Download or read book Essays in Empirical Macroeconomics Identification in Vector Autoregressive Models and Robust Inference in Early Warning Systems written by Martin Bruns and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Empirical Vector Autoregressive Modeling written by Marius Ooms and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1. 1 Integrating results The empirical study of macroeconomic time series is interesting. It is also difficult and not immediately rewarding. Many statistical and economic issues are involved. The main problems is that these issues are so interrelated that it does not seem sensible to address them one at a time. As soon as one sets about the making of a model of macroeconomic time series one has to choose which problems one will try to tackle oneself and which problems one will leave unresolved or to be solved by others. From a theoretic point of view it can be fruitful to concentrate oneself on only one problem. If one follows this strategy in empirical application one runs a serious risk of making a seemingly interesting model, that is just a corollary of some important mistake in the handling of other problems. Two well known examples of statistical artifacts are the finding of Kuznets "pseudo-waves" of about 20 years in economic activity (Sargent (1979, p. 248)) and the "spurious regression" of macroeconomic time series described in Granger and Newbold (1986, §6. 4). The easiest way to get away with possible mistakes is to admit they may be there in the first place, but that time constraints and unfamiliarity with the solution do not allow the researcher to do something about them. This can be a viable argument.

Download or read book Essays on Belief Updating Forecasting and Robust Policy Making Based on Macroeconomic Variables written by Yizhou Kuang and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of three essays that delve into the intersection of econometrics and macroeconomics. The essays employ econometric tools to investigate various topics related to macroeconomic forecasting and policy-making. The first essay aims to help policy-makers conduct robust inference on parameters that may suffer identification issues from DSGE models, and perform reliable counterfactual analysis based on available macroeconomic indicators. The second essay from a non-structural perspective, explores how to optimally forecast these variables in real-time utilizing available macroeconomic variables under model uncertainty. The last essay looks at Survey of Professional Forecasters and studies how agents update their beliefs based on common and private signals during business cycles.The first chapter introduces a new algorithm to conduct robust Bayesian estimation and inference in dynamic stochastic general equilibrium models. The algorithm combines standard Bayesian methods with an equivalence characterization of model solutions. This algorithm allows researchers to perform the following analysis: First, find the complete range of posterior means of both the deep parameters and any parameters of interest robust to the choice of priors in a sense I make precise. Second, derive the robust Bayesian credible region for these parameters. I prove the validity of this algorithm and apply this method to the models in Cochrane (2011) and An and Schorfheide (2007) to achieve robust estimations for structural parameters and impulse responses. In addition, I conduct a sensitivity analysis of optimal monetary policy rules with respect to the choice of priors and provide bounds to the optimal Taylor rule parameters.In the second chapter, my coauthors Yongmiao Hong, Yuying Sun and I focus on real-time monitoring of economic activities, also known as nowcasting. Nowcasting can be particularly challenging in the era of Big Data because it requires the management of a substantial amount of time series data that exhibit different frequencies and release dates. In this paper, we propose a novel now-casting strategy that utilizes dynamic factor models, which we call leave-b-out forward validation model averaging with penalization (LboFVMA). We demonstrate that the selected weight converges asymptotically to an optimal and consistent estimator, even in cases where all candidate models are misspecified. Further-more, the proposed estimator is consistent and follows an asymptotic Gaussian distribution if the true model is included among the candidate models. Our simulation results demonstrate that the LboFVMA approach performs well, as it generates low mean square forecast errors. This highlights its effectiveness and accuracy in the field of nowcasting.In the third chapter, my coauthors Nathan Mislang, Kristoffer Nimark and I propose a method to empirically decompose a cross-section of observed belief revisions into components driven by private and common signals under weak assumptions. We define a common signal as the single signal that if observed by all agents can explain the maximum amount of belief revisions across agents. Private signals are defined to explain the residual belief revisions unaccounted for by the common signal. When applied to probability forecasts from the Survey of Professional Forecasters we find that private signals account for more of the observed belief revisions than common signals. There is a large cross-sectional heterogeneity in signal precision across forecasters, with about 1/2 of them observing private signals that are less precise than the common signal. Unconditionally, the precision of private and common signals are positively correlated, suggesting that private and common information are complements. Inflation volatility, perceived stock market volatility and a high risk of recession are all factors associated with increased informativeness and precision of both private and common signals. Disagreement between the private and common signals can partly explain increases in uncertainty about macro variables. We discuss the implications of our findings for theoretical models of information acquisition.

