Regime-dependent impulse response functions in a Markov-switching vector autoregression model

Ehrmann, Michael; Ellison, Martin; Valla, Natacha

doi:10.1016/s0165-1765(02)00256-2

Cited by 155 publications

(50 citation statements)

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“…We set two regimes prior to the estimation of the model to identify bear and bull markets. As noted earlier, states are differentiated not only by their average growth 11 Refer to Ehrmann et al (2003) for details on characteristics and computation of the regime-dependent impulse responses. 12 The linear VAR is found to be stable as all roots were found to lie within the unit circle.…”

Section: Resultsmentioning

confidence: 99%

“…Because the Markov chain is unobservable, Ehrmann et al (2003) emphasise that the recursive nature of the likelihood function prevents standard estimation techniques from providing the maximised likelihood. One alternative suggested by Krolzig (1997) is the iterative maximum likelihood estimation technique known as Expectation-Maximisation (EM) algorithm which is designed for a general class of models where the observed time series depends on some hidden stochastic variables.…”

Section: Methodology: Markov-switching Vector Autoregressive (Ms-var)mentioning

confidence: 99%

“…Equation (3) gives the mathematical definition of the regimedependent IRFs for regime i. It traces the expected path of the endogenous variables at time t+h following a one standard deviation shock to the k-th initial disturbance at time t, conditional on regime i (Ehrmann et al, 2003).…”

Section: Methodology: Markov-switching Vector Autoregressive (Ms-var)mentioning

confidence: 99%

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Is the relationship between monetary policy and house prices asymmetric across bull and bear markets in South Africa? Evidence from a Markov-switching vector autoregressive model

et al. 2013

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Abstract. This paper examines asymmetries in the impact of monetary policy on the middle segment of the South African housing market from 1966:M2 to 2011:M12. We use Markov-switching vector autoregressive (MS-VAR) model in which parameters change according to the phase of the housing cycle. The results suggest that monetary policy is not neutral as house price growth decreases substantially with a contractionary monetary policy. We find that the impact of monetary policy is larger in bear regime than in bull regime; indicating the role of information asymmetry in reinforcing the financial constraint of economic agents. As expected, monetary policy reaction to a positive house price shock is found to be stronger in the bull regime. This suggests that central banks react more in bull regime in order to prevent potential crisis related to the subsequent bust in house prices bubbles which are more prominent in bull markets. These results substantiate important asymmetries in the dynamics of house prices in relation to monetary policy, vindicating the advantages of generating regime dependent impulse response functions.

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Section: Resultsmentioning

confidence: 99%

Section: Methodology: Markov-switching Vector Autoregressive (Ms-var)mentioning

confidence: 99%

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Is the relationship between monetary policy and house prices asymmetric across bull and bear markets in South Africa? Evidence from a Markov-switching vector autoregressive model

et al. 2013

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“…[42]; Balcilar et al [43] and so on). Conventionally, macroeconomic studies must consider regime shifts or structural changes in the movement of variables (Granger [13] …”

Section: Markov Switching-vector Autoregressive Model (Ms-var Model)mentioning

confidence: 98%

“…In the present study, variables are ordered as industrial production, consumer price index and global crude oil prices as a recursive structure for the model. It is based on the assumption that global crude prices react more instantaneously at the arrival of any news (liquidity in commodity markets) as compared to other variables (Ehrmann et al [42]). …”

Section: Estimationmentioning

confidence: 99%

How Indian CPI and Industrial Production Respond to Global Oil Price Shocks? Regime-Dependent Impulse Responses

Singh¹,

Singh²

2017

TEL

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For emerging markets like India, where around 80 percent of the crude requirements are met through imports, it is an imperative task to comprehend impact of global crude oil price shocks on Indian macroeconomic variables. The present study attempts to understand these asymmetric dynamic interactions between global crude oil price shocks and Indian macroeconomic variables by employing Markov switching-Vector Autoregressive (MS-VAR) regime-dependent impulse responses in level forms. The findings hold an important place in the wake of inflation targeting regime adopted by the monetary policy authorities. The findings highlight the existence of two regimes, namely lower and higher oil price variance regimes. The response of industrial production and consumer prices is different towards oil price shocks in different regimes. In the lower oil variance regime, there is negative (positive) relationship observed between crude oil shocks and industrial production (consumer prices). On the other hand, there is a positive equilibrium shift in the industrial production in the higher oil variance regime with cost pushing inflationary pressures in the long run. The findings bear strong implication for the policy makers in their attempt to combat effects of crude oil shocks. As per the findings, the emerging market policy makers should display a cautious approach during higher oil price volatile phases in order to support industrial production and consumer demand.

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Monetary policy shock and impact asymmetry in bank lending channel: Evidence from the UK housing sector

et al. 2022

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Banks play a defining role in translating monetary policy shocks to pull or push‐effects in the housing market. The literature is ambiguous on the exact role of bank lending channel (BLC) in translating such effects into either moderation or acceleration of dynamics in the housing market. This paper argues that monetary policy shocks, of the same magnitude, can have asymmetric implications for a housing market via a state dependent BLC, particularly during expansion and recessionary phases of the business cycle. We test this hypothesis for the UK housing sector using a long quarterly data (1973Q1‐2015Q4) and employing Markov Switching Vector Auto Regression (MSVAR) models. Our results show that the magnitude of the bank lending channel is contingent upon the state of the economy, with a one standard deviation expansionary monetary policy shock producing a significant effect only in normal economic times. Further study on whether large cuts in policy rates could stimulate mortgage lending and whether there is impact asymmetry to dissimilar expansionary monetary policy shocks during financial crisis, we show that a sharp cut in policy rate indeed stimulates the BLC greater compared to smaller expansionary money policy shocks during recessions.

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Regime-dependent impulse response functions in a Markov-switching vector autoregression model

Cited by 155 publications

References 5 publications

Is the relationship between monetary policy and house prices asymmetric across bull and bear markets in South Africa? Evidence from a Markov-switching vector autoregressive model

Is the relationship between monetary policy and house prices asymmetric across bull and bear markets in South Africa? Evidence from a Markov-switching vector autoregressive model

How Indian CPI and Industrial Production Respond to Global Oil Price Shocks? Regime-Dependent Impulse Responses

Monetary policy shock and impact asymmetry in bank lending channel: Evidence from the UK housing sector

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