Born, Benjamin: Four Essays in Econometrics and Macroeconomics. - Bonn, 2011. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
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author = {{Benjamin Born}},
title = {Four Essays in Econometrics and Macroeconomics},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2011,
month = sep,

note = {Chapter 1 proposes simple and robust diagnostic tests for spatial dependence, specifically for spatial error autocorrelation and spatial lag dependence. The idea of our tests is to reformulate the testing problem such that the outer product of gradients (OPG)-variant of the LM test can be employed. Our versions of the tests are based on simple auxiliary regressions, where ordinary regression t and F-statistics can be used to test for spatial autocorrelation and lag dependence. Monte Carlo simulations show that while, under homoskedasticity, our tests perform similarly to the established LM tests, the latter suffer from severe size distortions under heteroskedasticity. Therefore our approach gives practitioners an easy to implement and robust alternative to existing tests.
Chapter 2 proposes various tests for serial correlation in fixed-effects panel data regression models with a small number of time periods. First, a simplified version of the test for serial correlation suggested by Wooldridge (2002) and Drukker (2003) is considered. The second test is based on the LM statistic suggested by Baltagi and Li (1995), and the third test is a modification of the classical Durbin-Watson statistic. Under the null hypothesis of no serial correlation, all tests possess a standard normal limiting distribution as N to infinity and T is fixed. Analyzing the local power of the tests, we find that the LM statistic has superior power properties. Furthermore, a generalization to test for autocorrelation up to some given lag order and a test statistic that is robust against time dependent heteroskedasticity are proposed.
In chapter 3, we analyze the role of policy risk in explaining business cycle fluctuations by using an estimated New Keynesian model featuring policy risk as well as uncertainty about technology. The aftermath of the financial and economic crisis is clearly characterized by extraordinary uncertainty regarding U.S. economic policy. Hence, the argument that policy risk, i.e. uncertainty about monetary and fiscal policy, has been holding back the economic recovery in the U.S. during the Great Recession has a large popular appeal. But the empirical literature is still inconclusive with respect to the aggregate effects of (mostly TFP) uncertainty. Studies using different proxies and identification schemes to uncover the effects of uncertainty producing a variety of results.
We analyze the role of policy risk in explaining business cycle fluctuations by using an estimated New Keynesian model featuring policy risk as well as uncertainty about technology. We directly measure uncertainty from aggregate time series using Sequential Monte Carlo Methods. While we find considerable evidence of policy risk in the data, we show that the "pure uncertainty"-effect of policy risk is unlikely to play a major role in business cycle fluctuations. In the estimated model, output effects are relatively small due to i) dampening general equilibrium effects that imply a low amplification and ii) counteracting partial effects of uncertainty. Finally, we show that policy risk has effects that are an order of magnitude larger than the ones of uncertainty about aggregate TFP.
Central banks regularly communicate about financial stability issues, by publishing Financial Stability Reports (FSRs) and through speeches and interviews. Chapter 4 asks how such communications affect financial markets. For that purpose, we construct a unique and novel database on CB communication comprising more than 1000 releases of FSRs and speeches/interviews by central bank governors from 37 central banks over a time period from 1996 to 2009, i.e. spanning nearly one and a half decades. The degree of optimism that is expressed in these communications is determined using a computerized textual-analysis software. We then use an event study approach to analyze how financial sector stock indices react to the release of such communication.
The findings suggest that FSRs have a significant and potentially long-lasting effect on stock market returns. At the same time, they tend to reduce stock market volatility. Speeches and interviews, in contrast, have little effect on market returns and do not generate a volatility reduction during tranquil times. However, they had a substantial effect during the 2007-10 financial crisis. It seems that financial stability communication by central banks are perceived by markets to contain relevant information, underlining the importance of differentiating between communication tools, their content, and the environment in which they are employed.},

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