A Comparison of Threshold Cointegration and Markov-Switching Vector Error Correction Models in Price Transmission Analysis

We compare two regime-dependent econometric models for price transmission analysis, namely the threshold vector error correction model and Markov-switching vector error correction model. We first provide a detailed characterization of each of the models which is followed by a comprehensive comparison. We find that the assumptions regarding the nature of their regime-switching mechanisms are fundamentally different so that each model is suitable for a certain type of nonlinear price transmission. Furthermore, we conduct a Monte Carlo experiment in order to study the performance of the estimation techniques of both models for simulated data. We find that both models are adequate for studying price transmission since their characteristics match the underlying economic theory and allow hence for an easy interpretation. Nevertheless, the results of the corresponding estimation techniques do not reproduce the true parameters and are not robust against nuisance parameters. The comparison is supplemented by a review of empirical studies in price transmission analysis in which mostly the threshold vector error correction model is applied.price transmission, market integration, threshold vector error correction model, Markov-switching vector error correction model, comparison, nonlinear time series analysis, Agricultural Finance,

vector error correction model approach

Thesis(Master) -- KDI School: Master of Public Policy, 2022Economies all over the world aim to achieve high growth rate of output and stability in the general price level. But the tradeoff between output growth and inflation makes it imperative for Central Banks to conduct monetary policy. The study, therefore, aims to analyze the effect of price and money supply on GDP growth in Ghana using a forty-year time series data from 1980 to 2020. The empirical work used Vector Error Correction Model (VECM), cumulative impulse response function in VAR model and causality checks techniques to assess short-run and long- run relationship among price level, broad money supply, interest rate and GDP. Analysis of VECM short-run estimates revealed broad supply of money significantly affects GDP. The results further indicate that past year income and price level have negative and statistically significant effects on current year output. However, long-run estimates of the co-integrating vector shows that supply of money does not have statistically significant effect on GDP. This result is corroborated by the outcome of the cumulative orthogonal impulse response function. Furthermore, with -0.215 as the coefficient of the error correction model, a disequilibrium to GDP caused by shocks to the exogenous variables in the short-run are corrected at an adjustment speed of 21.5% in the long-run. Moreover, the study robustly concludes on bidirectional relationship between inflation and money supply. As a policy recommendation, this study proposes that the Bank of Ghana pays critical attention to the monetary policy rate since it is the channel through which the central bank targets inflation in order to achieve price stability and sustained output growth.1 INTRODUCTION 2 LITERATURE REVIEW 3 METHODOLOGY 4 PRESENTATION AND ANALYSIS OF EMPIRICAL RESULTS 5 CONCLUSION AND POLICY RECOMMENDATIONSmasterpublishedAbdul-Razak Abass SAEE

Bayesian Analysis of Markov Switching Vector Error Correction Model

This paper introduces a Bayesian approach to a Markov switching vector error correction model that allows for regime shifts in the intercept terms, the lag terms, the adjustment terms and the variance-covariance matrix. The proposed Bayesian method allows for estimation of the cointegrating vector within a nonlinear framework through Gibbs sampling so that it generates more efficient estimation than classical approaches that require a multi-stage maximum likelihood procedure. The Bayes factors are applied to test for Markov switching and model specifications. We apply the proposed model to U.S. term structure of interest rates allowing the risk premium and other parameters in the model to change with regime.Bayesian inference, Nonlinear cointegration, Markov switching model, Gibbs sampling, Bayes factor

Linear Vector Error Correction Model Versus Markov Switching Vector Error Correction Model To Investigate Stock Market Behaviour

The stock market can reflect the economy of a country. The movement of the stock market index may imply the economic condition in general. The 1997 Asian Financial Crisis and the 2008 Global Economic Crisis are examples of share depressions that impacted countries’ inflation, unemployment rates and gross national product (GNP). This study investigates how oil and gold prices impact the stock exchange using a linear vector error correction model (VECM) and a Markov switching vector error correction model (MS-VECM). The results show that oil and gold prices affect the stock market returns for the four selected countries, namely Malaysia, Singapore, Thailand and Indonesia. The MS-VECM is able to capture every change in the transition probabilities of the financial time series data and is more reliable than the linear VECM for examining the effect of oil and gold prices on the stock market

