Forecasting macro variables with a Qual VAR business cycle turning point index

One criticism of Vector Autoregression (VAR) forecasting is that macroeconomic variables tend not to behave as linear functions of their own past around business cycle turning points. A large amount of literature therefore focuses on nonlinear forecasting models, such as Markov switching models, which only indirectly capture the relation with turning points. This article investigates a direct approach to using information on turning points from the National Bureau of Economic Research (NBER) chronology to model and forecast macroeconomic data. Our Qual VAR model includes a truncated normal latent business cycle index that is negative during NBER recessions and positive during expansions. We motivate our forecasting exercise by demonstrating that if starting from a linear specification, a truncated normal variable is an omitted variable, then forecasts of the remaining variables will become nonlinear functions of their own past. We apply the Qual VAR model to recursive out-of-sample forecasting and find that the Qual VAR improves on out-of-sample forecasts from a standard VAR.     

Bootstrapping Smooth Functions of Slope Parameters and Innovation Variances in VAR(∞) Models*

It is common to conduct bootstrap inference in vector autoregressive (VAR) models based on the assumption that the underlying data‐generating process is of finite‐lag order. This assumption is implausible in practice. We establish the asymptotic validity of the residual‐based bootstrap method for smooth functions of VAR slope parameters and innovation variances under the alternative assumption that a sequence of finite‐lag order VAR models is fitted to data generated by a VAR process of possibly infinite order. This class of statistics includes measures of predictability and orthogonalized impulse responses and variance decompositions. Our approach provides an alternative to the use of the asymptotic normal approximation and can be used even in the absence of closed‐form solutions for the variance of the estimator. We illustrate the practical relevance of our findings for applied work, including the evaluation of macroeconomic models.     

Putting the present value model into practice: a comparison of two alternative approaches

A key issue around putting the present-value model into practice is how to construct the unobserved future expectations of the fundamental variables related to an asset. One approach is to fit a vector autoregression (VAR) for the fundamental variables and deduce their future expectations from the estimated VAR. An alternative is to directly specify the future expectations as unobserved components (UC) and use the Kalman filter to extract their estimates from the realized data. This article examines whether the predictions of the present-value model are consistent across the two approaches. Constructing the VAR and UC versions of the standard present-value model, we examine how the two versions compare in identifying the main driver of the US and UK housing markets. For the UK, the two approaches consistently attribute most variations in the price–rent ratio to the expected future risk premium for housing investment. For the US, however, the two approaches deliver considerably different results: the VAR version marks the expected risk-free rate of return, whereas the UC version singles out the expected risk premium as the main driver of the ratio. We conclude that the choice between the VAR and UC approaches is not a trivial issue related to utilizing the present-value model.     

Unemployment and inflation persistence in Spain: Are there Phillips trade-offs?

This paper studies the dynamic behavior of inflation and unemployment in Spain during the period 1964–1997. In particular, we analyze the implications of high persistence in both unemployment and inflation dynamics for inference regarding the size of Phillips trade-offs and sacrifice ratios in the Spanish economy, in response to a demand shock. To do so we use a Stuctural VAR approach with several identification outlines which give rise to alternative interpretations of the joint unemployment-inflation dynamics. When using a bivariate VAR we cannot reject the existence of a permanent output loss of one-half of one percentage point for each percentage point of permanent disinflation. However, when the VAR is augmented with a third variable, in order to disentangle monetary from non-monetary shocks within the demand class, the evidence favours a lower and marginally permanent trade-off with an output loss of about one-fourth of one percentage point.     

Asymmetric and Time‐Varying Causality between Inflation and Inflation Uncertainty in G‐7 Countries

We use Granger causality tests within a conditional Gaussian Markov switching vector autoregressive (MS‐VAR) model using monthly data for G‐7 countries covering the period 1959:12–2008:10 to examine the relationship between inflation and inflation‐uncertainty. The MS‐VAR model allows us to model parameter time‐variation so as to reflect changes in Granger causality, assuming that these changes are stochastic and governed by an unobservable Markov chain. Inflation uncertainty is measured as the conditional variance generated by a Fractionally Integrated Smooth Transition Autoregressive Moving Average‐Asymmetric Power ARCH (FISTARMA‐APARCH) model. The distinguishing feature of our approach from the previous studies is the determination of the sign of the Granger causality relationship between inflation and its uncertainty over time. First, using a rolling VAR model, we show that the relationship between inflation and inflation uncertainty is time varying with frequent breaks. Second, using the MS‐VAR model, we obtain strong evidence in favour of the Holland's ‘stabilizing Fed hypothesis’ for Canada, France, Germany, Japan, United Kingdom, and the United States. We also find evidence in favour of the Friedman hypothesis for Canada and the United States.     