Download or read book Dynamic Modeling Empirical Macroeconomics and Finance written by Lucas Bernard and published by Springer. This book was released on 2016-10-03 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume, with contributions by area experts, offers discussions on a range of evolving topics in economics and social development. At center are important issues central to sustainable development, economic growth, technological change, the economics of climate change, commodity markets, long wave theory, non-linear dynamic models, and boom-bust cycles. This is an excellent reference for academic and professional economists interested in emerging areas of empirical macroeconomics and finance. For policy makers and curious readers alike, it is also an outstanding introduction to the economic thinking of those who seek a holistic and all-compassing approach in economic theory and policy. Looking into new data and methodology, this book offers fresh approaches in a post-crisis environment. Set in a profound understanding of the diverse currents within the many traditions of economic thought, this book pushes the established frontiers of economic thinking. It is dedicated to a leading scholar in the areas covered in this book, Willi Semmler.

Download or read book Recent Advances and Future Directions in Causality Prediction and Specification Analysis written by Xiaohong Chen and published by Springer Science & Business Media. This book was released on 2012-08-01 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of articles that present the most recent cutting edge results on specification and estimation of economic models written by a number of the world’s foremost leaders in the fields of theoretical and methodological econometrics. Recent advances in asymptotic approximation theory, including the use of higher order asymptotics for things like estimator bias correction, and the use of various expansion and other theoretical tools for the development of bootstrap techniques designed for implementation when carrying out inference are at the forefront of theoretical development in the field of econometrics. One important feature of these advances in the theory of econometrics is that they are being seamlessly and almost immediately incorporated into the “empirical toolbox” that applied practitioners use when actually constructing models using data, for the purposes of both prediction and policy analysis and the more theoretically targeted chapters in the book will discuss these developments. Turning now to empirical methodology, chapters on prediction methodology will focus on macroeconomic and financial applications, such as the construction of diffusion index models for forecasting with very large numbers of variables, and the construction of data samples that result in optimal predictive accuracy tests when comparing alternative prediction models. Chapters carefully outline how applied practitioners can correctly implement the latest theoretical refinements in model specification in order to “build” the best models using large-scale and traditional datasets, making the book of interest to a broad readership of economists from theoretical econometricians to applied economic practitioners.

Download or read book Unconventional Identification in Vector Autoregressive Models Empirical Essays on Credit Risk and Uncertainty written by Maximilian Podstawski and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Var Models in Macroeconomics New Developments and Applications written by Thomas B. Fomby and published by Emerald Group Publishing Limited. This book was released on 2013-12-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Econometrics publishes original scholarly econometric papers with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics, throughout the empirical economic, business and social science literature.

Download or read book Essays in Time Series Econometrics written by Fei Han and published by . This book was released on 2012 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of three chapters dealing with different topics in time series econometrics including generalized method of moments (GMM) estimation and vector autoregressions (VAR). These econometric models have revolutionized empirical research in macroeconomics. Previous work by Hansen and Singleton (1982) showed that the GMM method can be applied to estimate nonlinear rational expectations models in a simple way that the models need not even be solved. The seminal work of Sims (1980) has demonstrated how VAR models can be used for macroeconomic forecasting and policy analysis. The objective of this dissertation is to provide some new econometric tools for applied research in macroeconomics using time series data. The first chapter develops an asymptotic theory for the GMM estimator in nonlinear econometric models with integrated regressors and instruments. We establish consistency and derive the limiting distribution of the GMM estimator for asymptotically homogeneous regression functions. The estimator is consistent under fairly general conditions, and the convergence rates are determined by the degree of the asymptotic homogeneity of regression functions. Similar to linear regressions, we find that the limiting distribution is generally biased and non-Gaussian, and that instruments themselves cannot eliminate the bias even when they are strictly exogenous. Therefore, GMM yields inefficient estimates and invalid $t$- and chi-square test statistics in general. By implementing the fully modified method developed by Phillips and Hansen (1990), we obtain an efficient GMM estimator which has an unbiased and mixed normal limiting distribution. In the second chapter, we develop a novel shock identification strategy in the context of two-country/block structural vector autoregressive (SVAR) models to identify the transmission of credit shocks. Specifically, we investigate how credit shocks originating in the U.S. or euro area affect domestic economic activity in emerging Asia. Shocks within each block are identified using sign restrictions, whereas shocks across the two blocks are identified using a recursive structure (block Cholesky decomposition). This strategy not only enables us to distinguish the external credit shock from the other structural shocks, but also captures the responses of the domestic country. The main findings include that the transmission of credit shocks across countries through the channel of credit contagion is fast and protracted. The adverse effects of external credit tightening are mitigated by domestic credit policy easing in China, but lead to significant decreases in credit and GDP growth in the other emerging Asian countries. We also find that the external credit shocks play a non-negligible role in driving economic fluctuations in emerging Asia, although the role is smaller in China. In the last chapter, we use a global vector autoregressive (GVAR) model to forecast the principal macroeconomic indicators of the original five ASEAN member countries (i.e. Indonesia, Malaysia, Philippines, Singapore, and Thailand). The GVAR model is a compact model of the world economy designed to explicitly model the economic and financial interdependencies at national and international levels. Our GVAR model covers twenty countries which are grouped into nine countries/regions. After applying vector error correction model (VECM) to estimate parameters in the GVAR, we generate twelve one-quarter-ahead forecasts of real GDP growth, inflation, short-term interest rates, real exchange rates, real equity prices, and world commodity prices over the period 2009Q1-2011Q4, with four out-of-sample forecasts during 2009Q1-2009Q4. Forecast evaluation based on the panel Diebold-Mariano (DM) tests shows that the forecasts of our GVAR model tend to outperform those of country-specific VAR models, especially for short-term interest rates and real equity prices. These results suggest that the interdependencies among countries in the global financial market play an important role in macroeconomic forecasting.

