Kim, Jin Woong (2006-08). Essays on empirical time series modeling with causality and structural change. Doctoral Dissertation. Thesis uri icon

abstract

  • In this dissertation, three related issues of building empirical time series models for financial markets are investigated with respect to contemporaneous causality, dynamics, and structural change. In the first essay, nation-wide industry information transmission among stock returns of ten sectors in the U.S. economy is examined through the Directed Acyclical Graph (DAG) for contemporaneous causality and Bernanke decomposition for dynamics. The evidence shows that the information technology sector is the most root cause sector. Test results show that DAG from ex ante forecast innovations is consistent with the DAG fro m ex post fit innovations. This supports innovation accounting based on DAGs using ex post innovations. In the second essay, the contemporaneous/dynamic behaviors of real estate and stock returns are investigated. Selected macroeconomic variables are included in the model to explain recent movements of both returns. During 1971-2004, there was a single structural break in October 1980. A distinct difference in contemporaneous causal structure before and after the break is found. DAG results show that REITs take the role of a causal parent after the break. Innovation accounting shows significantly positive responses of real estate returns due to an initial shock in default risk but insignificant responses of stock returns. Also, a shock in short run interest rates affects real estate returns negatively with significance but does not affect stock returns. In the third essay, a structural change in the volatility of five Asian and U.S. stock markets is examined during the post-liberalization period (1990-2005) in the Asian financial markets, using the Sup LM test. Four Asian financial markets (Hong Kong, Japan, Korea, and Singapore) experienced structural changes. However, test results do not support the existence of structural change in volatility for Thailand and U.S. Also, results show that the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) persistent coefficient increases, but the Autoregressive Conditional heteroskedasticity (ARCH) impact coefficient, implying short run adjustment, decreases in Asian markets. In conclusion, when the econometric model is set up, it is necessary to consider contemporaneous causality and possible structural breaks (changes). The dissertation emphasizes causal inference and structural consistency in econometric modeling. It highlights their importance in discovering contemporaneous/dynamic causal relationships among variables. These characteristics will likely be helpful in generating accurate forecasts.
  • In this dissertation, three related issues of building empirical time series models for
    financial markets are investigated with respect to contemporaneous causality, dynamics,
    and structural change. In the first essay, nation-wide industry information transmission
    among stock returns of ten sectors in the U.S. economy is examined through the
    Directed Acyclical Graph (DAG) for contemporaneous causality and Bernanke
    decomposition for dynamics. The evidence shows that the information technology sector
    is the most root cause sector. Test results show that DAG from ex ante forecast
    innovations is consistent with the DAG fro m ex post fit innovations. This supports
    innovation accounting based on DAGs using ex post innovations.
    In the second essay, the contemporaneous/dynamic behaviors of real estate and stock
    returns are investigated. Selected macroeconomic variables are included in the model to
    explain recent movements of both returns. During 1971-2004, there was a single
    structural break in October 1980. A distinct difference in contemporaneous causal
    structure before and after the break is found. DAG results show that REITs take the role of a causal parent after the break. Innovation accounting shows significantly positive
    responses of real estate returns due to an initial shock in default risk but insignificant
    responses of stock returns. Also, a shock in short run interest rates affects real estate
    returns negatively with significance but does not affect stock returns.
    In the third essay, a structural change in the volatility of five Asian and U.S. stock
    markets is examined during the post-liberalization period (1990-2005) in the Asian
    financial markets, using the Sup LM test. Four Asian financial markets (Hong Kong,
    Japan, Korea, and Singapore) experienced structural changes. However, test results do
    not support the existence of structural change in volatility for Thailand and U.S. Also,
    results show that the Generalized Autoregressive Conditional Heteroskedasticity
    (GARCH) persistent coefficient increases, but the Autoregressive Conditional
    heteroskedasticity (ARCH) impact coefficient, implying short run adjustment, decreases
    in Asian markets.
    In conclusion, when the econometric model is set up, it is necessary to consider
    contemporaneous causality and possible structural breaks (changes). The dissertation
    emphasizes causal inference and structural consistency in econometric modeling. It
    highlights their importance in discovering contemporaneous/dynamic causal
    relationships among variables. These characteristics will likely be helpful in generating
    accurate forecasts.

publication date

  • August 2006