Relevant bibliographies by topics / Vector autoregressive VAR model

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Vector autoregressive VAR model'

Author: Grafiati
Published: 4 June 2021
Last updated: 27 July 2025

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Journal articles on the topic "Vector autoregressive VAR model"

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Chapman, David, Mark A. Cane, Naomi Henderson, Dong Eun Lee, and Chen Chen. "A Vector Autoregressive ENSO Prediction Model." Journal of Climate 28, no. 21 (2015): 8511–20. http://dx.doi.org/10.1175/jcli-d-15-0306.1.

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Abstract The authors investigate a sea surface temperature anomaly (SSTA)-only vector autoregressive (VAR) model for prediction of El Niño–Southern Oscillation (ENSO). VAR generalizes the linear inverse method (LIM) framework to incorporate an extended state vector including many months of recent prior SSTA in addition to the present state. An SSTA-only VAR model implicitly captures subsurface forcing observable in the LIM residual as red noise. Optimal skill is achieved using a state vector of order 14–17 months in an exhaustive 120-yr cross-validated hindcast assessment. It is found that VAR
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Gankhuu, Battulga. "Gordon Growth Model with Vector Autoregressive Process." Mongolian Mathematical Journal, no. 25 (December 27, 2024): 1–9. https://doi.org/10.5564/mmj.v27i25.3505.

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In this study, we introduce a Gordon’s dividend discount model, based on Vector Auto Regressive Process (VAR). We provide two Propositions, which are related to the generic Gordon growth model and the Gordon growth model, which is based onthe VAR process.
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Tita, Rosita, Zaekhan, and Dwi Estuningsih Rachmawati. "Vector Autoregressive (VAR) for Rainfall Prediction." International Journal of Engineering and Management Research 8, no. 2 (2018): 96–102. https://doi.org/10.5281/zenodo.3361980.

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Weather and climate information is useful in a variety of areas including agriculture, tourism, transportation both land, sea and air. For that, up to date weather and climate data and its forecasting are essential. This study aims to create rainfall modeling with Vector Auto Regressive (VAR) using circular data and linear data. The data used comes from the station climatology Darmaga Bogor period 2006-2017. The VAR model (2) of the rainfall variables in the t-month is affected by the t-1 moisture air moisture, the t-2 moisture air and the air temperature at t2. This VAR model (2) is used to f
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Sihombing, Pardomuan, and Bekti Endar Susilowati. "Aplikasi Model Vector Autoregressive (VAR) pada Data Tamu Mancanegara di Hotel Bintang dan Non Bintang di Daerah Istimewa Yogyakarta." Jurnal Statistika dan Aplikasinya 3, no. 2 (2019): 6–15. http://dx.doi.org/10.21009/jsa.03202.

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Model Vector Autoregressive (VAR) merupakan gabungan dari beberapa model Autoregressive (AR), dimana model membentuk sebuah vektor yang antara variabel-variabelnya saling memengaruhi. Model AR(1) menyatakan bahwa pengamatan waktu sekarang dipengaruhi pengamatan satu waktu sebelumnya dan unsur error. Pada analisis ini, model Vector Autoregressive (VAR) digunakan pada data tamu mancanegara per bulan yang menginap di Hotel Bintang dan Non bintang di Daerah Istimewa Yogyakarta per bulan periode Januari 2008 sampai dengan Desember 2015. Pembentukan model VAR melalui beberapa tahap yaitu: uji stasio
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Ningrum, Dewi Kusuma, and Sugiyarto Surono. "Comparison the Error Rate of Autoregressive Distributed Lag (ARDL) and Vector Autoregressive (VAR) (Case study: Forecast of Export Quantities in DIY)." JURNAL EKSAKTA 18, no. 2 (2018): 167–77. http://dx.doi.org/10.20885/eksakta.vol18.iss2.art8.

