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1
Arı, Yakup. "The CARR-volatility connectedness between USD/TRY and foreign banks in Turkey: Evidence by TVP-VAR." Applied Econometrics 67, no. 3 (2022): 5–26. http://dx.doi.org/10.22394/1993-7601-2022-67-5-26.
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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.
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Shapor, Maria Alexandrovna, and Rafael Rubenovich Gevogyan. "Features of the vector autoregression models application in macroeconomic research." Mezhdunarodnaja jekonomika (The World Economics), no. 8 (August 10, 2021): 634–49. http://dx.doi.org/10.33920/vne-04-2108-05.
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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.
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Paibi, Bunting Boruku, Didi Essi Isaac, and Zorle Dum Deebom. "Exchange Rate, Interest Rate and Agricultural Export Earnings: An analysis Using Panel Data Vector Autoregressive Model." INTERNATIONAL JOURNAL OF APPLIED SCIENCE AND MATHEMATICAL THEORY 8, no. 2 (August 11, 2022): 14–37. http://dx.doi.org/10.56201/ijasmt.v8.no2.2022.pg14.37.
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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
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Anwar, Cep Jandi, and Indra Suhendra. "Measuring Response of Stock Market to Central Bank Independence Shock." SAGE Open 13, no. 1 (January 2023): 215824402311521. http://dx.doi.org/10.1177/21582440231152135.
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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.
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Ariutama, I. Gede Agus, and NFN Syahrul. "ANALISIS PANEL VAR: TINGKAT PENDIDIKAN, TINGKAT KESEHATAN, DAN KETIMPANGAN PENDAPATAN DI INDONESIA." INFO ARTHA 1 (June 7, 2017): 1–16. http://dx.doi.org/10.31092/jia.v1i1.74.
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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.
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Kovacevic, Radovan. "The effects of FDI net inflow on the current account of southeast Europe countries - a panel causality analysis." Ekonomski anali 67, no. 235 (2022): 95–122. http://dx.doi.org/10.2298/eka2235095k.
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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.
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Pacifico, Antonio. "Structural Panel Bayesian VAR Model to Deal with Model Misspecification and Unobserved Heterogeneity Problems." Econometrics 7, no. 1 (March 11, 2019): 8. http://dx.doi.org/10.3390/econometrics7010008.
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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.
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Gao, Ang. "Transmission Machine of International Financial Crisis Based on VAR Model." Frontiers in Business, Economics and Management 5, no. 1 (August 26, 2022): 48–52. http://dx.doi.org/10.54097/fbem.v5i1.1429.
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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.
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Kristianto, Doddy. "CREDIT FOR MSMES, PRIVATE CREDIT, AND REGIONAL ECONOMIC GROWTH IN INDONESIA: A PANEL VECTOR AUTOREGRESSIVE ANALYSIS." INFO ARTHA 3, no. 2 (November 5, 2019): 85–100. http://dx.doi.org/10.31092/jia.v3i2.576.
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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.
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Sekolah Tinggi Ilmu Ekonomi Y.A.I. Jakarta, Zara Tania Rahmadi, and Adji Suratman Sekolah Tinggi Ilmu Ekonomi Y.A.I. Jakarta. "JUMPA Vol.3 No.1 Feb 2016 ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI DIVIDEND PAYOUT RATIO (DPR) DI PERUSAHAAN GO PUBLICK YANG TERDAFTAR DI BURSA EFEK INDONESIA SELAIN JASA KEUANGANDENGAN MODEL VECTOR AUTOREGRESIVE PERIODE 2009 -2013." Jurnal Manajemen dan Perbankan (JUMPA) 3, no. 1 (February 29, 2016): 69–86. http://dx.doi.org/10.55963/jumpa.v3i1.192.
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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.
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Nikšić Radić, Maja, Daniel Dragičević, and Marina Barkiđija Sotošek. "Causality between Terrorism and FDI in Tourism: Evidence from Panel Data." Economies 7, no. 2 (May 6, 2019): 38. http://dx.doi.org/10.3390/economies7020038.
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The aim of this research was to examine the causal link between terrorism and FDI in tourism on the example of a panel of 50 countries for the period from 2000 to 2016. Other control variables were included in order to ensure the validity of the results—number of international tourist arrivals per capita, the KAOPEN index, the KOF Globalisation Index and GDP per capita. The main goal was to look at this issue from the perspective that terrorism does not affect FDI in tourism. The research employed the Granger causality test in a vector autoregressive model (VAR model), the analysis of variance decomposition and the impulse response function within the panel setting. Based on research results, it was found that terrorism does not Granger cause FDI in tourism. The results are in line with recent research related to the subject matter which indicated that the negative effect of terrorism on FDI in tourism was questionable.
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Boukattaya, Sonia, and Abdelwahed Omri. "Corporate Social Practices and Firm Financial Performance: Empirical Evidence from France." International Journal of Financial Studies 9, no. 4 (September 28, 2021): 54. http://dx.doi.org/10.3390/ijfs9040054.
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The present work aimed to examine the association between Corporate Social performance (CSP) and corporate financial performance (CFP) taking into account corporate social irresponsibility. Here, we used a sample of French non-financial firms listed on SBF 120 between 2011 and 2016. Our findings provided evidence that corporate social responsibility (CSR) and corporate social irresponsibility (CSI) exert opposite effects on the CFP. Using an estimation of the vector autoregressive (VAR) model for panel data, we showed that the CSI has a greater and more lasting impact on CFP than CSR.
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Pacifico, Antonio. "Structural Compressed Panel VAR with Stochastic Volatility: A Robust Bayesian Model Averaging Procedure." Econometrics 10, no. 3 (July 12, 2022): 28. http://dx.doi.org/10.3390/econometrics10030028.
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This paper improves the existing literature on the shrinkage of high dimensional model and parameter spaces through Bayesian priors and Markov Chains algorithms. A hierarchical semiparametric Bayes approach is developed to overtake limits and misspecificity involved in compressed regression models. Methodologically, a multicountry large structural Panel Vector Autoregression is compressed through a robust model averaging to select the best subset across all possible combinations of predictors, where robust stands for the use of mixtures of proper conjugate priors. Concerning dynamic analysis, volatility changes and conditional density forecasts are addressed ensuring accurate predictive performance and capability. An empirical and simulated experiment are developed to highlight and discuss the functioning of the estimating procedure and forecasting accuracy.
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ELENES PLATONA, Iulia. "TRADE OPENNESS, INVESTMENT FREEDOM- SELECTED COUNTRY RISK INDICATORS, IMPACT ON FOREIGN DIRECT INVESTMENTS, A PANEL VECTOR AUTOREGRESSION MODEL APPROACH." Annals of the University of Oradea. Economic Sciences 31, me 31 (December 2022): 198–205. http://dx.doi.org/10.47535/1991auoes31(2)019.
