Two DSGE models are calibrated and simulated to investigate how the role of monetarypolicy differs between a closed and an open economy. The central bank conducts monetary policy according to a Taylor (1993) rule, reacting to inflation- and output deviations. Prices are sticky and there are habit components which slow down adjustment of consumption and exports. The models are subjected to shocks in the interest rate, inflation, technology and consumption. In most of the cases the shocks have a bigger and quicker affect on output and employment in the open economy. In connection with positive consumption- and interest rate shocks inflation is big and negative at first but gets positive already two quarters after the shock, due to effects in the exchange rate channel. In closed and open economies, a stronger reaction to output, than in the standard Taylor (1993) rule, decreases welfare losses dramatically.

External economic shocks cause domestic macroeconomic aggregates to fluctuate. This may call for a macroeconomic policy intervention. Since the early 1990s an increasing number of countries have adopted an inflation targeting framework. In reality, inflation targeters do not have perfect information when determining the interest rate in order to maintain their goal of price stability and stable economic growth. Therefore it is relevant to understand how shocks affect the domestic macroeconomic aggregates theoretically and investigate whether the theoretical predictions hold empirically. I use the New Keynesian model by Clarida, Galí and Gertler from 1999 and investigate explicitly the theoretical effects of expected and unexpected supply and demand-side shocks on the monetary policy instrument and the two monetary policy target variables – the interest rate, output gap and inflation rate. By analysing the impulse-response functions of a structural VAR model applied to quarterly Swedish and British data from 1994 to 2011, I test empirically the theoretical predictions according to the New Keynesian model. I find that the empirical results are in line with the theoretical predictions.

<p>This dissertation asks whether frequency misspecification of a New Keynesian model</p><p>results in temporal aggregation bias of the Calvo parameter. First, when a</p><p>New Keynesian model is estimated at a quarterly frequency while the true</p><p>data generating process is the same but at a monthly frequency, the Calvo</p><p>parameter is upward biased and hence implies longer average price duration.</p><p>This suggests estimating a New Keynesian model at a monthly frequency may</p><p>yield different results. However, due to mixed frequency datasets in macro</p><p>time series recorded at quarterly and monthly intervals, an estimation</p><p>methodology is not straightforward. To accommodate mixed frequency datasets,</p><p>this paper proposes a data augmentation method borrowed from Bayesian</p><p>estimation literature by extending MCMC algorithm with</p><p>"Rao-Blackwellization" of the posterior density. Compared to two alternative</p><p>estimation methods in context of Bayesian estimation of DSGE models, this</p><p>augmentation method delivers lower root mean squared errors for parameters</p><p>of interest in New Keynesian model. Lastly, a medium scale New Keynesian</p><p>model is brought to the actual data, and the benchmark estimation, i.e. the</p><p>data augmentation method, finds that the average price duration implied by</p><p>the monthly model is 5 months while that by the quarterly model is 20.7</p><p>months.</p> / Dissertation

Recently, single equation approaches for estimating structural models have become popular in the monetary economics literature. In particular, single-equation Generalized Method Moments estimators have been used for estimating forward-looking models with rational expectations. Two important examples are found in Clarida, Gali, and Gertler (1998) for the estimation of forward- looking Taylor rules and in Gali and Gertler (1999) for the estimation of a forward-looking model for inflation dynamics. In this thesis, we address the issues of identification which have been overlooked due to the incompleteness of the single-equation formulations. We provide extensions to existing results on the properties of GMM estimators and inference under weak identification, pertaining to situations in which only functions of the parameters of interest are identified, and structural residuals exhibit negative autocorrelation. We also characterize the power of the Hansen test to detect mis specification, and address the issues arising from using too many irrelevant instruments as well as from general corrections for residual autocorrelation, beyond what is implied by the maintained model. In general, we show that the non-modelled variables cannot be weakly exogenous for the parameters of interest, and that they are informative about the identification and mis-specification of the model. Modelling the reduced form helps identify pathological situations in which the structural parameters are weakly identified and the GMM estimators are inconsistent and biased in the direction of OLS.We also ¯nd the OLS bias to be increasing in the number of over-identifying instruments, even when the latter are irrelevant, thus demonstrating the dangers of using too many potentially irrelevant instruments. Finally, with regards to the "New Phillips curve", we conclude that, for the US economy, this model is either un-identified or mis-specified, casting doubts on its utility as a model of in°ation dynamics.