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Forecasting is estimating the size or number of something in the future. Regression model that enters current independent variable value, and lagged value is called distributed-lag model, if it enters one or more lagged value, it is called autoregressive. Koyck method is used for dynamic model which the lagged length is unknown, for the known lagged length it is used the Almon method. Vector Autoregressive (VAR) is a method that explains every variable in the model depend on the lag movement from the variable itself and all the others variable. This research aimed to explain the application of
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Lanne, Markku, and Pentti Saikkonen. "NONCAUSAL VECTOR AUTOREGRESSION." Econometric Theory 29, no. 3 (2012): 447–81. http://dx.doi.org/10.1017/s0266466612000448.

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In this paper, we propose a new noncausal vector autoregressive (VAR) model for non-Gaussian time series. The assumption of non-Gaussianity is needed for reasons of identifiability. Assuming that the error distribution belongs to a fairly general class of elliptical distributions, we develop an asymptotic theory of maximum likelihood estimation and statistical inference. We argue that allowing for noncausality is of particular importance in economic applications that currently use only conventional causal VAR models. Indeed, if noncausality is incorrectly ignored, the use of a causal VAR model
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Iskandar, Iskandar. "ANALISIS VECTOR AUTOREGRESSION (VAR) TERHADAP INTERRELATIONSHIP ANTARA FINANCING DEPOSIT RATIO (FDR) DAN RETURN ON ASSET (ROA) PADA BANK SYARIAH DI INDONESIA." Jurnal Ekonomi Syariah, Akuntansi dan Perbankan (JESKaPe) 3, no. 2 (2019): 19–39. http://dx.doi.org/10.52490/jeskape.v3i2.430.

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The Vector Autoregressive Model (VAR) is a very useful analytical tool in understanding the existence of interrelationships between economic variables and in the formation of a structured economy. This study aims to explain the analysis of the Vector Autoregressive (VAR) model and explain the application of the Vector Autoregressive (VAR) model for influence analysis. The FDR ratio in the Sharia Commercial banks tends to be stable. This is illustrated from the coefficient of determination which is almost close to 100%, namely 91.55%. Cointegration test results show there is no long-term balanc
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Sathyanarayana, S., and Sudhindra Gargesa. "Modeling Cryptocurrency (Bitcoin) using Vector Autoregressive (Var) Model." SDMIMD Journal of Management 10, no. 2 (2019): 47–64. http://dx.doi.org/10.18311/sdmimd/2019/23181.

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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-tr
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Musyoki, Michael, David Alilah, and David Angwenyi. "Updated Vector Autoregressive Model Incorporating new Information Using the Bayesian Approach." SCIENCE MUNDI 4, no. 2 (2024): 178–97. http://dx.doi.org/10.51867/scimundi.mathematics.4.2.17.

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Vector Autoregressive (VAR) models have been applied extensively in modeling time series due to their high precision when used to forecast. In the VAR development, if we have information up to time t, then a VAR(p) model is fitted. However, if new information at time t + 1, is obtained, then a new VAR(p) model has to be fitted which makes one to go through the process again. Therefore, despite their good performance, a need would arise to incorporate new information that could be obtained after the model has been fitted to update the model instead of fitting a new model each and every time a n
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Dissertations / Theses on the topic "Vector autoregressive VAR model"

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Brüggemann, Ralf. "Model reduction methods for vector autoregressive processes /." Berlin [u.a.] : Springer, 2004. http://www.loc.gov/catdir/enhancements/fy0818/2003067373-d.html.

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Serpeka, Rokas. "Analyzing and modelling exchange rate data using VAR framework." Thesis, KTH, Matematik (Inst.), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-94180.

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Abstract   In this report analysis of foreign exchange rates time series are performed. First, triangular arbitrage is detected and eliminated from data series using linear algebra tools. Then Vector Autoregressive processes are calibrated and used to replicate dynamics of exchange rates as well as to forecast time series. Finally, optimal portfolio of currencies with minimal Expected Shortfall is formed using one time period ahead forecasts
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Louw, Riëtte. "Forecasting tourism demand for South Africa / Louw R." Thesis, North-West University, 2011. http://hdl.handle.net/10394/7607.

