In addition to quantitative assessment of economic growth using econometric models, business cycle analyses have been proved to be helpful to practitioners in order to assess current economic conditions or to anticipate upcoming fluctuations.
Using an analog of the boundary element method in engineering and science, we analyze and model unemployment rate in Austria, Italy, the Netherlands, Sweden, Switzerland, and the United States as a function of inflation and the change in labor force.
DSGE models are currently estimated with a two step approach: data is first filtered and then DSGE structural parameters are estimated. Two step procedures have problems, ranging from trend misspecification to wrong assumption about the correlation between trend and cycles.
In this paper, we perform a structural Bayesian estimation of the contribution of anticipated shocks to business cycles in the postwar United States. Our theoretical framework is a real-business-cycle model augmented with four real rigidities: investment adjustment costs, variable capacity utilization, habit formation in consumption, and habit formation in leisure.
We develop a dynamic stochastic general equilibrium model with an heterogeneous banking sector. We introduce endogenous default probabilities for both firms and banks, and allow for bank regulation and liquidity injection into the interbank market.
We explore the long and short run relationship between private consumption, disposable income and housing and financial wealth approximated by price indices for a panel of industrialized countries. Consumption, income and wealth are cointegrated in their common, but not in their idiosyncratic components.
We study the cross-section correlations of net, total, and disaggregated capital flows for the major source and recipient European Union countries. We seek evidence of changes in these correlations since the introduction of the euro to understand whether the European Union can be considered a unique entity with regard to its international capital flows.
We propose a method to estimate time invariant cyclical DSGE models using the information provided by a variety of filtering approaches. We treat data filtered with alternative procedures as contaminated proxy of the relevant model-based quantities and estimate structural and non-structural parameters jointly using an unobservable component structure.
We use US county level data (3,058 observations) from 1970 to 1998 to explore the relationship between economic growth and the extent of government employment at three levels: federal, state and local. We find that increases in federal, state and local government employments are all negatively associated with economic growth.