Codependent cycles

This paper extends the work of Engle and Kozicki (1993) to test for co-movement in multiple time series when their cycles are not exactly synchronized. We call these codependent cycles and show that testing and estimation in this case will be a Generalized Method of Moments test and estimation procedure. We also show that the Tiao and Tsay (1985) proposed test for scalar components models of order (0, q) can be seen as a test for codependent cycles based on a consistent, but sub-optimal, estimate of the cofeature vector. We assess the small sample performance of the proposed tests through a series of simulations. Finally we apply this test to investigate comovement between durable and non-durable consumption expenditures.     

Hours per capita and productivity: evidence from correlated unobserved components models

Recent studies debate the effect of a permanent productivity shock on hours per capita within a structural VAR context. This paper examines the issue using a correlated unobserved components (UC) framework. The estimates show that permanent shocks to productivity are negatively correlated with transitory shocks to hours. This result is robust for non‐stationary or levels stationary specifications of hours. Model comparisons indicate that the data do not favor imposing VAR‐type restrictions on the UC models. Copyright © 2008 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.     

Detecting Co‐Movements in Non‐Causal Time Series

This paper introduces the notion of common non‐causal features and proposes tools to detect them in multivariate time series models. We argue that the existence of co‐movements might not be detected using the conventional stationary vector autoregressive (VAR) model as the common dynamics are present in the non‐causal (i.e. forward‐looking) component of the series. We show that the presence of a reduced rank structure allows to identify purely causal and non‐causal VAR processes of order P>1 even in the Gaussian likelihood framework. Hence, usual test statistics and canonical correlation analysis can be applied, where either lags or leads are used as instruments to determine whether the common features are present in either the backward‐ or forward‐looking dynamics of the series. The proposed definitions of co‐movements are also valid for the mixed causal—non‐causal VAR, with the exception that a non‐Gaussian maximum likelihood estimator is necessary. This means however that one loses the benefits of the simple tools proposed. An empirical analysis on Brent and West Texas Intermediate oil prices illustrates the findings. No short run co‐movements are found in a conventional causal VAR, but they are detected when considering a purely non‐causal VAR.     

On the cointegration of international stock indices

This paper investigates the cointegration relationship among a group of international stock indices in light of new developments of econometric methods. Kasa (1992) first documented strong evidence for cointegration relations among five national stock indices, which suggests that there exists a common trend among those stock indices. Using Johansen multivariate cointegration test, we find that his findings are persistent in a sample of longer periods and more countries. In order to investigate whether these results are driven by statistical biases related to the sample size, we apply to our tests the Johansen’s small sample correction factor. The results still point toward the existence of a cointegration relationship but the evidence becomes much weaker. We next examine the empirical patterns emerged from different lag specifications and argue that Kasa’s findings are more likely due to the size distortion in extreme long lag VAR models. Indeed, when we employ a newly developed non-parametric test that does not require estimation VAR models, the null hypothesis of no cointegration cannot be rejected for the original sample of Kasa’s five-country stock indices from 1974 to 1990, nor for the extended period from 1970 to 2003.     

STRUCTURAL VECTOR AUTOREGRESSIONS: CHECKING IDENTIFYING LONG‐RUN RESTRICTIONS VIA HETEROSKEDASTICITY

Long‐run restrictions have been used extensively for identifying structural shocks in vector autoregressive (VAR) analysis. Such restrictions are typically just‐identifying but can be checked by utilizing changes in volatility. This paper reviews and contrasts the volatility models that have been used for this purpose. Three main approaches have been used, exogenously generated changes in the unconditional residual covariance matrix, changing volatility modelled by a Markov switching mechanism and multivariate generalized autoregressive conditional heteroskedasticity models. Using changes in volatility for checking long‐run identifying restrictions in structural VAR analysis is illustrated by reconsidering models for identifying fundamental components of stock prices.     

