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Prior research on the relationship between output volatility and growth has produced mixed results, failing to provide clear empirical evidence on the sign of the relationship. In this paper, we raise the possibility that such failure is due to misspecification in empirical models previously used, i.e., not taking into account the business cycle dependence of the volatility-growth relation. We set off with the conjecture that higher volatility exerts qualitatively different effect on growth depending on whether the economy is in expansion or contraction. We estimate a series of ARCH-type models with the monthly industrial production data of the U.K., and find strong evidence suggesting that the volatility-growth relation is positive when the economy is in expansion, while higher volatility lowers growth rate in the contraction phase. We also find evidence supporting that the volatility-growth relation estimated in the paper captures a a causal relation, not a bidirectional correlation.
This paper analyzes the relationship between housing and the business cycle in the US. We start with constructing and estimating a baseline Markov-switching common factor model, and the importance of housing variables is then evaluated by comparing the results for the baseline model with those for the extended models augmented with the housing market variables. Two strands of extended models are considered: one in which housing variables directly affect the individual macroeconomic series and thereby the business cycle, and the other in which they affect the probabilities of transitions between expansion/recession phases. Results for the first extension support the importance of the housing quantity variables as argued by Leamer (2007): the growth in housing permits and housing new housing starts exert significant effects on the macroeconomic indicators and consequently the business cycle, but house price growth does not. For the second extension, however, we find that house price growth contains useful information beyond what is in the housing quantity variables. More specifically, while higher quantity growth affects which phase will prevail in the next period only when the economy is currently in the expansion, higher house price growth is informative whether the economy is currently in recession or expansion.
To understand how the macro economy evolves, the central bank has two options in choosing how to estimate the economic model against actual data: one is to estimate each sector of the model piece-by-piece, and the other is to estimate the whole model altogether. This paper demonstrates the advantage for the central bank of estimating the whole model in terms of the estimation accuracy and the robustness of the resulting policy recommendations. For that aim, we construct a macro model for the monetary policy analysis of the Korean economy and estimate the model via the system approach and single-equation approach. We evaluate the data fits of the two estimation results and show that the fit of the system approach is far better than the other and comparable to other methods such as vector autoregressions. It is also shown that, if the two estimated models are equally likely, conducting the policy tailored for the model estimated by the system approach delivers better stabilization results for the Korean economy.
In this paper, we have estimated a model that incorporates two key features of business cycles, co‐movement among economic variables and switching between regimes of expansion and recession, to aggregate quarterly data for the former Europe countries in the OECD. Two common factors, interpreted as reflecting the permanent and transitory components of the business cycle in the region, and estimates of turning points from one regime to the other were extracted from the data by using the Kalman filter and maximum likelihood estimation approach of Kim (1994). Estimation results confirm a fairly typical stylized fact of business cycles ‐ recessions are steeper and shorter than recoveries, and both co‐movement and regime switching are found to be important features of the business cycle in the region. The two common factors produce sensible representations of the trend and cycle, and the estimated turning points agree quite well with independently determined chronologies.
This paper examines the long-run effects of the two crises, that is, the Asian currency crisis and the subprime financial crisis, on the Malaysian GDP. Using a Markov-switching unobserved components model, we decompose the Malaysian GDP into the permanent and transitory components which are subject to possible shifts around the two crises periods. According to the estimation results with the quarterly GDP over 1986:Q1 to 2011:Q1, the output loss caused by the two crises was moderate in the sense that the trend output did not decrease even in the midst of the two crisis-driven recessions, despite the sharp declines in actual GDP. Also, comparison of the actual and trend growth rates across the pre-, inter-, and post-crises periods strongly suggests that the growth potential of the Malaysian economy has declined after the two crises.
In this paper, we estimate a model that incorporates key features of business cycles, co-movement among economic variables and switching between regimes of expansion and recession, to aggregate quarterly data for the NAFTA region. Two common factors reflecting the permanent and transitory components of the business cycle in the region, along with the turning points from one regime to the other, were extracted from the data by using the Kalman filter and maximum likelihood estimation approach of Kim (1994). Estimation results confirm that a typical aspect of business cycles are also observed (i.e., recessions are steeper and shorter than recoveries) in the region, and that both co-movement and that regime switching are found to be important features of the business cycle. The two common factors produce sensible representations of the trend and cycle, and the estimated turning points are in line with independently determined chronologies. It also turns out that the degree of synchronization between the NAFTA region and Korea, has significantly increased since the entry into force of the NAFTA.
This study identifies the characteristics of communication in cyberspace, in particular, how an issue is formed, diffused and amplified to the extent that it arouses collective action in the off-line world. The degree of influence was tested by six media types and by three issue stages (n=298). Qualifications of how an issue shifted from a cyber issue to off-line action was suggested and tested. A Three-Stage Cyber-Issue Diffusion (CID) Model was proposed that identifies an issue cycle in cyberspace as a forming stage, a diffusion stage and an action stage.
We investigate the role of housing price in the conduct of monetary policy for the US economy. Since 1986, we construct an empirical model, simulate the estimated model with a set of alternative monetary policy rules, and compare the stabilization performances of the rules. Our findings are : i) there is plenty of room for further stabilization of inflation and output, if the Fed shifts from the historical monetary policy rule to the optimal counterpart; ii) the optimal rule improves upon the historical one not because the former takes into account additional policy indicators such as movements in housing prices, but because it takes a quite different reaction scheme reacts toward the historical policy indicators, and iii) as long as the Fed maintains appropriate reactions to the historical policy indicators, housing price inflation does not contain much extra information for further stabilization.