Download or read book Five Empirical Essays on Identifying Cointegrated Vector Autoregressive Systems written by Thórarinn G. Pétursson and published by . This book was released on 1998 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Cointegrated VAR Model written by Katarina Juselius and published by OUP Oxford. This book was released on 2006-12-07 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: This valuable text provides a comprehensive introduction to VAR modelling and how it can be applied. In particular, the author focuses on the properties of the Cointegrated VAR model and its implications for macroeconomic inference when data are non-stationary. The text provides a number of insights into the links between statistical econometric modelling and economic theory and gives a thorough treatment of identification of the long-run and short-run structure as well as of the common stochastic trends and the impulse response functions, providing in each case illustrations of applicability. This book presents the main ingredients of the Copenhagen School of Time-Series Econometrics in a transparent and coherent framework. The distinguishing feature of this school is that econometric theory and applications have been developed in close cooperation. The guiding principle is that good econometric work should take econometrics, institutions, and economics seriously. The author uses a single data set throughout most of the book to guide the reader through the econometric theory while also revealing the full implications for the underlying economic model. To test ensure full understanding the book concludes with the introduction of two new data sets to combine readers understanding of econometric theory and economic models, with economic reality.

Download or read book Three Essays on Identification in Structural Vector Autoregressive Models written by Robin Braun and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Three Essays on Identification and Dimension Reduction in Vector Autoregressive Models written by Dominik Bertsche and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays on Identification in Macroeconomics written by Andres Pablo Sarto and published by . This book was released on 2019 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis studies new methods to estimate the effects of interventions at the macroeconomic level using regional variation. Chapter 1 studies the relationship between elasticities at the regional level and elasticities at the macroeconomic level. To this end, I analyze regional versions of canonical macroeconomic models, along with different policies of interest, such as aggregate government spending. At the regional level, I show that there are two relevant elasticities for policy analyses, the micro-local elasticities and the micro-global elasticities. The former measure how a region reacts to a regional policy, the latter measure how a region reacts to an aggregate policy. I then show that the macro elasticity of interest is a function of the micro-global elasticities exclusively. Finally, I show that if we fix a policy and an outcome variable, the mapping from the micro-global elasticities to the macro elasticity is the same across models. Chapter 2 proposes a new approach (Regional Structural VAR (RSVAR)) to estimate macroeconomic elasticities using regional data that avoids the problem of model-specific estimates. I first define a class of models, which includes the most widely used models for policy analysis, that gives equilibrium regional equations that contain the micro-local and micro-global elasticities. I then specify different sets of identification assumptions, along with estimators of the macroeconomic elasticities, and show that the estimators proposed are consistent. The crucial assumption underlying all of these results is that regions are heterogeneous in the sense that they react differently to the same shocks. Chapter 3 provides a new identification strategy to estimate the fiscal multiplier in the US. Using state-level data for the period 1971-2008, I apply a RSVAR approach to recover the national fiscal multiplier. The instrument employed at the state level is the official declarations of natural disasters by the federal government. My results suggest a very precisely estimated fiscal multiplier of around 1, depending on the specification used. Thus, it is not possible to rule out the possibility that government spending crowds out/in private spending. However, the range of the estimates obtained (0.7 - 1.2) suggests that either effect should be small.