A great amount of available information over the internet makes it impossible for anyone to process it all. In this thesis, we use the rational inattention theory to see how the perceived signals about the exogenous variables would change under different levels of information capacity. Those signals are then applied in the New Keynesian model and corresponding impulse responses are compared with the case of unlimited attention. We found that for some autoregressive processes the differences from the perfect attention case are not very profound while for others the results vary considerably.

xi, 87 p. : ill. A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / The behavior of the macroeconomy and monetary policy is heavily influenced by expectations. Recent research has explored how minor changes in expectation formation can change the stability properties of a model. One common way to alter expectation formation involves agents' use of econometrics to form forecasting equations. Agents update their forecasts based on new information that arises as the economy progresses through time. In this way agents "learn" about the economy. Previous learning literature mostly focuses on agents using a fixed data size or increasing the amount of data they use. My research explores how agents might endogenously change the amount of data they use to update their forecast equations. My first chapter explores how an established endogenous learning algorithm, proposed by Marcet and Nicolini, may influence monetary policy decisions. Under rational expectations (RE) determinacy serves as the main criterion for favoring a model or monetary policy rule. A determinant model need not result in stability under an alternative expectation formation process called learning. Researchers appeal to stability under learning as a criterion for monetary policy rule selection. This chapter provides a cautionary tale for policy makers and reinforces the importance of the role of expectations. Simulations appear stable for a prolonged interval of time but may suddenly deviate from the RE solution. This exotic behavior exhibits significantly higher volatility relative to RE yet over long simulations remains true to the RE equilibrium. In the second chapter I address the effectiveness of endogenous gain learning algorithms in the presence of occasional structural breaks. Marcet and Nicolini's algorithm relies on agents reacting to forecast errors. I propose an alternative, which relies on agents using statistical information. The third chapter uses standard macroeconomic data to find out whether a model that has non-rational expectations can outperform RE. I answer this question affirmatively and explore what learning means to the economy. In addition, I conduct a Monte Carlo exercise to investigate whether a simple learning model does, empirically, imbed an RE model. While theoretically a very small constant gain implies RE, empirically learning creates bias in coefficient estimates. / Committee in charge: George Evans, Co-Chairperson, Economics; Jeremy Piger, Co-Chairperson, Economics; Shankha Chakraborty, Member, Economics; Sergio Koreisha, Outside Member, Decision Sciences

This analysis studies the phenomenon of the New Keynesian Phillips Curve - its inception from the RBC theory and DSGE modelling via incorporation of nominal rigidities, and its various specifications and empirical issues. The estimates on Czech macroeconomic data using the Generalised Method of Moments show that the hybrid New Keynesian Phillips Curve with the labour income share or the real unit labour cost as driving variables can be considered as an appropriate model describing inflation in the Czech Republic. Compared to other analyses, we show that the inflation process in the Czech Republic exhibits higher backwardness vis-a-vis other researchers' estimates based on US data.

Le premier chapitre questionne l'intuition conventionnelle selon laquelle une forte concentration au plus haut de la distribution des revenus devrait favoriser l'émergence de bulles d'actifs rationnelles. J'utilise un modèle OLG avec des fictions financières et des agents hétérogènes qui diffèrent en termes de taux d'épargne, portefeuilles d'actifs et talents. Je montre qu'une forte concentration promeut l'émergence de bulles si et seulement si ces bulles sont illiquides ou si tous les actifs offrent les mêmes rendements. A l'inverse, lorsque les bulles sont liquides et les actifs liquides paient une prime de liquidité, une faible concentration promeut l'émergence de bulles. Le deuxième papier étudie les conditions sous lesquelles une bulle d'actif augmente le PIB dans un modèle OLG-Nouveau Keynesien incluant le capital. Je montre que la stagnation séculaire est une condition nécessaire mais non suffisante. En effet, les bulles ne stimulent le PIB que si la demande agrégée est très fortement déficiente. Le troisième papier démontre que les modèle Nouveaux Keynesiens (NK) font des prédictions paradoxales lorsque la demande agrégée est chroniquement déficiente - un boom séculaire plutôt qu'une stagnation séculaire, et analyse comment ajuster ces modèles pour qu'ils deviennent viables dans l'environnement actuel. Je souligne l'importance cruciale des élasticités de l'offre et de la demande d'actifs par rapport au PIB à long terme ; j'effectue également une connexion entre le boom séculaire et d'autres prévisions paradoxales du modèle NK. / The first chapter questions the conventional intuition that a high concentration of income at the top of the distribution should promote the emergence of rational asset bubbles. I use an OLG model with financial fictions and heterogeneous agents that differ in terms of savings rate, portfolio choices and skills. I show that a high concentration at the top promotes the emergence of asset bubbles if and only if those asset bubbles are illiquid or financial markets are arbitrage-free. Instead, if asset bubbles are liquid and liquid assets pay a premium under illiquid assets, a low concentration promotes the emergence of asset bubbles. The second chapter studies the circumstances under which asset bubbles are expansionary in an OLG-New Keynesian that includes capital. I show that secular stagnation is a necessary but not sufficient condition. Indeed, asset bubbles stimulate investment, consumption and output if and only if there's a strong shortage of aggregate demand. Finally, the third paper shows that "standard" New Keynesian models make puzzling predictions when aggregate demand is chronically deficient they predict a secular boom, and seeks to understand how those models must be adjusted to analyze secular stagnation. I emphasize the crucial role of the long run elasticities of asset demand and supply with respect to the output gap in general equilibrium; and I also connect the secular boom to other puzzling predictions of the New Keynesian model.

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