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Tourism is currently the third largest industry within South Africa. Many African countries, including South Africa, have the potential to achieve increased economic growth and development with the aid of the tourism sector. As tourism is a great earner of foreign exchange and also creates employment opportunities, especially low–skilled employment, it is identified as a sector that can aid developing countries to increase economic growth and development. Accurate forecasting of tourism demand is important due to the perishable nature of tourism products and services. Little research on foreca
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Wong, Kin-man, and 黃健文. "A vector autoregression (VAR) model of housing starts and housing price in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hdl.handle.net/10722/194603.

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It is observed that there are many different models about housing price. Yet, this is relatively smaller number of studies about housing starts. This thesis is an empirical study to work out the relationship between housing starts, housing price and other economic and policy instrumental factors. To achieve this objective, a Vector Autoregression (VAR) model is built since there is inter-relationship between housing starts and housing price. By applying previous models filled with the research gaps, a new VAR model about the housing starts and housing price in Hong Kong is built. Four hypot
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Perez, Tomas Rene. "Oil Price and the Stock Market: A Structural VAR Model Identified with an External Instrument." Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1595877677072786.

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Pilström, Patrick, and Sebastian Pohl. "Forecasting GDP Growth : The Case of The Baltic States." Thesis, Jönköping University, JIBS, Economics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-9776.

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<p>The purpose of this thesis is to identify a general model to forecast GDP growth for the Baltic States, Estonia, Latvia and Lithuania. If the model provides reliable results for these states, then the model should be able to forecast GDP growth for other countries of interest. Forecasts are made by using a reduced vector autoregressive (VAR) model. The VAR models make use of past values of Gross Domestic Product-Inflation-Unemployment as explanatory variables.</p><p>The performed forecasts have provided good results for horizons up to t+8. The forecasts for 2009 (t+12) are in line with thos
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Jansson, Emelie, and Linda Kapple. "Vad styr företagens investeringar?En studie om hur förändringar i reporänta, makroekonomiska faktorer samt finansiella indikatorer påverkar investeringar hos svenska företag." Thesis, Linköpings universitet, Nationalekonomi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121716.

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Bakgrund: I november 2014 beslutade Riksbanken att ta steget mot en nollränta och i februari 2015 gick Riksbanken ut med ytterligare en sänkning till -0,10 procent. På så vis fick Sverige för första gången en negativ reporänta. Enligt makroekonomisk teori ska en sänkning av reporäntan stimulera konsumtion och investeringar i ekonomin. Huruvida reporäntan och dess räntesänkningar skapar förutsättningar för företag att investera är ett aktuellt och viktigt forskningsområde. Forskningen i ämnet är tunn på den svenska marknaden och således är forskningsbidraget från denna studie av betydelse.Syfte
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Alsaedi, Yasir H. "An Investigation of the Effects of Solar and Wind Prices on the Australia Electricity Spot and Options Markets: A Time Series Analysis." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/410472.

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Electricity pricing is recognised as being among the most important contemporary policy issues in Australia, and it also represents a critical component of current discussions concerning energy and climate-change policies. Attempts to move forward with energy and climate-change policies have been mostly stymied by concerns regarding potential increases in electricity prices. In relation to such policy discussions, renewable electricity generation is currently considered to be a fundamental factor influencing electricity prices. Due to the increasing penetration of both wind and solar power gen
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Ramanauskaitė, Giedrė. "Stress testing in credit risk analysis." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2008. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20080620_110415-38466.

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The supervising institutions do not give to commercial banks indications what models have to be used for stress testing. This research was done in order to find out which mathematical/statistical models are and can be used in credit risk stress testing. Credit risk is one of the biggest financial risks that every bank faces. Stress testing is a tool of credit risk assessment that helps to estimate the consequences of the events that have really small probability to happen but if they occur, banks can have significant losses. This study determined that the most plausible event is adverse macroe
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Figueiredo, Marta Isabel Fragoso Peralta de. "Análise da modelação dos preços do mercado de habitação na área de Lisboa entre 1972 e 2011." Master's thesis, Instituto Superior de Economia e Gestão, 2012. http://hdl.handle.net/10400.5/10453.