Download or read book Essays in Empirical Macroeconomics written by Ashish Rajbhandari and published by . This book was released on 2012 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: My dissertation is mostly focused on the effects and quantitative importance of news shocks in an open economy DSGE model. The novelty of these models pertain to their ability to analyze business cycle fluctuations in a structural setting with rigorous micro foundations. The first two chapters of my dissertation estimates open economy DSGE models and investigates the role of news shocks in explaining international business cycles. My third chapter focuses on identification and estimation of a partially observable bivariate probit model. The first paper, titled Propagation of News Shocks in an Open Economy DSGE model, estimates a large open economy DSGE model of US and the Euro area with frictions and news shocks along with other unanticipated structural shocks. The role of news shocks in generating business cycles is an area of ongoing research and has garnered attention as being a major contributor of output fluctuations. In this paper we find that news shocks that originate domestically have an important quantitative role in explaining domestic output, inflation and interest rates. More specifically, news shocks from the US explain about 30% of US output and those from the Euro explain about 35% of Euro output. The international transmission of news shocks however are not important in affecting business cycles across countries. The second paper, titled News shocks and Business Cycles in a Small Open Economy of Canada investigates the role of news shocks in a small open economy of Canada. Moreover we are also interested in the international transmission of such shocks from a large foreign economy such as the US. In this paper, we estimated a small open economy DSGE model with rigidities using Bayesian methods. We find that news shocks from the US have negligible role in explaining aggregate fluctuations in Canada. Nonetheless, we also find that news shocks originating in Canada play an important role domestically. The third paper is titled Identification and MCMC Estimation of bivariate probit models with partial observability. Partial observability in a bivariate probit model arises when one can only observe the binary outcome of a paired decision. Following Poirier (1980) we find a host of research applying a version of this model. However, most applications heavily rely on the assumption of independence across equations and forego estimation of the correlation parameter while some report misleading estimates. In this paper we perform Monte Carlo simulations to show that estimating the correlation parameter in a partially observable case is nontrivial as compared to a fully observable case. We also estimate the model using maximum likelihood as well as bayesian MCMC methods and apply to a dataset of Prezeworski and Vreeland (2002) studying the role of IMF.

Download or read book Essays in Financial and Macro Econometrics written by Paul Karapanagiotidis and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays in the Econometrics of Macroeconomic Models written by Andreas Tryphonides and published by . This book was released on 2016 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: The thesis has focused on issues related to the use of external information in the identification, estimation and evaluation of Dynamic Stochastic General Equilibrium (DSGE) models, and comprises three papers. The first paper, entitled Improving Inference for Dynamic Economies with Frictions - The role of Qualitative Survey data, proposes a new inferential methodology that is robust to misspecification of the mechanism generating frictions in a dynamic stochastic economy. I derive a characterization of the model economy that provides identifying restrictions on the solution of the model that are consistent with a variety of mechanisms. I show how qualitative survey data can be linked to the expectations of agents and how this link generates an additional informative set of identifying restrictions. Moreover, I show how the framework can be used to formally validate mechanisms that generate frictions. Finally, I apply the methodology to estimate the distortions in the Spanish economy due to financial frictions and derive an optimal robust Taylor rule. The second chapter, entitled Estimation and Inference for Incomplete Structural Models using Auxiliary Density Information considers an alternative method for estimating the parameters of an equilibrium model which does not require the equilibrium decision rules and produces an estimated probability model for the observables. This is done by introducing auxiliary information about the conditional density of the observables, and using density projections. I develop and assess frequentist inference in this framework. I provide the asymptotic theory for parameter estimates for a general set of conditional projection densities and simulation exercises. In the third chapter, entitled Monetary Policy Rules and External Information, I analyze how conclusions about monetary policy stance are altered when we explicitly acknowledge that model concepts like the output gap and inflation are non-observable and we utilize many proxies that are available in the data. I document the effects on Bayesian inference of introducing such proxy information.

Download or read book Essays on Alternative Methods of Identification and Estimation of Vector Autoregressive Moving Average Models written by George Athanasopoulos and published by . This book was released on 2005 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: