Vector Autoregressive (VAR) Model

This paper evaluates whether Nigeria is ready to adopt inflation targeting (IT), a monetary policy framework that several emerging markets have adopted over the last one decade. The paper reviews literature on selected conditions for successful implementation of IT and then ...

SUMMARY This paper proposes a Bayesian, graph-based approach to identification in vector autoregressive (VAR) models. In our Bayesian graphical VAR (BGVAR) model, the contemporaneous and temporal causal structures of the structural VAR model are represented by two different graphs. We also provide an efficient Markov chain Monte Carlo algorithm to estimate jointly the two causal structures and the parameters of the reduced-form VAR model. The BGVAR approach is shown to be quite effective in dealing with model identification and selection in multi-variate time series of moderate dimension, as those considered in the economic literature. In the macroeconomic application the BGVAR identifies the relevant structural relationships among 20 US economic variables, thus providing a useful tool for policy analysis. The financial application contributes to the recent econometric literature on financial interconnectedness. The BGVAR approach provides evidence of a strong unidirectional linkage from financial to non-financial super-sectors during the 2007–2009 financial crisis and a strong bidirectional linkage between the two sectors during the 2010–2013 European sovereign debt crisis.

This study investigates the response of unemployment to selective macroeconomics shocks for the period of 2000:Q1-2010:Q1. It finds that positive shocks to growth, growth in export and inflation reduce unemployment. On the other hand, shocks to exchange rate, interbank interest rate and money supply increase unemployment. The results are consistent with Phillips curve and Okun's Law suggestion. Namely, negative relationship between output and unemployment and positive relationship between unemployment and inflation are found. Also, this study finds consistent results with earlier literature.

Growth forecasts are at the heart of investment decisions and yet in emerging and developing markets they often receive limited support from quantitative models. This paper describes the main quantitative modelling techniques that have informed EBRD growth projections since 2009. The paper describes how bridge models use high-frequency data and the generalised dynamic factor model uses a vast body of cross-country data to nowcast growth. In addition, a Bayesian vector-autoregressive model is used to forecast growth under various scenarios. The paper includes a comparison between the forecasting performance of the model and that of economists, the latter working both at the EBRD and at other institutions. Osterholm for their comments and suggestions. We also thank Jeromin Zettelmeyer for sharing the Matlab version of the Bayesian VAR model with us. The working paper series has been produced to stimulate debate on the economic transformation of central and eastern Europe and the CIS. ...

Russian monetary policy has failed persistently to achieve sustained low inflation, both in absolute terms and relative to the peer group of countries similarly exiting from Soviet-style central planning. This paper explores the reasons for this state of affairs by analysing the kind of monetary policy that has been pursued by the central bank during the period 1995 to 2009. Our contribution is to search for a possible transmission channel between the real interest rate, inflation rate, exchange rate, output growth and foreign reserve growth, after having controlled for the effect of oil price inflation. Using a vector autoregressive model in error-correction form and using sign restrictions methodology, we show that the monetary authorities' failure to abate double-digit inflation appears to be driven by the policy of exchange rate targeting, as reflected in our identified exchange rate shocks.

Dynamic stochastic general equilibrium (DSGE) models have recently become standard tools for policy analysis. Nevertheless, their forecasting properties have still barely been explored. In this article, we address this problem by examining the quality of forecasts of the key U.S. economic variables: the three-month Treasury bill yield, the GDP growth rate and GDP price index inflation, from a small-size DSGE model, trivariate vector autoregression (VAR) models and the Philadelphia Fed Survey of Professional Forecasters (SPF). The ex post forecast errors are evaluated on the basis of the data from the period 1994-2006. We apply the Philadelphia Fed "Real-Time Data Set for Macroeconomists" to ensure that the data used in estimating the DSGE and VAR models was comparable to the information available to the SPF.