A copula-VAR-X approach for industrial production modelling and forecasting

World economies, and especially European ones, have become strongly interconnected in the last decade and a joint modelling is required. We propose here the use of copulae to build flexible multivariate distributions, since they allow for a rich dependence structure and more flexible marginal distributions that better fit the features of empirical data, such as leptokurtosis. We use our approach to forecast industrial production series in the core European Monetary Union (EMU) countries and we provide evidence that the copula-Vector Autoregression (VAR) model outperforms or at worst compares similarly to normal VAR models, keeping the same computational tractability of the latter approach.     

How similar are alcohol drinkers? International evidence

Using a Vector Autoregression (VAR) approach, several hypotheses are re-examined suggested by the literature concerning the relationship between financial development and economic growth, investment and productivity. The models use quarterly time-series data from ten OECD countries and China. Innovation accounting or variance decomposition and impulse response function analysis is applied to examine interrelationships between variables in the VAR system and, therefore, differs from the more usual Granger causality approach. In particular, it examines the relationship between financial development proxied by total credit. At best, weak support is found for the hypothesis that financial development ‘leads' economic growth.     

Time varying structural VARs with sign restrictions: The case of Taiwan

I apply a Bayesian approach to a time-varying structural vector autoregression model with stochastic volatility (TVP-SVAR-SV) to study the time-varying nature of the Taiwanese economy. In particular, the structural parameters are identified via the sign information in a three-variable VAR system. The estimated results show that TVP-SVAR-SV model has the best fit to the data, compared to the time-varying parameters VAR model with constant volatility and a classical VAR model with constant parameters and volatilities. Moreover, I find the time-varying contemporaneous relationship between the output growth and inflation rates, particularly significant before the year 2000. Lastly, the impulse responses and the volatilities of all the variables are found to be time-varying.     

Causality in EU macroeconomic variables

This article investigates the interdependence of macroeconomics, financial and other variables for European Union countries using a multivariate vector autoregressive (VAR) approach for quarterly data. The VAR analysis is applied to all bivariate cases, and the best fitted models are selected in order to conduct Granger causality testing and impulse response functions. Contrary to the existing literature, this study reveals evidence of a unilateral direction between several cases and ambiguous results regarding Impulse response functions analysis.     

Specification via model selection in vector error correction models

This paper proposes a model selection approach for the specification of the cointegrating rank in the VECM representation of VAR models. Asymptotic properties of estimates are derived and their features compared with the traditional likelihood ratio based approach.     

Financial Development and Economic Growth: An Egg‐and‐Chicken Problem?

This study uses a Granger causality procedure to investigate the relationship between financial development and economic growth. The authors estimate a vector autoregression (VAR) model for nine OECD countries and China. They argue that a time-series approach is superior to a cross-sectional one and that the VAR framework avoids technical problems common in other time-series models. Evidence is presented of bidirectional causality between financial development and growth in half of the countries and reverse causality in three others. There is little support for the hypothesis that finance "leads" growth, and caution must be exercised in making general conclusions about this relationship.     

Does the vector error correction model perform better than others in forecasting stock price? An application of residual income valuation theory

This paper employs a multi-equation model approach to consider three statistic problems (heteroskedasticity, endogeneity and persistency), which are sources of bias and inefficiency in the predictive regression models. This paper applied the residual income valuation model (RIM) proposed by Ohlson (1995) to forecast stock prices for Taiwan three sectors. We compare relative forecasting accuracy of vector error correction model (VECM) with the vector autoregressive model (VAR) as well as OLS and RW models used in the prior studies. We conduct out-of-sample forecasting and employ two instruments to assess forecasting performance. Our empirical results suggest that the VECM statistically outperforms other three models in forecasting stock prices. When forecasting horizons extend longer, VECM produces smaller forecasting errors and performs substantially better than VAR, suggesting that the ability of VECM to improve VAR forecast accuracy is stronger with longer horizons. These findings imply that an error correction term (ECT) of the VECM contributes to improving forecast accuracy of stock prices. Our economic significance analyses and robustness tests for different data frequency are in favor of the superiority of VECM estimator.     