Cointegration and joint efficiency of international commodity markets

This paper investigates the semi-strong efficiency hypothesis in the international commodity markets of four industrialized countries, using vector autoregression (VAR) and cointegration techniques. Efficiency in these markets requires the corresponding real exchange rates to be martingales with respect to any information set available in the public domain. In the context of a VAR consisting only of real exchange rates, we show that necessary and sufficient conditions for joint efficiency of all the markets under consideration amount to the VAR being of order one (Markovness) and non-cointegrated. On the contrary, in a VAR extended by other potentially “relevant” variables, such as the corresponding real interest rates, non-cointegration and Markovness are only sufficient conditions for the same commodity markets to be characterized as jointly efficient. We also suggest methods for efficiency testing in each individual market within a cointegrated VAR and, finally, we discuss possible long-run linkages among the real exchange rates and real interest rates in association with efficiency in the commodity markets. JEL Classification Number: F31     

Structural break threshold VARs for predicting US recessions using the spread

This paper proposes a model to predict recessions that accounts for non‐linearity and a structural break when the spread between long‐ and short‐term interest rates is the leading indicator. Estimation and model selection procedures allow us to estimate and identify time‐varying non‐linearity in a VAR. The structural break threshold VAR (SBTVAR) predicts better the timing of recessions than models with constant threshold or with only a break. Using real‐time data, the SBTVAR with spread as leading indicator is able to anticipate correctly the timing of the 2001 recession. Copyright © 2006 John Wiley & Sons, Ltd.     

增加值率能否反映经济增长质量?

研究目标：回答增加值率能否反映经济增长质量的问题。研究方法：通过建立CES型总产出生产函数和动态经济系统,从理论上提出增加值率门槛上限,并实证检验了中国增加值率的国际比较及省际比较。研究发现：增加值率存在着一个门槛上限,当低于该值时,实际增加值率越高表示增长质量越好,而超出时则完全相反;实际增加值率与门槛上限之间存在着长期的协整关系,且与全要素生产率之间存在着倒U形关系;增加值率门槛上限与资本折旧率、人口增长率和储蓄率等宏观经济指标相关。研究创新：采用增加值率评价经济增长质量,应该考虑增加值率门槛上限。研究价值：有助于《工业转型升级规划(2011~2015年)》和《中国制造2025》中以增加值率评价质量效益工作合理实施。     

On the computational competitiveness of full-information maximum-likelihood and three-stage least-squares in the estimation of nonlinear,simultaneous-equations models

While full-information maximum-likehood (FIML) estimation has long been considered an important theoretical econometric estimation technique, computational considerations have greatly restricted its use in practice. Recent advances in numerical analysis and in computational software, however, have combined to provide algorithms capable of carrying out the FIML calculations quite efficiently relative to past standards. This paper compares the computational competitiveness of FIML with its most popular competitor, 3SLS, in the estimation of a variety of linear and non-linear (in parameters and variables) models. The nonlinear full-information maximum-likelihood (NLFIML) estimator is described and a computatíonally efficient approximation, TRUNFIML, is defined. Nonlinear three-stage least-squares (NL3SLS) is accomplished by the method of Jorgenson-Laffont. Comparisons are made on the basis of numbers of iterations to convergence, number of function evaluations, and total computer CPU time required, this latter figure being most relevant to a comparison of computational effort and cost.     

In Search of the Transmission Mechanism of Fiscal Policy in the Euro Area

This paper applies the DSGE‐VAR methodology to assess the size of fiscal multipliers in the data and the relative contributions of two transmission mechanisms of government spending shocks, namely hand‐to‐mouth consumers and Edgeworth complementarity. Econometric experiments show that a DSGE model with Edgeworth complementarity is a better representation of the transmission mechanism of fiscal policy as it yields dynamic responses close to those obtained with the flexible DSGE‐VAR model (i.e. an impact output multiplier larger than one and a crowding‐in of private consumption). The estimated share of hand‐to‐mouth consumers is too small to replicate the positive response of private consumption. Copyright © 2016 John Wiley & Sons, Ltd.     

Sources of real exchange rate movements in Saudi Arabia

The paper investigates the sources of real exchange rate movements in Saudi Arabia by decomposing real exchange rate movements into those attributable to real and nominal shocks. Using a popular structural VAR model and assuming long-run neutrality of nominal shocks, we find that real shocks play a significant role in explaining real exchange rate movements in Saudi Arabia. Using a more disaggregated model, we also find that oil production shocks rather than real oil price shocks are responsible for real exchange rate movements. In order to stabilize the real exchange rate, Saudi Arabia should focus on stabilizing oil production.(JEL F3, C5)     

The non‐linear dynamics of output and unemployment in the U.S.

This paper studies the joint dynamics of U.S. output and unemployment rate in a non‐linear VAR model. The non‐linearity is introduced through a feedback variable that endogenously augments the output lags of the VAR in recessionary phases. Sufficient conditions for the ergodicity of the model, potentially applying to a larger class of threshold models, are provided. The linear specification is rejected in favour of our threshold VAR. However, in the estimation the feedback is found to be statistically significant only on unemployment, while it transmits to output through its cross‐correlation. This feedback effect from recessions generates important asymmetries in the propagation of shocks, a possible key to interpret the divergence in the measures of persistence in the literature. The regime‐dependent persistence also explains the finding that the feedback from recession exerts a positive effect on the long‐run growth rate of the economy, an empirical validation of the Schumpeterian macroeconomic theories. Copyright © 2001 John Wiley & Sons, Ltd.     