Purpose-A wide range of decision-makers is interested in educated forecasts for house prices. The technical analysis introduced in this study aims to estimate future (forecasted) house prices and provide sufficient evidence in support of the adequacy of the estimated models obtained from parametric and non-parametric modeling methods for Turkey's housing market. Methodology-We employ non-parametric and various time series methods to find appropriate fits to forecast Turkey's house price index (HPI). In our modelling, we consider macroeconomic indicators related to housing markets, such as; gold, interest rate and currencies. In this study, first using the explanatory variables, we construct two Generalized Linear Models (GLM) and a Vector Auto Regressive (VAR) model. Then, we construct two univariate time series models. HPI series inherits seasonality. Even though the HPI contains seasonality, first, we neglect the seasonal effect and come up an Autoregressive Moving Average ((,)) model among many other alternative ARMA models. Second, we consider the seasonality effect on the housing market index and construct a seasonal Autoregressive Integrated Moving Average ((, ,)(, ,)) and exponential smoothing models. Findings-The analysis identifies forecasts of Turkey's housing market index from both the seasonal (, ,)(, ,) and Holt Winter models as accurate models compared to classical time series models, namely (, ,) models, based on the explanation power measure (R^2) values and out-of-sample error measures MSE, RMSE and MAE. Conclusion-The study has three main contributions: i) Our forecast shows Turkey's housing market's return will not increase in the following 12months. ii) The seasonal ARIMA and exponential smoothing models forecast some negative returns within the given forecasting period, which should be considered a warning for Turkey's housing market for the future. iii) GLM and VAR models illustrate that Turkey's housing market shows a high dependence on gold, inflation, and foreign exchange rates than other well-known economic indicators.

This paper examines how short-term and long-term interest rates react to supply, demand and monetary policy shocks in South Africa. Use is made of the impulse response functions obtained from the structural vector autoregressive model with long-term restrictions. We find a positive correlation between the two interest rates after a monetary and demand shock and a negative correlation after a supply shock. The finding of this paper is that the operation of the monetary transmission mechanism should be effective in South Africa. Furthermore, this paper provides an approach to identify supply shocks in the South African business cycle.

The COVID-19 pandemic, as well as the threat of future pandemics, has transformed the focus of automation technology, compelling many businesses to adapt to remote working to increase productivity. This research aims to evaluate if Covid-19 impacts the automation-related occupations, remote work, or labour productivity in Canada. To determine if the series are cointegrated by indicating a vector error correction model for a long-term relationship, the Johansen Cointegration test, VECM (vector error correction model), and Granger causality test were employed in this work. The causality test results show that labour productivity has a positive causal relationship with Covid-19 while automation has a negative causal relationship with Covid-19. Individually, Covid-19 has a positive causal relationship with labour productivity and remote working. Covid-19, automation-related professions, remote working, and labour productivity are all linked in the short and long-run, according to the Johansen cointegration, vector autoregression, and vector error correction models. Granger causality demonstrates that Covid-19 occurrences in Canada have a causal effect on the risk of automation-related professions, remote work, and labour productivity, demonstrating the study's value.

A facsimile apparatus uses a single memory in a facsimile system and a printer system without using an interface between the two systems. In the facsimile apparatus, a FAX controller stores data received via a communication line. A recording control circuit fetches data from the memory via a data bus, and records an image based on the fetched data. A memory intervention circuit outputs a data bus selection signal, and switches an address of access to the recording medium and a connection of the data bus. Thus, a single memory is shared between a facsimile system and printer system.

The sale and lease real estate markets have cyclical developments which are often dissimilar in the
short term and then take coincident trends in longer horizons. The imbalance in the relationship between prices
and income is normally used by economists to determine any "housing bubbles". However, the structural
limitations require caution in the use of the ratio between prices and rents as an indicator of an over - or under -
evaluation in the real estate market. The present work has investigated the relationships between selling and
rental prices in the Italian housing market, trying to define the actual cause-effect relationships in quantitative
terms too. It was used a multivariate autoregressive (VAR) model to interpret the mutual influences between
the two sectors and the macroeconomic fundamentals . The results show that housing prices can influence rents,
but not the opposite. The Italian housing demand, even the one for investment , does not consider rent as a
proxy for the corresponding dividend. The work must be attributed equally to the three authors.