The Effect of Federal Government Size on Long-Term Economic Growth in the United States, 1792-2004

In this paper, we consider whether there is statistical evidence for a causal relationship between federal government expenditures and growth in real per-capita GDP in the United States, using available data going back to 1792. After studying the time-series properties of these variables for stationarity and cointegration, we investigate Granger causality in detail in the context of a Vector Error Correction Model. While we find causal evidence supporting Wagner’s Law, we find no evidence supporting the common assertion that a larger government sector leads to slower economic growth.long-term economic growth, federal government size, Wagner’s Law, United States, cointegration, Granger causality, vector autoregression, vector error correction model

Does the Solow Residual for Korea Reflect Pure Technology Shocks?

This study investigates the relationship between the measured Solow residual and demand side variables for the Korean economy. The measured Solow residuals are shown to be Granger-caused by some demand side variables such as exports, M1, and government expenditure. A vector error correction model is constructed to investigate dynamic relation between these demand side variables and the Solow residual. Impulse response functions shows that the measured Solow residual moves pro-cyclically with the demand shocks, and that the forecast error variance of the measured Solow residual is mostly explained by past innovations of these demand side variablesSolow residual, Productivity shock, Vector error correction model

Modeling the supply and demand for tourism: a fully identified VECM approach

Cointegration analysis has gradually appeared in the empirical tourism literature. However, the focus has been exclusively on the demand side, neglecting potentially-important supply-side influences and risking endogeneity bias. One reason for this omission may be the difficulty identifying structural relationships in a system setting. We estimate a vector error correction model of the supply and demand for Hawaii tourism using a theory-directed sequential reduction method suggested by Hall et al. (2002). We compare forecasts for the selected model and for two competing models. Diebold and Mariano (1995) tests for forecast accuracy demonstrate the satisfactory performance of this approach.catastrophe, Cointegration, Vector error correction model, Identification, Tourism demand and supply analysis, Hawaii

China's Meat Consumption: An Income Elasticity Analysis and Long-Term Projections

Bennett's law, China, meat consumption, income elasticity, vector error correction model (VECM), projection, Agricultural and Food Policy, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, C22, Q11, Q13,

Wheat / Flour Price Transmission and Agricultural Policies in Ukraine: A Markov-Switching Vector Error Correction Approach

The analysis of price transmission between raw and processed agricultural products in transition countries is complicated by the frequently changing conditions on their way from plan to market. We utilise a Markov-switching vector error correction model to allow for multiple regime shifts in the price relationship between wheat and wheat flour in Ukraine from June 2000 to November 2004. The analysis reveals four regimes. The observed temporal pattern of these regimes can be matched with certain political and economic events in Ukraine. In particular, we find a strong link between the 'high uncertainty' regime and discretionary policy interventions in 2003.Markov-switching vector error correction model, vertical price transmission, regime shifts, grain policies, Ukraine, Demand and Price Analysis, Industrial Organization, C22, Q11, Q18,

Links between the Indian, U.S. and Chinese Stock Markets

This study examines the bilateral relations between three pairs of stock markets, namely India-U.S., India-China and China-U.S. We use a Fractionally Integrated Vector Error Correction Model (FIVECM) to examine the cointegration mechanism between markets. By augmenting the FIVECM with a multivariate GARCH formulation, we study the first and second moment spillover effects simultaneously. Our empirical results show that all three pairs of stock markets are fractionally cointegrated. The U.S. stock market plays a dominant role in the relations with the other two markets, whereas there is an interactive relationship between the Indian and Chinese stock markets. In particular, the Indian stock market dominates the first moment feedback with the Chinese market, while the latter dominates the second moment feedback with the former.Stock market, Cointegration, Fractionally Integrated Vector Error Correction Model, Multivariate GARCH