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We employ a panel vector autoregression model (PVAR) selecting as endogenous variables Foreign Direct Investments percent of GDP, Trade Openness and Investment Freedom for a database comprised of European Countries. The data are collected from the Global Economy database. We compare different PVAR models changing the input of desired lags. We test the Hansen test for over-identifying restrictions and we generate the Generalised impulse response functions. The article uses a Hahn Kuehrsteiner Panel Var estimation estimating a stationarity PVAR with fixed effects. Econometric analysis shows a significant impact of trade openness and investment freedom indicators on foreign direct investment in Europe.
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Bao, May Xiaoyan, Xiaoyan Cheng, John Geppert, and David B. Smith. "Reexamination of Whether Accrual Quality Is a Price Factor." Accounting and Finance Research 8, no. 3 (July 8, 2019): 103. http://dx.doi.org/10.5430/afr.v8n3p103.
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In this study we investigate whether accrual quality is a factor in capital asset pricing. Our analysis consists of two parts. First, we use a panel data regression that controls for cross-section fixed effects to implement the second stage of the Fama-MacBeth regression (Petersen 2009). In the second part, we use the Campbell (1991) return decomposition and vector autoregressive model (VAR) to decompose the two-stage cross-sectional regressions. This allows us to investigate whether accrual quality is a priced factor in terms of the three components of the return, which include one-period expected return, cash flow news and discount-rate news.
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BEHANZIN, Tomondji Dayane Thiernaud, and Mamadou Abdoulaye KONTE. "Effets de l’ouverture commerciale et de l’afflux des investissements directs étrangers (IDE) sur le chômage dans les pays membres de l’Union Économique et Monétaire Ouest Africaine (UEMOA)." Revue Internationale des Économistes de Langue Française 7, no. 1 (2022): 135–53. http://dx.doi.org/10.18559/rielf.2022.1.8.
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The objective of this paper was to measure the effect of trade openness and foreign direct investment inflows (FDI) on unemployment in WAEMU countries. To do so, the Vector Autoregressive (VAR) model in panel was used. The results show that there is a bidirectional causality between FDI and trade openness, FDI and unemployment, and a unidirectional causality of unemployment on trade openness. Furthermore, the robust results show that FDI inflows reduce unemployment and thus promote job creation in WAEMU member countries. In addition, the analysis shows that trade openness and FDI inflows increase youth employment (15–24 years old) and encourage migration from vulnerable jobs to less vulnerable jobs.
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Kling, Gerhard, Charles Harvey, and Mairi Maclean. "Establishing Causal Order in Longitudinal Studies Combining Binary and Continuous Dependent Variables." Organizational Research Methods 20, no. 4 (November 30, 2015): 770–99. http://dx.doi.org/10.1177/1094428115618760.
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Longitudinal studies with a mix of binary outcomes and continuous variables are common in organizational research. Selecting the dependent variable is often difficult due to conflicting theories and contradictory empirical studies. In addition, organizational researchers are confronted with methodological challenges posed by latent variables relating to observed binary outcomes and within-subject correlation. We draw on Dueker’s qualitative vector autoregression (QVAR) and Lunn, Osorio, and Whittaker’s multivariate probit model to develop a solution to these problems in the form of a qualitative short panel vector autoregression (QSP-VAR). The QSP-VAR combines binary and continuous variables into a single vector of dependent variables, making every variable endogenous a priori. The QSP-VAR identifies causal order, reveals within-subject correlation, and accounts for latent variables. Using a Bayesian approach, the QSP-VAR provides reliable inference for short time dimension longitudinal research. This is demonstrated through analysis of the durability of elite corporate agents, social networks, and firm performance in France. We provide our OpenBUGS code to enable implementation of the QSP-VAR by other researchers.
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Dvouletý, Ondřej. "Relationship Between Unemployment and Entrepreneurship Dynamics in the Czech Regions: a Panel VAR Approach." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 65, no. 3 (2017): 987–95. http://dx.doi.org/10.11118/actaun201765030987.
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Investigation of the relationship between unemployment and entrepreneurship still does not provide conclusive results and scholars argue that the relationship needs to be further investigated. In the Czech context, the knowledge about entrepreneurship is still underdeveloped. The purpose of this paper is to investigate the dynamics of the relationship between unemployment and entrepreneurship, applying the methodology used by Koellinger and Thurik (2012) with usage of the quarterly data for the Czech NUTS 3 regions for the period of years 2003 – 2014. Collected sample of 672 region‑quarter observations was obtained from the Czech Statistical Office. Estimated panel vector autoregressive (VAR) models with impulse response function supported hypothesis assuming a positive relationship between unemployment and entrepreneurship, operationalized as annual growth in registered business activity. Obtained results also showed that after the shock in unemployment, dynamics of entrepreneurship increased above its initial level after two years, concluding that it may take up to two years before positive effects on entrepreneurship reveal. This finding provides value for entrepreneurship policy makers. Based on the obtained results author suggests to support entrepreneurial activity, especially during the times of higher unemployment rate.
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CHOW, HWEE KWAN, and KEEN MENG CHOY. "MONETARY POLICY AND ASSET PRICES IN A SMALL OPEN ECONOMY: A FACTOR-AUGMENTED VAR ANALYSIS FOR SINGAPORE." Annals of Financial Economics 05, no. 01 (June 2009): 0950004. http://dx.doi.org/10.1142/s2010495209500043.
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The ongoing global financial turmoil has revived the question of whether central bankers ought to tighten monetary policy pre-emptively in order to head off asset price misalignments before a sudden crash triggers financial instability. This study explores the issue of the appropriate monetary policy response to asset price swings in the small open economy of Singapore. Empirical analysis of monetary policy based on standard vector autoregression (VAR) models, unfortunately, is often hindered by the use of sparse information sets. To better reflect the extensive information monitored by Singapore's central bank, including global economic indicators, we augment a monetary vector autoregression (VAR) model with common factors extracted from a large panel dataset spanning 122 economic time series and the period 1980q1–2008q2. The resulting FAVAR model is used to assess the impact of monetary policy shocks on residential property and stock prices. Impulse response functions and variance decompositions suggest that monetary policy can potentially be used to lean against asset price booms in Singapore.
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Udeogu, Ejike, Shampa Roy-Mukherjee, and Uzochukwu Amakom. "Does Increasing Product Complexity and Diversity Cause Economic Growth in the Long-Run? A GMM Panel VAR Evidence." SAGE Open 11, no. 3 (July 2021): 215824402110329. http://dx.doi.org/10.1177/21582440211032918.