At this article we will try-in light of the macroeconomic statistical data-to assess and analyze the dynamics of employment in Morocco in a polarized economic context marked by the proliferation of free-trade agreements exchange and to be interested in the relationship between international trade and the labor market. For this, we will try to identify factors that determine employment using an econometric model, and to explain the apparent weakness of creation rate of job positions created by our economy in the framework of agreements free trade, when other economically similar countries are experiencing a massive increase in employment rates. This will naturally raise the question of the identification of these factors will allow us also to identify key trends and constraints of the labor market and external trade. Thus, in order to clarify this impact, we proceed to the verification of the link between employment and the variables that seem representative of the openness of our economy

The mortality and morbidity trends from road accidents are rising annually in almost all the developed countries. The total number of deaths and injuries continues to rise despite the decrease in road casualties in relation to the total number of vehicles. Road traffic accident in Ghana is also increasing at an alarming rate and has raised major concerns. In this study, univariate time series was used to model road accidents. The Box – Jenkins method was applied for a 20 year period from 1991-2010.A model was subsequently developed to fit the time series data. SARIMA (1,1,0) × (0,1,1)12 was found to be the best model for road accident cases with a maximum log likelihood value of 245.48, and least AIC value of 5.892, RMSE value of 17.930 and MAPE value value of 1.688. An ARCH-LM test and Ljung-Box test on the residuals of the models revealed that they are free from heteroscedasticity and serial correlation respectively.

We analyse the effects of aggregating the level of disagreement in survey-based expectations. With this aim, we construct several indicators based on two metrics of disagreement: the standard deviation of the balance and a geometric measure of discrepancy. We use data from business and consumer surveys in eleven European countries and the Euro Area. We evaluate the dynamic response of economic growth to shocks in agents' uncertainty gauged by the discrepancy measures in a bivariate vector autoregressive framework. We find that while the effect on economic activity to a shock in aggregate discrepancy is always negative for firms' disagreement, the effect to consumers' disagreement is positive in all countries except Italy. To shed some light regarding the effect of aggregating disagreement both across variables and economic agents on forecast accuracy, we also examine the predictive performance of the discrepancy indicators, using them to generate out-of-sample forecasts of economic growth. We do not find evidence that the aggregation of disagreement improves forecast accuracy. These findings are especially relevant when using cross-sectional dispersion of survey-based expectations of firms and households.

Neste trabalho estudamos o mecanismo do canal de crédito na economia brasileira. Foram usados os testes de raiz unitária de Dickey-Fuller, de causalidade de Granger e o de cointegração de Johansen com o objetivo de aplicar o modelo VAR/VEC à realidade do país. Nossa análise ocorre em dois períodos econômicos: jun.1999/jun.2004 (menor volume de crédito) e jun.2004/jun.2010 (maior volume de crédito). Buscamos suporte teórico nos autores que trabalham com o mecanismo do canal do crédito na linha pós-keynesiana (Fonseca in Oreiro, Paula e Sobreira, 2009), com o mecanismo de transmissão monetária (Bofinger, 2001) e com o regime de política de metas (Rocha e Oreiro, 2008). O trabalho analisa o mecanismo do crédito e seu impacto na taxa básica de juros, bem como compara os resultados da pesquisa à política monetária adotada pelo Banco Central do Brasil na última década.

This study has examined the effectiveness of credit on tobacco output in Zimbabwe over the period 1990 to 2018. Time-series data were collected from the Tobacco Industry and Marketing Board (TIMB), Reserve Bank of Zimbabwe's publications and Zimbabwe Statistics Agency (ZIMSTAT). To check the stationary of the series ADF and Phillips Perron (PP) unit root tests have been applied. The results of ADF tests revealed that all variables become stationary at first difference which confirms to co-integration test. Furthermore, Johansen Co-integration test has been used to examine the long-run relationship between the dependent and independent variables; therefore, the Johansen Co-integration test revealed that; there exists a long-run relationship among agricultural credit distribution and tobacco output. The associated vector error correction model was estimated to obtain short-run elasticity's. More so, Granger Causality approach has been used to determine the direction of the long-run relationship between credit and tobacco output. The results showed that the coefficient of credit is significant at all levels of significance,  which indicates that there is a  strong positive and significant long-run relationship between credit and tobacco output.  This means that a 1% increase in agricultural credit will enhance tobacco output by 0.64%. Granger causality suggests that there is a bidirectional causality relationship exists among agricultural credit and tobacco output.

In this paper we review the existing empirical literature on price asymmetries in commodities, providing a way to classify and compare different studies which are highly heterogeneous in terms of econometric models, type of asymmetries and empirical findings. Relative to the previous literature, this paper is novel in several respects. First, it presents a detailed and updated survey of the existing empirical contributions on the existence of price asymmetries in the transmission mechanism linking input prices to output prices. Second, this paper presents an extension of the traditional distinction between long-run and short-run asymmetries to new categories of asymmetries, such as: contemporaneous impact, distributed lag effect, cumulated impact, reaction time, equilibrium and momentum equilibrium adjustment path, regime effect, regime equilibrium adjustment path. Third, each empirical study is critically discussed in the light of this new classification of asymmetries. Fourth, this paper evaluates the relative merits of the most popular econometric models for price asymmetries, namely autoregressive distributed lags, partial adjustments, error correction models, regime switching and vector autoregressive models.

