Unrestricted Vector Autoregression Research Articles

Estimation of transmission mechanism of monetary policy in Serbia

Transmission mechanism of monetary policy recently has been subject to several studies in Serbia. The so called 'black box' of monetary policy is investigated with aim to identify the effects of transmission channel in environment where exchange rate has a dominant role in central bank operations. Therefore, it is a challenge to approach this problem in inflation targeting regime where key interest rate is expected to prevail as a main policy instrument. The study employs unrestricted Vector Autoregression model for estimating significance of exchange rate and interest rate channel. As expected, exchange rate has far more stronger influence on inflation, even though there are some signs of interest rate channel existence. Introducing Euribor as endogenous variables in VAR system displayed important impact on real variables.

"Investigating Banking Households' Deposits Using Vector Autoregressive Model Var "

Nowadays, settling a proper and adequate relationship with the customers became a concern of the banks, that have to back to basics and obtain the trust when interact with customers. Banking customers represented by the population's householders matter in banks' financing if we retain that in the last year, the household deposits represented 29.2% of total liabilities of credit institutions active in Romania. This paper argues that in order to study the influence factors that affect the banking customers' behavior, it is important to consider the saving process of banking customers as an exogenous dynamic phenomenon, while the study does not deny, but it not approached another face of thinks - the endogenous influences. The paper examines if there exist any long-run relationships between deposits made by the population's householders and their behavior influenced by the interest rate on the deposits set up in banks by householders, the unemployment rate, the monthly net wages in the economy and the consumer price index. We provide an unrestricted Vector Autoregression Model (VAR) in order to investigate the relationship between variables mentioned above, using the data set on Romanian banking system, which covers the period January 2007 - December 2012. Our research confirms the impact that the interest rate on deposits has on the banking customers' behavior, mirrored in the deposits made with active banks in Romania by the population's householders.

Empirical Econometric Analysis of Relationship between Fiscal-Monetary Policies and Output on SAARC Countries

The seminal 1968 paper of Anderson and Jordan on the relative effectiveness of monetary and fiscal policy on output stabilization caused many debates among both economists and policy makers. This paper uses a standard unrestricted VAR (vector autoregression) model to analyze the above relationship for five SAARC (South Asian Association of Regional Cooperation) countries (Bangladesh, India, Nepal, Pakistan and Sri Lanka) over the period of 1974–2007. In a system of five-equation of VAR model, this paper reveals that money supply, government expenditure, the real exchange rate and the foreign interest rate are co-integrated for all countries. The results of both the VD (Variance decomposition) and the IRFs (Impulse response functions) indicate that monetary policy has been more effective on output than fiscal policy in the case of Pakistan and Sri Lanka, whereas fiscal policy has had a more powerful effect than monetary policy on Bangladesh, India and Nepal.

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Where is U.S. Sovereign Debt Heading? A Forecasting Model

We develop a debt-to-GDP forecasting framework incorporating the classical debt accounting relationship relating the debt-to-GDP ratio to its previous period value, the growth rate of the economy, the government cost of debt service, and the primary balance. We present a linearization of the debt buildup equation, and a parsimonious model of the evolution of the government borrowing costs and the primary balance dynamics. We apply our framework to the U.S. economy described by an unrestricted Vector Auto-Regression (VAR), and forecast the multi-year path of the federal debt load from 2010 onwards. We find that our forecasts are in good agreement with realized values of debt-to-GDP across 2010, 2011 and 2012. We also perform a scenario analysis under different assumptions for the persistence of the budget balance, and show that President Obama's 2009 budget projection was less realistic than one based on a historically observed persistence.

Ocena stopnia zgodności wybranego modelu równowagi ogólnej z danymi empirycznymi

The paper presents the derivation of structural equations of an estimated general equilibrium model, illustrates techniques of its connection with the data observed and discusses a method of assessing the degree of acceptance by the data. The results suggest that the model is not confirmed by the data. Logarithms of the marginal data density tend to systematically decrease when the weight of the structural model is being increased in hybrid vector autoregression. This defines an econometric tool which can capture a general equilibrium model on the one hand and almost unrestricted vector autoregression on the other. As a consequence of high structural model misspecification, economic conclusions it leads one to draw may be highly inaccurate.

