Estimation Of VAR Model Research Articles

Ridge regularized estimation of VAR models for inference

Ridge regression is a popular method for dense least squares regularization. In this article, ridge regression is studied in the context of VAR model estimation and inference. The implications of anisotropic penalization are discussed, and a comparison is made with Bayesian ridge‐type estimators. The asymptotic distribution and the properties of cross‐validation techniques are analyzed. Finally, the estimation of impulse response functions is evaluated with Monte Carlo simulations and ridge regression is compared with a number of similar and competing methods.

Risk-return-volume causality on the Croatian stock market

Purpose: Causality between stock returns, volatility and traded volume for 10 most liquid stocks from Zagreb Stock Exchange (ZSE) is examined in this paper. Methodology: The paper relies on historical daily data regarding return, standard deviation and turnover for the period from 2015 to 2021. Vector Autoregressive Models (VARs) were estimated for each stock in-dividually. Based on estimated VAR models, Granger-causality tests were performed to estimate causality between trading volume, stock returns and volatility for most liquid stocks from the Croatian stock market. Results: Results strongly confirm that traded volume Granger causes volatility. Return remained irrelevant in terms of predicting traded volume and volatility of stock returns. Conclusion: Causality from return to volatility or causality from volatility to return can be confirmed only in shorter periods. Traded volume causes volatility for the majority of stocks regardless of how volatility was calculated. Causality from volatility to return and causality from volatility to volume are valid for half of the sample and need to be further investigated.

Veza između SDI, eksterne (ne)ravnoteže i ekonomskog rasta na putu realne konvergencije Republike Srbije

The focus of this research is the nexus between foreign direct investments, FDIs, external imbalance and economic growth, in the case of Serbia in the period 2007-2024. From one side, convergence process towards more developed European economies implies fostering of economic growth i.e. real convergence, which is positively connected with FDIs inflows. From the other side, real convergence is usually accompanied with growing external imbalance i.e. current account deficit. The aim of this research is to shed more light onto these relations from the angle of national economy, under methodological framework of estimated VAR model. Empirical findings confirm that FDIs positively influence real convergence, while real convergence is connected with external imbalance deterioration. National economic authorities should continue efforts to maintain and attract FDIs as beneficial type of external capital inflows, having in mind their positive real repercussions and mediumterm external balancing. Nevertheless, essential and long-run efforts should be oriented towards resolving of chronic CA deficit, thereby increasing country's resistance to global crisis shocks and sudden stop episodes.

Analysis of the contribution of rural road infrastructure development to economic growth based on computer algorithms

Abstract A convenient and efficient rural road network helps to develop the rural economy and promote national rural revitalization. This paper systematically analyzes the role of rural road infrastructure construction on economic growth from a theoretical perspective. Simultaneously, it employs a computer algorithm based on vector autoregression to construct an econometric model. Based on this theoretical analysis empirically examines the relationship between rural infrastructure construction and economic development. It collects data from a city’s rural area from 2000 to 2020 as a research sample and conducts a series of analyses, including VAR model estimation, impulse response, and variance decomposition. The results show that rural road infrastructure construction has a significant impact on economic growth, with coefficients of −0.288 and 0.356 for lags 1 and 2. The construction of rural road infrastructure is responsible for more than 90% of the variation in economic growth, whereas the opposite is about 10%. Therefore, rural road infrastructure development does not have a significant effect on economic growth in the short term but has a significant effect in the medium and long term.

Gas price shocks, the current account, and the real exchange rate: An empirical analysis for the EU

The aim of this paper is to analyse how gas price shocks affect the real exchange rate (RER) and the current account (CA) for a panel of countries from the EU28. We estimate VAR models and account for the possibility of asymmetric effects in gas price shocks. Our results show that the effects on the RER and CA are short-lived and that there are asymmetries in some cases.