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Mestrado em Gestão e Avaliação Imobiliária<br>O propósito deste estudo é investigarmos empiricamente os determinantes que influenciaram a formação do preço da habitação em Portugal. A evolução dos preços da habitação em Portugal reveste-se de grande importância para os profissionais do sector. Conhecer, estudar e analisar a evolução deste mercado ao longo dos últimos anos permite aos profissionais tomar decisões fundamentadas em análises profundas e cuidadas sobre quais foram os determinantes que influenciaram a procura e a oferta que por sua vez determinaram os preços. Pretendemos conhecer o
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Books on the topic "Vector autoregressive VAR model"

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Aggarwal, Shalini, Sunita Arora, and Arvinder Kaur. How to Use Vector Autoregressive (VAR) Models. SAGE Publications Ltd, 2025. https://doi.org/10.4135/9781036213596.

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Brüggemann, Ralf. Model Reduction Methods for Vector Autoregressive Processes. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-17029-4.

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Mocan, H. Naci. Business cycles and fertility dynamics in the U.S.: A vector-autoregressive model. National Bureau of Economic Research, 1989.

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Hasan, Mohammad S. Monetary policy, fiscal policy, and aggregate economic activity in a vector autoregressive model. University of Northumbria at Newcastle, 1995.

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Johansen, Søren. The asymptotic variance of the estimated roots in a cointegrated vector autoregressive model. European University Institute, Department of Economics, 2001.

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Fernández-Villaverde, Jesús. A, B, C's, (and D's) for understanding VARS. Federal Reserve Bank of Atlanta, 2005.

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Fernández-Villaverde, Jesús. A, B, C's (and D)'s for understanding VARS. National Bureau of Economic Research, 2005.

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Johansen, Søren. Controlling inflation in a cointegrated vector autoregressive model with an application to US data. European University Institute, Department of Economics, 2001.

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Johansen, Søren. A small sample correction of the test for cointegrating rank in the vector autoregressive model. European University Institute, 2000.

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Johansen, Søren. A small sample correction of the test for cointegrating rank in the vector autoregressive model. European University Institute, 2000.

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Book chapters on the topic "Vector autoregressive VAR model"

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Min, Chung-ki. "Vector autoregressive (VAR) models." In Applied Econometrics. Routledge, 2019. http://dx.doi.org/10.4324/9780429024429-9.

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Aljandali, Abdulkader, and Motasam Tatahi. "Vector Autoregression (VAR) Model." In Economic and Financial Modelling with EViews. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92985-9_10.

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Asteriou, Dimitrios, and Stephen G. Hall. "Vector Autoregressive (VAR) Models and Causality Tests." In Applied Econometrics. Macmillan Education UK, 2016. http://dx.doi.org/10.1057/978-1-137-41547-9_15.

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Srinivasan, Shuba. "Modeling Marketing Dynamics Using Vector Autoregressive (VAR) Models." In Handbook of Market Research. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-57413-4_10.

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Srinivasan, Shuba. "Modeling Marketing Dynamics Using Vector Autoregressive (VAR) Models." In Handbook of Market Research. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-05542-8_10-1.

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Jefferson, Al, and J. Pabelic. "Bootstrap Efficiency on Granger Causality Test in Bivariate Vector Autoregressive (VAR) Model." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40630-0_43.

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Pabelic, Al Jefferson J. "Erratum to: Bootstrap Efficiency on Granger Causality Test in Bivariate Vector Autoregressive (VAR) Model." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40630-0_103.

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Mokhtarzadeh, Fatemeh. "A global vector autoregression model for softwood lumber trade." In International trade in forest products: lumber trade disputes, models and examples. CABI, 2021. http://dx.doi.org/10.1079/9781789248234.0174.

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Abstract A novel econometric approach is developed in this chapter, namely, the Global Vector Autoregressive (GVAR) model. It provides a comprehensive framework for analyzing the country-level impacts of various domestic, foreign, and/or global shocks on softwood lumber trade. The GVAR approach is applied to Canada-U.S. trade in softwood lumber and used to analyze the effect of external shocks on Canadian lumber prices. Findings indicate that Canada's export prices are positively correlated to U.S. housing starts and real GDP. Further, using impulse response functions, it is used to examine th
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Mokhtarzadeh, Fatemeh. "A global vector autoregression model for softwood lumber trade." In International trade in forest products: lumber trade disputes, models and examples. CABI, 2021. http://dx.doi.org/10.1079/9781789248234.0008.

