Bayesian inference in a time varying cointegration model

There are both theoretical and empirical reasons for believing that the parameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper, we develop a new time varying parameter model which permits cointegration. We use a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP–VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving the Fisher effect.     

Two-stage non Gaussian QML estimation of GARCH models and testing the efficiency of the Gaussian QMLE

In generalized autoregressive conditional heteroskedastic (GARCH) models, the standard identifiability assumption that the variance of the iid process is equal to 1 can be replaced by an alternative moment assumption. We show that, for estimating the original specification based on the standard identifiability assumption, efficiency gains can be expected from using a quasi-maximum likelihood (QML) estimator based on a non Gaussian density and a reparameterization based on an alternative identifiability assumption. A test allowing to determine whether a reparameterization is needed, that is, whether the more efficient QMLE is obtained with a non Gaussian density, is proposed.     

Volatility contagion: A range-based volatility approach

This article proposes a new approach to evaluate volatility contagion in financial markets. A time-varying logarithmic conditional autoregressive range model with the lognormal distribution (TVLCARR) is proposed to capture the possible smooth transition in the range process. Additionally, a smooth transition copula function is employed to detect the volatility contagion between financial markets. The approach proposed is applied to the stock markets of the G7 countries to investigate the volatility contagion due to the subprime mortgage crisis. Empirical evidence shows that volatility is contagious from the US market to several markets examined.     

Independent component analysis for realized volatility: Analysis of the stock market crash of 2008

This paper investigates the factors that drove the U.S. equity market returns from 2007 to early 2010. The period was highlighted by volatile energy and commodity prices, the collapse of insurance and banking firms, extreme implied volatility and a subsequent rally in the overall market. To extract the driving factors, we decompose the returns of the S&P500 sector ETFs into statistically independent signals using independent component analysis. We find that the generated factors have interesting financial interpretations and are consistent with the major economic themes of the period. We find that there are two sets of general market betas during the period along with a dominant factor for energy and materials sector. In addition, we find that the EGARCH model which accommodates asymmetric responses between returns and volatility can plausibly fit the high levels of variance during the crash. Finally, estimated correlations dropped when commodity prices moved higher, but then spiked when the S&P500 crashed in late 2008.     

Foreign and domestic growth drivers in Eastern Europe

This paper analyses the growth effects of capital formation, exports and FDI as major, drivers of economic development in Eastern Europe. The fundamental innovations are, identified by empirically and theoretically motivated short- and long-run restrictions in, structural cointegrated vector autoregressions. Impulse responses and variance, decompositions reveal quite different growth effects in various Eastern European countries. Generally, a strong reliance on exports goes along with higher GDP, and FDI bears, substantial potential for fostering economic growth. It is shown that the recent worldwide, recession clearly hit Eastern Europe through the export channel, whereas the recovery is, mainly supported by positive demand shocks.     

Should the government directly intervene in stock market during a crisis?

Unlike foreign exchange markets where central banks frequently intervene, the governments strive not to intervene in the stock markets since intervention transmit negative signals and carry market-related side effects. The main reasons often cited in support of intervention are to bring price stability and to restore investors’ confidence. During the recent economic turmoil, opportunities for the governments to intervene in the stock markets were mainly exploited in emerging and developing countries. We study the outcome of the Russian government's intervention in its major stock market between September and October 2008. This intervention was intended to reverse the sudden and swift declining trend in traded security prices by altering the market's expectations. By using a combination of event study and a multivariate GARCH model, our findings does not support direct government intervention in the stock market during a crisis.     

A Wald test for the cointegration rank in nonstationary fractional systems

This paper develops new methods for determining the cointegration rank in a nonstationary fractionally integrated system, extending univariate optimal methods for testing the degree of integration. We propose a simple Wald test based on the singular value decomposition of the unrestricted estimate of the long run multiplier matrix. When the “strength” of the cointegrating relationship is less than 1/2, the test statistic has a standard asymptotic distribution, like Lagrange Multiplier tests exploiting local properties. We consider the behavior of our test under estimation of short run parameters and local alternatives. We compare our procedure with other cointegration tests based on different principles and find that the new method has better properties in a range of situations by using information on the alternative obtained through a preliminary estimate of the cointegration strength.     

Particle filters for continuous likelihood evaluation and maximisation

In this paper, a method is introduced for approximating the likelihood for the unknown parameters of a state space model. The approximation converges to the true likelihood as the simulation size goes to infinity. In addition, the approximating likelihood is continuous as a function of the unknown parameters under rather general conditions. The approach advocated is fast and robust, and it avoids many of the pitfalls associated with current techniques based upon importance sampling. We assess the performance of the method by considering a linear state space model, comparing the results with the Kalman filter, which delivers the true likelihood. We also apply the method to a non-Gaussian state space model, the stochastic volatility model, finding that the approach is efficient and effective. Applications to continuous time finance models and latent panel data models are considered. Two different multivariate approaches are proposed. The neoclassical growth model is considered as an application.     