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Using aggregate data from 31 Organization for Economic Co-operation and Development (OECD) countries covering periods from 1982 to 2017, this study examines the notion that the level of product complexity is a good determinant of economic growth in the long run. We use the impulse-response function (IRF) computed from the consistent generalized method of moment panel vector autoregressive (GMM pVAR) model to estimate the response of the real output growth to a change in the economic complexity index. The IRF shows that the economic complexity index has a significant impact on economic growth; a 1 standard deviation shock to the economic complexity index at time 0 contributes around 2.34 percentage points to the average rate of growth of output within the first period. The point estimates are positive and significant up to the third period. The cumulative IRF shows that the aggregate impact on economic growth is about 4.4% in the long run. Compared to some widely used innovation proxies such as the gross expenditure on research and development and secondary school enrollment, the economic complexity index performs relatively better in our model in determining economic growth in the long run.
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Jakšić, Saša. "Modelling Determinants of Inflation in CESEE Countries: Global Vector Autoregressive Approach." Review of Economic Perspectives 22, no. 1 (June 1, 2022): 137–69. http://dx.doi.org/10.2478/revecp-2022-0007.
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Abstract After a prolonged period of relatively stable price levels, the beginning of the third decade of the 21st century has brought inflation once again into the spotlight. This paper focuses on the inflation dynamics in a set of post-communist countries that eventually became members of the European Union. Due to EU accession augmented by the globalization process and involvement in global value chains (GVC), the international impacts are becoming progressively important for the domestic inflation dynamics and domestic variables are not sufficient to fully describe the domestic inflation dynamics. The employed methodology, Global Vector Autoregressive (GVAR) approach, allows modelling interactions and spillovers among countries, making the most of its advantages over the usual VAR models that model each economy separately and panel models, where countries are often treated as independent units. The results of the empirical analysis confirm that the globalisation process has led to increasing the importance of international impacts on the domestic inflation dynamics. On the other hand, the results also indicate that accounting for a larger set of countries decreases the severity of the commodity price shocks and makes them less persistent. Furthermore, monetary policy acts as a buffer against adverse shocks, especially in the countries that are still not members of the euro-zone. The findings of the paper show that the analysed countries are pronouncedly heterogeneous. Hence, each of the analysed economies has its own set of country-specific factors which, from country to country, play a more important or a less significant role in explaining national inflation dynamics. Thus, the paper should contribute to a more comprehensive understanding of the inflation dynamics in the policy-making context.
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Zungu, Lindokuhle Talent, and Lorraine Greyling. "Exploring the Dynamic Shock of Unconventional Monetary Policy Channels on Income Inequality: A Panel VAR Approach." Social Sciences 11, no. 8 (August 18, 2022): 369. http://dx.doi.org/10.3390/socsci11080369.
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In response to the “Great Recession and Global Financial Crisis”, central banks had to deploy unconventional monetary policies (UMP) in order to fight the severe impact of the crisis. Therefore, the purpose of this study is to examine the dynamic shock of unconventional monetary policies through earning heterogeneity, income composition, and portfolio channels on income inequality in emerging economies covering the period 2000–2019, using the panel vector autoregressive (PVAR) model. A PVAR model was designed for this study because of its ability to address the dynamics of numerous entities considered in parallel. The findings suggest that the UMPs used by these countries’ central banks may have increased income inequality through all of the channels investigated in this study, as a shock to unconventional monetary policy results in a positive response in income inequality. Even when pre-tax income, held by the top 10%, is adopted to measure income inequality, the study yields similar results. It is evident that a central bank’s objective is and should be to fulfil its mandate of achieving maximum employment and price stability, thus bringing wide economic benefits. Thus, some forms of policies are more appropriate for addressing concerns about inequality (income policy or fiscal policy) than others. However, the current study alerts the central bank to the fact that monetary policies may have a wounding impact on income inequality. Therefore, the central banks should consider the cost of monetary policies on income inequality when drafting or implementing these kinds of policies.
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Carfora, Alfonso, Renato Passaro, Giuseppe Scandurra, and Antonio Thomas. "The Casual Nexus between Income and Energy Poverty in EU Member States." Energies 15, no. 8 (April 12, 2022): 2822. http://dx.doi.org/10.3390/en15082822.
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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.
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Kusumawati, Nidaa Nazaahah, Nunung Nuryartono, and Irfan Syauqi Beik. "ANALISIS PEMBIAYAAN DAN KREDIT SEKTOR KONSTRUKSI DI INDONESIA: STUDI PERBANKAN SYARIAH DAN KONVENSIONAL." JURNAL EKONOMI DAN KEBIJAKAN PEMBANGUNAN 6, no. 1 (July 31, 2018): 21–40. http://dx.doi.org/10.29244/jekp.6.1.2017.21-40.
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The construction sector is an important sector in supporting development projects in Indonesia. The development of the construction sector requires the role of the banking sector to provide access of capital through credit or financing. This study aims to analyze the factors affecting construction financing and credit in Islamic and Conventional Banking in Indonesia and among regions in Indonesia. This study uses Vector Autoregression/ Vector Error Correction Model (VAR/VECM) with monthly data from 2006 until 2014 and panel data analysis with yearly data from 2009 until 2013. The study results that the factors affecting financing and credit on Construction Sector in Indonesia are Third Party Funds (DPK), Wholesale price index, fee of SBIS (interest rate of SBI), percentage of Non Performing Financing (Non Performing Loan), Consumer Price Index and equivalent rate of financing (Interest rate of Credit). Furthermore, the factors affecting financing and credit on Construction Sector among regions in Indonesia are Third Party Funds, Gross Domestic Regional Product of Construction Sector, Gross Domestic Regional Product per Capita and percentage of Non Performing Financing (Non Perfoming Loan). Keywords: Construction, Credit, Financing, Panel data, VAR/VECM
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Kusumawati, Nidaa Nazaahah, Nunung Nuryartono, and Irfan Syauqi Beik. "ANALISIS PEMBIAYAAN DAN KREDIT SEKTOR KONSTRUKSI DI INDONESIA: STUDI PERBANKAN SYARIAH DAN KONVENSIONAL." JURNAL EKONOMI DAN KEBIJAKAN PEMBANGUNAN 6, no. 1 (July 31, 2018): 21–40. http://dx.doi.org/10.29244/jekp.6.1.21-40.
