Refine
Year of publication
Document Type
- Working Paper (1459) (remove)
Has Fulltext
- yes (1459)
Is part of the Bibliography
- no (1459) (remove)
Keywords
- Deutschland (53)
- Geldpolitik (49)
- USA (45)
- monetary policy (41)
- Europäische Union (29)
- Monetary Policy (26)
- Schätzung (23)
- Währungsunion (22)
- Bank (21)
- Venture Capital (21)
Institute
- Center for Financial Studies (CFS) (1459) (remove)
Venture capital (VC) investment has long been conceptualized as a local business , in which the VC’s ability to source, syndicate, fund, monitor, and add value to portfolio firms critically depends on their access to knowledge obtained through their ties to the local (i.e., geographically proximate) network. Consistent with the view that local networks matter, existing research confirms that local and geographically distant portfolio firms are sourced, syndicated, funded, and monitored differently. Curiously, emerging research on VC investment practice within the United States finds that distant investments, as measured by “exits” (either initial public offering or merger & acquisition) out-perform local investments. These findings raise important questions about the assumed benefits of local network membership and proximity. To more deeply probe these questions, we contrast the deal structure of cross-border VC investment with domestic VC investment, and contrast the deal structure of cross-border VC investments that include a local
partner with those that do not. Evidence from 139,892 rounds of venture capital financing in the period 1980-2009 suggests that cross-border investment practice, in terms of deal sourcing, syndication, and performance indeed change with proximity, but that monitoring practices do not. Further, we find that the inclusion of a local partner in the investment syndicate yields surprisingly few benefits. This evidence, we argue, raises important questions about VC investment practice as well as the ability of firms to capture and lever the presumed benefits of network membership.
We examine the dynamics of assets under management (AUM) and management fees at the portfolio manager level in the closed-end fund industry. We find that managers capitalize on good past performance and favorable investor perception about future performance, as reflected in fund premiums, through AUM expansions and fee increases. However, the penalties for poor performance or unfavorable investor perception are either insignificant, or substantially mitigated by manager tenure. Long tenure is generally associated with poor performance and high discounts. Our findings suggest substantial managerial power in capturing CEF rents. We also document significant diseconomies of scale at the manager level.
This paper considers the desirability of the observed tendency of central banks to adjust interest rates only gradually in response to changes in economic conditions. It shows, in the context of a simple model of optimizing private-sector behavior, that such inertial behavior on the part of the central bank may indeed be optimal, in the sense of minimizing a loss function that penalizes inflation variations, deviations of output from potential, and interest-rate variability. Sluggish adjustment characterizes an optimal policy commitment, even though no such inertia would be present in the case of a reputationless (Markovian) equilibrium under discretion. Optimal interest-rate feedback rules are also characterized, and shown to involve substantial positive coefficients on lagged interest rates. This provides a theoretical explanation for the numerical results obtained by Rotemberg and Woodford (1998) in their quantitative model of the U.S. economy.
The paper considers optimal monetary stabilization policy in a forward-looking model, when the central bank recognizes that private-sector expectations need not be precisely model-consistent, and wishes to choose a policy that will be as good as possible in the case of any beliefs that are close enough to model-consistency. It is found that commitment continues to be important for optimal policy, that the optimal long-run inflation target is unaffected by the degree of potential distortion of beliefs, and that optimal policy is even more history-dependent than if rational expectations are assumed. JEL Classification: E52, E58, E42
The paper illustrates based on an example the importance of consistency between the empirical measurement and the concept of variables in estimated macroeconomic models. Since standard New Keynesian models do not account for demographic trends and sectoral shifts, the authors proposes adjusting hours worked per capita used to estimate such models accordingly to enhance the consistency between the data and the model. Without this adjustment, low frequency shifts in hours lead to unreasonable trends in the output gap, caused by the close link between hours and the output gap in such models.
The retirement wave of baby boomers, for example, lowers U.S. aggregate hours per capita, which leads to erroneous permanently negative output gap estimates following the Great Recession. After correcting hours for changes in the age composition, the estimated output gap closes gradually instead following the years after the Great Recession.
This paper studies the long-run effects of credit market disruptions on real firm outcomes and how these effects depend on nominal wage rigidities at the firm level. I trace out the long-run investment and growth trajectories of firms which are more adversely affected by a transitory shock to aggregate credit supply. Affected firms exhibit a temporary investment gap for two years following the shock, resulting in a persistent accumulated growth gap. I show that affected firms with a higher degree of wage rigidity exhibit a steeper drop in investment and grow more slowly than affected firms with more flexible wages.