This study aims to analyze the relationship of exchange rate of Rupiah per U.S. Dollar and interest rate, whether the one of these affects the other one or both of these affect each other. This study also wants to know if there is long term relationship between those. This study tested using the Vector Autoregressive (VAR) model and Johansen cointegration test by Eviews 8 software. The data used is monthly data January 2009 – April 2015 periode. The results of this study are the difference of interest rate affects the difference of exchange rate of Rupiah per U.S. Dollar positively, while  the difference of exchange rate of Rupiah per U.S. Dollar does not affects the difference of interest rate. Beside that, there is no long term relationship between interest rate and exchange rate of Rupiah per U.S. Dollar.

While there has been strong managerial and academic interest in price promotions, much of the focus has been on the impact of such promotions on category sales, brand sales and brand choice. In contrast, little is known about the long-run impact of price promotions on manufacturer and retailer revenues and margins, although both marketing researchers and practitioners consider this a priority area (Marketing Science Institute 2000). Do promotions generate additional revenue and for whom? Which brand, category and market conditions influence promotional benefits and their allocation across manufacturers and retailers?

We study the finite-sample accuracy and average length of pointwise confidence intervals for impulse responses in vector autoregressive models with many variables and many lags. Our results complement existing simulation evidence based on much simpler bivariate models.

Finansal piyasalardaki aktörler açısından risk son derece önemli bir kavramdır. Tüm finansal kuruluşların karşı karşıya olduğu temel risk faktörlerinden birisi kredi riskidir. Kredi riskinin piyasada görünür hale gelmesiyle birlikte bu riskten korunmayı sağlayacak finansal çözümler de geliştirilmeye başlanmıştır. Kredi türevleri, bu çözüm arayışları sonucu ortaya çıkmıştır. Kredi türevleri arasında en yaygın kullanılan sözleşmeler kredi temerrüt swaplarıdır (CDS). CDS' ler, en basit anlamıyla kredi riskine karşı yapılan bir sigorta işlemi olarak ifade edilebilir. Bu çalışmada kredi riskinden yola çıkılarak kredi risk yönetimi ve kredi riskini transfer edebilmek için kullanılan kredi temerrüt swapları detaylı bir şekilde incelenmiştir. Gelişmekte olan sekiz ekonominin dâhil edildiği çalışmada; Türkiye, Brezilya, Hindistan, Güney Afrika, Endonezya, Arjantin, Rusya ve Şili'den oluşan ülkelerin CDS primleri arasındaki nedensellik ilişkisi araştırılmıştır. Ocak 2008 – Aralık 2017 döneminde ülkelere ait 5 yıl vadeli CDS primlerinin incelendiği çalışmada; ülkelerin CDS primleri arasındaki etkileşim VAR modeli kapsamında Granger nedensellik analizi, etki-tepki fonksiyonu ve varyans ayrıştırması ile analiz edilmiştir. Çalışmanın sonuçlarına göre, gelişmekte olan ülkelerin CDS primleri arasında anlamlı nedensellik ilişkisi saptanmıştır.

While many offline retailers have developed informational websites that offer information on products and prices, the key question for such informational websites is whether they can increase revenues via web-to-store shopping. The current paper draws on the information search literature to specify and test hypotheses regarding the offline revenue impact of adding an informational website. Explicitly considering marketing efforts, a latent class model distinguishes consumer segments with different short-term revenue effects, while a Vector Autoregressive model on these segments reveals different long-term marketing response.

