Markov-switching Vector Error Correction Model Research Articles

Listed Real Estate as an Inflation Hedge Across Regimes

AbstractThis paper examines the inflation-hedging capability of listed real estate (LRE) companies in the US from 1975 to 2023, and in three other economies—the UK, Japan, and Australia—from 1990 to 2023. By using a Markov switching vector error correction model (MS-VECM), we identify that the short-term hedging ability moves towards being negative or zero during turbulent periods. In stable periods, LRE provides good protection against inflation. In the long term, LRE offers a good hedge against expected inflation and shows a superior inflation hedging ability than stocks. Additionally, we identify inflation-hedging portfolios by minimizing the expected shortfall. This inflation-hedging portfolio allocation methodology suggests that listed real estate stocks should play a significant role in investor portfolios.

Price discovery in equity markets: A state-dependent analysis of spot and futures markets

This paper investigates the potentially time-varying importance of spot and futures markets in the price discovery process of financial assets. For this purpose, we generalize the concept of component shares and information shares to allow for state-dependent relevance of different markets over time. Instead of using a linear vector error correction model (VECM) to construct the component shares and information shares as it is common in the literature, we employ a Markov-switching VECM with time-varying adjustment behaviour and state-dependent covariance matrices. Simulation results confirm that state-dependent component shares and information shares can be estimated consistently within this framework. We apply our approach to spot and futures prices for different stock indices such as EuroStoxx50, FTSE100, Nikkei225, and SP500. We find a clear state probability pattern over the trading day that closely resembles the well-studied volatility smile and might be related to the presence of heterogeneous agents in those markets.

Regime switching effect of financial development on energy intensity: Evidence from Markov-switching vector error correction model

Studies that deal with financial development and energy intensity usually show the single effect of one variable on another or the causality running between them during the whole sample period. But this study is an attempt to explore the regime switching effect of financial development on energy intensity in different periods within the sample. Using yearly data from 1972 to 2017 in case of Bangladesh, a Markov-switching vector error correction model is applied to carry out the study, and the results reveal a two-regime switching nature of the effect of financial development on energy intensity. Financial development plays a stimulating role in regime 1 where it plays an inhibiting role in regime 2 to influence energy intensity. The duration of regime 1 is longer than that of regime 2 specifying that the promoting effect of financial development on energy intensity is more enduring than the inhibiting effect in Bangladesh. The results have important policy implications to formulate energy policy and to maintain a balance between financial development and energy intensity in Bangladesh and other emerging nations.

Transmisión de los precios del arroz en Colombia y el mundo

The aim of this paper is to analyse the spatial price transmission of rice in Colombia, emphasizing the impact of trade policies. For this purpose, a Markov-switching vector error correction model was used to model regime shifts in the relationship between domestic and international rice prices in Colombia and some control countries, from January 1996 to September 2018. The results reveal three price transmission regimes that coincide with internal trade policies and with the food crisis of 2007-2008. The high volatility regime was the most persistent, with an average duration of 15.4 months, a transition probability of 93 % and an adjustment speed of 0.24. In addition, during this regime, Colombia was less integrated into the international rice market. These results are relevant, since they constitute the application of a threshold methodology to the analysis of the transmission of agricultural prices and can be useful for the design of agrarian policies that contribute to the integration and competitiveness of the Colombian rice sector.

Fiscal sustainability in India: evidence from Markov switching and threshold regression models

PurposeThe purpose of this study is to examine the fiscal sustainability issue by dividing the fiscal deficit into high and low regimes using the quarterly data from 1997: Q1 to 2013: Q3. Further, we obtain the optimum level of public debt at which fiscal sustainability can be achieved.Design/methodology/approachThis study uses the Markov Switching-Vector Error Correction Model (MS-VECM) for examining fiscal sustainability and threshold regression model to obtain the optimum level of debt.FindingsThe results derived from MS-VECM reveal the evidence in favor of fiscal sustainability during low fiscal deficit periods. Similarly, using a threshold regression model, the optimum public debt as a percentage to GDP seems to be around 21 per cent on a quarterly basis, beyond this level, public debt hurts economic growth.Practical implicationsFrom the policy front, the government of India should cut down the fiscal deficit only if debt reaches beyond a threshold level.Originality/valueNoting that the vast literature has focused on examining the fiscal sustainability in India, the novelty of this study is to examine the fiscal sustainability by considering high and low deficits regimes using a non-linear approach.

Do gold prices respond to real interest rates? Evidence from the Bayesian Markov Switching VECM model

The goal of this paper is to examine the transmission dynamics between the real interest rate and gold prices in the G7. The methodology follows the Bayesian Markov-Switching Vector Error-Correction (MS-VECM) model, along with regime-dependent impulse response functions, spanning the period 1975–2016. The findings suggest a positive association between gold prices and real interest rates, with the estimates remaining consistently positive and statistically significant across all G7 countries. The results indicate that gold prices can provide hedging services against real interest rate movements mainly during recessionary times. Our results continue to be robust when we extend the bivariate version of our modeling approach to include more drivers for gold prices.