This paper investigates the accuracy and heterogeneity of output growth and inflation forecasts during the current and the four preceding NBER-dated U.S. recessions. We generate forecasts from six different models of the U.S. economy and compare them to professional forecasts from the Federal Reserve’s Greenbook and the Survey of Professional Forecasters (SPF). The model parameters and model forecasts are derived from historical data vintages so as to ensure comparability to historical forecasts by professionals. The mean model forecast comes surprisingly close to the mean SPF and Greenbook forecasts in terms of accuracy even though the models only make use of a small number of data series. Model forecasts compare particularly well to professional forecasts at a horizon of three to four quarters and during recoveries. The extent of forecast heterogeneity is similar for model and professional forecasts but varies substantially over time. Thus, forecast heterogeneity constitutes a potentially important source of economic fluctuations. While the particular reasons for diversity in professional forecasts are not observable, the diversity in model forecasts can be traced to different modeling assumptions, information sets and parameter estimates. JEL Classification: C53, D84, E31, E32, E37 Keywords: Forecasting, Business Cycles, Heterogeneous Beliefs, Forecast Distribution, Model Uncertainty, Bayesian Estimation
In the aftermath of the global financial crisis, the state of macroeconomic modeling and the use of macroeconomic models in policy analysis has come under heavy criticism. Macroeconomists in academia and policy institutions have been blamed for relying too much on a particular class of macroeconomic models. This paper proposes a comparative approach to macroeconomic policy analysis that is open to competing modeling paradigms. Macroeconomic model comparison projects have helped produce some very influential insights such as the Taylor rule. However, they have been infrequent and costly, because they require the input of many teams of researchers and multiple meetings to obtain a limited set of comparative findings. This paper provides a new approach that enables individual researchers to conduct model comparisons easily, frequently, at low cost and on a large scale. Using this approach a model archive is built that includes many well-known empirically estimated models that may be used for quantitative analysis of monetary and fiscal stabilization policies. A computational platform is created that allows straightforward comparisons of models’ implications. Its application is illustrated by comparing different monetary and fiscal policies across selected models. Researchers can easily include new models in the data base and compare the effects of novel extensions to established benchmarks thereby fostering a comparative instead of insular approach to model development.
The global financial crisis and the ensuing criticism of macroeconomics have inspired researchers to explore new modeling approaches. There are many new models that deliver improved estimates of the transmission of macroeconomic policies and aim to better integrate the financial sector in business cycle analysis. Policy making institutions need to compare available models of policy transmission and evaluate the impact and interaction of policy instruments in order to design effective policy strategies. This paper reviews the literature on model comparison and presents a new approach for comparative analysis. Its computational implementation enables individual researchers to conduct systematic model comparisons and policy evaluations easily and at low cost. This approach also contributes to improving reproducibility of computational research in macroeconomic modeling. Several applications serve to illustrate the usefulness of model comparison and the new tools in the area of monetary and fiscal policy. They include an analysis of the impact of parameter shifts on the effects of fiscal policy, a comparison of monetary policy transmission across model generations and a cross-country comparison of the impact of changes in central bank rates in the United States and the euro area. Furthermore, the paper includes a large-scale comparison of the dynamics and policy implications of different macro-financial models. The models considered account for financial accelerator effects in investment financing, credit and house price booms and a role for bank capital. A final exercise illustrates how these models can be used to assess the benefits of leaning against credit growth in monetary policy.
This paper reviews the rationale for quantitative easing when central bank policy rates reach near zero levels in light of recent announcements regarding direct asset purchases by the Bank of England, the Bank of Japan, the U.S. Federal Reserve and the European Central Bank. Empirical evidence from the previous period of quantitative easing in Japan between 2001 and 2006 is presented. During this earlier period the Bank of Japan was able to expand the monetary base very quickly and significantly. Quantitative easing translated into a greater and more lasting expansion of M1 relative to nominal GDP. Deflation subsided by 2005. As soon as inflation appeared to stabilize near a rate of zero, the Bank of Japan rapidly reduced the monetary base as a share of nominal income as it had announced in 2001. The Bank was able to exit from extensive quantitative easing within less than a year. Some implications for the current situation in Europe and the United States are discussed.