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The construction sector is an important sector in supporting development projects in Indonesia. The development of the construction sector requires the role of the banking sector to provide access of capital through credit or financing. This study aims to analyze the factors affecting construction financing and credit in Islamic and Conventional Banking in Indonesia and among regions in Indonesia. This study uses Vector Autoregression/ Vector Error Correction Model (VAR/VECM) with monthly data from 2006 until 2014 and panel data analysis with yearly data from 2009 until 2013. The study results that the factors affecting financing and credit on Construction Sector in Indonesia are Third Party Funds (DPK), Wholesale price index, fee of SBIS (interest rate of SBI), percentage of Non Performing Financing (Non Performing Loan), Consumer Price Index and equivalent rate of financing (Interest rate of Credit). Furthermore, the factors affecting financing and credit on Construction Sector among regions in Indonesia are Third Party Funds, Gross Domestic Regional Product of Construction Sector, Gross Domestic Regional Product per Capita and percentage of Non Performing Financing (Non Perfoming Loan). Keywords: Construction, Credit, Financing, Panel data, VAR/VECM
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Deng, Qi, Weiguo Xiao, and Huan Yan. "The Spillover Effects of U.S. Monetary Policy Normalization on the BRICS Based on Panel VAR Model." Journal of Mathematics 2022 (January 27, 2022): 1–9. http://dx.doi.org/10.1155/2022/3844128.
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Using the monthly data from December 2008 to March 2018 and a panel vector autoregression (PVAR) model, this paper empirically analyzes the spillover effects of U.S. monetary policy normalization on the total output, inflation, trade balance, and exchange rates in BRICS. The results show that the Fed’s interest rate hike and balance sheet shrinking will both lead to a decrease in BRICS’ output, a decline in inflation, a deterioration in the trade balance, and a depreciation of the exchange rate. In addition, the spillover effects of the Fed’s interest rate hike and shrinking of a balance sheet are both relatively long lasting, but there is a certain difference between the two effects; that is, the Fed’s interest rate hike has a greater impact on the macroeconomic variables of BRICS countries than the shrinking of balance sheet. Based on the conclusions, we propose to establish and improve the regulatory system of international capital flows, pay close attention to commodity prices, and strengthen policy coordination and communication among BRICS countries so as to mitigate the adverse impact of U.S. monetary policy normalization.
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Jama, Abdikarim Bashir, and Sabri Nayan. "The Nexus between Institutional Quality & Foreign Direct Investment (FDI) in Sub-Saharan Africa." International Journal of Economics and Finance 14, no. 8 (July 10, 2022): 11. http://dx.doi.org/10.5539/ijef.v14n8p11.
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This study analyzes the nexus between foreign direct investment and institutional quality including political stability, rules of law, government effectiveness, voice & accountability, and regulatory quality. The major aim of this study is to examine the relationship between institutional quality and foreign direct investment. This study consists of a sample of Sub-Saharan African countries. Our study employed two-panel data techniques including Random Effect Model (REM) and Vector Autoregressive Model (VAR). The study period covers from 2015 to 2019. Empirical findings of REM indicated that both rules of law and government effectiveness have positive and statistically significant influences on foreign direct investment inflow in the SSA region. Similarly, the study utilized other explanatory variables such as the trade and labor force. The result of VAR highlighted the positive and statistically significant influence of labor force and trade on foreign direct investment inflow, therefore, the effectiveness & efficiency of region institutional quality are usually dependent on the robustness of those variables. Thus, the study recommends having higher foreign direct investment inflow in the region is necessary to make policy reforms that strengthen the quality and efficiency of governance.
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Li, Houjian, Xiaolei Zhou, Mengqian Tang, and Lili Guo. "Impact of Population Aging and Renewable Energy Consumption on Agricultural Green Total Factor Productivity in Rural China: Evidence from Panel VAR Approach." Agriculture 12, no. 5 (May 18, 2022): 715. http://dx.doi.org/10.3390/agriculture12050715.
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China is moving toward the important goal of being a green and low-carbon country, and the current severity level of population aging is of particular concern to the government. Aging, renewable energy consumption, and technological progress are closely linked. In this research, a panel vector autoregressive (PVAR) model is employed to investigate the long-run equilibrium relationship between population aging, renewable energy consumption and agricultural green total factor productivity using panel data for 30 Chinese provinces (cities) from 2000 to 2019. The findings reveal that, in the long run, both population aging and renewable energy use have considerable positive impacts on agricultural green total factor productivity. In addition, in order to more intuitively understand the impact of population aging and renewable energy consumption on agricultural green total factor productivity, the analysis adopts the impulse response function and variance decomposition. The contributions of population aging and renewable energy consumption to agricultural green total factor productivity are 2.23% and 0.56%, respectively, when the lag period is chosen to be 15, which implies that population aging and renewable energy use will continuously contribute to agricultural green total factor productivity. The study results have significant theoretical implications for understanding China’s aging population structure and current renewable energy use. Given the above results, this study puts forward countermeasures and suggestions from four aspects: improving agricultural infrastructure, increasing agricultural technology investment, increasing the stock of agricultural human capital and strengthening international cooperation.
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Mohd Basri, Nurliyana, Zulkefly Abdul Karim, and Noorasiah Sulaiman. "The Effects of Factors of Production Shocks on Labor Productivity: New Evidence Using Panel VAR Analysis." Sustainability 12, no. 20 (October 20, 2020): 8710. http://dx.doi.org/10.3390/su12208710.
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Labor productivity has an essential role in creating a more sustainable labor market platform, leading to better economic sustainability. However, the sluggish growth in labor productivity in Malaysia could hinder the vision in realizing the status of a high-income nation in the future. Thus, understanding how production shocks affect labor productivity sustainability is crucial for firms in managing their inputs (resources). This paper aims to elucidate how shocks in wage, capital intensity, and human capital may affect the dynamic of labor productivity in the Malaysian manufacturing industry. The study further explains the magnitude of this impact on labor productivity. This study employs the panel vector autoregression (PVAR) model in analyzing the propagation of the shocks through the impulse response function and variance decomposition. The main findings reveal that shocks in production factors have a positive and significant transitional impact on productivity and the cumulative effects are positive over time. The economic impact of wage shock is material, whereas capital intensity shock is moderate and only exerts a minor effect on labor productivity emanating from human capital shock. These findings provide further insights into assisting policymakers in amplifying the current labor market policy for sustainable economic growth.
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Pacifico, Antonio. "Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues." Econometrics 9, no. 2 (May 2, 2021): 20. http://dx.doi.org/10.3390/econometrics9020020.
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This paper improves a standard Structural Panel Bayesian Vector Autoregression model in order to jointly deal with issues of endogeneity, because of omitted factors and unobserved heterogeneity, and volatility, because of policy regime shifts and structural changes. Bayesian methods are used to select the best model solution for examining if international spillovers come from multivariate volatility, time variation, or contemporaneous relationship. An empirical application among Central-Eastern and Western Europe economies is conducted to describe the performance of the methodology, with particular emphasis on the Great Recession and post-crisis periods. A simulated example is also addressed to highlight the performance of the estimating procedure. Findings from evidence-based forecasting are also addressed to evaluate the impact of an ongoing pandemic crisis on the global economy.
