Academic literature on the topic 'Panel Vector Autoregressive Model (panel VAR)'

This study focuses on the volatility spillover between the stock prices of foreign banks having business in Turkey and the exchange rate. More particularly, it analyzes the connectedness between the USD-TRY exchange rate volatility and the foreign banks’ stock price volatility in their own country’s stock markets. We select ten foreign banks with the biggest total assets and divide them into two panels: eastern and western capitalized banks. The dataset contains weekly data from 2016-01-04 to 2022-01-17. We estimate volatilities utilizing the Conditional Autoregressive Range (CARR) model and then apply the Time-Varying Parameter- Vector Autoregressive (TVP-VAR) based Diebold–Yilmaz Connectedness Index to reveal the transition and connectedness of volatility. The total connectedness indices show that 26.72 and 54.75% of the forecast error variance originate from other assets included in the spillover analysis for eastern and western panels, respectively. We also explore net pairwise comovements and find that shocks in USD-TRY have dominated on the forecast error variance of bank stocks in the eastern panel, while it is a net volatility receiver in the western panel.

In this paper, we analyzed articles by foreign authors that use various vector autoregression models to calculate the impact of qualitative indicators on the economic processes of countries or a group of countries. In particular, the article analyzed the classical model of vector autoregression (VAR), panel model of autoregressive (PVAR), Bayesian model of autoregressive (BVAR), structural model of autoregressive (SVAR), and the global model of autoregressive (GVAR). Among the works using vector autoregressive models, the main emphasis is on financial indicators. Moreover, articles with non-trivial variables are rare. This is because financial macroeconomic variables in most cases have a direct impact on economic processes in the country. The analysis of financial indicators and the results obtained can play a significant role in the development of economic strategies in different states, since the results obtained with the help of vector autoregression models are usually quite accurate. The studied articles analyze the data of both developed and developing states or groups of states in different periods. The studied articles were classified according to several criteria, which were selected by the author to structure the work. Note that among the works using vector autoregressive models, the main emphasis is on financial indicators. Moreover, articles with non-trivial variables are rare. This is since financial macroeconomic variables in most cases have a direct impact on economic processes in the country. The analysis of financial indicators and the results obtained can play a significant role in the development of economic strategies in different states, since the results obtained with the help of vector autoregression models are usually quite accurate. In the conclusion of this study, the author presented conclusions based on the analysis of autoregressive models.

The study modeled the dynamic interaction between exchange rate, interest rate and agricultural export earnings using panel VAR Model. The specific objectives of the study include to; interdependencies in the dynamic interaction between exchange rate, interest rate and agricultural export earnings, parameters of panel VAR model using PVAR Stata code developed by Abrigo and love, determine the shocks associated with their dynamic interactions between these variables, investigate direction of causality between interest rate, exchange rate and agricultural export earnings from six African countries and make appropriate recommendations. The data used for the study was secondary data extracted from index mundi website and world data indicators for the period of 40 years (1980-2020). The data was on exchange rate, interest rate and agricultural export earnings. Geographically, the six African countries include; Algeria, Angola, Egypt, Libya, Gabon and Nigeria. The study uses vector Autoregressive model estimation results with PVAR Stata code developed by Abrigo and love. The post estimation test on the Vector Autoregressive (VAR) model shows a contemporary Co-efficient of Correlation analysis. It was found that lending interest rate and exchange rate are negatively associated with Co-efficient of Correlation of (-0.0873). Also, it was found that there exist a positive association between exchange rate and agricultural export earnings. Also, there is a positive association between lending interest rate and agricultural export earnings. The inverse roots of a characteristic polynomial of the estimated Panel VAR model satisfied the stability condition (of the diagnostic test) since no root lied outside the unit root circle. Therefore, the estimated VAR is stable. However, it was confirmed that there is no directional relationship that exist between the variables. Also, the results show that exchange rate and lending rate have positive on agricultural export earnings, whereas exchange rate is likely to reduce the level of lending interest rate slightly. Therefore, it is recommended that in estimating the dynamic interaction between variables in a panel data system, there is need for the inclusion of the lags of the response variable among the determinants to measures the dynamic interaction as well capture heterogeneities in the series and also, policies should be formulated to stabilized exchange and lending rates in order to improve and strengthen the countries’ agricultural economy amongst others

This paper examines the responses of stock traded and economic activity in relation to central bank independence shocks. The analysis is based on a panel Vector Autoregressive estimation covering 25 developing countries for a quarterly period between 1990 Q1 and 2021 Q4. Panel VAR estimation is known to be potentially biased in a dynamic panel data model if the coefficient on the endogenous variables differs across countries. To test the pooling assumption of the model, this paper applies the Chow and Roy-Zellner tests. The results establish that the models contain the heterogeneity among samples; thus, mean-group estimation for panel VAR is performed as a solution for heterogeneity problem. The results show that there is a delayed effect of CBI to increase stock traded. This demonstrates that CBI takes around six quarters to strengthen the financial market. By dividing the sample into two groups, we find that CBI has a different effect on stock traded for countries that have high and low stock traded.

By utilizing Panel Vector Autoregressive (PVAR) model, this study aims to identify the reciprocal effect of the level of education, health, and income inequality in Indonesia. Data of 33 provinces from 2009-2013 specifically means of school years for education level, life expectancy for health level, and gini ratio for the income inequality are explored. Furthermore, Granger Causality Test is employed to test the causality of the variables. The results showed that the levels of education, health, and income inequality in Indonesia shared mutual relationship by applying one lag as the best PVAR model in this study.

This paper examines the relationship between the current account (CA) and the foreign direct investment (FDI) net inflow in the Southeast Europe (SEE) countries. The panel data framework of five SEE countries for the period 2000- 2020 are used. Our research has three main findings. First, using the vector autoregressive VAR(2) model, a long-run relationship between the CA and the net FDI inflow is identified (a 1% increase in the net FDI inflow leads to a 1.011% increase in the CA deficit). This suggests that FDI stock will put upward pressure on the CA of the SEE countries in the long run. Second, applying the panel VAR model Granger causality test, we found that there is a two-way directional Granger causality. Third, our results from the vector error correction (VEC) model suggest that about 26% of the dynamics of the CA deficit adjusts to the long-run equilibrium path with the net FDI inflow each year.

This paper provides an overview of a time-varying Structural Panel Bayesian Vector Autoregression model that deals with model misspecification and unobserved heterogeneity problems in applied macroeconomic analyses when studying time-varying relationships and dynamic interdependencies among countries and variables. I discuss what its distinctive features are, what it is used for, and how it can be analytically derived. I also describe how it is estimated and how structural spillovers and shock identification are performed. The model is empirically applied to a set of developed European economies to illustrate the functioning and the ability of the model. The paper also discusses more recent studies that have used multivariate dynamic macro-panels to evaluate idiosyncratic business cycles, policy-making, and spillover effects among different sectors and countries.

The financial crisis has always been accompanied by human economic activities, and its outbreak has a serious impact on people's normal life, and it has no warning, which is a problem of great concern to all countries in the current economic development. Based on the monthly data of long-term bond yields of eight countries (six European countries, the United States and Japan) from December 2009 to February 2012, through correlation test and Granger causality analysis, the results show that there is no Granger causality between the bond yields of various countries and the bond yields of Greece before the European debt crisis, but Granger causality exists between the bond yields of Germany, France and Italy and Greece after the crisis. Finally, it puts forward the process of China's complete opening of capital account and the problems that should be paid attention to after that. The latest development direction of vector autoregressive model is the identification of exogenous policy shocks and the estimation of panel vector autoregressive model. This paper studies and analyzes the transmission mechanism of international financial crisis. Vector autoregressive model is used to describe the transmission mechanism of international financial crisis. The enhancement of the ability to resist the contagion of financial crisis is an important factor to promote the sound development of China's economy. Starting with the related concepts of the transmission mechanism of international financial crisis, this paper probes into the specific transmission modes of international financial crisis and the suppression measures of the transmission mechanism of international financial crisis.

This study aims to analyse the dynamic between credit to micro, small, and medium enterprises (MSMEs), private credit, and regional economic growth in Indonesia. A panel vector autoregression model is employed to understand the dynamic in the model. Unlike previous cross-country studies, this paper is using provincial panel data. The relationship between variables in the model are connected under the same regulation, monetary authority, and fiscal institution. Thus, there will be no effects that appear from the differences of institutions. The results suggest that the interaction between credit to MSMEs and private credit is bi-directional. Also, credit to MSMEs and private credit does affect regional economic growth. However, the result does not provide strong evidence for causality from regional economic growth to credit for MSMEs or private credit. Penelitian ini bertujuan untuk menganalisis hubungan dinamis antara kredit kepada UMKM, kredit kepada sektor privat, dan pertumbuhan ekonomi regional di Indonesia. Untuk memahami hubungan ketiga variable tersebut, penelitian ini menggunakan panel vector autoregression (Panel VAR). Penelitian ini berbeda dengan penelitian antar negara yang telah ada sebelumnya karena penelitian ini menggunakan data pada level provinsi. Data pada level provinsi memiliki keunggulan karena berada pada sistem regulasi perbankan dan regulasi fiskal yang sama sehingga tidak terdapat efek dari adanya perbedaan institusional. Dari penelitian ini diketahui bahwa interaksi antara kredit kepada UMKM dan kredit kepada sektor privat adalah dua arah. Kredit kepada UMKM dan kredit kepada sektor privat mempengaruhi pertumbuhan ekonomi regional, namun tidak terdapat bukti kuat yang menjelaskan hubungan sebaliknya.

This research aimed to analyze the influence of factors such as current ratio, debt to asset ratio, debt to equity ratio, return on assets and return on equity of the company dividend policy with vector autoregressive models as a tool of analysis, Sample of this research is the company to go public in addition to the financial services listed in the Indonesia Stock Exchange (BEI) as many as 25 companies were observed for five years (2009-2013).The analytical method used in this research is panel data regression model (a combination of time series and cross section) and vector autoregressive models (VAR) by outlining this research model into several sub-structural. The research results with the VAR model shows that the current ratio, debt to asset ratio, return on assets have a significant influence on the dividend payout ratio and debt to equity ratio, return on equity does not have a significant influence on the dividend payout ratio.so itcan be concluded that this is dueif therate of return on asset sincreased currentm ratio automatically rises and dividend payments can be smoothlypaid outso as to provide symmetry between these variables.

L’instabilità politica é stata a lungo al centro dei dibattiti internazionali in termini di dimensioni,ragioni e conseguenze. La questione di un ambiente politico instabile riveste molta importanza per il suo legame con i problemi socio-economici che l'instabilità politica arreca alle persone di un paese. Ma prima che queste connessioni siano osservate, la misura dell'instabilità politica dovrebbe essere definita correttamente. Pertanto, la prima fase degli studi che si occupano di instabilità politica dovrebbe includere una spiegazione esauriente di cosa si intende per "instabilità politica", considerando la possibilità che diverse dimensioni dell'instabilità politica possano avere conseguenze diverse. In questo contesto, questa tesi si propone di approfondire il tema dell'instabilità politica partendo dall’idea che si tratti di un concetto complesso e multidimensionale. La tesi si propone, in primo luogo, di riuscire a misurare tale concetto individuandone le necessarie dimensioni ed indicatori che la caratterizzano. Dopo aver risolto la questione cruciale della misurazione dell'instabilità politica, la tesi propone un’analisi delle connessioni tra l’instabilità politica e la performance macroeconomica ma anche tra instabilità politica, sicurezza alimentare e disuguaglianza di reddito. La tesi inizia con la parte introduttiva, che introduce l'obiettivo dello studio e dati e metodi quantitativi che verranno utilizzati nei capitoli successivi. Inoltre, questa parte mostra anche i risultati generali, il contributo principale alla letteratura, i vincoli e la ricerca futura. Il Capitolo I, in cui si determinano le dimensioni dell'instabilità politica, è la pietra angolare della tesi, in quanto i due capitoli successivi impiegano i risultati ottenuti in tale capitolo. L’analisi delle Componenti Principali (ACP), che è un metodo di riduzione della dimensionalità, viene utilizzato come strumento per misurare l'instabilità politica utilizando 11 variabili di rischio politico tratte dal dataset della International Country Risk Guide (The PRS Group 2014) osservato in 117 paesi. I risultati suggeriscono che le l’instabilità politica debba essere declinata in due componenti, denominate rispettivamente come Il Difetto Strutturale e Il Disordine della Qualità Politica. Inoltre, il Capitolo I mostra anche come questi due aspetti dell'instabilità politica siano caratterizzati dalle seguenti tre forme di governo: Sistema Parlamentare, Sistema Presidenziale, Sistema Semi-Presidenziale. Inoltre, il Clustering Gerarchico, utilizzando l’algoritmo di collegamento di Ward, viene eseguito per dividere i paesi in gruppi omogenei rispetto alle componenti dell’instabilità precedentemente indivduate, Il Difetto Strutturale e Il Disordine della Qualità Politica. Il Capitolo II e il Capitolo III utilizzano la panel Vector Autoregression Analysis (panel VAR) nei generalized methods of moment (GMM) nel periodo 2008-2017. Mentre il Capitolo II analizza il legame tra instabilità politica e performance macroeconomica dei paesi considerati, il Capitolo III si occupa del nesso tra instabilità politica, sicurezza alimentare e disuguaglianza di reddito. In entrambi i capitoli, i risultati suggeriscono che la direzione e il significato di questi legami a volte cambiano in base alle due diverse dimensioni dell'instabilità politica. Questo significa che diversi aspetti dell'instabilità politica producono risultati diversi. Per di più, c'è sempre una relazione avversa tra i due diversi aspetti dell'instabilità politica e altre variabili nell'analisi. Inoltre, sia il Capitolo II che il Capitolo III analizzano la Funzione di Risposta Impulsiva (IRFs) per comprendere meglio la reazione delle variabili tra loro (scosse di assestamento). Infine, questi capitoli esaminano ulteriormente la Scomposizione della Varianza dell'errore di Previsione (FEVDs) per mostrare la proporzione dei movimenti nelle variabili dipendenti che sono dovuti ai propri shock rispetto agli shock delle altre variabili.
Political instability has long been at the centre of international debates in terms of its dimensions, reasons, and consequences. The issue of an unstable political environment is highly important due to its link with socio-economic problems that political instability brings to the people of a country. But before these connections are observed, the measurement of political instability should be correctly defined. Therefore, the first step of studies dealing with political instability should include a comprehensive explanation of what is meant by “political instability”, considering the possibility that different dimensions of political instability may have different consequences. In this context, this thesis claims that political instability cannot be fitted into a single mould and it has more than one dimension. When the crucial issue of how to measure political instability is settled, this thesis empirically investigates both the connections between political instability and macroeconomic performance and the nexus between political instability, food security and income inequality. The thesis starts with the Introduction part, which introduces the aim of the study and data and quantitative methods that will be exploited in the next chapters. In addition, this part also displays the general findings, main contribution to existence literature, constraints and future research. Chapter I, in which the dimensions of political instability is determined, is the cornerstone of the thesis, since the next two chapters employ these identifications of political instability. Principal Component Analysis (PCA), which is a dimensionality reduction method, is used as a tool to identify the measurement of political instability by using 11 political risk variables taken from the International Country Risk Guide dataset (The PRS Group 2014) observed on 117 countries. The results suggest that the first two principal components are selected and named as Structural Defect and Disorder of Polity Quality, respectively. Furthermore, Chapter I also shows how these two aspects of political instability are characterized by the following three government forms: Parliamentary System, Presidential System, Semi-Presidential System. In addition, Hierarchical Clustering by using Ward’s linkage algorithm is performed to divide countries into smaller clusters based on their similarities in terms of Structural Defect and Disorder of Polity Quality. Chapter II and Chapter III use panel Vector Autoregression Analysis (panel VAR) in generalized methods of moment (GMM) over the period of 2008-2017. While Chapter II analyzes the link between political instability and macroeconomic performance in the set of considered countries, Chapter III deals with the nexus between political instability, food security and income inequality. In both chapters, the results suggest that the direction and significance of these links sometimes change according to two different dimensions of political instability. That means that different aspects of political instability produce different results. Additionally, there is always an adverse relationship between two different aspects of political instability and other variables in the analysis. Furthermore, both Chapter II and Chapter III analyze the impulse response functions (IRFs) to better understand the reaction of variables to each other (aftershocks). Finally, these chapters further examine the forecast-error variance decompositions (FEVDs) to show the proportion of movements in the dependent variables that are due to their own shocks versus shocks to the other variables.

This dissertation examines the causal relationship between inward foreign direct investment (FDI) and economic growth (GDP) in SADC countries. The study investigates, within a panel data context, whether causation is short-term, long-term or both; and explores whether the causal relationship between the two variables differs according to income level. The study covered a panel of 15 SADC countries over the period 1980-2012. In order to assess whether the causal relationship between FDI inflows and economic growth is dependent on the level of income, the study divided the SADC countries into two groups, namely, the low-income and the middleincome countries. The study used the recently developed panel data analysis methods to examine this causal relationship. It adopted a three stage approach, which consists of panel unit root, panel cointegration and Granger causality to examine the dynamic causal relationship between the two variables. Panel unit root results show that both variables in the two SADC country groups were integrated of order one. Panel cointegration tests showed that the variables for low-income country group were not cointegrated, while the variables for the middle-income countries were cointegrated. Since the low-income country group panels were not cointegrated, Grangercausality tests were conducted within a VAR framework, while causality tests for the middleincome country group were conducted within an ECM framework. Panel Granger causality results for the low-income countries showed no evidence of causality in either direction. However, for the middle-income countries’ panel, there was evidence of a unidirectional causal flow from GDP to FDI in both the long- and short- run. The study concludes that the FDI-led growth hypothesis does not apply to SADC countries. The results imply that the recent high economic growth rates recorded in the SADC region, especially middle-income countries, have been attracting FDI. In other words, it is economic growth that drives FDI inflows into the SADC region, and not vice versa. These findings have profound policy implications for the SADC region at large and individual countries.
Economics
MCOM (Economics)

Dissertação de mestrado em Economia
A hipótese dos défices gémeos postula que o défice orçamental e o défice externo estão relacionados positivamente e a direção de causalidade verifica-se do primeiro para o segundo défice. A sua origem remonta à década de 80, nos Estados Unidos da América, quando o saldo orçamental e o saldo comercial se deterioraram de forma quase simultânea. Recentemente, com a crise financeira internacional e a crise da zona euro, os desequilíbrios internos e externos têm assumido uma importância crescente nas economias europeias, o que reacendeu o debate sobre os défices gémeos. Deste modo, este trabalho pretende analisar a relação causal entre o saldo orçamental e o saldo da balança corrente para os países fundadores da Área do Euro (incluindo a Grécia), dividindo-se a amostra em dois grupos de países: países centrais (Alemanha, Áustria, Bélgica, Finlândia, França, Holanda e Luxemburgo) e países periféricos (Espanha, Grécia, Irlanda, Itália e Portugal). Foram utilizados dados anuais, para o período 1995-2017, recorrendo ao Vetor Autorregressivo em painel, cujos os resultados são interpretados recorrendo aos testes de causalidade à Granger, funções de impulso resposta ortogonais e decomposição da variância do erro. Os resultados dos testes de causalidade à Granger, para os países centrais, sugerem fortemente a causalidade do saldo da balança corrente para o saldo orçamental. Nos países periféricos, os resultados sugerem a existência de influência bilateral entre os dois saldos, embora a causalidade do saldo da balança corrente para o saldo orçamental esteja mais fortemente evidenciada. Os resultados das funções de impulso resposta, em ambos os grupos de países, mostram que apenas o choque positivo no saldo da balança corrente leva a uma resposta positiva e estatisticamente significativa por parte do saldo orçamental, entre o 1º e o 8º período. Por último, a magnitude dos choques é analisada com a decomposição da variância do erro. Os resultados sugerem que, nos dois conjuntos de países, o impacto do saldo da balança corrente sobre o saldo orçamental é mais forte. Nos países centrais, o choque no saldo da balança corrente explica mais de 40% da variância do saldo orçamental entre o 9º e o 10º período. Nos países periféricos, o choque no saldo da balança corrente explica mais de 30% da variância do saldo orçamental entre o 5º e o 10º período.
The twin deficits hypothesis postulates that the budget deficit and the external deficit are positively related and the causal relationship runs from the first to the second deficit. Its origin dates to the 80´s, in the United States of America, when the budget balance and the trade balance deteriorated almost simultaneously. Recently, with the global financial crisis and the Eurozone crisis, internal and external imbalances have taken on a growing importance in European economies, which has rekindled the debate on twin deficits. Thus, this work intends to analyze the causal relationship between the budget balance and the current account balance for the founding countries of the Eurozone (including Greece), dividing the sample into two groups of countries: core countries (Germany, Austria, Belgium, Finland, France, Netherlands and Luxembourg) and peripheral countries (Spain, Greece, Ireland, Italy and Portugal). Annual data were used for the period 1995-2017, using the Panel Vector Autoregressive, whose results are interpreted using the Granger causality tests, orthogonal impulse response functions and error variance decomposition. The results of the Granger causality tests, for the core countries, strongly suggest that the causality runs from the current account balance to the budget balance. In peripheral countries, the results suggest the existence of bilateral influence between the two balances, although the causality from current account balance to the budget balance is more strongly evidenced. The results of the impulse response functions, in both groups of countries, show that only the positive shock on the current account balance leads to a positive and statistically significant response of the budget balance, between the 1st and 8th period. Last of all, the magnitude of the shocks is analyzed with the error variance decomposition. The results suggest that, in the two groups of countries, the impact of the current account balance on the budget balance is stronger. In the core countries, the impact on the current account balance accounts for more than 40% of the budget balance variance between the 9th and 10th period. In the peripheral countries, the impact on the current account balance accounts for more than 30% of the budget balance variance between the 5th and 10th period.

This article discusses time-series methods such as simple time-series regressions, ARIMA models, vector autoregression (VAR) models, and unit root and error correction models (ECM). It specifically presents a brief history of time-series analysis before moving to a review of the basic time-series model. It then describes the stationary models in univariate and multivariate analyses. The nonstationary models of each type are addressed. In addition, various issues regarding the analysis of time series including data aggregation and temporal stability are considered. Before concluding, the article briefly reports the time-series techniques in the context of panel data. In general, time-series analysis can help improve the understanding of the political world.

The aim of this chapter is to study the impact of the selected macroeconomic indicators on unemployment rate in the region of Western Balkan countries and, more specifically, Albania, Serbia, Macedonia, Montenegro, Bosnia-Herzegovina, and Kosovo. This research is based on the time period 2000 to 2017 and includes five countries and the econometric model used in here is panel data. Data are retrieved from official and trustable sources such as World Bank and International Monetary Fund (IMF). The methodology used is the vector autoregressive model (VAR), unit root test, Hausman test, Granger causality test. All the macroeconomic variables, inflation, interest rates, GDP, and FDI are found to have a significant impact on unemployment rate of this group of countries. The novelty of this study remains the fact that this analysis is performed for the Western Balkan countries as a group. The results can serve and can be taken into consideration when applying similar econometric analysis in the future researches or implementing new policies that influences the macroeconomic factors.

The aim of this chapter is to study the impact of the selected macroeconomic indicators on unemployment rate in the region of Western Balkan countries and, more specifically, Albania, Serbia, Macedonia, Montenegro, Bosnia-Herzegovina, and Kosovo. This research is based on the time period 2000 to 2017 and includes five countries and the econometric model used in here is panel data. Data are retrieved from official and trustable sources such as World Bank and International Monetary Fund (IMF). The methodology used is the vector autoregressive model (VAR), unit root test, Hausman test, Granger causality test. All the macroeconomic variables, inflation, interest rates, GDP, and FDI are found to have a significant impact on unemployment rate of this group of countries. The novelty of this study remains the fact that this analysis is performed for the Western Balkan countries as a group. The results can serve and can be taken into consideration when applying similar econometric analysis in the future researches or implementing new policies that influences the macroeconomic factors.

The main purpose of the study is to compare various factors that affect the development of the industry. The chapter analyzes the literature on various issues related directly or indirectly to the development of the industry. Several research methods are used: comparison of the influence of various factors on the price of solar electricity using the vector autoregression model (VAR model). The chapter describes the risks associated with competition (first of all, for the territories where solar panels are supposed to be located). The result of the chapter is a forecast for the supply of solar energy in the next 20 years. In the 21st century, the use of solar energy has become very popular, primarily due to the fact that solar power plants are least harmful to the environment, compared to other types of power plants. Recent research in the field of solar power engineering has shown that using carbon nanotubes will double the efficiency of power plants, breaking the Shockley-Queisser limit. Such technologies can make solar power the most used electricity in the world.

There is an immense literature on the effects of exchange rate changes on macroeconomic indicators, specifically on the trade balance, growth, inflation, and overall productivity in open economies. One of the main attempts in the related literature is about ascertaining whether the exchange rate fluctuations alter domestic prices. This possible mechanism is called as the pass-through effect which is getting more important since the argument that exchange rate adjustment is a part of the solution for global rebalancing is empirically well-supported. Starting from this claim, this study purposes to explore whether there is an exchange rate pass-through effect in 19 high-income OECD countries over the period 1990-2015. To this end, using a panel data set of consumer price index, producer price index proxied by wholesale price index, the nominal effective exchange rates, and industrial production presented by the value-added share of industry sectors in gross domestic product, structural vector autoregressive (VAR) and autoregressive distributed lag (ARDL) models are estimated in an unbalanced panel data analysis procedure. Results reveal that exchange rate pass-through effects on the domestic prices are significant but not that strong in both the short-run and the long-run. Expectedly, the pass-through effects tend to diminish over time. The study concludes that policy-makers need to consider policy actions accompanying the exchange rate changes to ensure domestic price stability which consequently interacts with many macroeconomic indicators.

Purpose – the purpose of this paper is to investigate whether supply line engineering strategies of goods and service exports, exports transport services and export time have a significant impact on GDP growth of BIMSTEC countries or not. Research methodology – the study employed a panel vector error correction model (VECM) instead of loose VAR to examine the short and long-run relationship among the selected indicators and GDP growth. Findings – in the long-run, the time of export negatively and suggestively associate with GDP. Conversely, VECM based Granger causality test signposted that in short-run only unidirectional causality running from goods and service exports (GSE), trade duration like exports time (ET) toward GDP and for the rest of the variables no causality found. Research limitations – this study is contextualized only on Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand. Practical implications – to investigate the current position of the link between supply line logistics strategies and economic growth by using annual data for the period of 1980 to 2014 and possible weaknesses and logistics presence. Originality/Value – this paper is an attempt, first of its kind, to fill up this shortfall, to estimate the relationship of exports transport services, exports time, and goods and services exports with GDP growth of BIMSTEC countries.