The subject of this dissertation is fiscal policy in the United States. In recent years the limitations of monetary policy have become more evident, generating greater interest in the use of fiscal policy as a stabilization tool. Despite considerable advances in the fiscal policy literature, many important questions about the effects and implementation of such policy remain unresolved. This motivates the present work, which explores both topics in the chapters that follow. I begin in the second chapter by estimating Federal Reserve responses to changes in taxes and spending. Monetary responses are a critical determinant of fiscal policy effectiveness since central banks have the ability to offset many of the economic changes resulting from fiscal shocks. Using techniques commonly employed in the fiscal multiplier literature, my results indicate a willingness by monetary policymakers to alter policy directly in response to fiscal shocks in a way that either reinforces or counteracts the resulting effects. In the third and fourth chapters I shift my focus to the conduct of fiscal policy. Specifically, I use Bayesian methods to estimate the response of federal discretionary policy to different macroeconomic variables. I allow for uncertainty about various characteristics of the underlying model which enables me to determine, for example, which variables matter to policymakers; whether policy conduct has changed over time; and whether policy responses are state dependent. My results indicate, among other things, that policy responds countercyclically to changes in the labor market, but only during periods of weak economic activity.

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This thesis empirically investigates the effects of monetary policy instruments on the real estate market for the following countries: Germany, France, the Netherlands, Spain and the United Kingdom, using a Structural Vector Autoregression model (SVAR) with Choleski recursive identification. This was done from the three different aspects: interest rate, scale of credit, and output. The covered period lasts from the first quarter of 2005 and then varies, depending on the country. The Wu-Xia shadow rate was used as a proxy for the interest rate, households' debt was used as a proxy for scale of credit, and real GDP was used as a proxy for the output. As the output of the analysis, we used the impulse response functions (IRF) and forecast errors variance decomposition (FEVD). The results suggest that the Residential Property Prices (RPPI) in every country react positively to an output shock and negatively to interest rates (except Spain). The effect of household debt on RPPI and statistical significance of intervals depend on the country observed.

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There are many channels that the Fed uses to transmit monetary policy, bank lending channel being one of them. The lending view focuses on the potential fluctuations in loan supplied by banks have on aggregate activity due to a fall in Fed Reserves. This thesis investigates the significance of the bank lending channel because of its important effect on investment (and consequently, aggregate output). In addition, Institutional Memory, deteriorating memory in loan officers causing more loans to be processed at the top of the business cycle (Berger and Udell, 2002) is tested on Core loans using 4 lags (1 year) to find out if bank lending behavior exists. Using Core loans (Commercial and Industrial, Real Estate, and Consumer loans) of commercial banks for the United States over a nineteen year period (1985-2004) results find significant evidence in the bank lending channel through Commercial & Industrial, and Real Estate loans. Firstly, through a correlation computation, it was found that Core loans were procyclical with aggregate output (GDP). Analyzing the [ cyclical] movements of Core loans around their trends with respect to Business cycle peaks, troughs, and GDP, it was found that Commercial & Industrial, and Real Estate loans provided supporting evidence on procyclical movements with the economy, implying the connection of the Federal Reserve and the economy through the bank lending channel is more effective through the aforementioned loans. Finally, four periods (1 year) in lags were used in autocorrelations to test for Institutional Memory. The computations find that Real Estate loans have a one year memory. This means that, for instance, if a recession were occurred today, Real Estate loans will not be affected until one year from today.

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