Exploring Dynamic Impact of Foreign Direct Investment on China’s CO $$_{2}$$ 2 Emissions Using Markov-Switching Vector Error Correction Model

The impact of foreign direct investment (FDI) on China’s CO $$_{2}$$ emissions is an important index to evaluate the effect of foreign investment policy. This paper uses the monthly data of CO $$_{2}$$ emissions and FDI from January 1997 to December 2013 to analyze the regime states, switching probability and regime correlation between FDI and CO $$_{2}$$ emissions with the help of nonlinear Markov-switching vector error correction model (MS-VECM), The results indicate that the influence of FDI on CO $$_{2}$$ emissions shows the two-regime dynamic characteristics, FDI has played a stimulating role in promoting China’s CO $$_{2}$$ emissions during the period from January 1997 to October 2003, while played an inhibiting role during the period from November 2003 to December 2013. The duration of the inhibiting effect of FDI on CO $$_{2}$$ emissions is longer, and the frequency is higher than that of the stimulating effect. Therefore, the overall influence of FDI on CO $$_{2}$$ emissions during the period from January 1997 to December 2013 is inhibitive, which means FDI has contributed to CO $$_{2}$$ emissions reduction. The innovation points of this study are mainly reflected in the following two aspects: first, nonlinear MS-VECM is introduced to dynamically study the relationship between FDI and CO $$_{2}$$ emissions in contrast to prior studies that simply use static analysis method; second, the effect of China’s foreign investment policies on CO $$_{2}$$ emissions is evaluated in each period according to the empirical results of MS-VECM.

A Markov regime-switching model of crude oil market integration

This paper revisits the globalization-regionalization hypothesis for the world crude oil market. We examine long-run equilibrium relationships between major crude oil prices–WTI, Brent, Bonny Light, Dubai and Tapis–and focus on the adjustment behaviour following disequilibrium states. We account for a changing adjustment behaviour over time by using a Markov-switching vector error correction model. Our overall findings suggest that the crude oil market is globalized. Dubai turned out to be the only weakly exogenous price in all regimes, indicating its important role as a benchmark price. Furthermore, an interesting finding of our study is that the degree of market integration seems to be connected to global economic uncertainty.

Food scare crisis: the effect on Serbian dairy market

The increasing trend of food scandal crises is not well followed in recent studies of spatial price transmission. This paper analyses the impact on the domestic market of an Aflatoxin M1 outbreak in the Serbian dairy sector during 2013/2014 using a spatial price transmission approach. Monthly farm milk prices in Serbia for the period 2007/2014 were contrasted with leading dairy exporting countries New Zealand, USA and Germany, which did not have a food scare in their dairy sectors. To estimate the impacts a Markov-switching vector error-correction model was utilized. For all four dairy markets the model identified two price change regimes: standard and extreme. Although it was predictable, an extreme regime was not identified during the Aflatoxin M1 crises in Serbia because of some specific characteristics of its dairy production. The results suggest that the Aflatoxin M1 outbreak ‘froze’ the Serbian dairy market and temporally disconnected it from the world milk market. Farmer’s prices fell below their long-run equilibrium levels. The total loss of the Serbian farm-level dairy sector during the crisis reached up to 96.2 million EUR. These ‘missed opportunity’ significantly slowed investment in the dairy sector.

Oil Prices and Exchange Rates: Based on Bayesian MS-VEC Model

This study takes into account two crucial economic variables in its analysis of the relationship between oil prices and Rouble exchange rate, namely, nonlinear adjustment dynamics and impulse response functions. Employing a Markov-switching vector error correction model, this allows us to discriminate long-run and time-varying short-run dynamics. Our findings suggest not only that short-run adjustments of Rouble exchange rate exhibit significantly asymmetry across regimes, but also that the reverse relationship between oil price and Rouble exchange rate is mainly derived by high volatility regime, which seems closely relate to recession of Russian business cycle.

Study on the price co-movement among the Asia Pacific, European and Chinese coal markets – based on the empirical analysis of MS-VEC model

ABSTRACTIn this article, based on weekly data of the three major coal markets (the Asia Pacific, Europe and China) from March 2008 to November 2014, an empirical research on their mutual influence and price co-movement effect among the three major coal markets is conducted by using the Co-integration Theory, Granger Causality Test and markov switching-Vector Error Correction (MS-VEC) model. The conclusions are as follows. (1) There exists a long-term cointegration relationship and bidirectional causality relationship between coal prices at home and abroad, and the influences of foreign coal markets on the domestic coal markets are stronger than the influences of domestic coal markets on foreign coal markets, and thus the interaction between the two markets leads to asymmetric linkage effects. (2) Compared with the VEC model, the MS-VEC model can reflect the nonlinear feature of price co-movement effects. (3) There exists an inherent adjustment mechanism between domestic and foreign coal markets, i.e. the coal prices will be self-revised continuously until a long-term equilibrium state is achieved when a deviation from the equilibrium state occurs. (4) There exists a co-movement effect which varies with the change of regime among the three coal prices, and the self-maintenance is strong and the status transfer phenomenon is clear in different regimes.