Stock returns and economic activity in mature and emerging markets

This paper empirically investigates the dynamic interdependencies between stock returns and economic activity in mature and emerging markets. The existence, kind and strength of potential uni-directional and/or bi-directional relations are examined, running from stock returns to future economic activity and/or from economic activity to future stock returns. A bivariate VAR(12) model is applied and Granger causality tests are performed. Monthly data covering the January 1991–December 2006 period are used. The existence of an empirical relationship, with forecasting ability, between stock returns and future economic activity is confirmed. The results are strongly differentiated between mature and emerging markets.     

Subsampling vector autoregressive tests of linear constraints

This paper studies subsampling VAR tests of linear constraints as a way of finding approximations of their finite sample distributions that are valid regardless of the stochastic nature of the data generating processes for the tests. In computing the VAR tests with subsamples (i.e., blocks of consecutive time series), both the tests of the original form and the tests with the subsample OLS coefficient estimates centered at the full-sample estimates are used. Subsampling using the latter is called centered subsampling in this paper. It is shown that the subsamplings provide asymptotic distributions that are equivalent to the asymptotic distributions of the VAR tests. In addition, the tests using critical values from the subsamplings are shown to be consistent. The subsampling methods are applied to testing for causality. To choose the block sizes for subsample causality tests, the minimum volatility method, a new simulation-based calibration rule and a bootstrap-based calibration rule are used. Simulation results in this paper indicate that the centered subsampling using the simulation-based calibration rule for the block size is quite promising. It delivers stable empirical size and reasonably high-powered causality tests. Moreover, when the causality test has a chi-square distribution in the limit, the test using critical values from the centered subsampling has better size properties than the one using chi-square critical values. The centered subsampling using the bootstrap-based calibration rule for the block size also works well, but it is slightly inferior to that using the simulation-based calibration rule.     

CO‐INTEGRATING VAR MODELS AND ECONOMIC POLICY

This paper surveys some relevant contributions to the economic literature on co‐integrating vector autoregressive (VAR) models [vector error correction mechanisms (VECMs)], emphasizing their usefulness for economic policy. It further discusses some theoretical aspects that are necessary for a complete understanding of their potential. The theoretical introduction of the co‐integrating VAR model is followed by an illustration of its applications to monetary policy, fiscal policy and exchanges rates as well as in establishing the effects of structural bilateral shocks between countries (the so‐called global VAR, or GVAR, models). Special attention is paid to the VECM capacities of being used in conjunction with dynamic stochastic general equilibrium models and of jointly specifying the short‐ and long‐run dynamics, thus representing the steady‐state of economic systems (by means of the co‐integration relations) and the short‐run dynamics around it.     

Bayesian Graphical Models for STructural Vector Autoregressive Processes

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 multivariate 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. Copyright © 2015 John Wiley & Sons, Ltd.     

A Reconciliation of Some Paradoxical Empirical Results on the Expectations Model of the Term Structure

In this paper we attempt to reconcile contradictory empirical results for the expectations model of the term structure which are found when it is tested by a variety of methods based on single-equation and VAR models. Using monthly data for one-month and three-month interest rates, we show that the expectations hypothesis is rejected for the US and UK term structures on the basis of some popular tests. However, tests based on VAR models or on IV regressions of yield spreads on future short rate changes provide no evidence against the expectations model with a random component in the term premium.     

Steady‐state priors for vector autoregressions

Bayesian priors are often used to restrain the otherwise highly over‐parametrized vector autoregressive (VAR) models. The currently available Bayesian VAR methodology does not allow the user to specify prior beliefs about the unconditional mean, or steady state, of the system. This is unfortunate as the steady state is something that economists usually claim to know relatively well. This paper develops easily implemented methods for analyzing both stationary and cointegrated VARs, in reduced or structural form, with an informative prior on the steady state. We document that prior information on the steady state leads to substantial gains in forecasting accuracy on Swedish macro data. A second example illustrates the use of informative steady‐state priors in a cointegration model of the consumption‐wealth relationship in the USA. Copyright © 2009 John Wiley & Sons, Ltd.