Asymmetric Oil Price Shock Response: A Comparative Analysis

This paper extends the literature on the effects of oil-price shocks using United States, Norway and South Africa as case studies between 1980 and 2010. The Structural Vector Autoregressive (SVAR) and Panel VAR methodologies are employed as an extension to the conventional unrestricted Vector Autoregressive (VAR) model. Results show that the developed economies (United States and Norway) stick to the non-linear oil-price shock specifications as argued in the literature. However, these are not feasible within the context of the emerging net-oil importing economy. Furthermore, Structural Vector Autoregressive (SVAR) model decisively restricts the oil-price shock effects while the effects intended to be captured may have been overruled by the identification restrictions imposed. Nevertheless, the Panel VAR methodology is able to accommodate all oil-price shock specifications. The claim that there exists a transmission mechanism through which positive oil price shock accruals can be beneficial to the global community was empirically verified using Foreign Direct Investment (FDI) as a proxy. In the other way round, there is suggestive evidence of possible unprecedented and unsatisfactory effects during negative oil-price shock periods.

Model selection criteria for reduced rank multivariate time series: a simulation study

The main focus of our paper is to compare the performance of different model selection criteria used for multivariate reduced rank time series. We consider one of the most commonly used reduced rank model, that is, the reduced rank vector autoregression (RRVAR (p, r)) introduced by Velu et al. [Reduced rank models for multiple time series. Biometrika. 1986;7(31):105–118]. In our study, the most popular model selection criteria are included. The criteria are divided into two groups, that is, simultaneous selection and two-step selection criteria, accordingly. Methods from the former group select both an autoregressive order p and a rank r simultaneously, while in the case of two-step criteria, first an optimal order p is chosen (using model selection criteria intended for the unrestricted VAR model) and then an optimal rank r of coefficient matrices is selected (e.g. by means of sequential testing). Considered model selection criteria include well-known information criteria (such as Akaike information criterion, Schwarz criterion, Hannan–Quinn criterion, etc.) as well as widely used sequential tests (e.g. the Bartlett test) and the bootstrap method. An extensive simulation study is carried out in order to investigate the efficiency of all model selection criteria included in our study. The analysis takes into account 34 methods, including 6 simultaneous methods and 28 two-step approaches, accordingly. In order to carefully analyse how different factors affect performance of model selection criteria, we consider over 150 simulation settings. In particular, we investigate the influence of the following factors: time series dimension, different covariance structure, different level of correlation among components and different level of noise (variance). Moreover, we analyse the prediction accuracy concerned with the application of the RRVAR model and compare it with results obtained for the unrestricted vector autoregression. In this paper, we also present a real data application of model selection criteria for the RRVAR model using the Polish macroeconomic time series data observed in the period 1997–2007.

The Orthogonal Response of Stock Returns to Dividend Yield and Price-to-Earning Innovations

This study investigates how returns on the S&P 500 index respond orthogonally to dividend yield and price-to-earning innovations. The unrestricted vector autoregression (VAR) analysis of monthly data from 1871 to 2012 shows that the response of returns on the S&P 500 index to dividend yield innovation, based on the 12-month horizon, is positive in the first three months, negative in the 4th through 7th months and positive again after that. The returns on the S&P 500 index are negative in the first five months following price-to-earning shock. The Granger causality tests indicate a causal link between returns on the S&P 500 index, dividend yield and price-to-earning. This study offers an important implication for asset management and valuation.

Commercial Paper Rates and Stock Market Excess Returns

This study investigates how commercial paper rates respond to the innovations in stock market risk premiums. The unrestricted vector autoregression (VAR) analysis of monthly data from 1997:1 to 2012:M6 shows that the changes in the one-, two-, and three-month non-financial and financial commercial paper rates positively respond to the innovations in the excess returns on the CRSP value weighted index. The response is especially strong during the first few months following shocks to stock market risk premiums. The Granger-causality test results show the changes in commercial paper rates can be predicted by the excess returns on the CRSP value weighted index. The findings from this study provide evidence that there is a link between equity market and commercial paper market.