The main purpose of this article is twofold to analyze: (a) the long-term relation among the commodities prices and between spot electricity market price and commodity prices, and (b) the short-term dynamics among commodity prices and between electricity prices and commodity prices. Data between 2002 and 2005 from the Spanish electricity market was used. Econometric methods were used in the

This paper provides new evidence on the long-run convergence between imports and exports in 50 countries over the quarterly period 1973:2 to 1998:1. Cointegration analyses are based on the Johansen [Johansen, S. (1995). Likelihood-based inference in cointegrating vector autoregressive models. New York: Oxford University Press.] and the Stock and Watson [J. Am. Stat. Assoc. 83 (1988) 1097.] system approaches. Evidence of stability of the cointegration space is examined using the SupF test developed by Hansen [J. Bus. Econ. Stat. 10 (1992) 321]. Based on the Johansen technique, we find evidence in favor of cointegration in 35 of the 50 countries. In addition, cointegration is confirmed for all countries (except Mexico) using the Stock and Watson test. This finding indicates that macroeconomic policies have been effective in the long-run and suggests that these countries are largely not in violation of their international budget constraint. We find evidence that in most of the countries where the slope coefficient on the export variable is positive, the cointegrating coefficient is also unity. The cointegration space appears stable for most of the countries. Nonetheless, the results suggest that countries in the regions of the Middle East, Latin America, and Europe have cointegrating relations that are more unstable than those in other regions.

This Paper examines the impact of demand and supply shocks on oil prices to consumer prices, interest rates, economic growth (GDP), exchange rates, and money supply of an emerging economy. In this paper, we consider the case of the Philippines, an oil-importing emerging Asian Economy. Given few literature on the effect of oil price shocks to emerging economies, we adopt Kilian (2009), Roach (2014), and Taghizadeh-Hesary & Yoshino's (2015) framework. We incorporate monetary variables to account for its significance to general pricing and economic growth movement (Taghizadeh-Hesary & Yoshino, 2015). Providing a quarterly data from 1981 to 2015, we use Structural Vector Auto-Regressive (SVAR) approach and estimate the Impulse-Response Functions (IRFs) in order to assess the impact of oil prices to macroeconomic variables.

An increase or decrease in crude oil price can both be pain and gain to the Nigerian’s economy simultaneously, this is because a strong link between the country’s budgetary operations and the happenings in the international oil market exists. Therefore, this research employed the restricted vector auto regression (VAR) technique, to empirically investigate into the impact of oil price volatility on Nigeria’s economy from 1981 to 2014.  Both the Augmented Dickey Fuller and Philip Perron unit root test, revealed that all the variables considered in the study are non-stationary at levels, but achieved stationary after estimating their first difference. Furthermore, majority of the variables were found to have long run relationships, justifying the need to estimate the model through the vector error correction model. The short run coefficient deduced from the VECM revealed that oil price shock price shock significantly impacts economic growth in the short run. Also, both the impulse response function and variance decomposition results confirmed the Dutch disease syndrome associated with Nigeria economy, real GDP negatively responded to oil price shock in all the periods despite the positive response of real government expenditure to oil shock in most period. This implies that economic growth is negatively affected in the long run, even though its impact on the real government expenditure seems to be positive mostly, the Pass-through effect it has on high inflation rate, declining exchange rate explains its negative effect on real GDP. In conclusion this study recommends that, for long run macroeconomic growth and performance there is a strong need for policy makers to concentrate on policy that will stabilize and strengthen the macroeconomic structure of the country with specific focus on; alternative sources of government revenue, aggressive savings from revenue proceeds in periods of oil booms, so as to withstand variations of oil shocks in future.
KEY WORDS: crude oil price, Volatility, economic growth, Vector Auto Regression

Through this paper, we assess the sustainability of Tunisian external debt and its effect on the growth of the country. Based on two main approaches, namely the actuarial approach and the accounting approach, we check whether Tunisia was able to support its external debt during the period 1970-2012, while ensuring the balance of its economic fundamentals And its financial indicators. At a second level, we evaluate, empirically, the effects of foreign debt on the economic growth of the country in order to validate the thesis of over indebtedness for the case of Tunisia. Finally, we calculate, under a quadratic approach, the optimal sustainable external debt threshold that ensures regular economic growth and the sustainability of the country's fiscal policy. According to the actuarial method based on tests of stationarity and
cointegration, it was not possible to verify, absolutely, the sustainability of the external debt during the period studied. Some tests verify sustainability, others have given contradictory results. The accounting method shows that this debt was no longer sustainable except for a
few years, namely, 1972, 1974, 1996. This result reflects Tunisia's current situation of overindebtedness, and the problem of external debt for Growth and economic performance. After calculating the external debt threshold, it seems that 51% is the sustainable threshold that allows maximum economic growth. This threshold of external debt stock can only be beneficial to the Tunisian economy if it is allocated to profitable investments that generate wealth and capital.