Structural Analysis with SVAR Model of the Effectiveness of Fiscal Policy in Peru: 1995 – 2019

Aim: The objective of this research work is the analysis of macroeconomic shocks on fiscal policy in Peru in the years 1995 - 2019, based on empirical evidence collected, a structural autoregressive vector model (SVAR) will be formalized.
 Methodology: The SVAR technique offers the possibility of analyzing the dynamic interrelationships between a set of variables, which gives it greater possibilities to analyze and contrast theoretical models.
 Results: In the first part, certain definitions and arguments that justify the use of this type of model will be shown, then we will show our variables to use and we will propose the model. Next we will show the basic steps to be able to work with time series, such as the unit root tests for our series in levels and then we will use a transformation of these to extract characteristics such that the model presents stability and convergence.
 Conclusion: Then we will show the steps to be able to estimate VAR models, how to choose the optimal lags to later (through an identification process) obtain our structural model. In this part we will use a particular identification methodology and we will discuss its definitions and how economic theory is used to be able to impose restrictions. Finally, in the central part, the impulse-response functions will be estimated, which is (together with the decomposition of the variance prediction error and the history decomposition) the tool that will allow us to draw a conclusion and results about the dynamics of macroeconomic behavior.
 Originality/value: will allow us to draw a conclusion and results about the dynamics of macroeconomic behavior.

A Review of Outlier Detection and Robust Estimation Methods for High Dimensional Time Series Data

Diagnostic procedures for finding outliers in high dimensional multivariate time series and robust estimation methods for these data are reviewed. First, methods for searching for outliers assuming that the data have been generated by a Dynamic Factor Model are presented. Then, other existing methods for detecting different types of multivariate time series outliers are analyzed. They include identifying outlying series and, also, looking for segments, or periods of time, where the series have unusual dynamics. Second, robust estimation methods are considered. Dynamic Principal Components, as a very general procedure to estimate the dynamic in a high dimensional data set, is introduced and different types of robust estimation of these components are reviewed. Dynamic Principal Components can be applied for robust estimation of Generalized Dynamic Factor models and some results are given. Finally, other methods proposed for robust estimation of high dimensional VAR models and other multivariate time series problems are also briefly discussed.

Dynamic Interactions Between the Bitcoin Price Index and Widely Traded Financial Assets: Evidence from the Recent COVID-19 Crisis

We investigate the connectedness between the Bitcoin Price Index (BPI) and widely traded financial assets from different markets (equities, bonds, commodities and fiat currency). Using daily data from 5 August 2013 to 31 August 2021 (before and during the COVID-19 crisis), we run the VAR model estimation to investigate any connectedness between the BPI and financial assets, followed by the Granger causality test. We then test Diebold and Yilmaz’s (2012) framework to analyse the spill-over effects among our set of variables. Our empirical results provide strong evidence that the BPI index exhibits significant independence from widely traded financial assets. This independence is less pronounced during the COVID-19 crisis, but remains relatively important. To test whether Bitcoin constitutes a relevant diversification vehicle, we compute the Sharpe portfolio performance index of two portfolios of conventional assets with and without the BPI, before and during the COVID-19 crisis. Our results show that the introduction of the BPI index as a diversification asset does not improve portfolio performance. Overall, our empirical findings are robust to different robustness tests and provide several implications for hedgers, portfolio managers and policymakers.

THE RELATIONSHIP BETWEEN DIRECT INVESTMENT AND GDP IN ROMANIA

According to the general theory, direct investment has many positive effects on the economy of a state. Romania has attracted a growing number of direct investments. Romania's economy is still marked by the transition from a closed to a market economy. Thus, the effects of communism are still felt today. However, it is making every effort to develop and provide its citizens with a better way of life in line with European norms. It is well-known that direct investments in a country creates opportunities for its economy and people. Various empirical studies have analysed the impact of direct investment on the GDP growth of a country. The present study explored the relationship between direct investment and Romania's GDP using bivariate VAR models. Granger causality principle was used to test the hypothesis that the volume of direct investments in the past explains the current GDP values and the current volume of direct investments. The study found that the rising trend in direct investments in Romania leads to the growth of GDP. The estimated VAR models for Romania provide evidence that increasing GDP results in increased direct investments in the country, reinforcing the idea that investors are sensitive to stable macroeconomic conditions. Subsequent research could also include a comparative study with European Union countries or the introduction of other variables such as inflation rate, unemployment rate, labor costs, etc.

