARIMA model extends the classical Seasonal ARIMA framework by explicitly detecting and accommodating abrupt, permanent shifts in the level, trend, or seasonal pattern of a time series. Rather than forcing a single SARI...
Structural Break System GMM
Structural Break System GMM extends the Blundell-Bond System GMM estimator for dynamic panel data by explicitly accounting for structural breaks — abrupt regime changes in slopes, intercepts, or dynamics — that, if ignored, bias the coeffic...
Structural Break TGARCH
Structural Break TGARCH extends the Threshold GARCH (GJR-GARCH) model to accommodate discrete, permanent shifts in the volatility process. By detecting structural breaks and incorporating them — either as regime-specific intercepts or dummy...
Structural Break Toda-Yamamoto Causality
The structural break Toda-Yamamoto causality test extends the standard Toda-Yamamoto modified Wald (MWALD) procedure to accommodate one or more structural breaks in the time series. By identifying break dates first and then including dummy...
Structural Break VAR Model
The Structural Break VAR model extends the standard Vector Autoregression (VAR) framework by allowing coefficient matrices and error covariance to shift at one or more unknown break dates. It is designed for multivariate time series where e...
Structural Break WLS
Structural Break WLS combines Weighted Least Squares estimation with explicit detection and correction for structural breaks — abrupt regime shifts — in the data. By identifying break points and assigning observation-level weights that acco...
Structural Time Series Model
The Structural Time Series Model, in its Basic Structural Model (BSM) form, is Andrew Harvey's state-space approach that decomposes a series into separate stochastic trend, seasonal, cyclical, and irregular components. Developed in Harvey's...
Structural VAR
Structural VAR extends the reduced-form VAR by imposing economic theory-based restrictions that identify orthogonal structural shocks. This allows researchers to disentangle the causal effects of distinct economic disturbances — such as sup...
Structural break DCC-GARCH
Structural break DCC-GARCH extends Engle's Dynamic Conditional Correlation GARCH framework by explicitly allowing the correlation and volatility structure to shift at one or more structural break points in the sample. It models time-varying...
Structural break Engle-Granger cointegration
The structural break Engle-Granger cointegration test, most commonly implemented via the Gregory-Hansen (1996) procedure, extends the classical Engle-Granger two-step test to allow for a single unknown structural break in the long-run coint...
Structural break Johansen cointegration
The structural break Johansen cointegration test extends the standard maximum-likelihood Johansen procedure to settings where the multivariate time series exhibits level shifts or trend breaks. By incorporating dummy variables or shift regr...
Structural break PP unit root test
The structural break Phillips-Perron (PP) unit root test extends the classical PP framework to allow for one or more discrete shifts in the level or trend of a time series. By endogenously or exogenously identifying break dates and controll...
Structural break SVAR model
The structural break SVAR model extends the standard Structural Vector Autoregression by allowing one or more discrete shifts in the system's parameters across time. It simultaneously identifies causal (structural) shocks and accounts for r...
Structural break VECM
The Structural Break VECM extends the standard Vector Error Correction Model to allow the cointegrating relationships, adjustment speeds, or short-run dynamics to shift at one or more known or estimated break dates. It preserves the long-ru...
Structural break Zivot-Andrews test
The Zivot-Andrews test is an endogenous structural break unit root test that determines the break point from the data rather than imposing it externally. It tests for a unit root against the alternative of stationarity around a single struc...
Student Growth Percentiles
Student growth percentiles (SGPs) describe how much a student grew academically relative to peers with similar score histories. Introduced by Damian Betebenner in 2009, the method fits a series of conditional quantile regressions of a curre...
Sullivan Method
The Sullivan method is a simple, widely used technique for estimating health expectancy — the average number of years a person can expect to live in a given health state, such as free of disability. Introduced by Daniel Sullivan in 1971, it...
Super-Efficiency DEA
Super-Efficiency DEA is a nonparametric linear programming extension of classical Data Envelopment Analysis (DEA) introduced by Andersen and Petersen (1993). While standard DEA assigns a maximum efficiency score of 1.0 to all units on the e...
Support for Political Violence Measure
This measure assesses citizens' willingness to endorse violence against political opponents, a key indicator of democratic fragility. Nathan Kalmoe and Lilliana Mason's research, synthesized in Radical American Partisanship (2022), maps a c...
Supports Intensity Scale
The Supports Intensity Scale (SIS) is a standardized assessment developed by the American Association on Intellectual and Developmental Disabilities (AAIDD) to measure the pattern and intensity of the supports a person with intellectual or...