Cointegrated Vector Autoregressive Model Research Articles

Testing rational expectations in a cointegrated VAR with structural change

Testing rational expectations in a cointegrated VAR with structural change

Exploring price level trajectory in India: Does it validate the fiscal theory of price level?

Exploring price level trajectory in India: Does it validate the fiscal theory of price level?

Price discovery and long‐memory property: Simulation and empirical evidence from the bitcoin market

AbstractPrice discovery studies of a single asset traded in multiple markets have traditionally focused on assessing the relative price discovery contribution of each market. However, in this paper, we demonstrate that the overall price discovery across all markets can undergo changes even when the relative price discovery of each market remains constant. We propose that this overall change in price discovery can be effectively captured by the fractional parameter in the fractionally cointegrated vector autoregressive (FCVAR) model. In contrast, the widely used cointegrated vector autoregressive (CVAR) model fails to account for this dynamic in overall price discovery. Through a combination of simulation exercises and empirical applications, we show that the FCVAR approach outperforms the CVAR model not only in evaluating the relative price discovery contributions but also, more importantly, in providing a comprehensive measurement of overall price discovery.

Market uncertainty, persistent arbitrage-free violation, and price discovery in RMB market

Market uncertainty, persistent arbitrage-free violation, and price discovery in RMB market

Adjustment coefficients and exact rational expectations in cointegrated vector autoregressive models

In this article, we consider the cointegrated vector autoregressive model with adjustment parameters and cointegration vectors . We discuss estimation of the model under the exact linear rational expectations, when we also have linear restrictions on the adjustment parameters . In particular we consider the same restriction on all vectors in and the hypothesis that some vectors in are known.

Impact of Internationalization on Human Development: A Comparative Analysis of Mexico and France, 2000–2019

The objective is to determine the relationship between the openness of markets and human development in Mexico and France for the period 2000–2019. A comparative analysis is carried out by looking at the effect of migration (measured by the inflow of remittances) and the opening of capital markets and trade on the Human Development Index in both countries. Estimations are based on a Cointegrated Vector Autoregressive model. Results show that Foreign Direct Investments has a positive influence on HDI in both countries, but remittances seem to contribute more to human development, in Mexico, than trade and capital liberalization do.

A Tripolar Model of Gas Price Formation in Germany. Does the Shale Revolution in the US Matter?

Abstract Presented analysis of gas price formation mechanism in Germany was prompted by changes brought about by technological advancements and the liberalization and harmonization of natural gas markets in the European Union after the year 2000. Because the data used in the study is generated by nonstationary stochastic processes, the cointegrated vector autoregressive model was applied as the most appropriate. The analysis pointed out that the price of natural gas, oil and the USD/EUR exchange rate influence each other in the long run and thus should be modelled together. Gas price in Germany is driven by both fundamental and financial factors, and so it rises with economic expansion, oil price increases, and the depreciation of the USD. It also reacts to changes in short-term interest rates and the volume of gas production in the US, which confirms that the shale revolution in this country has been consequential for gas prices in Europe, like any other supply shock would have been.

Technical Analysis of Tourism Price Process in the Eurozone

This study is a specific contribution to investigating normalities in prices to a well-established cointegrated vector autoregressive model (VAR). While the role of prices in computational economics has been investigated, the real prices vis-à-vis nominal prices in the decision process has been neglected. The paper investigates the transition from nominal to real time-series of prices without losing information in the data set when deflating or de-seasonalizing. The likelihood approach is based on careful specifications of the (co)integration characteristics of tourism prices. The results confirm that the transmission of tourism prices in the Eurozone positively impacts Slovenian tourism prices when the spatial consolidated cointegrated VAR model is used. The theoretical-conceptual and empirical contribution is twofold: first, the study develops and empirically applies bona fide divisor of normality consolidation for time-series in levels instead of routinely utilised inflation integers, and second, the study introduces perfection of prices on a long-run time-series treatment.

Modeling the United States crack spread: Market efficiency, persistence and the Verleger hypothesis

ABSTRACT The price formation of crude oil and its refined products plays an essential role in the global economic system and mainly in the United States, where any shock on this market has implications for the different concerned parties. In this sense, we employ the fractionally cointegrated vector autoregressive model to analyze the long-run relationship between crude oil and each refined product and the persistence of the error term resulting, i.e., the crack spread, simultaneously. Once the cointegrating relationships between crude oil price and each refined product price are tested, we also evidence that the order of integration of the crack spread displays a long memory process. Finally, by attending to the coefficient adjustments, supply-driven market integration is given. Additionally, the Verleger hypothesis is rejected for all refined products, corroborated by the component share. This paper has important policy implications for investors, energy policymakers and refiners.