Dynamic interactions between the bitcoin price index and widely traded financial assets: evidence from the recent covid-19 crisis

We investigate the connectedness between the Bitcoin Price Index (BPI) and widelytraded financial assets from a variety of markets (equities, bonds, commoditiesand fiat currency). Using daily data from 5 August 2013 to 31 August 2021 (beforeand during the COVID-19 crisis), we run the VAR model estimation to investigateany connectedness between the BPI and financial assets, followed by the Grangercausality test. We then test Diebold and Yilmaz’s (2012) framework to analyse thespillover effects among our set of variables. Our empirical results provide strongevidence that the BPI index exhibits significant independence from widely tradedfinancial assets. This independence is less pronounced during the COVID-19 crisis,but remains relatively important. To test whether Bitcoin constitutes a relevantdiversification vehicle, we compute the Sharpe portfolio performance index of twoportfolios of conventional assets with and without the BPI, before and during theCOVID-19 crisis. Our results show that the introduction of the BPI index as a diversificationasset does not improve portfolio performance. Overall, our empiricalfindings are robust to different robustness tests and provide several implicationsfor hedgers, portfolio managers and policymakers.

The Casual Nexus between Income and Energy Poverty in EU Member States

This paper investigates the presence of a causal relationship between energy poverty and income poverty in the EU Member States through a Panel Vector Autoregressive specification, and controlled with a set of explanatory variables collected from the Eurostat energy database and the OECD environment database for 2007–2018. Deepening the nexus between energy poverty and income poverty is a relevant issue for tailoring policies to tackle poverty and improve the well-being of citizens, supporting the policy makers in the allocation of planned funds provided by the Recovery plan, “Next Generation EU”. The results of the panel VAR model estimation and Dumitrescu and Hurlin test suggest that there will be no change in the long-run equilibrium when income poverty remains constant. Moreover, the reduction in energy poverty is expected to have a positive effect in terms of overall economic poverty reduction. Finally, there is evidence that substituting fossil fuels with renewables helps to reduce energy poverty and widespread poverty due to the leverage effect on economic development as well as to support the achievement of some of the 17 Sustainable Development Goals addressed by United Nations.

Monetary Policy Shocks in Open Economies and the Inflation Unemployment Trade-Off: The Case of the Euro Area

In this paper, we show that in order to obtain a sound identification of Euro Area monetary policy shocks, one needs to deal with the interaction of the European Central Bank and the US Federal Reserve. In other words, a proper identification of monetary policy shocks for an open economy like the Euro Area requires consideration of the US policy rate. Indeed, when we exclude the Federal Funds Rate from an estimated VAR model including a set of Euro Area variables, i.e., Eonia, inflation and unemployment, we detect a wrong sign in the response of inflation to contractionary monetary policy shocks. Moreover, even adding the world price of oil does not help to overcome the problem. Instead, for a sample covering the period 1999–2019, when the Federal Funds Rate and the Euro–Dollar exchange rate are added to the VAR model inflation shows statistically non-significant effects for two years and thereafter decreases. Under this specification of the model, a clear and significant unemployment inflation trade-off emerges. These conclusions are confirmed by using industrial production instead of the unemployment rate in the VAR model.

Assessment of country institutional factor on sustainable energy target achievement in European Union

This study examines causality relation between the quality of national institutional frameworks designed to ensure higher energy efficiency and the distance to the achievement of the EU Commission targets in terms of energy consumption, using a panel of 21 EU member states. Through panel unit root tests and an estimated VAR model, our results reveal that the quality of a nation’s institutional and economic energy efficiency framework does not significantly influence the gap between annual energy consumption and related EU targets, as prescribed by the energy efficiency EU Directives. However, the results show a bi-directional causality relationship suggests that the nation’s institutional framework on energy efficiency should be improved. According to the impulse response function, this relationship is more related to a short-run perspective. Hence, a strong correlation exists between the level of achieving the reduction targets on energy consumption and the level of gas emissions. Our findings further reveal that the level of reported GHCs significantly influences national regulations and strategies for gas emission reductions. This research highlights the importance of each EU member state creating an appropriate legislative and institutional framework that promotes energy efficiency.