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Asuamah Yeboah, Samuel. "Modelling inflation-interest rate nexus for Ghana." International Journal of Financial, Accounting, and Management 2, no. 3 (September 15, 2020): 227–41. http://dx.doi.org/10.35912/ijfam.v2i3.257.
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Purpose: The research assesses the interest rates-inflation association in the case of Ghana between 2007 and 2013. Monthly and quarterly data were used. Research Methodology: The model of the vector error correction and Johansen were used to investigate the long-term and short-term association in the model estimated respectively. The vector autoregression (VAR) test was used to model the joint dynamics between the variables. GRETL software was used in these tests. Granger predictive test was done with the EViews software. Results: The findings of the result confirm both long-run and a short-run association in the model and as well as neutral granger predictive causality. Limitations: Though the Johansen test is more appropriate for multivariate modelling, Engle-Granger test is considered to be more robust in most cases and as such future studies should consider using the two models in a comparative study to assess whether the current conclusions can collaborate. Contribution: The paper contributes to knowledge in the field of inflation and Interest rates association, in relation to the financial markets. Future Research models that account for structural breaks and panel works are worth doing. Keywords: Fisher effect, Treasury bill rates long run, Johansen model
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Alam, Shahi Md Tanvir. "Renewable Energy (Solar and Wind) Generation and its Effect on some Variables for Selected EU Countries with Panel VAR Model." International Journal of Energy Economics and Policy 12, no. 5 (September 27, 2022): 303–10. http://dx.doi.org/10.32479/ijeep.13292.
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Keeping the world livable, the policy makers are giving their extended focus on green energy. They are trying to move on hand-on-hand with rising green energy and lessening carbon dioxide (CO2) emission steading the economic activities specially for the open and developing countries. This can be helpful to provide a more lucrative economic environment to meet the extended demand of the society. The paper highlights to find out whether the economic growth, renewable energy consumption, fossil fuel-based energy generation and CO2 emission are significantly impactful on renewable energy generation or not? Is there any mutual, bi-directorial, unidirectional relationship with each other? For this, the Vector Autoregression (VAR) model is run. The paper focuses on six EU countries who are practicing auction scheme for deploying robust green energy (especially solar and wind) by reducing dependency on fossil fuel and expanding their economy with less CO2 emission. The result of the analysis shows that a positive influence of each concern variable on renewable energy (RE) generation and auction scheme might have a significant impact if robustness of the generation occurs.
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Chhabra Roy, Neha. "Banks and their technology investment decision are aligned or not – an experience of Indian banks." Journal of Facilities Management 19, no. 1 (January 22, 2021): 1–20. http://dx.doi.org/10.1108/jfm-04-2020-0020.
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Purpose The purpose of this study is to measure the impact of technology spend on bank profitability focusing on Indian public and private sector commercial banks. The study also assesses the longevity duration of impact for both public and private sector banks. The trade-off is created between the bank’s profitability and technology spent across four identified columns: increase product sales, reduce cost, enhance employee efficiency and optimally use existing resources. Design/methodology/approach The metrics of four columns converted to measurable 11 financial alarming indicators and impact is again checked on profitability indicator ROE. The data used for empirical analysis for the study are between the year 2003 and 2019, across 12 public and 15 private banks. The interface between technology spend and profitability is measured using panel vector autoregression (VAR) and panel vector error correction model (VECM) and further the link between 11 financial indicators and profitability measures is established using panel data analysis. Findings The study found that there is a mixed effect of technology spent on profitability and performance of Indian banks, where public sector banks were found to be more unstructured over private sector banks. The study advises the optimal technology spend strategies to gain enhanced productivity for banking business which are to name a few – planned technology reserves, customer awareness campaigns for products, robust employee-customer motivation policy and customized technologies aligned to existing infrastructure. Originality/value The data was original and extracted from the Reserve bank of India website and respective banks’ annual reports.
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Yang, Zan, Shuping Wu, and Yanhao Shen. "International Real Estate Review." International Real Estate Review 20, no. 1 (March 31, 2017): 23–49. http://dx.doi.org/10.53383/100234.
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This paper studies the relationships among monetary policy, house prices, and consumption in China from both national and regional perspectives. Using a panel vector autoregression (VAR) model and a counterfactual simulation method, we find that monetary policy has a significant effect on consumption but with a regional pattern, in terms of the magnitude and the housing wealth channel. It is found that in the middle southern and the western cities, the monetary policy has strong effects on consumption while the house prices have minimal contribution to the monetary policy transmission to household consumption. By contrast, in the Tier-1 and the eastern cities, house prices play a more important role in monetary policy transmission; even household consumption is less sensitive to monetary policy changes.
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Chen, Zhenhuan, Hongge Zhu, Wencheng Zhao, Bo Cao, and Yingli Cai. "Dynamic Nonlinear Connectedness between the Financial Inclusion, Economic Growth, and China’s Poverty Alleviation: Evidence from a Panel VAR Analysis." Complexity 2022 (August 29, 2022): 1–24. http://dx.doi.org/10.1155/2022/9584126.
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Whether financial inclusion and economic growth can sustainably release poverty alleviation effects in long term has been the focus of academia and government sector. This article uses provincial panel data from 2004 to 2019 to examine the dynamic nonlinear connectedness between the financial inclusion, economic growth, income inequality, and poverty alleviation; the main objective is to reveal the direction and intensity of the long-term and short-term impact of each factor on poverty alleviation. By building a panel vector autoregression model (PVAR), the comparison analyses of national, eastern, central, and western sample groups verify the existence of dynamic nonlinear connectedness among the four variables. The study found that there is complex bidirectional causality between these variables, financial inclusion has the long-term impact on promoting poverty alleviation in China, the impact of economic growth is relatively weak, and income inequality has weakened the positive impact of financial inclusion on poverty alleviation. Through the analysis of impulse response function, variance decomposition, and time-varying nonparametric estimates in different economic regions, we find that the impact of financial inclusion on poverty alleviation presents a U-shaped characteristic, and the contribution of financial inclusion to poverty alleviation in western regions is significant, but poverty reduction in eastern and central region mainly depends on economic growth. For policymakers, financial inclusion can be an effective way to alleviate relative poverty, but the poverty governance should focus more on reducing income inequality in China.
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Gričar, Sergej. "IMPLEMENTATION OF VECTOR AUTO-REGRESSION MODELS IN TOURISM: STATE OF THE ART ANALYSIS AND FURTHER DEVELOPMENT." Tourism and hospitality management 28, no. 3 (December 2022): 707–9. http://dx.doi.org/10.20867/thm.28.3.16.