Electric power demand forecasts play an essential role in the electric industry, as they provide the basis for making decisions in power system planning and operation. A great variety of mathematical methods have been used for demand forecasting. The development and improvement of appropriate mathematical tools will lead to more accurate demand forecasting techniques.

Base metal prices, especially steel, play a significant role in industrial economics, making them worth knowing about future values. In most cases, we expect superior performance from multivariate forecasting models comparing univariate methods due to the involvement of explanatory variables in the system. Standard vector auto regressive model can only capture short-run dynamics because of the differencing process for non-stationary series that eliminates the possible long-run relationship. Instead, performing non-stationary series on levels through the vector auto-regressive framework does not suffers such loss. Moreover, the vector error correction model can define both short-term and long-run dynamics explicitly. These models can yield more robust forecasts in the mid-term and long-term by investigating short-run and long-run relationships simultaneously. The current study aims to perform an out-of-sample forecast for the United States steel prices index 18 months ahead using cointegrated variables. The results suggest that the non-stationary vector auto-regressive model outperforms the vector error correction model regarding mean absolute percentage error and root mean square error as forecast accuracy measures.

Large and persistent current account deficits are among the most serious problems of many developing countries. The Current Account in Kenya has continuously been in deficit in the last three decades prompting the country to rely increasingly on risky short-term flows to balance the accounts. This has consistently created a financing gap. The purpose of this study was to provide empirically characterization of the dynamics of current account deficit and other macroeconomic variables. Based on the absorption approach, the study established the persistence and determinants of the current account deficit; Explanatory research design was adopted. Due to the time series nature of the study, Multivariate Vector Autoregressive, Granger causality test together with Variance decomposition and impulse response functions were used to empirically establish the determinants and dynamics of the current account deficit. The results indicate that current account deficit, gross domestic product growth, inflation and foreign direct investment are I(0). Degree of openness, terms of trade, external debt stock, foreign exchange, gross domestic savings, fiscal deficit, exports and imports are I (1) . The major determinants of the current balance are the degree of openness,
terms of trade, oil price on the international market and inflation. The variance in the current account is better explained by its own shocks followed by shocks from degree of openness, fiscal deficit, terms of trade, external debt of stock, foreign direct investment, growth rate of gross domestic product, and inflation. From the findings, the study recommends the Country to focus on current account targeting policies together with policies that focus on increasing and stabilizing gross domestic product in order to increase exports and its competitiveness and focus on policies that reduce the burden of depending on oil from the world market.

Purpose- A wide range of decision-makers is interested in educated forecasts for house prices. The technical analysis introduced in this study aims to estimate future (forecasted) house prices and provide sufficient evidence in support of the adequacy of the estimated models obtained from parametric and non-parametric modeling methods for Turkey's housing market. Methodology- We employ non-parametric and various time series methods to find appropriate fits to forecast Turkey's house price index (HPI). In our modelling, we consider macroeconomic indicators related to housing markets, such as; gold, interest rate and currencies. In this study, first using the explanatory variables, we construct two Generalized Linear Models (GLM) and a Vector Auto Regressive (VAR) model. Then, we construct two univariate time series models. HPI series inherits seasonality. Even though the HPI contains seasonality, first, we neglect the seasonal effect and come up an Autoregressive Moving Average (ARMA(p,q)) model among many other alternative ARMA models. Second, we consider the seasonality effect on the housing market index and construct a seasonal Autoregressive Integrated Moving Average (ARIMA(p,d,q)(P,D,Q)) and exponential smoothing models. Findings- The analysis identifies forecasts of Turkey’s housing market index from both the seasonal ARIMA(p,d,q) (P,D,Q)_m and Holt Winter models as accurate models compared to classical time series models, namely ARIMA(p,d,q) models, based on the explanation power measure (R^2) values and out-of-sample error measures MSE, RMSE and MAE. Conclusion- The study has three main contributions: i) Our forecast shows Turkey's housing market's return will not increase in the following 12-months. ii) The seasonal ARIMA and exponential smoothing models forecast some negative returns within the given forecasting period, which should be considered a warning for Turkey's housing market for the future. iii) GLM and VAR models illustrate that Turkey's housing market shows a high dependence on gold, inflation, and foreign exchange rates than other well-known economic indicators.