Short-Term Capital Flows, Exchange Rate Expectation and Currency Internationalization: Evidence from China

This paper intended to employ a portfolio approach to assess the effect of exchange rate expectation on Chinese RMB internationalization and empirically test the interactive effects among short-term capital flows, RMB appreciation expectation and the internationalization process using a VAR model with monthly data ranging from February 2004 to December 2020. The results suggest that RMB exchange rate appreciation could lead to an increase in the foreign demand for RMB and RMB denominated assets, while RMB internationalization would attract more short-term capital inflow due to the reduced transaction costs. The empirical evidence from the VAR model estimation confirms the finding that expected RMB appreciation induces short-term capital inflow and promotes RMB internationalization. The robustness checks confirm the evidence. The results have important policy implication for RMB internationalization and for maintaining a sound and stable financial system.

Integration in Central European capital markets in the context of the global COVID-19 pandemic

Research background: Covid-19 pandemic had a strong impact on the economy and capital market. In times of crisis, it is important for investors to be able to diversify their investment portfolio in order to mitigate risk. However, the growing trend towards capital market integration may make it ineffective. Research on financial integration, during the Covid-19 period, has started to develop, mainly in major global capital markets. It is, therefore, important to extend this research to other capital markets.
 The purpose of the article: This contribution aims to analyze financial integration in the stock indexes of the capital markets of Austria (ATX), Slovenia (SBITOP), Hungary (BUDAPEST SE), Lithuania (OMX VILNIUS), Poland (WIG), the Czech Republic (PX PRAGUE), Russia (MOEX) and Serbia (BELEX 15), in the context of the global pandemic (COVID-19).
 Methods: To measure the unit roots in the time series, we used ADF, PP, and KPSS tests, and Clemente et al. (1998) test to detect structural breaks. To ana-lyse financial integration, we applied the Gregory and Hansen integration test, and to validate the robustness of results, we use the impulse-response function (IRF) methodology, with Monte Carlo simulations, as they provide a dynamic analysis generated from the VAR model estimates.
 Findings & Value added: The results suggest very significant levels of integration, which decreases the chances of portfolio diversification in the long-term. Evidence shows 47 pairs of integrated stock market indexes (out of 56 possible). The stock indexes ATX, BUDAPESTE SE, BELEX 15 show financial integration with all other indexes. On the contrary, the index of OMX VILNIUS shows only 3 integrations. Results also show that most of the significant structural breaks occurred in March 2020. The analysis of the relationship between markets, in the short term, shows positive/negative co-movements, with statis-tical significance and with a persistence longer than one week.

The Role of the Prior in Estimating VAR Models with Sign Restrictions

Several recent studies have expressed concern that the Haar prior typically imposed in estimating sign-identified VAR models may be unintentionally informative about the implied prior for the structural impulse responses. This question is indeed important, but we show that the tools that have been used in the literature to illustrate this potential problem are invalid. Specifically, we show that it does not make sense from a Bayesian point of view to characterize the impulse response prior based on the distribution of the impulse responses conditional on the maximum likelihood estimator of the reduced-form parameters, since the the prior does not, in general, depend on the data. We illustrate that this approach tends to produce highly misleading estimates of the impulse response priors. We formally derive the correct impulse response prior distribution and show that there is no evidence that typical sign-identified VAR models estimated using conventional priors tend to imply unintentionally informative priors for the impulse response vector or that the corresponding posterior is dominated by the prior. Our evidence suggests that concerns about the Haar prior for the rotation matrix have been greatly overstated and that alternative estimation methods are not required in typical applications. Finally, we demonstrate that the alternative Bayesian approach to estimating sign-identified VAR models proposed by Baumeister and Hamilton (2015) suffers from exactly the same conceptual shortcoming as the conventional approach. We illustrate that this alternative approach may imply highly economically implausible impulse response priors.

