The study is intended to identify relevant channels and possibly biasing factors with respect to fiscal multipliers, and thus to contribute to improving the precision of multiplier forecasts. This is done by, first, defining the concept of the multiplier used in the present study, presenting the main theoretical channels of influence as discussed in the literature and the problems of empirical identification. Second, by conducting a meta-regression analysis on the reported multipliers from a unique data set of 1069 multiplier observations and the respective study characteristics in order to derive quantitative stylzed facts. Third, by developing a simple multiplier model that explicitly takes into account the time elapse of the multiplier process as an explanatory factor that has been largely overlooked by the relevant theoretical literature. Fourth, by identifying, for US macroeconomic time series data, the extent to which fiscal multiplier estimates could be biased in the presence of financial cycles that have not been taken into account by the relevant empirical literature.

No description available.

The elasticity of factor substitution between capital and labor is a crucial parameter in many economic fields. However, despite extensive research, there is no agreement on its value. Utilizing 738 estimates from 41 studies published between 1961 and 2016, this paper provides the first meta-regression analysis of capital-labor substitution elasticities for the U.S. economy. We show that heterogeneity in reported estimates is driven by the choice of estimation equations, the modeling of technological dynamics, and data characteristics. Based on the underlying meta-regression sample and a "best practice" specification, we estimate a long-run elasticity in the range of 0.6 to 0.7. For all estimated elasticities the hypothesis of a Cobb-Douglas production function is rejected.

The study is intended to identify relevant channels and possibly biasing factors with respect to fiscal multipliers, and thus to contribute to improving the precision of multiplier forecasts. This is done by, first, defining the concept of the multiplier used in the present study, presenting the main theoretical channels of influence as discussed in the literature and the problems of empirical identification. Second, by conducting a meta-regression analysis on the reported multipliers from a unique data set of 1069 multiplier observations and the respective study characteristics in order to derive quantitative stylzed facts. Third, by developing a simple multiplier model that explicitly takes into account the time elapse of the multiplier process as an explanatory factor that has been largely overlooked by the relevant theoretical literature. Fourth, by identifying, for US macroeconomic time series data, the extent to which fiscal multiplier estimates could be biased in the presence of financial cycles that have not been taken into account by the relevant empirical literature.:List of Figures IV List of Tables VI List of Acronyms VII List of Symbols IX 1 General Introduction, Aim and Scope 2 Principles of the Measurement, Theory and Estimation of Fiscal Multipliers 2.1 Introduction 7 2.2 Definition and Measurement of the Fiscal Multiplier 7 2.3 Determinants of the Fiscal Multiplier 14 2.4 Principles of Estimating Fiscal Multipliers 29 2.5 Conclusions 38 3 A Meta-Regression Analysis of Fiscal Multipliers 43 3.1 Introduction 43 3.2 Literature Review 45 3.3 Data Set and Descriptive Statistics 49 3.4 Meta Regression—Method 54 3.5 Meta Regression—Moderator Variables 56 3.6 Meta Regression—Results 60 3.7 Conclusions 74 4 The Multiplier Principle, Credit-Money and Time 82 4.1 Introduction 82 4.2 Literature Review 85 4.3 Developing an Augmented Multiplier Model 89 4.4 Dynamic Stability of the Multiplier Process 106 4.5 Identifying the Lag-length 109 4.6 Conclusions 111 5 Financial Cycles and Fiscal Multiplier Estimations 114 5.1 Introduction 114 5.2 Literature Review 116 5.3 Asset and Credit Markets and Fiscal Multiplier Estimations 118 5.4 A Formal Framework 120 5.5 Empirical Strategy 124 5.6 Data 125 5.7 Structure and Identification 126 5.8 Effects of Fiscal Policy Changes—Baseline vs. Augmented Models 132 5.9 Robustness 140 5.10 Conclusions 142 6 General Conclusions and Research Prospects 148 Bibliography 153