A Markov-Switching Model for Indian Stock Price and Volume

Using weekly data from the Indian stock market, we examine the relationship between stock price and trading volume. Our framework is Markov Switching-Vector Error Correction Model (MS-VECM). We justify the use of nonlinear model using the Brock, Dechert and Scheinkman (BDS) test and the information criteria. The long-run dynamics are characterised by one cointegrating vector relating the price to trading volume. We find that stock price is weakly exogenous only in the high volatility regime. The MS-VECM with two regimes provides a good characterisation of the Indian stock market and performs well relative to the other linear and nonlinear models. JEL Classification: C32, G12, E32

Regime switching model of US crude oil and stock market prices: 1859 to 2013

This paper examines the relationship between US crude oil and stock market prices, using a Markov-Switching vector error-correction model and a monthly data set from 1859 to 2013. The sample covers the entire modern era of the petroleum industry, which typically begins with the first drilled oil well in Titusville, Pennsylvania in 1858. We estimate a two-regime model that divides the sample into high- and low-volatility regimes based on the variance–covariance matrix of the oil and stock prices. We find that the high-volatility regime more frequently exists prior to the Great Depression and after the 1973 oil price shock caused by the Organization of Petroleum Exporting Countries. The low-volatility regime occurs more frequently when the oil markets fell largely under the control of the major international oil companies from the end of the Great Depression to the first oil price shock in 1973. Using the National Bureau of Economic research business cycle dates, we also find that the high-volatility regime more likely occurs when the economy experiences a recession.

A regime-dependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates

We use the Bayesian Markov-switching vector error correction (MS-VEC) model and the regime-dependent impulse response functions (RDIRFs) to examine the transmission dynamics between oil spot prices, precious metals (gold, silver, platinum, and palladium) spot prices and the US dollar/euro exchange rate. Using daily data from 1987 to 2012, two regimes (low and high volatility regimes) appear to be prevalent for this system. We find evidence that among the five commodity prices the gold prices are the most informative in the group in the high volatility regime, while gold, palladium, and platinum are the most informative in the low volatility regime. Though the platinum and palladium prices impact each other, the impacts in the high volatility regime are asymmetric. In addition to its low correlation in the group, palladium's negative impact on the exchange rate and gold makes it a reliable hedge asset for investors. Gold is the least volatile variable, thus affirming its use as a “safe haven” asset, while silver and oil are the most volatile in the group. Understanding the dynamics of these commodity prices should help investors decide how to invest during periods of low vs. highly volatile regimes.

The time-varying causality between spot and futures crude oil prices: A regime switching approach

One puzzling result in the literature on the linkages between the spot and futures crude oil prices is the sensitivity of causality tests to the sample period that one considers, which is usually handled by sample splitting. In order to overcome this difficulty, we propose a model that allows time-varying Granger causality between these prices. The model is used to investigate the time-varying causal linkages between the daily spot and futures prices for maturities of one, two, three and four months of the West Texas Intermediate (WTI) crude oil benchmark over the period January 2, 1986–July 31, 2013. The results indicate that the causal links between these oil prices are strongly time-varying. Both variables have a predictive power for each other during various subperiods, but not in all periods. Further, these periods coincide with major influential changes in the oil and stock markets and the geopolitics, implying that the findings are not statistical artifacts, but reflect real economic, financial and geopolitical regime changes. The full sample's conditional Granger causality tests based on the Markov-switching vector-error correction (MS-VEC) model reject both the causal impact of the lagged futures prices on the spot prices and the causal impact from the lagged spot prices on the futures prices. Therefore, the results show that the lead–lag relationship between the spot and futures oil markets exists only temporarily. While encompassing the previous findings, they also offer new insights into the nature of the lead–lag relationships between the spot and futures oil markets by taking non-linearity and time-variation into account.