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Purpose The dissertation focuses on time series analysis and is based on several research strategies and methods. The methodology used in the research process was published in four papers as part of international scientific journals indexed in the Web of Science database. Since tourism is one of the most lagged industries in science there is need for new and innovative approaches in key tourist sector determinants modelling and forecasting. This doctoral thesis introduces an extension of time series methodology that focuses on investigating and testing the normal distribution of residuals, as a key adequacy prerequisite of econometric models. This issue has not systematically been considered in quantitative approaches in tourism. The motivation for research of the doctoral thesis are multidimensional: to filter previous research on time series in tourism and to theoretically and empirically improve and redesign time series methodology and methods for tourism. Both issues were successfully presented in one of the published papers. Finally, tourism forecasts should be based on reliable models as evident, from the most recent shocks, ex-ante tourism forecasting has to be considered crucial in evaluating model efficiency. The dissertation aimed to research and develop appropriate econometric models able to capture the specifics of multiple interactions in the tourism market. The research seeks to develop econometric models for the Republics of Slovenia and Croatia, two countries whose economic development is predicated on tourism. Four goals and four specific objectives have been specified during the research process: 1) To introduce an improved time series approach in cointegrated panels. The first specific objective (SO1) is to test at least ten econometric modelling structures that reduce cycle breaks. 2) To examine previous theoretical thinking regarding the cointegration of time series, cross-sectional data, and panels. The second specific objective (SO2) is to outline at least 250 previous empirical studies for the tourism industry. 3) To examine cointegration in tourism data for Slovenia and Croatia. The third objective (SO3) is to model at least three econometric time series equations and mathematical theorems/ lemmas for the tourism industry. 4) To improve and better understand unit root tests in tourism. The specific objective (SO4) is to approach the design of at least three stable and innovative models. Methodology The research relies upon econometric modelling in time series and panels as well as misspecification tests implementation. The study is primarily oriented to the hypotheses testing on a reliable modelling procedure. The research methodology is based on time series and the vector autoregression model (VAR) implementation. Moreover, the cointegrated VAR and the error correction model (ECM) are used. The Granger causality is used to identify trends to determine the direction of the hypothesised research problems. Overall, the study uses regression analysis and summary descriptive statistics. The sensitive analysis relies on panel regression. Summarizing, the added value of the doctoral thesis can be reflected in investigating the normal distribution of time series residuals to obtain accurate results for interpretation and prediction. Findings The most significant research results include time series and panel testing and modelling based on research hypotheses. The main hypothesis (an innovative approach to cointegration, based on empirical evidence for Slovenia and Croatia, which provides unbiased, accurate and validated results for tourism development) was confirmed. The first published paper investigates the possibility and accuracy of using time series data in forecasting tourism demands. The theoretical added value provides ex-ante research results regarding the consequences of the most recent pandemic. The empirical part of the paper discusses the direction of daily Slovenian and Croatian COVID-19 infections and tourist arrivals. Hypothesis 1 the tourism industry in Slovenia has developed rapidly and is expected to continue growing in a positive and sustainable direction without seasonal fluctuation, and 2, the tourism industry in Croatia has a long tradition and opportunity to grow at unprecedented rates hitherto. Volatility in the Croatian tourism industry is significant and has a high standard deviation; were confirmed. Additionally, the modelling strategy was introduced in one of the published papers. The results emphasized a significant influence on tourism demand and, depending on the modelling methodology, the existence of an impact on tourist arrivals of chosen determinants. Moreover, two published papers discussed the direction of economic impacts on tourist arrivals and vice versa. The decisive significance of productivity to real gross wages with a rise in tourist arrivals was confirmed. Furthermore, prices in tourism based on short-run effects and two cointegrated relations were modelled and forecasted. It can be concluded that tourism demand, approximated by tourist arrivals, is volatile on different determinants which were previously not researched or tested by reliable econometrics. Therefore, the set goals and specific study objectives were achieved.
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Wang, Fengting, Hao Wang, Cong Liu, Lichun Xiong, and Fanbin Kong. "Does economic agglomeration improve agricultural green total factor productivity? Evidence from China's Yangtze river delta." Science Progress 105, no. 4 (October 2022): 003685042211354. http://dx.doi.org/10.1177/00368504221135460.
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Economic agglomeration plays an important role in China's social transformation process of industry feeding agriculture and urban supporting rural areas, and is one of the core weapons to promote agricultural economic growth and green and efficient development. Based on panel data of 41 cities in the Yangtze River Delta (YRD) from 2010 to 2020, this paper constructs an “environment-resource-energy-economy” agricultural input-output system, taking into account carbon emissions and surface pollution, and provides a more comprehensive accounting of agricultural green total factor productivity (AGTFP), the non-linear effects of economic agglomeration on AGTFP and shock responses were empirically analyzed using a panel threshold model and a panel vector autoregression (VAR), respectively. The findings show that: (1) during the period 2010–2020, the AGTFP in the YRD showed an overall rising trend with regional spatial agglomeration characteristics. (2) Economic agglomeration has a triple threshold effect on AGTFP, which was a weak facilitative effect in the early stage, inhibited by the siphoning effect of resource loss and arable land fragmentation in the growth stage, promoted by the radiation effect of external increasing return to scale in the form of sharing, matching and learning in the maturity stage, and finally tends to decline. (3) The shock response of economic agglomeration to AGTFP showed a continuous positive shock, peaking in the first period and then gradually converging to zero. (4) The heterogeneity analysis demonstrated that economic agglomeration has a considerable impact on boosting AGTFP in non-metropolitan areas and cities on the outskirts of YRD. In the future, China should effectively play a positive role in economic agglomeration on AGTFP and enhance the mutual coordination of economic agglomeration and agricultural green development in the process of urban cluster economic growth.
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Putri, Riska Dewi, and Hasdi Aimon. "Analisis Pertumbuhan Ekonomi, Kemiskinan dan Korupsi di Indonesia di Negara ASEAN Lower Middle Income." Jurnal Kajian Ekonomi dan Pembangunan 2, no. 3 (September 1, 2020): 11. http://dx.doi.org/10.24036/jkep.v2i3.12672.
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This study aim to indentify and analyze responses economic growth, poverty and corruption in ASEAN lower middle income countries. Type of this research is descriptive and associative, used a secondary panel data from 2010 to 2017. This research was conducted using the Vector Autoregression (VAR) model through the analysis of Impulse Response Funtion (IRF) and Variance Decomposition (VD) to determine the variability response of a particular variable due to the shock of other variables. The results of this study indicate that: (1) Variability of economic growth is not contributed by the shock of poverty and corruption in the short term, but in the long run the variability of economic growth is contributed by the shock of poverty and corruption. (2) In the short variability of poverty is not contributed by the shock of economic growth and corruption term, but in the long run economic growth and corruption contribute to influencing poverty variability. (3) The variability of corruption is contributed by the shock of economic growth and poverty in the short and long term.
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Hendrati, Ignatia Martha, Unggul Heriqbaldi, Miguel Angel Esquivias, Bekti Setyorani, and Ari Dwi Jayanti. "Propagation of Economic Shocks from the United States, China, the European Union, and Japan to Selected Asian Economies: Does the Global Value Chain Matters?" International Journal of Energy Economics and Policy 13, no. 1 (January 22, 2023): 91–102. http://dx.doi.org/10.32479/ijeep.13789.
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A panel vector autoregression (VAR) model is employed to estimate whether growth shocks from the United States (US), China, Japan, and the European Union (EU) can be transferred to selected Asian countries. We examine 1) the effect of shocks through five channels: international trade, monetary policy, finance, global uncertainty, and oil prices; 2) whether a country’s deeper integration with the global value chain (GVC) enhances or decreases the effect of growth shocks from major economies more intensively than trade openness. We found evidence of the shock transfer from major economies to Asia through the five channels. The impact differs across countries depending on their participation in GVC; for example, the impact is high in Indonesia and low in South Korea. Moreover, Asian countries are more exposed to trade shocks through China’s trade channel than other major economies. Zooming in on the channels’ impacts, global uncertainty affects countries’ growth (e.g., Indonesia) more significantly than other channels (i.e., GVC); and Asian countries respond positively to oil prices in the short run but negatively in the long run.
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Putri, Rani Gusminda, and Idris Idris. "ANALISIS PERTUMBUHAN EKONOMI PENGGUNA INTERNET DAN KONSUMSI ENERGI LISTRIK DI INDONESIA." Jurnal Kajian Ekonomi dan Pembangunan 3, no. 4 (December 1, 2021): 73. http://dx.doi.org/10.24036/jkep.v3i4.12381.
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This study aims to identify and analyze the response between economicgrowth, internet users, and consumption of electrical energy in Indonesia. This type of research is descriptive and associative, the data used are secondary panel data from 2016 to 2020. This research was conducted using the Vector Autoregression (VAR) model through the analysis of Impulse Response Funtion (IRF) and Variance Decomposition (VD) to determine the variability response of a particular variable due to the shock of other variables. The results of this study indicate that: (1) Variability of econmic growth is not contributed by internet users in the short term, but in the long term variability of economic growth is contributed by the shock of internet users in Indonesia, (2) Variability internet users is contributed by economic growth in short and long term,(3) Variability internet users in short term is not contibuted by consumption of electrical energy , but in long term is contrubuted by the consumption of electrical energy in Indonesia, (4) Variability consumption of electrical energy in short term and long term is contributed by internet users in Indonesia, (5) Variability consumption of electrical energy in short term and long term is contributed by economic growth in Indonesia, (6) Variability econmic growth is contributed by the consumption of electrical energy ionlyin the long term.
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Putri, Riska Dewi, and Hasdi Aimon. "Analisis Pertumbuhan Ekonomi Pengguna Internet, Kemiskinan dan Korupsi di Negara ASEAN: Lower Middle Income." Jurnal Kajian Ekonomi dan Pembangunan 4, no. 2 (July 13, 2022): 11. http://dx.doi.org/10.24036/jkep.v4i2.13317.
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This study aims to identify and analyze the response between economic growth, poverty, and corruption in in ASEAN lower middle income countries. Type of this research is descriptive and associative, used a secondary panel data from 2010 to 2017. This research was conducted using the Vector Autoregression (VAR) model through the analysis of Impulse Response Funtion (IRF) and Variance Decomposition (VD) to determine the variability response of a particular variable due to the shock of other variables. The results of this study indicate that: (1) The variability of economic growth is not contributed by the poverty shock in the short term, but in long term the variability of economic growth is contributed by the poverty shock in ASEAN countries:Lower Middle Income. (2) In the short term and long term variability poverty is contributed by the economic growth in ASEAN countries:Lower Middle Income. (3) The variability of poverty is not contibuted by the shock of corruption in the short term, but in the long term the variability of poverty is contributed by the shock of courruption in ASEAN countries:Lower Middle Income. (4) In the short and long term variability curruption is contributed by the shock poverty in ASEAN countries:Lower Middle Income. (5) In the short and long term variability curruption is contributed by the shock economic growth in ASEAN countries:Lower Middle Income. (6) The variability of economic growth is not contributed by the curruption shock in the short term, but in the long term the variability of economic growth is contributed by the curruption shock
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Koop, Gary, and Dimitris Korobilis. "Model uncertainty in Panel Vector Autoregressive models." European Economic Review 81 (January 2016): 115–31. http://dx.doi.org/10.1016/j.euroecorev.2015.09.006.
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Bouvet, Florence, Ryan Brady, and Sharmila King. "Debt Contagion in Europe: A Panel-Vector Autoregressive (VAR) Analysis." Social Sciences 2, no. 4 (December 18, 2013): 318–40. http://dx.doi.org/10.3390/socsci2040318.
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Greenaway-McGrevy, Ryan. "MULTISTEP PREDICTION OF PANEL VECTOR AUTOREGRESSIVE PROCESSES." Econometric Theory 29, no. 4 (January 16, 2013): 699–734. http://dx.doi.org/10.1017/s0266466612000679.
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This paper considers the conventional recursive (otherwise known as plug-in) and direct multistep forecasts in a panel vector autoregressive framework. We derive asymptotic expressions for the mean square prediction error (MSPE) of both forecasts as N (cross sections) and T (time periods) grow large. Both the bias and variance of the least squares fitting are manifest in the MSPE. Using these expressions, we consider the effect of model specification on predictor accuracy. When the fitted lag order (q) is equal to or exceeds the true lag order (p), the direct MSPE is larger than the recursive MSPE. On the other hand, when the fitted lag order is underspecified, the direct MSPE is smaller than the recursive MSPE. The recursive MSPE is increasing in q for all q ≥ p. In contrast, the direct MSPE is not monotonic in q within the permissible parameter space. Extensions to bias-corrected least squares estimators are considered.
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Irawan, Denny, and Febrio Kacaribu. "TRI-CYCLES ANALYSIS ON BANK PERFORMANCE: PANEL VAR APPROACH." Buletin Ekonomi Moneter dan Perbankan 19, no. 4 (July 7, 2017): 403–42. http://dx.doi.org/10.21098/bemp.v19i4.694.