Volatility discovery in cryptocurrency markets

PurposeCryptocurrency markets are notoriously noisy, but not all markets might behave in the exact same way. Therefore, the aim of this paper is to investigate which one of the cryptocurrency markets contributes the most to the common volatility component inherent in the market.Design/methodology/approachThe paper extracts each of the cryptocurrency's markets' latent volatility using a stochastic volatility model and, subsequently, models their dynamics in a fractionally cointegrated vector autoregressive model. The authors use the refinement of Lien and Shrestha (2009, J. Futures Mark) to come up with unique Hasbrouck (1995, J. Finance) information shares.FindingsThe authors’ findings indicate that Bitfinex is the leading market for Bitcoin and Ripple, while Bitstamp dominates for Ethereum and Litecoin. Based on the dominant market for each cryptocurrency, the authors find that the volatility of Bitcoin explains most of the volatility among the different cryptocurrencies.Research limitations/implicationsThe authors’ findings are limited by the availability of the cryptocurrency data. Apart from Bitcoin, the data series for the other cryptocurrencies are not long enough to ensure the precision of the authors’ estimates.Originality/valueTo date, only price discovery in cryptocurrencies has been studied and identified. This paper extends the current literature into the realm of volatility discovery. In addition, the authors propose a discrete version for the evolution of a markets fundamental volatility, extending the work of Dias et al. (2018).

Adjustment coefficients and exact rational expectations in cointegrated vector autoregressive models

In cointegrated vector autoregressive models exact linear rational expectation relations can imply restrictions on the adjustment parameters. We show how such restrictions can be tested, in particular when the restrictions imply weak exogeneity of some variables.

On Monetary Policy and Stock Price Relationship: Long and Short-run Dynamics

In this paper, we investigate the relationship between monetary policy and stock prices across advanced and emerging economies from January 1999 to December 2017. We also examine the impact of global monetary policy on the sample stock markets. Using the Structural Cointegrated Vector-Autoregressive model, we explore long-run equilibrium relationship and short-run dynamics of monetary policy and stock markets before and after the global financial crisis. Our results demonstrate that domestic policy rate and stock prices are often not tied together in long-term equilibrium relationships for a majority of the economies. Cross-sectional heterogeneity is observed as the relationship differs in terms of sign, magnitude and adjustment dynamics. Further, US monetary conditions are found to play an important role in influencing global output or liquidity conditions. Short-run dynamics reveal a positive impact of expansionary monetary policy shock on equity prices in those economies where transmission mechanism of monetary policy is weak. Further, we find limited response of central banks to domestic equity price shocks. The influence of US monetary policy shocks in driving equity prices is also found to be insignificant for a majority of the economies.

Multivariate Cointegration and Temporal Aggregation: Some Further Simulation Results

We perform Monte Carlo simulations to study the effect of increasing the frequency of observations and data span on the Johansen (J Econ Dyn Control 12(2–3):231–254, 1988; Likelihood-based inference in cointegrated vector autoregressive models, Oxford University Press, Oxford, 1995) maximum likelihood cointegration testing approach, as well as on the bootstrap and wild bootstrap implementations of the method developed by Cavaliere et al. (Econometrica 80(4):1721–1740, 2012; Econ Rev 33(5–6):606– 650, 2014). Considering systems with three and four variables, we find that when both the data span and the frequency vary, the power of the tests depend more on the sample length. We illustrate our findings by investigating th existence of long-run equilibrium relationships among four indicators prices of coffee.

The Consumption Euler Equation or the Keynesian Consumption Function?*

AbstractWe formulate a general cointegrated vector autoregressive (CVAR) model that nests both a class of consumption Euler equations and various Keynesian‐type consumption functions. Using likelihood‐based methods and Norwegian data, we find support for cointegration between consumption, income and wealth once a structural break around the time of the financial crisis is allowed for. The fact that consumption cointegrates with both income and wealth and not only with income points to the empirical irrelevance of an Euler equation. Moreover, we find that consumption equilibrium corrects to changes in income and wealth, but not that income equilibrium corrects to changes in consumption, which would follow from an Euler equation. We also find that most of the parameters stemming from the class of Euler equations are not corroborated by the data when conditional expectations of future consumption and income in CVAR models are considered. Only habit formation seems important in explaining Norwegian consumer behaviour. Our estimated conditional Keynesian‐type consumption function implies a first year marginal propensity to consume (MPC) out of income of close to 40%.