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Abstract A novel econometric approach is developed in this chapter, namely, the Global Vector Autoregressive (GVAR) model. It provides a comprehensive framework for analyzing the country-level impacts of various domestic, foreign, and/or global shocks on softwood lumber trade. The GVAR approach is applied to Canada-U.S. trade in softwood lumber and used to analyze the effect of external shocks on Canadian lumber prices. Findings indicate that Canada's export prices are positively correlated to U.S. housing starts and real GDP. Further, using impulse response functions, it is used to examine th
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Shahzad, Syed Jawad Hussain, Elie Bouri, Sang Hoon Kang, and Tareq Saeed. "Regime Specific Spillover Across Cryptocurrencies and the Role of COVID-19." In Blockchain, Crypto Assets, and Financial Innovation. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-6839-7_11.

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Abstract The aim of this study is to examine the daily return spillover among 18 cryptocurrencies under low and high volatility regimes, while considering three pricing factors and the effect of the COVID-19 outbreak. To do so, we apply a Markov regime-switching (MS) vector autoregressive with exogenous variables (VARX) model to a daily dataset from 25-July-2016 to 1-April-2020. The results indicate various patterns of spillover in high and low volatility regimes, especially during the COVID-19 outbreak. The total spillover index varies with time and abruptly intensifies following the outbreak
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Conference papers on the topic "Vector autoregressive VAR model"

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Yu, Jiaxin, Yining Dong, and S. Joe Qin. "Kernel Latent Vector Autoregressive Model for Nonlinear Dynamic Data Modeling and Monitoring." In 2024 IEEE 63rd Conference on Decision and Control (CDC). IEEE, 2024. https://doi.org/10.1109/cdc56724.2024.10885978.

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Devianto, Dodi, Tiansi Ade Bora, Maiyastri, Yudiantri Asdi, Dony Permana, and Erna Tri Herdiani. "The Causality Model of Indonesia Rupiah Exchange Rates, Imports, and Exports Using Multivariate Time Series Model of Vector Autoregressive." In 2024 2nd International Symposium on Information Technology and Digital Innovation (ISITDI). IEEE, 2024. https://doi.org/10.1109/isitdi62380.2024.10796690.

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Samadi, Dr S. Yaser. "Enhancing Business and Financial Analysis through Reduced-Rank Envelope Vector Autoregressive Models." In 5th World Conference on Business, Management, Finance, Economics, and Marketing. Eurasia Conferences, 2024. http://dx.doi.org/10.62422/978-81-968539-6-9-018.

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Vector autoregressive (VAR) models have historically been favored for their adaptability and simplicity in modeling multivariate time series data. However, the VAR framework often encounters overparameterization issues, particularly in high-dimensional time series datasets, limiting the incorporation of variables and lags. Several statistical approaches have been proposed to address dimension reduction in VAR models, yet, they prove inefficient in extracting relevant information from complex datasets, as they fail to distinguish between information aligned with scientific objectives and are al
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Burentegsh, Dorjjugder, and Péter Elek. "Macroeconomic policy empirical analysis using an unrestricted standard VAR Model." In The European Union’s Contention in the Reshaping Global Economy. Szegedi Tudományegyetem Gazdaságtudományi Kar, 2022. http://dx.doi.org/10.14232/eucrge.2022.11.

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This paper is mainly about key fiscal policy indicators and their interrelations between each other. The model that is used in the analysis is the Vector Autoregressive Model. There are seven variables selected: GDP, Money Supply, Government Revenue, Government Expenditure, Export, Government Debt, and Global Copper Price. Besides VAR estimation, IRFs are computed to define how variables react to certain shocks. The key finding of the research is that both GDP and government revenue are sensitive to copper price changes and the resulting shock. Copper Price is an effective tool to predict thes
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Suharsono, Agus, Auliya Aziza, and Wara Pramesti. "Comparison of vector autoregressive (VAR) and vector error correction models (VECM) for index of ASEAN stock price." In INTERNATIONAL CONFERENCE AND WORKSHOP ON MATHEMATICAL ANALYSIS AND ITS APPLICATIONS (ICWOMAA 2017). Author(s), 2017. http://dx.doi.org/10.1063/1.5016666.

