CEE Banking Sector Co-Movement: Contagion or Interdependence?

We study the evolution of global equity market integration using US dollar denominated iShares. Designed to mimic the movements of MSCI indices, these securities provide an easy pool of international diversification products for the investor. As such they allow us to conduct an analysis of the largest equity markets comovements devoid of problems associated with trading restrictions, exchange rates fluctuations and non-synchronous trading. In contrast to most of the previous studies, we apply time varying methodology for the analysis of both short-term and long-term comovements that provide detailed evidence on the pattern and dynamics of the equity market linkages. We find evidence in favour of increasing conditional correlations for all of the markets since 2001. Time-varying and recursive cointegration tests provide somewhat weak evidence in favour of the presence of bivariate cointegration relationships, but stronger evidence in the multivariate case, suggesting limited diversification opportunities for the U.S. based investor in the long run.Stock Market Integration, G7 Stock markets, Cointegration, GARCH

Re-assessing co-movements among G7 equity markets: evidence from iShares

iShares funds are products designed to mimic the movements of MSCI stock market indices. Being devoid of problems associated with trading restrictions, exchange-rate fluctuations and non-synchronous trading, iShares data are better suited for measuring, firstly, equity-market co-movements and, secondly, diversification potential than national indices data; the latter data are used by most of the studies in the area. Applying recent time-varying methodology for the analysis of short- and long-term co-movements, a detailed analysis of the dynamics of the equity market linkages over the period 1996-2005 is provided. Evidence is found of increasing conditional correlations and significant time-varying long-run relationships between the US and the majority of other G7 markets since 2001, as measured by iShares. However, the extent of both short-term and long-term linkages between the G7 equity markets is lower for national indices data. Our findings suggest that (i) the results of earlier studies that are based on stock market indices should be interpreted with caution, since using these may overestimate the extent of available diversification benefits; and (ii) iShares funds do not represent perfect diversification products. These results appear to be robust to alternative model specifications, data frequency and conditioning bias

Forecasting House Prices in the United States with Multiple Structural Breaks

The boom-bust cycle in U.S. house prices has been a fundamental determinant of the recent financial crisis leading up to the Great Recession. The risky financial innovations in the housing market prior to the recent crisis fueled the speculative housing boom. In this backdrop, the main objectives of this empirical study are to i) detect the possibility of multiple structural breaks in the US house price data during 1995-2010, exhibiting very sharp upturns and downturns; ii) endogenously determine the break points and iii) conduct house price forecasting exercises to see how models with structural breaks fare with competing time series models – linear and nonlinear. Using a very general methodology (Bai-Perron, 1998, 2003), we found four break points in the trend in the S&P/Case-Shiller 10 city aggregate house-price index series. Next, we compared the forecasting performance of the model with structural breaks to four competing models – namely, Random Acceleration (RA), Autoregressive Moving Average (ARMA), SelfExciting Threshold Autoregressive (SETAR), and Smooth Transition Autoregressive (STAR). Our findings suggest that house price series not only has undergone structural changes but also regime shifts. Hence, forecasting models that assume constant coefficients such as ARMA may not accurately capture house price dynamics

Asset markets, stochastic policy and international trade

The present study examines the role of financial markets for trade policy under conditions of uncertainty. It builds upon and extends an earlier work by Stockman and Dellas. Using a two country, two good stochastic general equilibrium model where both countries impose a combination of export and import tariffs and the agents trade in financial contracts to insure against policy risk, with the provision of spot trading in consumption goods, it is shown that: (i) the structure of commercial policy (i.e. import or export tariffs) matters, so that Lerner's symmetry theorem does not extend to a stochastic framework with asset markets; (ii) the Stockman-Dellas conclusions are sensitive to the choice of tariffs; (iii) in general, it is optimal to use both export and import tariffs in such a framework;The assumption of exogenous tariffs is relaxed next by making endowments random and by assuming tariffs are chosen optimally. The values of optimal policies are compared across states within any regime as well as across alternative policy regimes. The simulation results indicate that the expected welfare when both export and import tariffs are used is at least as high as that when only import tariffs are used. However, if commercial policy is restricted to import tariffs, the introduction of asset markets can be welfare-deteriorating, even though there remains potential gains from engaging in inter-state trade. Finally, the potential time consistency issues inherent in such a framework are addressed. The financial structure is found to play a crucial role in determining the time consistent policy ex post.</p

Equity market integration in Latin America: A time-varying integration score analysis

We develop a measure of market integration score by extending the methodology of Akdogan to reflect the degree of integration of domestic equity markets with other markets in and beyond the region. We empirically estimate the integration scores for a sample of six Latin American markets between January 1988 and December 2001. We find a trend towards increased regional integration relative to global integration until the mid-1990s. A distinct change in trend is noted during the second half of the 1990s, with global integration proceeding faster than regional integration

The Role of the Federal Reserve in the U.S. Housing Crisis: A VAR Analysis with Endogenous Structural Breaks

This paper reexamines the role of the Federal Reserve in triggering the recent housing crisis. Specifically, we explore if the relationship between the federal funds rate and the housing variables underwent structural changes in the wake of the housing crisis. Using quarterly data spanning 1960&ndash;2017, we estimate a VAR model involving federal funds rate, real GDP growth and a housing variable (captured by house price inflation or residential investment share or housing starts) and conduct time series analysis for the pre- and post-crisis periods. While previous studies mostly set break-dates based on events known a priori to split the full sample to subsamples, we endogenously determine structural break points occurring at multiple unknown dates. Our Granger causality analysis indicates that the federal funds rate did not cause house price inflation, although it caused residential investment share and housing starts in the pre-crisis period. In the post-crisis period, the real GDP growth caused residential investment and housing starts while house price inflation had a momentum of its own. Our impulse response and forecast error variance decomposition analysis reinforce these results. Overall, our findings suggest that housing volume fluctuates more than house prices over the business cycle