The forecasting ability of a cointegrated VAR system of the UK tourism demand for France, Spain and Portugal

This paper uses the vector autoregressive (VAR) methodology as an alternative to Deaton and Muellbauer’s Almost Ideal Demand System (AIDS), to establish the long-run relationships between I(1) variables: tourism shares, tourism prices and UK tourism budget. With appropriate testing, the deterministic components and sets of exogenous and endogenous variables of the VAR are established, and Johansen’s rank test is used to determine the number of cointegrated vectors in the system. The cointegrated VAR structural form is identified and the long-run structural parameters are estimated. Theoretical restrictions such as homogeneity and symmetry are tested and not rejected by the VAR structure. The fully restricted cointegrated VAR model reveals itself a theoretically consistent and statistically robust means to analyse the long-run demand behaviour of UK tourists, and an accurate multi-step forecaster of the destinations’ shares when compared with unrestricted reduced form and first differenced VARs, or even with the structural AIDS model.     

How have inflation-targeting central banks responded to supply shocks?

This paper examines how inflation-targeting central banks have responded to supply shocks, based on the sign-restriction VAR approach. It is found that inflation-targeting central banks have become accommodative to adverse supply shocks following the adoption of inflation targeting.     

The Effects of Monetary Policy Shocks in the USA: A Forecast‐Augmented VAR Approach

This paper formulates a forward‐looking monetary policy function for the USA in a structural vector autoregression (VAR) model, by using forecasts of key macroeconomic variables, in addition to the ex post realised variables used in a standard VAR. Since this forecast‐augmented VAR (FOAVAR) uses both forecasted and realised variables, and the standard VAR uses only realised variables, the standard VAR is nested in the FOAVAR. I find that the Fed responds to forecasted macroeconomic variables more significantly than realised variables. I also find that the monetary policy shock in the FOAVAR generates impulse responses of variables that are consistent with the predictions of economic theories, while the policy shock in the standard VAR causes a price puzzle: an increase in the price level due to a contractionary policy shock. These results suggest that a monetary policy function identified in a standard VAR, by using only realised macroeconomic variables, may incorrectly represent the Fed's policy function.     

财政政策对产业结构动态冲击效应的实证分析

本文运用向量自回归（VAR）模型,通过残差分析、脉冲响应分析和方差分解分析,研究我国财政政策对传统产业、新兴产业和落后产业的动态冲击影响。主要结论是：财政政策包括收入和支出政策对新兴产业的影响比较显著,且是中长期有效的;财政政策中的支出政策对传统产业和落后产业的影响都比较显著,也是中长期有效的,而财政收入政策对其影响较弱。     

Monetary Policy and Financial Stability: The Role of Inflation Targeting

This article examines the relationship between Inflation targeting (IT) and financial instability from 1990 to 2015 for Asian economies. To measure financial instability, a multidimensional financial conditioning index is calculated following the ECB's approach. Using a fixed effects panel data model the study finds that adoption of IT policy in Asian economies has an adverse impact on financial stability, thus rejecting the ‘conventional wisdom’ hypothesis. Further, the Vector Autoregression (VAR) result shows that an IT regime increases housing returns and encourages investors to take higher risks.     

Systemic risk contagion in FX market: A frequency connectedness and network analysis

In this study, we analyse systemic risk contagion between a set of most actively traded currencies (EURO, JPY, GBP, AUD, CAD and CHF) by application of VAR based frequency connectedness proposed by Baruník and K?ehlík. By using this novel approach, we gauge foreign exchange (FX) market connectedness in 200‐day frequency band using spectral representation of variance decompositions of VAR and identify directional spillovers between the most actively traded foreign exchange rates. Dynamics of the overall spillover index reveals that the index capture well‐known financial stress incidents properly. Finally, network topology of directional spillovers between currency pairs is provided for visulalization interconnectedness between them.     

The Relative Dynamics of Investment and the Current Account in the G7-Economies

This paper contributes to the empirics of the intertemporal approach to the current account. We use a cointegrated VAR framework to identify permanent and transitory components of country-specific and global shocks. Our approach allows us to investigate empirically the sensitivity to persistence implied by many forward-looking models and our results shed new light on the excess volatility of investment encountered by Glick and Rogoff (1995). In G7 data, we find the relative current-account and investment response to be in line with the intertemporal approach.