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Hasanah, Rini Nur, R. P. Ravie O.M.P., and Hadi Suyono. "Comparison Analysis of Electricity Load Demand Prediction using Recurrent Neural Network (RNN) and Vector Autoregressive Model (VAR)." In 2020 12th International Conference on Electrical Engineering (ICEENG). IEEE, 2020. http://dx.doi.org/10.1109/iceeng45378.2020.9171778.

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Gholamhossein, Maryam, Ameneh Vatani, Najmeh Daroogheh, and K. Khorasani. "Prediction of the Jet Engine Performance Deterioration." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-87936.

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This paper deals with performance deterioration modelling of a single spool gas turbine engine based on time-series methods. Towards this end, two univariate and multivariate methods, namely the Autoregressive Integrated Moving Average (ARIMA) and the Vector Autoregressive (VAR) schemes are applied to predict the Turbine Entry Temperature (TET) evolution during the flight cycles for maintenance purposes. In the VAR scheme, two engine process parameters i.e. the Turbine Entry Temperature (TET) and the Compressor Temperature are employed to achieve this prediction goal. The results show that emp
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Guth, Karel, Tereza Aišmannová, and Irena Benešová. "Application of VAR Model to Determine Sustainability of Short-Term Rental Accommodation." In Liberec Economic Forum 2023. Technical University of Liberec, 2023. http://dx.doi.org/10.15240/tul/009/lef-2023-57.

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Platforms like Airbnb have fundamentally reshaped the hospitality sector as we have known it. With its distinctive model, short-term rentals (STR) have gained significant popularity among tourists and property owners alike. As the popularity of STR continues to grow, questions arise regarding its implications for sustainable tourism. In this paper, we investigate the impact of short-term rental accommodation on residential housing prices in the centre of Prague by employing an econometric analysis of time series. For this purpose, we apply the vector autoregressive (VAR) model. In the modellin
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Bashir, Faraj, and Hua-Liang Wei. "Handling Missing Data in Multivariate Time Series Using a Vector Autoregressive Model Based Imputation (VAR-IM) Algorithm. Part II: VAR-IM Algorithm Versus Modern Methods." In 2016 19th IEEE Intl Conference on Computational Science and Engineering (CSE), IEEE 14th Intl Conference on Embedded and Ubiquitous Computing (EUC), and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES). IEEE, 2016. http://dx.doi.org/10.1109/cse-euc-dcabes.2016.224.

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Bashir, Faraj, and Hua-Liang Wei. "Handling missing data in multivariate time series using a vector autoregressive model based imputation (VAR-IM) algorithm: Part I: VAR-IM algorithm versus traditional methods." In 2016 24th Mediterranean Conference on Control and Automation (MED). IEEE, 2016. http://dx.doi.org/10.1109/med.2016.7535976.

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Reports on the topic "Vector autoregressive VAR model"

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Kim, Sei-Wan, Donghyun Park, and Shu Tian. How Does Inflation in Advanced Economies Affect Emerging Market Bond Yields? Empirical Evidence from Two Channels. Asian Development Bank, 2023. http://dx.doi.org/10.22617/wps230372-2.

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This study uses multivariable smooth transition autoregressive–vector autoregressive (STAR–VAR), a novel model to explore how inflation in advanced economies affects emerging market bond yields. Results reveal two key findings. First, advanced economy inflation has a significant effect on emerging market bond yields. Second, the short-run effect of advanced economy inflation on the bond yields of emerging markets is asymmetric between the expansion and contraction regimes. The effect is mostly positive in both regimes but stronger in a bond yield’s contraction regime.
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Granados, Camilo, and Daniel Parra-Amado. Output Gap Measurement after COVID for Colombia: Lessons from a Permanent-Transitory Approach. Banco de la República, 2025. https://doi.org/10.32468/be.1295.