An empirical analysis of loan supply and demand in the euro area

Abstract Using a cointegrated vector autoregressive model (CVAR), this paper empirically examines the supply and demand for euro area loans to the non-financial private sector for the sample 1981 to 2017. We distinguish between loan demand and supply and disentangle the impact of the financial crisis on loans from conventional drivers. Applying I(2) cointegration analysis, we find two long-run (polynomial) cointegration relations and identify them as loan demand and supply functions. Despite rejecting long-run price homogeneity for euro area loans in the unrestricted model, we identify a stable system with (long-run) loan supply and demand functions based on conventional drivers and housing wealth. In terms of forecasting properties, we show that the loan demand function helps to improve the accuracy of euro area inflation forecasts for horizons of up to 8 quarters ahead and for loan forecasts for horizons of up to 2 quarters ahead, while the loan supply function does not have this property.

Dinamika stope nezaposlenosti u maloj otvorenoj privredi - slučaj Srbije

Dynamic relationship among unemployment rate and key macroeconomic variables is explored for the Serbian economy that has been characterized by high unemployment rates since the outcome of the Great Recession. This analysis reveals how effective policy measures can be in reducing unemployment rate. Cointegrated vector autoregressive model is employed for the period 2014-2019. Prior to multivariate dynamic modelling, the validity of hysteresis hypothesis for unemployment rate is assessed. Obtained results show significant negative long-run effect of real wages on unemployment rate, and positive long-run effect of real effective exchange rate appreciation on real wages. For further reduction of unemployment rate demand-side measures should be employed.

Volatility Discovery in Cryptocurrency Markets

Cryptocurrency markets are notoriously noisy, but not all markets might behave in the exact same way. Therefore, we investigate which market contributes the most to the evolution of the common volatility component of cryptocurrency markets. We extract each of the markets’ latent volatility using a stochastic volatility model and subsequently model their dynamics in a fractionally cointegrated vector autoregressive model. We use the refinement of Lien and Shresta (2009, J. Futures Mark) to come up with unique Hasbrouck (1995, J. Finance) information shares and find that Bitfinex is the leading market for Bitcoin and Ripple while Bitstamp dominates for Ethereum and Litecoin. Based on the dominant market for each cryptocurrency, we find that Bitcoin volatility explains most of the volatility among the different cryptocurrencies.

Trajectories to High Income: Growth Dynamics in Japan, the People’s Republic of China, and the Republic of Korea

We analyze and compare the patterns of economic growth and development in the Japan, the People’s Republic of China, and the Republic of Korea in the postwar period. The geographical proximity and cultural affinity between the three countries, as well as the key role of the development state in the economies, suggest that an analytical comparison would be a meaningful and valuable exercise. Furthermore, Japan and the Republic of Korea are two of the few economies that have jumped from middle income to high income in a short period and thus offer potentially valuable lessons for the PRC. We use Cobb–Douglas production functions to assess the long-run equilibrium relationships between per capita gross domestic product, capital, and labor by means of cointegrated vector autoregressive models. We show that such equilibrium relationships cannot be rejected for all three countries, while the evidence is stronger for the PRC and the Republic of Korea than for Japan. Our hypothesis tests show that the estimated Cobb–Douglas production functions display coefficients of capital and employment that sum up to 1 and broken linear trends that can be attributed to structural breaks and (changes in) total factor productivity growth. We observe a striking similarity between the experience in the Republic of Korea and the PRC, which gives some optimism that the PRC may be capable of graduating to high income, like the Republic of Korea.

Prices of short-stay accommodation: time series of a eurozone country

Purpose This paper aims to provide a reliable statistical model for time-series prices of short-stay accommodation and overnight stays in a eurozone country. Design/methodology/approach Exploiting the unit root feature, the cointegrated vector autoregressive model solves the problem of misspecification. Subsequently, variables are modelled for a long-run equilibrium with included deterministic variables. Findings The empirical results confirmed that overnight stays for foreign tourists were positively associated with the prices of short-stay accommodation. Research limitations/implications The major limitation lies in the data vector and its time horizon; its extension could provide a more specific view. Practical implications Findings can assist practitioners and hotel executives by providing the information and rationale for adopting seasonal volatility pricing. Structural breaks in price time-series have practical implications for setting seasonal-pricing schemes. Tourists could benefit either from greater price stability or from differentiated seasonal prices, which are important in the promotion of the price attractiveness of the tourist destination. Originality/value The originality of the paper lies in the applied unit root econometrics for tourism price time-series modelling and the prediction of short-stay accommodation prices.

The Tobit cointegrated vector autoregressive model: An application to the currency market

The Tobit cointegrated vector autoregressive model proposed in this study extends the existing methodology by allowing the censored variable to be nonstationary. The approach requires deriving the distribution of the cointegration rank test and simulating new critical values. The empirical application refers to the currency market. It has confirmed that the exchange rate is driven by four main forces: inflation, terms of trade, the perception of the country-specific risk, and the state of the currency market. Temporary disequilibria in the currency market arise not only from the “fundamental” factors, but also from the contagion effect.