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The previous financial crisis has revealed the importance of risk in the financial and business cycle within the economy. This paper examines relationship among three cycles in the economy, namely (i) business cycle macro risk, (ii) credit cycle and (iii) risk cycle, and their impacts toward individual bank performance. We examine the responses of individual bank credit cycle and risk cycle toward a shock in business cycle macro risk and its consequence to the bank performance. We use Indonesian data for period of 2005q1 to 2014q4. We use unbalanced panel data of individual banks’ balance sheet with Panel Vector Autoregressive approach based on GMM style estimation by implementing PVAR package developed by Abrigo and Love (2015). The result shows dynamic relationship between business cycle macro risk and financial risk cycles. The study also observes prominent role of risk cycles in driving bank performance. We also show the existence of financial accelerator phenomenon in Indonesian banking system, in which financial cycles precede the business cycle macro risk.
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Shobande, Olatunji, and Simplice Asongu. "The rise and fall of the energy-carbon Kuznets curve: evidence from Africa." Management of Environmental Quality: An International Journal 33, no. 2 (November 1, 2021): 390–405. http://dx.doi.org/10.1108/meq-08-2021-0185.
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PurposeThis paper provides an analysis of the energy-carbon Kuznets curve hypothesis (CKC) using a second-generation panel methodology.Design/methodology/approachSpecifically, the authors investigate whether energy consumption, natural resources and governance explain the CKC proposition. The study’s empirical strategy is based on the Westerlund panel cointegration test, augmented mean group (AMG) and vector autoregressive (VAR) panel Granger-causality tests.FindingsThe results suggest that the CKC hypothesis is incomplete without these mechanisms, as they play a critical role in reducing carbon emissions in Africa. The authors recommend improving the environmental standards and proper regulatory and monitoring systems to reduce carbon emissions and promote sustainable development in the continent.Originality/valueThe study revisits the CKC hypothesis with particular emphasis on governance and more robust empirical estimation techniques.
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Belucio, Matheus, José Fuinhas, Liberato Banks, José Antunes, and Fábio Fernandes. "The tourism in Latin America and Caribbean: A Panel VAR evidence." Turizam 26, no. 4 (2022): 176–91. http://dx.doi.org/10.5937/turizam26-30985.
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In the late twentieth century, the increase in globalization was vital for the tourism industry. The tourism industry is commonly understood as essential for several economies. In this study, through a Panel Vector Autoregressive composed of 26 countries in Latin America and the Caribbean, there was a relationship between the Gross Domestic Product of tourism, the Gross Domestic Product, the decomposition of the KOF Globalization Index (social, economic, and political), public investment, the exchange rate, and the population. The time horizon for the empirical analysis comprises annual information from 1995 to 2015. The results show a bidirectional relationship between social globalization and public investment. In addition, evidence shows other important results: Gross Domestic Product and Gross Domestic Product of tourism, Gross Domestic Product of tourism and public investment, and Gross Domestic Product and public investment. The empirical results contribute to the discussions on tourism in Latin America and the Caribbean, providing a theoretical basis that contributes to the deci sion-making of public and private agents.
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Rady, El-Housainy A., Mohamed Abdallah, and Mohamed R. Abonazel. "A Proposed Generalized Method of Moment Estimation of the Panel Vector Autoregressive Model with Missing Data." Journal of Computational and Theoretical Nanoscience 18, no. 6 (June 1, 2021): 1730–36. http://dx.doi.org/10.1166/jctn.2021.9721.
Full textAbstract:
Estimation methods to handle missing data problems in various panel data models are rarely discussed. However in the panel vector autoregressive model, there is no estimator to handling this type of problems. The traditional treatment for cases of involving incomplete data is to use generalized method of moment estimation based only on the available data without imputation the missing data. Thus, this study introduces a generalized method of moment estimator for the panel vector autoregressive model for solving problems involving incomplete dataset. Our proposed estimator is based on mean imputation with generalized method of moment estimation to achieve more efficiency. The statistical properties of the proposed estimator are presented. Additionally, real data application is used to investigate the efficiency of the proposed estimator compared with the traditional generalized method of moment estimator. The results showed that the proposed estimator is better than the traditional generalized method of moment estimator, even if the percentage of missing data is up to 40%.
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Rady, El-Housainy A., Mohamed Abdallah, and Mohamed R. Abonazel. "A Proposed Generalized Method of Moment Estimation of the Panel Vector Autoregressive Model with Missing Data." Journal of Computational and Theoretical Nanoscience 18, no. 6 (June 1, 2021): 1730–36. http://dx.doi.org/10.1166/jctn.2021.9721.
Full textAbstract:
Estimation methods to handle missing data problems in various panel data models are rarely discussed. However in the panel vector autoregressive model, there is no estimator to handling this type of problems. The traditional treatment for cases of involving incomplete data is to use generalized method of moment estimation based only on the available data without imputation the missing data. Thus, this study introduces a generalized method of moment estimator for the panel vector autoregressive model for solving problems involving incomplete dataset. Our proposed estimator is based on mean imputation with generalized method of moment estimation to achieve more efficiency. The statistical properties of the proposed estimator are presented. Additionally, real data application is used to investigate the efficiency of the proposed estimator compared with the traditional generalized method of moment estimator. The results showed that the proposed estimator is better than the traditional generalized method of moment estimator, even if the percentage of missing data is up to 40%.
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Ferina, Mutia, and Ali Anis. "KAUSALITAS PENANAMAN MODAL DALAM NEGERI, PENANAMAN MODAL ASING DAN PENYERAPAN TENAGA KERJA DI INDONESIA." Jurnal Kajian Ekonomi dan Pembangunan 2, no. 1 (March 1, 2020): 177. http://dx.doi.org/10.24036/jkep.v2i1.8962.
Full textAbstract:
This study aims to determine and analyze the causality of Domestic Investment (PMDN), Foreign Investment (PMA), and Labor Absorption in Indonesia. This type of research is descriptive and associative research that is research that describes the research variables and find the presence or absence of causality between each of these variables. The type of data in this study are secondary data and panel data from 2013-2017 per Province in Indonesia. Analysis of the data used is descriptive analysis and inductive analysis. In inductive analysis there are several tests, namely: Analysis of Vector Auto Regression (VAR), Empirical Model Analysis of Vector Auto Regression (VAR), Steps of Analysis of Vector Auto Regression (VAR) such as: Root Unit Test (Panel Root Test), Coordination Test ( Panel Cointegration Test), Optimum Lag, Granger Causality Test, Stability Test, Implementation of Vector Auto Regression (VAR) Models. The results of this study indicate that (1) domestic investment and foreign investment are not qualified in Indonesia, (2) foreign investment and absorption of unsuspected workers in Indonesia, (3) domestic investment and absorption of qualified workers in Indonesia.