Exploiting Heterogeneous Parallelism on Hybrid Metaheuristics for Vector Autoregression Models

In the last years, the huge amount of data available in many disciplines makes the mathematical modeling, and, more concretely, econometric models, a very important technique to explain those data. One of the most used of those econometric techniques is the Vector Autoregression Models (VAR) which are multi-equation models that linearly describe the interactions and behavior of a group of variables by using their past. Traditionally, Ordinary Least Squares and Maximum likelihood estimators have been used in the estimation of VAR models. These techniques are consistent and asymptotically efficient under ideal conditions of the data and the identification problem. Otherwise, these techniques would yield inconsistent parameter estimations. This paper considers the estimation of a VAR model by minimizing the difference between the dependent variables in a certain time, and the expression of their own past and the exogenous variables of the model (in this case denoted as VARX model). The solution of this optimization problem is approached through hybrid metaheuristics. The high computational cost due to the huge amount of data makes it necessary to exploit High-Performance Computing for the acceleration of methods to obtain the models. The parameterized, parallel implementation of the metaheuristics and the matrix formulation ease the simultaneous exploitation of parallelism for groups of hybrid metaheuristics. Multilevel and heterogeneous parallelism are exploited in multicore CPU plus multiGPU nodes, with the optimum combination of the different parallelism parameters depending on the particular metaheuristic and the problem it is applied to.

OLS Estimation of Markov switching VAR models: asymptotics and application to energy use

We show that the ordinary least squares (OLS) estimates of population parameters for Markov switching vector autoregressive (MS VAR) models coincide with the maximum likelihood estimates. Then, we propose an algorithm in matrix form for the estimation of model parameters, and derive an explicit expression in closed-form for the asymptotic covariance matrix of the OLS estimator of such models. The obtained characterization of the asymptotic variance is new to our knowledge. It is easier to program than the usual approach based on second derivatives, and more accurate. Our theorems generalize the classical results known for a linear VAR process, and complete those existing in the literature on the estimation of the asymptotic covariance matrix for multivariate stationary time series. Numerical simulations are provided to illustrate the obtained theoretical results. Finally, an application on energy use and economic growth in the Euro area gives some insights on the nonlinear nature of the corresponding time series, and reproduces the major stylized facts.

SHAPING ECONOMIC GROWTH OF THAILAND THROUGH CRUDE OIL DYNAMICS: ROLE OF ITS EXPLORATION, CONSUMPTION AND PRICES

The exploration, consumption and prices of crude oil are very important aspects for the enhancement of the economy of any country. Therefore in order to check the impact of these three aspects of crude oil on economic growth of the country, this study has been conducted by the author. Data collection process has been done in Thailand and 26 years data has been accumulated for analysis purpose. Unit root test, co-integration test and VAR model estimation are the most important tests that have been employed in this particular study. The results of all these tests have been discussed in the study in detail. The impacts of exploration, consumption and prices of crude oil as well as population growth and energy consumption have been found to be significant in regard to economic growth. Various theoretical, practical and policy making benefits of these results have been identified and explored by the author all of which point towards the enhancement of economic growth. In addition, the limitations found in the study along with some recommendations have also been described so that the future researchers may consider them and work on them in order to overcome these limitations.

SEEING DOMESTIC AND INDUSTRIAL LOGISTIC IN CONTEXT OF CO2 EMISSION: ROLE OF CONTAINER PORT TRAFFIC, RAILWAY TRANSPORT, AND AIR TRANSPORT INTENSITY IN THAILAND

CO2 emission has becoming a global issue with its increasing intensity and quantity. There are various factors that have been found that affect CO2 emission positively or negatively. In this study, the author has selected three independent variables i.e. container port traffic, railway transport and air transport intensity so that their impact can be studied on CO2 emission. The author has gathered data from Thailand in context of the above-mentioned variables for 27 years. After application of several tests and approaches such as unit root tests, co-integration test and VAR model estimation, the results of these approaches have been obtained. The order of integration, scholastic properties, co-integrated relationships and short and long run relationships have been explored by the use of these approaches. According to these results, the impact of all the independent and control variables have been found as significant on CO2 emission. After the detailed discussion of results obtained by the author, some of the benefits related to this study have been discussed. These benefits may be for many people such as researchers, government and other authorities.Keywords: Domestic and Industrial Logistic, CO2 Emission, Container Port Traffic, Railway Transport, Air Transport IntensityJEL Classifications: L92, L93DOI: https://doi.org/10.32479/ijeep.10227