scholarly journals Dynamic Factor Models with Time-Varying Parameters: Measuring Changes in International Business Cycles

2008 ◽  
Author(s):  
Marco Del Negro ◽  
Christopher Mark Otrok
Keyword(s):  
Business Cycles ◽  
International Business ◽  
Factor Models ◽  
International Business Cycles ◽  
Dynamic Factor ◽  
Time Varying ◽  
Dynamic Factor Models ◽  
Varying Parameters ◽  
Time Varying Parameters

scholarly journals GLOBAL VS. GROUP-SPECIFIC BUSINESS CYCLES: THE IMPORTANCE OF DEFINING THE GROUPS

2020 ◽  
pp. 1-23
Author(s):  
Tino Berger ◽  
Marcus Wortmann
Keyword(s):  
Business Cycles ◽  
International Business ◽  
Factor Models ◽  
Macroeconomic Fluctuations ◽  
International Business Cycles ◽  
Dynamic Factor ◽  
Global Business ◽  
Dynamic Factor Models ◽  
Specific Factors ◽  
National Business

The literature on international business cycles has employed dynamic factor models (DFMs) to disentangle global from group-specific and national factors in countries’ macroeconomic aggregates. Therefore, the countries have simply been classified ex ante as belonging to the same region or the same level of development. This paper estimates a DFM for a sample of 106 countries and three variables (output, consumption, investment) over the period 1960–2014, in which the countries are classified according to the outcome of a cluster analysis. By comparing the results with those obtained by the previous grouping approaches, we show substantial deviations in the importance of global and group-specific factors. Remarkably, when the groups are defined properly, the “global business cycle” accounts for only a very small fraction of macroeconomic fluctuations, most evidently in the industrialized world. The group-specific factors, on the other hand, play a much greater role for national business cycles than previously thought—also in the pre-globalization period.

scholarly journals Dynamic factor models: Does the specification matter?

SERIEs ◽  
2021 ◽  
Author(s):  
Karen Miranda ◽  
Pilar Poncela ◽  
Esther Ruiz
Keyword(s):  
Factor Models ◽  
Model Specification ◽  
Dynamic Factor ◽  
Dynamic Factor Models ◽  
Number Of Factors ◽  
Time Varying Parameters ◽  
Out Of Sample ◽  
Mixed Frequency Data ◽  
Natural Way ◽  
Factor Estimation

AbstractDynamic factor models (DFMs), which assume the existence of a small number of unobserved underlying factors common to a large number of variables, are very popular among empirical macroeconomists. Factors can be extracted using either nonparametric principal components or parametric Kalman filter and smoothing procedures, with the former being computationally simpler and robust against misspecification and the latter coping in a natural way with missing and mixed-frequency data, time-varying parameters, nonlinearities and non-stationarity, among many other stylized facts often observed in real systems of economic variables. This paper analyses the empirical consequences on factor estimation, in-sample predictions and out-of-sample forecasting of using alternative estimators of the DFM under various sources of potential misspecification. In particular, we consider factor extraction when assuming different number of factors and different factor dynamics. The factors are extracted from a popular data base of US macroeconomic variables, widely analyzed in the literature without consensus about the most appropriate model specification. We show that this lack of consensus is only marginally crucial when it comes to factor extraction, but it matters when the objective is out-of-sample forecasting.

Measuring Chinese business cycles with dynamic factor models

2009 ◽  
Vol 20 (2) ◽  
pp. 89-97 ◽  
Author(s):  
Jin-ming Wang ◽  
Tie-mei Gao ◽  
Robert McNown
Keyword(s):  
Business Cycles ◽  
Factor Models ◽  
Dynamic Factor ◽  
Dynamic Factor Models ◽  
Chinese Business

Dynamic Factor Analysis Models With Time-Varying Parameters

2011 ◽  
Vol 46 (2) ◽  
pp. 303-339 ◽  
Author(s):  
Sy-Miin Chow ◽  
Jiyun Zu ◽  
Kim Shifren ◽  
Guangjian Zhang
Keyword(s):  
Factor Analysis ◽  
Dynamic Factor Analysis ◽  
Dynamic Factor ◽  
Time Varying ◽  
Varying Parameters ◽  
Time Varying Parameters ◽  
Analysis Models

Die Identifikation internationaler Konjunkturzyklen in disaggregierten Daten: Deutschland, Frankreich und Großbritannien, 1862-1913

2011 ◽  
Vol 52 (1) ◽  
Author(s):  
Martin Uebele
Keyword(s):  
Great Britain ◽  
World War I ◽  
Business Cycles ◽  
International Business ◽  
International Business Cycles ◽  
Dynamic Factor Analysis ◽  
Dynamic Factor ◽  
National Accounts ◽  
World War ◽  
Disaggregated Data

AbstractThis article analyzes international business cycles in Europe 1862-1913 using disaggregated data and Dynamic Factor Analysis. It is important to know if crises are of national or international nature in order to correctly understand their causes and develop adequate solutions to prevent future crises. In comparison with estimates of real national product there is more evidence for international business cycles in disaggregated data of Germany, France and Great Britain before World War I. This is because data used to construct historical national accounts are often not sufficient, and especially because little is known about general price fluctuations. Thus, national products in current prices show higher degrees of international correlation than deflated ones although price indices themselves are not very well correlated across countries.

Synchronization of Chaotic Systems with Uncertain Time-Varying Parameters

2015 ◽  
Vol 9 (6) ◽  
pp. 568
Author(s):  
Ahmad Al-Jarrah ◽  
Mohammad Ababneh ◽  
Suleiman Bani Hani ◽  
Khalid Al-Widyan
Keyword(s):  
Chaotic Systems ◽  
Time Varying ◽  
Varying Parameters ◽  
Time Varying Parameters ◽  
Uncertain Time
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