Implications of Long-Run Risk for Asset Allocation Decisions

This paper proposes a structural approach to long-horizon asset allocation. In particular, the investor draws inferences about asset returns from a vector autoregression (VAR) with economic restrictions on the intercept, slope, and covariance matrix implied by the long-run risk model of Bansal and Yaron (2004). Comparing the optimal allocations of investors using the longrun risk VAR versus an unrestricted reduced-form VAR reveals stark differences in portfolio strategies. Long-run risk investors are quite conservative relative to reduced-form investors due to intertemporal hedging concerns. Despite the differing strategies, both investors achieve success in timing the market. The gains of the long-run risk investor appear to arise from his ability to avoid exposure to large negative events, while the reduced-form investor better capitalizes on periods of high average returns.

Taxes And Economic Growth In Romania. A Var Approach

The paper analyzes the relationship between taxes and economic growth in the case of Romania in the period January 1999 - March 2010, using an unrestricted Vector Autoregression Model (VAR) based on the rate of dynamic taxation's level and the rate of dynamic economic growth. The relationship is questioned in both directions, namely with reference to the manner in which taxes affect economic growth, but also in terms of the influence that economic growth exerts on taxes in the case of Romania for the mentioned period. The results show that tax policy in Romania cannot be taken to extremes, and should be very carefully implemented because a large amount of factors can influence the results

How to manage the relationship between democracy and economic development in Nigeria

The paper analyzes empirically, in Nigeria’s case, the biunivoque relationship between democratization and economic development. The analysis is based on the construction of an Unrestricted Vector Autoregressive Model (Unrestricted VAR), in the matrix form. For a better control of the results, regarding governance’s factors, we have introduced a third variable: The political regime durability. The results show us that, for Nigeria’s case, to ensure a higher level of economic development, the political regime must be democratic and the durability of the political regime reasonable. On the other hand, only high economic development, with very low political regime durability, can ensure a solid democracy. Otherwise, there is a very sensitive relationship between democracy, development and the political regime durability. Key words: Democracy, regime durability, development, VAR analysis, impulse functions.

Examining tourism-led growth hypothesis for India

The impact of international tourism on a country’s economic growth has attracted a great deal of attention among economists and policy makers. This study probes tourism-led growth (TLG) hypothesis for India employing bounds test and Johansen approaches of cointegration using annual data for the time span from 1980 to 2006 in a multivariate framework. Empirical results reveal the absence of a long-term equilibrium relationship between international tourist arrivals and economic activity in India. It also fails to establish any short-run relationship between international tourist arrivals and economic growth in an unrestricted vector autoregression framework. Thus, this study rejects TLG hypothesis for India.

Market Integration and Price Causality in the Myanmar Rice Market

In Myanmar, rice is an invaluable commodity both as a staple food and a source of high foreign exchange earnings through export. The country's agricultural economy has been transitioning from a planned economy to a market system since the late 1980s; however, the government has yet to engage in full-scale rice export deregulation. Therefore, Myanmar's rice marketing system works within the boundaries and limitations of a halfway-liberalized economy, inevitably eliciting questions about its performance. Using the Engle and Granger two-step co-integration method and the restructured Ravallion model of unrestricted vector auto-regression (VAR) error correction form, three surplus markets, three deficit markets, and Thai rice price series were tested to determine market integration and price causality. All price series were monthly data in both nominal and real values from 2001 to 2004. Results revealed that in the domestic market, integration was weak in real value of rice price, and the supply side eventually depended on the demand side. Price co-integration did not exist between Myanmar and Thai rice prices in real value, reflecting market segmentation. Consequently, accurate price information from international rice market price over time was unavailable for Myanmar rice price movement. Looking at the direction of rice price causality, deficit market prices were driving the consumer price index (CPI), and the CPI was forcing the surplus rice market price. Hence, deficit markets are the prime movers in rice price changes in Myanmar. Market integration suggests that the government should focus on managing inflationary pressure instead of being directly involved in the rice marketing sector in order to control the domestic rice price stability in the long run. Government monopoly in rice export has caused segmentation between domestic and international markets. If private rice export was permitted via trade policies, the marketing system would be able to transfer correct price signals from the world market to the producers, consumers, market participants, and finally, the government. Only then will Myanmar's rice market not be isolated from the international market and get the right price co-integration that may push the efficient market-oriented economy to move faster.

