Managing, Inducing, and Preventing Regime Shifts: A Review of the Literature

38 Pages Posted: 26 Jul 2019

See all articles by Ngo Van Long

Ngo Van Long

McGill University - Department of Economics; CESifo (Center for Economic Studies and Ifo Institute)

Date Written: 2019


How do economic agents manage expected shifts in regimes? How do they try to influence or prevent the arrival of such shifts? This paper provides a selective survey of the analysis of regime shifts from an economic view point, with particular emphasis on the use of the techniques of optimal control theory and differential games. The paper is organized as follows. Section 2 gives an overview of the concepts of regime shifts, thresholds, and tipping points. Section 3 shows how unknown tipping points affect the optimal current policy of decision makers, with or without ambiguity aversion. Section 4.s focus is on political regime shifts in a two-class economy: how the elite may try to prevent revolution by using policy instruments such as repression, redistribution, and gradual democratization. Section 5 reviews models of dynamic games in resource exploitation involving regime shifts and thresholds. Section 6 reviews some studies of regime shifts in industrial organization theory, with focus on R&D races, including efforts to sabotage rivals in order to prevent entry. Section 7 reviews games of regime shifts when players can manage a Big Push. Section 8 discusses some directions for future research.

Keywords: regime shifts, thresholds, tipping points, political repression, democratization

JEL Classification: C000, C700

Suggested Citation

Van Long, Ngo, Managing, Inducing, and Preventing Regime Shifts: A Review of the Literature (2019). CESifo Working Paper No. 7749. Available at SSRN:

Ngo Van Long (Contact Author)

McGill University - Department of Economics ( email )

855 Sherbrooke Street West
Montreal, QC H3A 2T7
514-398-4850 (Phone)
514-398-4938 (Fax)

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
PlumX Metrics