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We estimate the output gap for the Colombian economy explicitly accounting for the COVID-19 period. Our estimates reveal a significant $20$\% decline in the output gap but with a faster recovery compared to previous crises. Our empirical strategy follows a two-stage Bayesian vector autoregressive (BSVAR) model where i) a scaling factor in the reduced form of VAR is used to model extreme data, such as those observed around the COVID-19 period, and ii) permanent and transitory shocks are structurally identified. As a result, we obtain that a single structural shock explains the potential GDP, wh
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Martin, Julien, Kevin Moran, and Dalibor Stevanovic. Macroeconomic Impacts of a Canada-U.S. Tariff War. CIRANO, 2025. https://doi.org/10.54932/rfdn9707.

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We use a vector autoregressive (VAR) model to produce macroeconomic forecasts conditional on two trade war scenarios between the United States and Canada. The first scenario examines the impact of tariff imposition on Canadian exports to the United States, while the second scenario incorporates the effect of Canadian retaliatory tariffs on imports from the United States. Our results show that these trade tensions would have significant consequences on the Canadian economy, with notable declines in GDP and employment. The analysis highlights a more pronounced contraction when imports are also a
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Alviarez, Vanessa, Peter Pedroni, Andrew Powell, and Ingri Katherine Quevedo Rocha. International versus Domestic Shocks and Pass-Through to Country Prices: A Heterogeneous VAR Approach. Inter-American Development Bank, 2025. https://doi.org/10.18235/0013406.

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This study investigates the disconnect between falling agricultural commodity prices and persistent food inflation by applying a Heterogeneous Vector Autoregression (VAR) model to a panel of 203 countries using data from 1961 to 2022. It analyzes the impact of global crops, fertilizer, and oil prices on domestic inflation and explores the asymmetries in the pass-through of global shocks. Results show that fertilizer price shocks significantly influence crop prices, especially maize and soybeans, while production shocks have a weaker effect. Demand-driven price changes exhibit higher pass-throu
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Rosser, J. Barkley, and Richard G. Sheehan. A Vector Autoregressive Model of Saudi Arabian Inflation. Federal Reserve Bank of St. Louis, 1985. http://dx.doi.org/10.20955/wp.1985.011.

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Ahmed, Ehsan, J. Barkley Rosser, and Richard G. Sheehan. A Model of Global Aggregate Supply and Demand Using Vector Autoregressive Techniques. Federal Reserve Bank of St. Louis, 1986. http://dx.doi.org/10.20955/wp.1986.004.

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Mocan, Naci. Business Cycles and Fertility Dynamics in the U.S.: A Vector-Autoregressive Model. National Bureau of Economic Research, 1989. http://dx.doi.org/10.3386/w3177.

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Yamada, Tadashi. The Crime Rate and the Condition of the Labor Market: A Vector Autoregressive Model. National Bureau of Economic Research, 1985. http://dx.doi.org/10.3386/w1782.

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Hajdini, Ina. Mis-specified Forecasts and Myopia in an Estimated New Keynesian Model. Federal Reserve Bank of Cleveland, 2023. http://dx.doi.org/10.26509/frbc-wp-202203r.

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The paper considers a New Keynesian framework in which agents form expectations based on a combination of autoregressive mis-specified forecasts and myopia. The proposed expectations formation process is shown to be consistent with all three empirical facts on consensus inflation forecasts. However, while mis-specified forecasts can be both sufficient and necessary to match all three facts, myopia alone is neither. The paper then derives the general equilibrium solution consistent with the proposed expectations formation process and estimates the model with likelihood-based Bayesian methods, y
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de Padua, David, Matteo Lanzafame, Irfan Qureshi, and Kiyoshi Taniguchi. Understanding the Drivers of Remittances to Pakistan. Asian Development Bank, 2024. http://dx.doi.org/10.22617/wps240348-2.

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This paper analyzes remittances to Pakistan and identifies the key macroeconomic variables influencing this important source of external financing. Remittances account for approximately 10% of gross domestic product in Pakistan and a better understanding of remittance drivers is needed to inform policies that can bolster their contribution to poverty reduction and other development priorities. To develop this understanding, the authors combined a database of bilateral remittances between Pakistan and its main remittance-sending countries with monthly macroeconomic data over 2003–2021, and appl
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