Optimal monetary policy using an unrestricted VAR

SUMMARYThis paper proposes a simple benchmark for monetary policy. Assuming the true model of the economy is unknown, it is based on an unrestricted vector autoregression (VAR). The key result is that instead of deriving optimal policy using the original VAR equations as the constraint, when no restriction is placed on the correlation structure of the VAR disturbances, the constraint should be formed from a transformation of the VAR. This method is applied to the USA, 1964–2009. Significant welfare gains are found compared with actual policy and using a Taylor rule. Incorporating a zero interest rate lower bound lowers output and inflation. Copyright © 2010 John Wiley & Sons, Ltd.

Simulation-based tests of forward-looking models under VAR learning dynamics

In this paper we propose a simulation-based technique to investigate the finite sample performance of likelihood ratio (LR) tests for the nonlinear restrictions that arise when a class of forward-looking (FL) models typically used in monetary policy analysis is evaluated with vector autoregressive (VAR) models. We consider ‘one-shot’ tests to evaluate the FL model under the rational expectations hypothesis and sequences of tests obtained under the adaptive learning hypothesis. The analysis is based on a comparison between the unrestricted and restricted VAR likelihoods, and the p-values associated with the LR test statistics are computed by Monte Carlo simulation. We also address the case where the variables of the FL model can be approximated as non-stationary cointegrated processes. Application to the ‘hybrid’ New Keynesian Phillips Curve (NKPC) in the euro area shows that (i) the forward-looking component of inflation dynamics is much larger than the backward-looking component and (ii) the sequence of restrictions implied by the cointegrated NKPC under learning dynamics is not rejected over the monitoring period 1984–2005. Copyright © 2010 John Wiley & Sons, Ltd.

Inflation Targeting in Brazil, Chile and South Africa: An Empirical Investigation of Their Monetary Policy Framework

This paper tackles the monetary policy performance in Brazil, Chile and South Africa under inflation targeting framework. Furthermore, it provides an empirical assessment through using the unrestricted Vector Auto-regression (VAR) and Structural Vector Auto-regression (SVAR) approaches depending on data spans the period from the first quarter of 1970 to the fourth quarter of 2007. On the other hand, it utilizes the Likelihood Ratio (LR) Statistic to test for possible structural changes due to the adoption of inflation targeting regime in those countries. The main findings are as follows: inflation targeting does make a difference in the performance of monetary policy in those countries. Furthermore, the experience of Brazil, Chile and South Africa provides important lessons for other emerging market economies to adopt such a framework.

SPATIAL BAYESIAN METHODS OF FORECASTING HOUSE PRICES IN SIX METROPOLITAN AREAS OF SOUTH AFRICA

AbstractThis paper estimates Spatial Bayesian Vector Autoregressive (SBVAR) models, based on the First‐Order Spatial Contiguity and the Random Walk Averaging priors, for six metropolitan areas of South Africa, using monthly data over the period of 1993:07 to 2005:06. We then forecast one‐ to six‐months‐ahead house prices over the forecast horizon of 2005:07 to 2007:06. When we compare forecasts generated from the SBVARs with those from an unrestricted Vector Autoregressive (VAR) and the Bayesian Vector Autoregressive (BVAR) models based on the Minnesota prior, we find that the spatial models tend to outperform the other models for large middle‐segment houses; while the VAR and the BVAR models tend to produce lower average out‐of‐sample forecast errors for middle and small‐middle segment houses, respectively. In addition, based on the priors used to estimate the Bayesian models, our results also suggest that prices tend to converge for both large‐ and middle‐sized houses, but no such evidence could be obtained for the small‐sized houses.

No-Arbitrage Restrictions and Yield Curve Forecasting

This paper proposes to use No-Arbitrage Affine Term Structure Models as prior information on a Vector Autoregression (VAR) of yields. We evaluate the forecasting performance of the proposed approach against alternative models such as an unrestricted VAR and a Random Walk. As a result, we show that using No-Arbitrage restrictions leads to significant improvements in forecasting the yield curve.