השוואת שיטות

	מודל מיתוג-משטרים של מרקוב (MS-AR / MS-VAR)	רגרסיית ריבועים פחותים רגילים (OLS)
תחום	אקונומטריקה	אקונומטריקה
משפחה	Regression model	Regression model
שנת המקור	1989	2019
הוגה השיטה	Hamilton (1989); Kim & Nelson (1999)	Wooldridge (textbook treatment); classical least squares
סוג	Regime-switching time series model	Linear regression
מקור מכונן	Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
כינויים	regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
קשורות	5	5
תקציר	The Markov regime-switching model lets the parameters of a time series change probabilistically across hidden regimes governed by a Markov chain. Introduced by Hamilton (1989) and developed further by Kim and Nelson (1999), it automatically detects business-cycle phases such as expansions and contractions.	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).