Resumen. El presente trabajo analiza los objetivos e instrumentos de la política monetaria actual en Cuba. Se describen las transformaciones financieras de los años noventa, así como aspectos institucionales y características de los mercados que condicionan la nueva estrategia monetaria del Banco Central de Cuba. Se estima un modelo de Vectores Autorregresivos (VAR) con una identificación estructural, con el objetivo de encontrar evidencia empírica sobre los mecanismos monetarios de transmisión.

This note discusses some issues that arise when framework is used to analyze cointegrating relationships among variables with deterministic linear time trends. We distinguish "stochastic" and "deterministic" cointegration, arguing that stochastic cointegration is sufficient for the existence of an error correction representation and that it is often the hypothesis of interest in empirical applications. We show that Johansen's (1991) method, which includes only a constant term in the estimated regression system, does not allow for stochastic cointegration. We propose to modify Johansen's method by including a vector of deterministic linear trends in the estimated model. We present tabulated critical values of the maximal eigenvalue and trace statistics appropriate for this case. We discuss the circumstances under which our modification may be useful.

The high level of hunger incidence in the country is perhaps one of the most pressing issues that need to be addressed by our policy makers. Official government statistics and data from self-rated hunger surveys show an increasing trend in hunger incidence among Filipino households. Data from National Statistical Coordination Board (NSCB) show that the percentage of subsistence poor in

This master’s thesis investigates the relationship between GDP growth and video games revenues’ growth by testing for the presence of Granger-causal relationships between GDP growth rates and video game revenue growth rates through the application of VAR models, IRF curves, and the Toda-Yamamoto (1995) Granger Causality method; using Video Games Revenues’ annual Growth Rates (Total and by segment) and GDP Growth Rates of North America, Europe & Central Asia, East Asia Pacific, and South Asia from 1972 to 2019.
Our analysis shows no general evidence of GDP growth rates Granger-causing Video Games Growth rates, except in the region of North America for the console segment and video games industry. We also find strong evidence that the mobile gaming revenue is granger-caused by GDP growth in Europe & Central Asia and South Asia. IRF curves further show a short-run inverse relationship between GDP-growth rates and video games growth rates across segments in North America, which points to the industry being recession-resistant in that area.

Recipient of "Best MA Thesis in Quantitative Economics" award from Swedbank

Resumen: Este documento identifica la relación existente entre la tasa de cambio y los diferentes agregados macroeconómicos en la economía colombiana, principalmente en la producción, el consumo, la inflación, la balanza comercial, la tasa de desempleo y la inversión, a través de la metodología Factor Augmented var (favar). Se identifica que una apreciación del dólar genera cambios significativos sobre la actividad económica, la balanza comercial, los precios, el consumo y el gasto público.

يعد أنموذج الانحدار الذاتي المتجه (VAR) من الاساليب القياسية المستخدمة في دراسة التفاعل بين المتغيرات. إذ من الشائع جداً ان يكون هناك نماذج فيها بعض المتغيرات ليست فقط متغيرات مفسرة لمتغير تابع، ولكن هي ايضاً تفسر بالمتغيرات التي كانت تفسرها. وفي هذه الحالة نحصل على نماذج المعادلات الآنية، وعندما تكون هناك آنية بين عدد من المتغيرات كان من المفروض ان تعامل جميع المتغيرات بنفس الطريقة، بمعنى ان لا يكون هناك تمييز بين المتغيرات الداخلية والخارجية . بذلك فأن جميع المتغيرات تعامل كمتغيرات داخلية، هذا يعني في شكلها المختزل كل معادلة تأخذ نفس المتغيرات مما يقود الى بناء نماذج الانحدار الذاتي (VAR) . وسيتم دراسة العلاقة التفاعلية بين الناتج المحلي الاجمالي والتضخم في الاقتصاد العراقي للسنوات (1997-2013) . وقد خلصت الدراسة الى ان تعرض كل من الناتج المحلي الاجمالي (GDP) لصدمة هيكلية واحدة فان استجابة التضخم يكون له اثر معنوي سلبي على المدى الطويل .