Investigating Agricultural Production Relations across Bangladesh, India and Pakistan Using Vector Error Correction and Markov-Switching Models

This paper has investigated the short- and long-term relationships as well as regime switching behaviour across the per-capita agricultural production of Bangladesh, India and Pakistan using vector error correction model (VECM) and Markov-switching VECM model (MS-VECM). These countries were selected due to their high agricultural economic importance to the South Asian region. The study has used FAO's statistical dataset and the study period was 1961–2010. The residual diagnostics have validated the models since there is no deficiency in normality, autocorrelation or heteroskedasticity. The empirical results have confirmed the existence of two long-term cointegrating vectors between the variables and have demonstrated that an unexpected shock to the respective log per-capita agricultural production of India and Pakistan cause transitory impacts. On the other hand, an unexpected shock to the log per-capita agricultural production of Bangladesh causes a permanent disequilibrium in all variables. Finally, MS-VECM model has shown two volatility regimes (i.e. low and high volatility). The Markov-switching impulse responses have indicated that, one, agricultural production adjustments in the first regime are smoother than those in the second regime, and two, these adjustments are faster in the case of a shock to the agricultural production of Pakistan than to the agricultural production of either Bangladesh or India.

Does global liquidity drive commodity prices?

This paper tackles the question of whether a cross-sectional perspective on monetary policy is capable of explaining movements in global commodity prices. In this vein, we contribute to the rich literature on global liquidity in two different ways: on the one hand, to achieve a global series in terms of common monetary policy shocks, we propose a distinction between common and idiosyncratic factors across economies, as proposed by Bai and Ng (2004). Our second innovation stems from the consideration of a Markov-switching vector error correction model when analyzing time-varying short-run dynamics. Having identified the long-run structure which includes a proportional relationship between commodity prices and global liquidity in the first step, our results indeed show that the impact of a global liquidity measure on different commodity prices is significant and varies over time. One regime approximately accounts for times where commodity prices significantly adjust to disequilibria, while the second regime is characterized by either a weak or no commodity price adjustment. The fact that global liquidity also reacts to disequilibria in a specific regime demonstrates the two-way causality between monetary policy and commodity prices.

Regime Switching Model of US Crude Oil and Stock Market Prices: 1859 to 2013

This paper examines the relationship between US crude oil and stock market prices, using a Markov-Switching vector error-correction model and a monthly data set from 1859 to 2013. The sample covers the entire modern era of the petroleum industry, which typically begins with the first drilled oil well in Titusville, Pennsylvania in 1858. We estimate a two regime model that divides the sample into high- and low-volatility regimes based on the variance-covariance matrix of the oil and stock prices. We find that the high-volatility regime more frequently exists prior to the Great Depression and after the 1973 oil price shock caused by the Organization of Petroleum Exporting Countries. The low-volatility regime occurs more frequently when the oil markets fell largely under the control of the major international oil companies from the end of the Great Depression to the first oil price shock in 1973. Using the National Bureau of Economic research business cycle dates, we also find that the high-volatility regime more likely occurs when the economy experiences a recession.

Is there a homogeneous causality pattern between oil prices and currencies of oil importers and exporters?

Although the link between oil prices and dollar exchange rates has been frequently analyzed, a clear distinction between prices and nominal exchange rate dynamics and a clarification of the issue of causality has not been provided. In addition, previous studies have mostly neglected nonlinearities which for example may stem from exogenous oil price shocks. Using monthly data for various oil-exporting and oil-importing countries, this study contributes to the clarification of those issues. We discriminate between long-run and time-varying short-run dynamics, using a Markov-switching vector error correction model. In terms of causality, the results differ between the economies under observation but suggest that the most important causality runs from exchange rates to oil prices, with a depreciation of the dollar triggering an increase in oil prices. On the other hand, changes in nominal oil prices are responsible for ambiguous real exchange rate effects mostly through the price differential and partly also through a direct influence on the nominal exchange rate. Overall, the fact that the adjustment pattern frequently differs between regimes underlines the fact that the relationships are subject to changes over time, suggesting that nonlinearities are an important issue when analyzing oil prices and exchange rates.

Is There a Homogeneous Causality Pattern between Oil Prices and Currencies of Oil Importers and Exporters?

Although the link between oil prices and dollar exchange rates has been frequently analyzed, a clear distinction between prices and nominal exchange rate dynamics and a clarification of the issue of causality has not been provided. In addition, previous studies have mostly neglected nonlinearities which for example may stem from exogenous oil price shocks. Using monthly data for various oil-exporting and oil-importing countries, this study contributes to the clarification of those issues. We discriminate between long-run and time-varying short-run dynamics, using a Markov-switching vector error correction model. In terms of causality, the results differ between the economies under observation but suggest that the most important causality runs from exchange rates to oil prices, with a depreciation of the dollar triggering an increase in oil prices.On the other hand, changes in nominal oil prices are responsible for ambiguous real exchange rate effects mostly through the price differential and partly also through a direct influence on the nominal exchange rate. Overall, the fact that the adjustment pattern frequently differs between regimes underlines the fact that the relationships are subject to changes over time, suggesting that nonlinearities are an important issue when analyzing oil prices and exchange rates.