Do house price developments spillover across euro area countries? Evidence from a global VAR

This paper empirically assesses the prospects for house price spillovers in the euro area, where co-movement in house prices across countries may be particularly relevant given a general trend with monetary union toward increasing linkages in trade, financial markets, and general economic conditions. A global VAR is estimated for three housing demand variables (real house prices, real per capita income, and the cost of borrowing, captured by a real long-term interest rate) on the basis of quarterly data for 7 euro area countries (Belgium, Germany, Ireland, Spain, France, Italy and the Netherlands), which together comprise nearly 90% of euro area GDP, over the period 1971–2009. The results suggest limited house price spillovers in the euro area, albeit with evidence of some overshooting in the first year after the shock, followed by a long run aggregate euro area impact of country-specific changes in real house prices related in part to the country’s economic weight. This contrasts with the impacts of a shock to domestic long-term interest rates, causing a permanent shift in house prices after 2–3 years. Underlying this aggregate development are rather heterogeneous house price spillovers at the country level, with a strong importance for weights – either economic or geographic – in governing their general magnitude. More generally, the impact of financing costs on house prices appears to have grown though time.     

Generalized method of moments (GMM) based inference with stratified samples when the aggregate shares are known

We show how to do efficient moment based inference using the generalized method of moments (GMM) when data is collected by stratified sampling and the maintained assumption is that the aggregate shares are known.     

Metonymy and cross-section demand

Cross-section consumer expenditure data are frequently used to draw conclusions about consumer demand behavior. Such conclusions, however, are justified only under certain assumptions, which are often left unstated in the empirical demand literature. An assumption of this type, the metonymy hypothesis, was stated rigorously and exploited by Härdle et al. when analyzing the monotonicity of aggregate demand functions. The purpose of the present paper is to examine the metonymy hypothesis in more detail. We prove that the distribution of demand vectors derived from a not necessarily metonymic population is identical with the distribution derived from some metonymic population. This implies, in particular, that the metonymy hypothesis cannot be rejected or confirmed on the basis of data from a single cross-section.     

Improved likelihood ratio tests for cointegration rank in the VAR model

We suggest improved tests for cointegration rank in the vector autoregressive (VAR) model and develop asymptotic distribution theory and local power results. The tests are (quasi-)likelihood ratio tests based on a Gaussian likelihood, but as usual the asymptotic results do not require normally distributed innovations. Our tests differ from existing tests in two respects. First, instead of basing our tests on the conditional (with respect to the initial observations) likelihood, we follow the recent unit root literature and base our tests on the full likelihood as in, e.g., Elliott et al. (1996). Second, our tests incorporate a “sign” restriction which generalizes the one-sided unit root test. We show that the asymptotic local power of the proposed tests dominates that of existing cointegration rank tests.     

Trade credit versus bank credit: Evidence from corporate inventory financing

In this study, I introduce capital market imperfections into a structure framework of inventory investments and investigate impacts of trade credit on firms’ inventory dynamics and analyze the relationship between trade credit and bank loans. As a result, firms end up using a mix of trade credit and bank loans. I find that the use of trade credit and bank credit can be either complements or substitutes. During tight monetary periods, trade credit operates mainly as a substitute for bank borrowing while during looser monetary episodes even when the economy is weak, trade credit and bank loans are dominated by a complementary effect.     

Restricted houseswapping games

Restricted houseswapping games (RHGs) are a generalization of ‘one-sided matching games’, in which we specify a class II* of ‘allowable’ simple trading cycles. The cores of such games may be empty. Given II*, all possible closed RHGs have non-empty cores of II* is ‘strongly balanced’. Examples include the one-sided matching markets (^{Shapley and Scarf. Journal of Mathematical Economics 1974. 1. 23–37}. ^{Tijs et al., OR Spektrum 1984, 6, 119–123}; ^{Quinzii, International Journal of Game Theory 1984, 13, 41–60}) and the two-sided matching markets (^{Gale and Shapley. American Mathematical Monthly 1962. 69, 9–16}; ^{Shapley and Shubik, International Journal of Game Theory 1972, 1, 111–130}: and ^{Demange and Gale Econometrica 1985, 53, 873–888}).We then consider the subclass of RHGs in which there is no transferable resource. In this case, a weaker condition on II*, called ‘weak balancedness’, is sufficient to guarantee core non-emptiness. In addition, if II* is not weakly balanced, then there exists a preference profile such that the strict core of the resultant game is empty.Several other examples are given of II* that are (a) strongly balanced: (b) weakly balanced but not strongly balanced: and (c) not even weakly balanced.Finally, we discuss the issues of equilibrium definition, existence, and core-equilibrium allocation equivalence in RHGs.     

Implementation in generalized matching problems

We search for (Nash) implementable solutions on a class of one-to-one matching problems which includes both the housing market (Shapley and Scarf, Journal of Mathematical Economics, 1974, 1, 23–28) and marriage problems (Gale and Shapley, American Mathematical Monthly, 1962, 69, 9–15). We show that the core correspondence is implementable. We show, furthermore, that any solution that is Pareto efficient, individually rational, and implementable is a supersolution of the core correspondence. That is, the core correspondence is the minimal solution that is Pareto efficient, individually rational, and implementable. A corollary of independent interest in the context of the housing market is that the core correspondence is the only single-valued solution that is Pareto efficient, individually rational, and implementable.