The empirical analysis of the economic interactions between factors of production, output and corresponding prices has received much attention over the last two decades. Most contributions in this area have agreed on the neoclassical principle of a representative optimizing firm and typically use theory-based structural equation models (SEM). A popular alternative to SEM is given by the vector autoregression (VAR) methodology. The most recent attempts to link the SEM approach with VAR analysis in the area of factor demands concentrate on single-equation models, whereas no effort has been devoted to compare these alternative approaches when a firm is assumed to face a multi-factor technology and to decide simultaneously the optimal quantity for each input. This paper bridges this gap. First, we illustrate how the SEM and the VAR approaches can both represent valid alternatives to model systems of dynamic factor demands. Second, we show how to apply both methodologies to estimate dynamic factor demands derived from a cost-minimizing capital-labourenergy-materials (KLEM) technology with adjustment costs (ADC) on the quasi-fixed capital factor. Third, we explain how to use both models to calculate some widely accepted indicators of the production structure of an economic sector, such as price and quantity elasticities, and alternative measures of ADC. In particular, we propose and discuss some theoretical and empirical justifications of the differences between observed elasticities, measures of ADC, and the assumption of exogeneity of output and/or input prices. Finally, we offer some suggestions for the applied researcher.

The agricultural sector of Mexico has the greatest volatility with respect to the rest of the economic activities, which makes it difficult to estimate. This research paper provides a methodology for the estimation and forecast of this unpredictable sector. For that purpose it is used a measurement approach based on the current procedure held by the National Institute of Statistics in Mexico. Regarding the forecast approach, the agricultural sector is modeled with a Vector Autoregressive, an ARIMA model and a Dynamic Factor Model. Using the Diebold-Mariano test it is found that the best model to forecast the agricultural sector of Mexico is the ARIMA proposed.

We employ a 10-variable dynamic structural general equilibrium model to forecast the US real house price index as well as its turning point in 2006:Q2. We also examine various Bayesian and classical time-series models in our forecasting exercise to compare to the dynamic stochastic general equilibrium model, estimated using Bayesian methods. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of either 10 or 120 quarterly series in some models to capture the influence of fundamentals. We consider two approaches for including information from large data setsextracting common factors (principle components) in a Factor-Augmented Vector Autoregressive or Factor-Augmented Bayesian Vector Autoregressive models or Bayesian shrinkage in a large-scale Bayesian Vector Autoregressive models. We compare the out-ofsample forecast performance of the alternative models, using the average root mean squared error for the forecasts. We find that the small-scale Bayesian-shrinkage model (10 variables) outperforms the other models, including the large-scale Bayesian-shrinkage model (120 variables). Finally, we use each model to forecast the turning point in 2006:Q2, using the estimated model through 2005:Q2. Only the dynamic stochastic general equilibrium model actually forecasts a turning point with any accuracy, suggesting that attention to developing forward-looking microfounded dynamic stochastic general equilibrium models of the housing market, over and above fundamentals, proves crucial in forecasting turning points.

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ABSTRACT
Nowadays, the stock markets are becoming a crucial part of economies in many
countries. Moreover, the stock markets are becoming increasingly dependent on each other.
This paper investigates the relationship between Borsa Istanbul (BIST) and Tokyo Stock
Exchange with VAR model by using data of 1987:M1-2013:M12. According to impulse
response functions, the reaction of BIST 100 Index in response to an impulse given to Japan
Nikkei 225 Index is statistically meaningful and positive during the entire period. However
the response of this variable exists in short time and it shows a gradually decreasing
tendency.
Keywords: Stock Price Indices, Impulse-Response, Vector Autoregression (VAR),
Variance Decomposition.
Jel Classification: G15

The success of the enlarged Economic and Monetary Union (EMU) depends on the relative incidence of demand and supply shocks in both the participating and the accession countries. This paper addresses the issue using bivariate vector autoregression models for current and would-be EMU member countries. While the degree of symmetry in business cycle shocks among EMU accession countries is significant, idiosyncratic shocks between current and would-be member states dominate. Our results suggest a costly process of adjustment following EMU enlargement. Journal of Comparative Economics 32 (2) (2004) 202-211. analyze regions outside Europe. The paucity of related research on EMU accession countries in Eastern Europe is explained partly by the lack of sufficiently long time series data. , are exceptions.

Presented at the Second South Asian Network on Economic Modeling (SANEM) Annual Economists’ Conference 2017 held on February 18-19, 2017. Link:
http://sanemnet.org/conference_2017/agenda_1.html#public

Full working paper:
https://ideas.repec.org/p/pra/mprapa/75495.html